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1 | {"measureId": 1, "measureName": "Enrollment in CMC Plans", "groupId": 1, "groupName": "Enrollment Benchmarking", "pdfVersionLink": "downloads/background-and-methods/TAF-DQ-Enroll-CMC-Plans.pdf", "background": {"content": "<p class=\"msword-paragraph\"> <a id=\"_Hlk30592933\"></a> The majority of Medicaid beneficiaries receive most or all of their care through managed care models. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[1]</a> </sup> </sup> In 2016, the three Medicaid managed care models most commonly used by states were: (1) comprehensive managed care organizations (CMCs), where states pay comprehensive managed care organizations (MCOs) a risk-based capitation rate to cover a broad set of services that typically include acute, primary, and specialty medical services; (2) primary care case management (PCCM), where primary care practitioners provide a core set of case management services in exchange for an administrative fee, but nearly all services continue to be provided on a fee-for-service basis; and (3) limited-benefit plans, including behavioral health organizations (BHOs), where plans manage a subset of services such as treatment for substance use disorders and inpatient or institutional mental health services.</p><p class=\"msword-paragraph\"> All states providing services through managed care plans must report enrollment for beneficiaries covered under such plans; however, the accuracy of T-MSIS enrollment reporting varies considerably across both states and plan types. This data quality assessment examines alignment between July data from the T-MSIS Analytic Files (TAF) and the benchmark, the annual Medicaid Managed Care Enrollment and Program Characteristics (MMCEPC) report. <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[2]</a> </sup> </sup></p><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"> <p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). “Medicaid Managed Care Enrollment and Program Characteristics, 2016.” Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"> <p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). “Medicaid Managed Care Enrollment and Program Characteristics, 2016.” Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"><p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). \u201cMedicaid Managed Care Enrollment and Program Characteristics, 2016.\u201d Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"><p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). \u201cMedicaid Managed Care Enrollment and Program Characteristics, 2016.\u201d Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}]}, "methods": {"content": "<p class=\"msword-paragraph\"> The analysis relies on two main data sources: (1) the TAF annual Demographic and Eligibility (DE) file <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[3]</a> </sup> </sup> and (2) the annual MMCEPC report.</p><ul> <li class=\"msword-list-bullet\"> The TAF DE file contains demographic, eligibility, and enrollment information for all Medicaid and Children’s Health Insurance Program (CHIP) beneficiaries who were enrolled for at least one day during the calendar year. The file contains monthly flags that indicate whether a beneficiary was enrolled for at least one day in a given month in different types of managed care. </li> <li class=\"msword-list-bullet\"> The annual MMCEPC contains data collected directly from states on enrollment in managed care models at the state and plan type levels, as well as information about key program features (for instance, type of enrollment by population group enrolled). The information in the MMCEPC is based on beneficiary enrollment as of July 1 of each year. </li></ul><p class=\"msword-paragraph\"> We compared how well the TAF aligned with the benchmark by measuring the percent difference between the data sources in each month, then averaged the percent difference over all twelve months of the calendar year. We calculated TAF-based enrollment counts for beneficiaries in managed care by using managed care plan type information found in the TAF DE file. To align TAF counts as closely as possible with the benchmark data, we used information about beneficiary enrollment for July of the given year. We first counted the number of beneficiaries enrolled in CMCs, PCCM entities, and BHOs in July <a id=\"_Hlk31805930\"></a> . <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[4]</a> </sup> </sup> We then limited the analysis to beneficiaries enrolled in Medicaid. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-4\" id=\"footnote-ref-4\">[5]</a> </sup> </sup> Because the benchmark data can be viewed as a baseline and the TAF-based calculations as the comparison, the percent difference is calculated as a percent error or change: 100*(TAF – MMCEPC)/MMCEPC. We categorized a state’s enrollment data into one of four categories according to the level of alignment with the benchmark and the corresponding level of data quality concern (Table 1).</p><p class=\"msword-table-title\"> Table 1. <a id=\"_Hlk34816350\"></a> Criteria for DQ assessment of enrollment in managed care</p><table aria-label=\"Table 1. Criteria for DQ assessment of enrollment in managed care\" class=\"dq-assessment-table\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Average monthly percent difference between TAF and MMCEPC enrollment counts </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Level of alignment between TAF and MMCEPC enrollment counts </p> </th> <th class=\"msword-table-header-center dq-assessment-col\"> <p class=\"msword-table-header-center\"> DQ assessment </p> </th> </tr> </thead> <tbody> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x ≤ 10 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> High </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 10 percent < x ≤ 20 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Moderate </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level medium\"> <p class=\"msword-table-text-centered\"> Medium concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 20 percent < x ≤ 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level high\"> <p class=\"msword-table-text-centered\"> High concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x > 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level unusable\"> <p class=\"msword-table-text-centered\"> Unusable </p> </td> </tr> </tbody></table><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"3\"> <p class=\"msword-footnote-text\"> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide “Production of the TAF Research Identifiable Files.” </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"4\"> <p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in managed care, we relied on the managed care plan type information (MC_PLAN_TYPE_CD1_07 through MC_PLAN_TYPE_CD16_07) found in the TAF DE file. CMC programs included beneficiaries enrolled in a CMC plan or a health insuring organization (HIO) (managed care plan type 01 or 04); PCCMs included traditional PCCM provider arrangements and enhanced PCCM provider arrangements (managed care plan type 02 or 03); and BHOs included mental health prepaid inpatient health plans (PIHPs) and prepaid ambulatory health plans (PAHPs), substance use disorder (SUD) PIHPs and PAHPs, and mental health and SUD PIHPs and PAHPs (managed care plan types of 08 through 13). </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-4\" value=\"5\"> <p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in Medicaid, we relied on the CHIP code variable for July (CHIP_CD_07) in the TAF DE file, or eligibility group variable for July (ELGBLTY_GRP_CD_07) if the CHIP code was missing. Medicaid beneficiaries are identified using CHIP code 1 and eligibility group code 1-60 or 69-75. For analyses of 2014 through 2017 TAF, we also use CHIP code 4 (Medicaid and S-CHIP) to identify Medicaid beneficiaries, because CHIP code 4 is a valid value for those TAF data years. </p> <p> <a href=\"#footnote-ref-4\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"3\"><p class=\"msword-footnote-text\"> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide \u201cProduction of the TAF Research Identifiable Files.\u201d </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"4\"><p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in managed care, we relied on the managed care plan type information (MC_PLAN_TYPE_CD1_07 through MC_PLAN_TYPE_CD16_07) found in the TAF DE file. CMC programs included beneficiaries enrolled in a CMC plan or a health insuring organization (HIO) (managed care plan type 01 or 04); PCCMs included traditional PCCM provider arrangements and enhanced PCCM provider arrangements (managed care plan type 02 or 03); and BHOs included mental health prepaid inpatient health plans (PIHPs) and prepaid ambulatory health plans (PAHPs), substance use disorder (SUD) PIHPs and PAHPs, and mental health and SUD PIHPs and PAHPs (managed care plan types of 08 through 13). </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}, {"number": 4, "content": "<li class=\"footnoteBody\" id=\"footnote-4\" value=\"5\"><p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in Medicaid, we relied on the CHIP code variable for July (CHIP_CD_07) in the TAF DE file, or eligibility group variable for July (ELGBLTY_GRP_CD_07) if the CHIP code was missing. Medicaid beneficiaries are identified using CHIP code 1 and eligibility group code 1-60 or 69-75. For analyses of 2014 through 2017 TAF, we also use CHIP code 4 (Medicaid and S-CHIP) to identify Medicaid beneficiaries, because CHIP code 4 is a valid value for those TAF data years. </p><p><a href=\"#footnote-ref-4\">\u2191</a></p></li>"}]}, "summary": {"content": "<p>The TAF eligibility files include information about the enrollment of Medicaid and CHIP beneficiaries into different types of managed care models. One of the most common is comprehensive managed care organizations (CMCs), which deliver a broad range of services, including primary care, specialty care, and most other acute services. This analysis examines how well the TAF data on CMC enrollment align with an external benchmark, the Medicaid Managed Care Enrollment and Program Characteristics report.</p>", "footnotes": []}, "originalIssueBriefId": "4021", "relatedTopics": [{"measureId": 2, "measureName": "Enrollment in PCCM Programs", "groupId": 1, "groupName": "Enrollment Benchmarking", "order": 1}, {"measureId": 3, "measureName": "Enrollment in BHO Plans", "groupId": 1, "groupName": "Enrollment Benchmarking", "order": 2}]} |
2 | {"measureId": 2, "measureName": "Enrollment in PCCM Programs", "groupId": 1, "groupName": "Enrollment Benchmarking", "pdfVersionLink": "downloads/background-and-methods/TAF-DQ-Enroll-PCCM-Programs.pdf", "background": {"content": "<p class=\"msword-paragraph\"> <a id=\"_Hlk30592933\"></a> The majority of Medicaid beneficiaries receive most or all of their care through managed care models. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[1]</a> </sup> </sup> In 2016, the three Medicaid managed care models most commonly used by states were: (1) comprehensive managed care organizations (CMCs), where states pay comprehensive managed care organizations (MCOs) a risk-based capitation rate to cover a broad set of services that typically include acute, primary, and specialty medical services; (2) primary care case management (PCCM), where primary care practitioners provide a core set of case management services in exchange for an administrative fee, but nearly all services continue to be provided on a fee-for-service basis; and (3) limited-benefit plans, including behavioral health organizations (BHOs), where plans manage a subset of services such as treatment for substance use disorders and inpatient or institutional mental health services.</p><p class=\"msword-paragraph\"> All states providing services through managed care plans must report enrollment for beneficiaries covered under such plans; however, the accuracy of T-MSIS enrollment reporting varies considerably across both states and plan types. This data quality assessment examines alignment between July data from the T-MSIS Analytic Files (TAF) and the benchmark, the annual Medicaid Managed Care Enrollment and Program Characteristics (MMCEPC) report. <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[2]</a> </sup> </sup></p><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"> <p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). “Medicaid Managed Care Enrollment and Program Characteristics, 2016.” Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"> <p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). “Medicaid Managed Care Enrollment and Program Characteristics, 2016.” Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"><p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). \u201cMedicaid Managed Care Enrollment and Program Characteristics, 2016.\u201d Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"><p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). \u201cMedicaid Managed Care Enrollment and Program Characteristics, 2016.\u201d Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}]}, "methods": {"content": "<p class=\"msword-paragraph\"> The analysis relies on two main data sources: (1) the TAF annual Demographic and Eligibility (DE) file <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[3]</a> </sup> </sup> and (2) the annual MMCEPC report.</p><ul> <li class=\"msword-list-bullet\"> The TAF DE file contains demographic, eligibility, and enrollment information for all Medicaid and Children’s Health Insurance Program (CHIP) beneficiaries who were enrolled for at least one day during the calendar year. The file contains monthly flags that indicate whether a beneficiary was enrolled for at least one day in a given month in different types of managed care. </li> <li class=\"msword-list-bullet\"> The annual MMCEPC contains data collected directly from states on enrollment in managed care models at the state and plan type levels, as well as information about key program features (for instance, type of enrollment by population group enrolled). The information in the MMCEPC is based on beneficiary enrollment as of July 1 of each year. </li></ul><p class=\"msword-paragraph\"> We compared how well the TAF aligned with the benchmark by measuring the percent difference between the data sources in each month, then averaged the percent difference over all twelve months of the calendar year. We calculated TAF-based enrollment counts for beneficiaries in managed care by using managed care plan type information found in the TAF DE file. To align TAF counts as closely as possible with the benchmark data, we used information about beneficiary enrollment for July of the given year. We first counted the number of beneficiaries enrolled in CMCs, PCCM entities, and BHOs in July <a id=\"_Hlk31805930\"></a> . <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[4]</a> </sup> </sup> We then limited the analysis to beneficiaries enrolled in Medicaid. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-4\" id=\"footnote-ref-4\">[5]</a> </sup> </sup> Because the benchmark data can be viewed as a baseline and the TAF-based calculations as the comparison, the percent difference is calculated as a percent error or change: 100*(TAF – MMCEPC)/MMCEPC. We categorized a state’s enrollment data into one of four categories according to the level of alignment with the benchmark and the corresponding level of data quality concern (Table 1).</p><p class=\"msword-table-title\"> Table 1. <a id=\"_Hlk34816350\"></a> Criteria for DQ assessment of enrollment in managed care</p><table aria-label=\"Table 1. Criteria for DQ assessment of enrollment in managed care\" class=\"dq-assessment-table\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Average monthly percent difference between TAF and MMCEPC enrollment counts </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Level of alignment between TAF and MMCEPC enrollment counts </p> </th> <th class=\"msword-table-header-center dq-assessment-col\"> <p class=\"msword-table-header-center\"> DQ assessment </p> </th> </tr> </thead> <tbody> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x ≤ 10 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> High </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 10 percent < x ≤ 20 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Moderate </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level medium\"> <p class=\"msword-table-text-centered\"> Medium concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 20 percent < x ≤ 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level high\"> <p class=\"msword-table-text-centered\"> High concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x > 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level unusable\"> <p class=\"msword-table-text-centered\"> Unusable </p> </td> </tr> </tbody></table><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"3\"> <p class=\"msword-footnote-text\"> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide “Production of the TAF Research Identifiable Files.” </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"4\"> <p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in managed care, we relied on the managed care plan type information (MC_PLAN_TYPE_CD1_07 through MC_PLAN_TYPE_CD16_07) found in the TAF DE file. CMC programs included beneficiaries enrolled in a CMC plan or a health insuring organization (HIO) (managed care plan type 01 or 04); PCCMs included traditional PCCM provider arrangements and enhanced PCCM provider arrangements (managed care plan type 02 or 03); and BHOs included mental health prepaid inpatient health plans (PIHPs) and prepaid ambulatory health plans (PAHPs), substance use disorder (SUD) PIHPs and PAHPs, and mental health and SUD PIHPs and PAHPs (managed care plan types of 08 through 13). </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-4\" value=\"5\"> <p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in Medicaid, we relied on the CHIP code variable for July (CHIP_CD_07) in the TAF DE file, or eligibility group variable for July (ELGBLTY_GRP_CD_07) if the CHIP code was missing. Medicaid beneficiaries are identified using CHIP code 1 and eligibility group code 1-60 or 69-75. For analyses of 2014 through 2017 TAF, we also use CHIP code 4 (Medicaid and S-CHIP) to identify Medicaid beneficiaries, because CHIP code 4 is a valid value for those TAF data years. </p> <p> <a href=\"#footnote-ref-4\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"3\"><p class=\"msword-footnote-text\"> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide \u201cProduction of the TAF Research Identifiable Files.\u201d </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"4\"><p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in managed care, we relied on the managed care plan type information (MC_PLAN_TYPE_CD1_07 through MC_PLAN_TYPE_CD16_07) found in the TAF DE file. CMC programs included beneficiaries enrolled in a CMC plan or a health insuring organization (HIO) (managed care plan type 01 or 04); PCCMs included traditional PCCM provider arrangements and enhanced PCCM provider arrangements (managed care plan type 02 or 03); and BHOs included mental health prepaid inpatient health plans (PIHPs) and prepaid ambulatory health plans (PAHPs), substance use disorder (SUD) PIHPs and PAHPs, and mental health and SUD PIHPs and PAHPs (managed care plan types of 08 through 13). </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}, {"number": 4, "content": "<li class=\"footnoteBody\" id=\"footnote-4\" value=\"5\"><p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in Medicaid, we relied on the CHIP code variable for July (CHIP_CD_07) in the TAF DE file, or eligibility group variable for July (ELGBLTY_GRP_CD_07) if the CHIP code was missing. Medicaid beneficiaries are identified using CHIP code 1 and eligibility group code 1-60 or 69-75. For analyses of 2014 through 2017 TAF, we also use CHIP code 4 (Medicaid and S-CHIP) to identify Medicaid beneficiaries, because CHIP code 4 is a valid value for those TAF data years. </p><p><a href=\"#footnote-ref-4\">\u2191</a></p></li>"}]}, "summary": {"content": "<p>The TAF eligibility files include information about the enrollment of Medicaid and CHIP beneficiaries into different types of managed care models. Some states enroll beneficiaries in primary care case management (PCCM) programs, in which a primary care practitioner provides a core set of case management services in exchange for an administrative fee, but all other services continue to be delivered on a fee-for-service basis. This analysis examines how well the TAF data on PCCM enrollment align with an external benchmark, the Medicaid Managed Care Enrollment and Program Characteristics report.</p>", "footnotes": []}, "originalIssueBriefId": "4021", "relatedTopics": [{"measureId": 1, "measureName": "Enrollment in CMC Plans", "groupId": 1, "groupName": "Enrollment Benchmarking", "order": 0}, {"measureId": 3, "measureName": "Enrollment in BHO Plans", "groupId": 1, "groupName": "Enrollment Benchmarking", "order": 2}]} |
3 | {"measureId": 3, "measureName": "Enrollment in BHO Plans", "groupId": 1, "groupName": "Enrollment Benchmarking", "pdfVersionLink": "downloads/background-and-methods/TAF-DQ-Enroll-BHO-Plans.pdf", "background": {"content": "<p class=\"msword-paragraph\"> <a id=\"_Hlk30592933\"></a> The majority of Medicaid beneficiaries receive most or all of their care through managed care models. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[1]</a> </sup> </sup> In 2016, the three Medicaid managed care models most commonly used by states were: (1) comprehensive managed care organizations (CMCs), where states pay comprehensive managed care organizations (MCOs) a risk-based capitation rate to cover a broad set of services that typically include acute, primary, and specialty medical services; (2) primary care case management (PCCM), where primary care practitioners provide a core set of case management services in exchange for an administrative fee, but nearly all services continue to be provided on a fee-for-service basis; and (3) limited-benefit plans, including behavioral health organizations (BHOs), where plans manage a subset of services such as treatment for substance use disorders and inpatient or institutional mental health services.</p><p class=\"msword-paragraph\"> All states providing services through managed care plans must report enrollment for beneficiaries covered under such plans; however, the accuracy of T-MSIS enrollment reporting varies considerably across both states and plan types. This data quality assessment examines alignment between July data from the T-MSIS Analytic Files (TAF) and the benchmark, the annual Medicaid Managed Care Enrollment and Program Characteristics (MMCEPC) report. <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[2]</a> </sup> </sup></p><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"> <p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). “Medicaid Managed Care Enrollment and Program Characteristics, 2016.” Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"> <p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). “Medicaid Managed Care Enrollment and Program Characteristics, 2016.” Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"><p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). \u201cMedicaid Managed Care Enrollment and Program Characteristics, 2016.\u201d Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"><p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services (CMS). \u201cMedicaid Managed Care Enrollment and Program Characteristics, 2016.\u201d Spring 2018. Available at <a aria-label=\"View the Medicaid Managed Care Enrollment and Program Characteristics report for 2016\" href=\"https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf\">https://www.medicaid.gov/Medicaid/downloads/2016-medicaid-managed-care-enrollment-report.pdf</a> . Accessed April 10, 2018. </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}]}, "methods": {"content": "<p class=\"msword-paragraph\"> The analysis relies on two main data sources: (1) the TAF annual Demographic and Eligibility (DE) file <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[3]</a> </sup> </sup> and (2) the annual MMCEPC report.</p><ul> <li class=\"msword-list-bullet\"> The TAF DE file contains demographic, eligibility, and enrollment information for all Medicaid and Children’s Health Insurance Program (CHIP) beneficiaries who were enrolled for at least one day during the calendar year. The file contains monthly flags that indicate whether a beneficiary was enrolled for at least one day in a given month in different types of managed care. </li> <li class=\"msword-list-bullet\"> The annual MMCEPC contains data collected directly from states on enrollment in managed care models at the state and plan type levels, as well as information about key program features (for instance, type of enrollment by population group enrolled). The information in the MMCEPC is based on beneficiary enrollment as of July 1 of each year. </li></ul><p class=\"msword-paragraph\"> We compared how well the TAF aligned with the benchmark by measuring the percent difference between the data sources in each month, then averaged the percent difference over all twelve months of the calendar year. We calculated TAF-based enrollment counts for beneficiaries in managed care by using managed care plan type information found in the TAF DE file. To align TAF counts as closely as possible with the benchmark data, we used information about beneficiary enrollment for July of the given year. We first counted the number of beneficiaries enrolled in CMCs, PCCM entities, and BHOs in July <a id=\"_Hlk31805930\"></a> . <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[4]</a> </sup> </sup> We then limited the analysis to beneficiaries enrolled in Medicaid. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-4\" id=\"footnote-ref-4\">[5]</a> </sup> </sup> Because the benchmark data can be viewed as a baseline and the TAF-based calculations as the comparison, the percent difference is calculated as a percent error or change: 100*(TAF – MMCEPC)/MMCEPC. We categorized a state’s enrollment data into one of four categories according to the level of alignment with the benchmark and the corresponding level of data quality concern (Table 1).</p><p class=\"msword-table-title\"> Table 1. <a id=\"_Hlk34816350\"></a> Criteria for DQ assessment of enrollment in managed care</p><table aria-label=\"Table 1. Criteria for DQ assessment of enrollment in managed care\" class=\"dq-assessment-table\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Average monthly percent difference between TAF and MMCEPC enrollment counts </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Level of alignment between TAF and MMCEPC enrollment counts </p> </th> <th class=\"msword-table-header-center dq-assessment-col\"> <p class=\"msword-table-header-center\"> DQ assessment </p> </th> </tr> </thead> <tbody> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x ≤ 10 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> High </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 10 percent < x ≤ 20 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Moderate </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level medium\"> <p class=\"msword-table-text-centered\"> Medium concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 20 percent < x ≤ 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level high\"> <p class=\"msword-table-text-centered\"> High concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x > 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level unusable\"> <p class=\"msword-table-text-centered\"> Unusable </p> </td> </tr> </tbody></table><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"3\"> <p class=\"msword-footnote-text\"> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide “Production of the TAF Research Identifiable Files.” </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"4\"> <p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in managed care, we relied on the managed care plan type information (MC_PLAN_TYPE_CD1_07 through MC_PLAN_TYPE_CD16_07) found in the TAF DE file. CMC programs included beneficiaries enrolled in a CMC plan or a health insuring organization (HIO) (managed care plan type 01 or 04); PCCMs included traditional PCCM provider arrangements and enhanced PCCM provider arrangements (managed care plan type 02 or 03); and BHOs included mental health prepaid inpatient health plans (PIHPs) and prepaid ambulatory health plans (PAHPs), substance use disorder (SUD) PIHPs and PAHPs, and mental health and SUD PIHPs and PAHPs (managed care plan types of 08 through 13). </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-4\" value=\"5\"> <p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in Medicaid, we relied on the CHIP code variable for July (CHIP_CD_07) in the TAF DE file, or eligibility group variable for July (ELGBLTY_GRP_CD_07) if the CHIP code was missing. Medicaid beneficiaries are identified using CHIP code 1 and eligibility group code 1-60 or 69-75. For analyses of 2014 through 2017 TAF, we also use CHIP code 4 (Medicaid and S-CHIP) to identify Medicaid beneficiaries, because CHIP code 4 is a valid value for those TAF data years. </p> <p> <a href=\"#footnote-ref-4\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"3\"><p class=\"msword-footnote-text\"> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide \u201cProduction of the TAF Research Identifiable Files.\u201d </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"4\"><p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in managed care, we relied on the managed care plan type information (MC_PLAN_TYPE_CD1_07 through MC_PLAN_TYPE_CD16_07) found in the TAF DE file. CMC programs included beneficiaries enrolled in a CMC plan or a health insuring organization (HIO) (managed care plan type 01 or 04); PCCMs included traditional PCCM provider arrangements and enhanced PCCM provider arrangements (managed care plan type 02 or 03); and BHOs included mental health prepaid inpatient health plans (PIHPs) and prepaid ambulatory health plans (PAHPs), substance use disorder (SUD) PIHPs and PAHPs, and mental health and SUD PIHPs and PAHPs (managed care plan types of 08 through 13). </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}, {"number": 4, "content": "<li class=\"footnoteBody\" id=\"footnote-4\" value=\"5\"><p class=\"msword-footnote-text\"> To identify beneficiaries enrolled in Medicaid, we relied on the CHIP code variable for July (CHIP_CD_07) in the TAF DE file, or eligibility group variable for July (ELGBLTY_GRP_CD_07) if the CHIP code was missing. Medicaid beneficiaries are identified using CHIP code 1 and eligibility group code 1-60 or 69-75. For analyses of 2014 through 2017 TAF, we also use CHIP code 4 (Medicaid and S-CHIP) to identify Medicaid beneficiaries, because CHIP code 4 is a valid value for those TAF data years. </p><p><a href=\"#footnote-ref-4\">\u2191</a></p></li>"}]}, "summary": {"content": "<p>The TAF eligibility files include information about the enrollment of Medicaid and CHIP beneficiaries into different types of managed care models. Many states enroll beneficiaries in behavioral health organizations (BHOs), which provide mental health and substance use disorder services. This analysis examines how well the TAF data on BHO enrollment align with an external benchmark, the Medicaid Managed Care Enrollment and Program Characteristics report.</p>", "footnotes": []}, "originalIssueBriefId": "4021", "relatedTopics": [{"measureId": 1, "measureName": "Enrollment in CMC Plans", "groupId": 1, "groupName": "Enrollment Benchmarking", "order": 0}, {"measureId": 2, "measureName": "Enrollment in PCCM Programs", "groupId": 1, "groupName": "Enrollment Benchmarking", "order": 1}]} |
4 | {"measureId": 4, "measureName": "M-CHIP and S-CHIP Enrollment", "groupId": 1, "groupName": "Enrollment Benchmarking", "pdfVersionLink": "downloads/background-and-methods/TAF-DQ-MCHIP-SCHIP-Enroll.pdf", "background": {"content": "<p class=\"msword-paragraph\"> Created as part of the Balanced Budget Act of 1997, the Children’s Health Insurance Program (CHIP) provides health care coverage to otherwise uninsured children in low-income families whose income exceeds Medicaid income-eligibility thresholds. <a id=\"_Hlk34139369\"></a> States may use CHIP funds to expand their Medicaid programs (referred to as Medicaid expansion CHIP, or M-CHIP); create a program separate from their existing Medicaid programs (referred to as separate CHIP, or S-CHIP); or adopt a combination of both approaches. Because the CHIP population is important for both program administration and policy, many users of the T\u2011MSIS Analytic Files (TAF) data will want to identify CHIP beneficiaries either to study them explicitly or to exclude them from analyses.</p><p class=\"msword-paragraph\"> There are three relevant data elements in the Annual Demographic and Eligibility (DE) file that can be used to identify different groups of CHIP beneficiaries (Table 1): <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[1]</a> </sup> </sup></p><ol> <li class=\"msword-list-number\"> <strong> CHIP code (CHIP_CD) </strong> is the only data element that can be used alone to distinguish between enrollment in S-CHIP, M-CHIP, or the Medicaid program. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[2]</a> </sup> </sup> </li> <li class=\"msword-list-number\"> <strong> Eligibility group code (ELGBLTY_GRP_CD) </strong> is useful for obtaining detailed information on the eligibility group through which a beneficiary is enrolled in Medicaid or CHIP. However, TAF users cannot use this data element alone to distinguish between Title XXI M-CHIP and S-CHIP beneficiaries. </li> <li class=\"msword-list-number\"> The <strong> number of CHIP enrollment days (CHIP_ENRLMT_DAYS) </strong> specifies how many days an individual was enrolled in S-CHIP during the month. This data element cannot be used to identify beneficiaries in M-CHIP. </li></ol><p class=\"msword-table-title\"> Table 1. Potential DE TAF variables for identifying CHIP beneficiaries</p><table aria-label=\"Table 1. Potential DE TAF variables for identifying CHIP beneficiaries\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Data element </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Use for identifying CHIP beneficiaries </p> </th> </tr> </thead> <tbody> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> CHIP_CD </p> </td> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> Identifies beneficiaries in Medicaid (CHIP_CD = 1), M-CHIP (CHIP_CD = 2), and S-CHIP (CHIP_CD = 3). </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> CHIP_ENRLMT_DAYS </p> </td> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> Constructed from T-MSIS enrollment date and enrollment type variables (ENROLLMENT-EFF-DATE, ENROLLMENT-END-DATE, and ENROLLMENT-TYPE). <br/> The enrollee will have at least one day of S-CHIP enrollment (CHIP_ENRLMT_DAYS > 0) if he or she had an enrollment span that covered at least one day in the month and that enrollment span was classified as S-CHIP (ENROLLMENT-TYPE = 2 [Separate Title XXI CHIP]). </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> ELGBLTY_GRP_CD </p> </td> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> Contains the eligibility group applicable to the individual based on the state’s eligibility determination process. When CHIP_CD is missing, ELGBLTY_GRP_CD can be used to indicate CHIP enrollment (ELGBLTY_GRP_CD = 61–68, with 61 used for both M-CHIP and S-CHIP and 62–68 exclusive to S-CHIP) and Medicaid enrollment (ELGBLTY_GRP_CD = 1–60 or 69–76). </p> </td> </tr> </tbody></table><p class=\"msword-table-source\"> Note: \tThese three data elements are available monthly in the annual DE TAF, with the number of each month appended to the end of the data element name (for instance, CHIP_CD_01 for January, CHIP_CD_02 for February, and so on). For simplicity, we did not list the monthly indicators in this table because we used all months of data. A list of valid values and descriptions of these data elements can be found in the TAF Demographic and Eligibility Codebook at <a aria-label=\"View the TAF Claims Codebook on the Chronic Conditions Data Warehouse Data Dictionaries page\" href=\"https://www2.ccwdata.org/web/guest/data-dictionaries\">https://www2.ccwdata.org/web/guest/data-dictionaries</a> .</p><p class=\"msword-table-source\"> Maintenance assistance status and basis of eligibility, which was constructed from T-MSIS data elements maintenance assistance status and Medicaid basis of eligibility, has been phased out in favor of the new, more detailed eligibility group code; the maintenance assistance status and basis of eligibility code is not recommended for use.</p><p class=\"msword-table-source\"> Enrollment type flag groups M-CHIP with Medicaid beneficiaries and therefore cannot be used to identify all CHIP beneficiaries.</p><p class=\"msword-paragraph-continued\"> Analyses conducted on the 2016 TAF data found that CHIP code is the most reliable data element for counting total enrollment in M-CHIP and S-CHIP across the largest number of states (results not shown). However, in states with high rates of missing data in CHIP code, using eligibility group code may result in more accurate counts of CHIP enrollment. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-4\" id=\"footnote-ref-4\">[3]</a> </sup> </sup> This analysis evaluates whether CHIP code and eligibility group code (when CHIP code is missing) can be used to accurately count total CHIP enrollment in each state. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-5\" id=\"footnote-ref-5\">[4]</a> </sup> </sup></p><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"> <p class=\"msword-footnote-text\"> Two other data elements—Medicaid enrollment days and enrollment type flag—combine Medicaid and M-CHIP beneficiaries. They can be used only in combination with other data elements such as CHIP code and eligibility group code to identify CHIP beneficiaries. Therefore, they are not listed here as potential TAF variables for identifying CHIP beneficiaries. </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"> <p class=\"msword-footnote-text\"> More information on state CHIP programs is available at <a aria-label=\"View more information on state CHIP programs\" href=\"https://www.medicaid.gov/chip/state-program-information/index.html\">https://www.medicaid.gov/chip/state-program-information/index.html</a> and <a aria-label=\"View more information on state CHIP programs\" href=\"https://www.macpac.gov/subtopic/key-design-features/\">https://www.macpac.gov/subtopic/key-design-features/</a> . </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-4\" value=\"3\"> <p class=\"msword-footnote-text\"> TAF users should first verify that their state(s) of interest are reporting data for CHIP beneficiaries. </p> <p> <a href=\"#footnote-ref-4\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-5\" value=\"4\"> <p class=\"msword-footnote-text\"> In some states, CHIP code may be used to accurately count total enrollment but does not differentiate well between M-CHIP and S-CHIP enrollees. </p> <p> <a href=\"#footnote-ref-5\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"><p class=\"msword-footnote-text\"> Two other data elements\u2014Medicaid enrollment days and enrollment type flag\u2014combine Medicaid and M-CHIP beneficiaries. They can be used only in combination with other data elements such as CHIP code and eligibility group code to identify CHIP beneficiaries. Therefore, they are not listed here as potential TAF variables for identifying CHIP beneficiaries. </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"><p class=\"msword-footnote-text\"> More information on state CHIP programs is available at <a aria-label=\"View more information on state CHIP programs\" href=\"https://www.medicaid.gov/chip/state-program-information/index.html\">https://www.medicaid.gov/chip/state-program-information/index.html</a> and <a aria-label=\"View more information on state CHIP programs\" href=\"https://www.macpac.gov/subtopic/key-design-features/\">https://www.macpac.gov/subtopic/key-design-features/</a> . </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}, {"number": 4, "content": "<li class=\"footnoteBody\" id=\"footnote-4\" value=\"3\"><p class=\"msword-footnote-text\"> TAF users should first verify that their state(s) of interest are reporting data for CHIP beneficiaries. </p><p><a href=\"#footnote-ref-4\">\u2191</a></p></li>"}, {"number": 5, "content": "<li class=\"footnoteBody\" id=\"footnote-5\" value=\"4\"><p class=\"msword-footnote-text\"> In some states, CHIP code may be used to accurately count total enrollment but does not differentiate well between M-CHIP and S-CHIP enrollees. </p><p><a href=\"#footnote-ref-5\">\u2191</a></p></li>"}]}, "methods": {"content": "<p class=\"msword-callout\"> The following describes current methods used to assess data quality. Information about methods previously used to assess data quality can be found at the bottom of this section.</p><p class=\"msword-paragraph\"> We used the Eligibility and Enrollment Performance Indicator (PI) data as the external benchmark to examine the accuracy of TAF-based enrollment counts for the CHIP population. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[5]</a> </sup> </sup> The PI data include both M-CHIP and S-CHIP beneficiaries as of the last day of each month. Although some states’ PI data contain quality issues prior to 2017 that may affect their accuracy, these data are the best source available for benchmarking the CHIP population because many of the data quality issues are known, and the data provide a consistent benchmark across multiple data quality assessments. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[6]</a> </sup> </sup></p><p class=\"msword-paragraph\"> In the TAF, we identified CHIP beneficiaries by selecting DE records where CHIP code <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-4\" id=\"footnote-ref-4\">[7]</a> </sup> </sup> was equal to 2 (M-CHIP), 3 (S-CHIP) or 4 (Medicaid and S-CHIP). <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-5\" id=\"footnote-ref-5\">[8]</a> </sup> </sup> If the CHIP code was missing, we counted beneficiaries with an eligibility group code that indicated they were eligible for CHIP benefits (eligibility group code of 61–68). In creating the TAF-based counts, we included individuals enrolled at any point (“ever enrolled”) in the month. We compared the PI and TAF-based counts by (1) evaluating the percent difference between TAF-based enrollment counts and the benchmark, averaged across all 12 months, and (2) examining the standard deviation of this measure to assess variation in the difference across months. The average monthly TAF enrollment count is calculated as the sum of the monthly TAF counts divided by 12, and the average monthly PI enrollment count is calculated as the sum of the monthly PI counts divided by 12. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-6\" id=\"footnote-ref-6\">[9]</a> </sup> </sup> Because the benchmark data can be viewed as a baseline and the TAF-based calculations as the comparison, the percent difference is calculated as a percent error or change: the difference between the TAF and PI counts divided by the PI count and multiplied by 100. The average monthly percent difference is calculated as the sum of the monthly percent differences, divided by 12. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-7\" id=\"footnote-ref-7\">[10]</a> </sup> </sup> The standard deviation of the monthly percent differences between the TAF-based count and the PI count is calculated as the square root of the sum of the squared differences between the monthly percent differences and the average percent difference, divided by 12.</p><p class=\"msword-paragraph\"> Table 2 shows the level of concern for the TAF Medicaid enrollment counts based on both the percent difference and the level of alignment between the TAF and the PI enrollment counts. Although we did not assign the level of concern based on the standard deviation, we provide this information in Table 3, and TAF users may want to consider the monthly variability between TAF and the benchmark when determining whether the data are usable for their analysis <a id=\"_Hlk34136761\"></a> and whether all months are of similar quality.</p><p class=\"msword-table-title\"> Table 2. Criteria for DQ assessment of CHIP enrollment</p><table aria-label=\"Table 2. Criteria for DQ assessment of CHIP enrollment \" class=\"dq-assessment-table\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Average monthly percent difference between TAF and PI enrollment counts </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Level of alignment between TAF and PI enrollment counts </p> </th> <th class=\"msword-table-header-center dq-assessment-col\"> <p class=\"msword-table-header-center\"> DQ assessment </p> </th> </tr> </thead> <tbody> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x ≤ 5 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> High </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 5 percent < x ≤ 10 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Moderate </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 10 percent < x ≤ 20 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level medium\"> <p class=\"msword-table-text-centered\"> Medium concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 20 percent < x ≤ 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level high\"> <p class=\"msword-table-text-centered\"> High concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x > 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level unusable\"> <p class=\"msword-table-text-centered\"> Unusable </p> </td> </tr> </tbody></table><p class=\"msword-header\"> Methods previously used to assess data quality</p><p> <a id=\"_Hlk71024897\"></a> Table 3 includes information about methods previously used to assess data quality and the data years and versions assessed using those methods. Each table record describes how the assessment methods for the listed data years and versions differ from current methods. Aside from those differences, the assessments for these data years and versions align with current methods. All data years and versions not listed in the table are assessed using current methods.</p><p class=\"msword-table-title\"> Table 3. Previously used methods and applicable data years and versions</p><table aria-label=\"Table 3. Previously used methods and applicable data years and versions\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Data year(s) and version(s) </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Description of difference(s) from current methods </p> </th> </tr> </thead> <tbody> <tr> <td> <ul> <li class=\"msword-table-list-bullet\"> 2014 Release 2 </li> <li class=\"msword-table-list-bullet\"> 2015 Release 2 </li> <li class=\"msword-table-list-bullet\"> 2016 Releases 1 and 2 </li> <li class=\"msword-table-list-bullet\"> 2017 Release 1 </li> <li class=\"msword-table-list-bullet\"> 2018 Release 1 </li> <li class=\"msword-table-list-bullet\"> 2019 Preliminary Release </li> </ul> </td> <td> <ul> <li class=\"msword-table-list-bullet\"> CHIP beneficiaries include those identified using CHIP code alone. </li> </ul> </td> </tr> </tbody></table><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"5\"> <p class=\"msword-footnote-text\"> <a id=\"_Hlk37689908\"></a> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide “Production of the TAF Research Identifiable Files.” </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"6\"> <p class=\"msword-footnote-text\"> More information about the PI data set can be found at <a aria-label=\"View more information about the PI data set\" href=\"https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html\">https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html</a> . <a id=\"_Hlk36815293\"></a> In some cases, the PI data in the Atlas may not match exactly the PI data publicly available on Medicaid.gov, because our analysis uses a version of the data set that may have been updated more recently. </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-4\" value=\"7\"> <p class=\"msword-footnote-text\"> TAF users should check that CHIP code differentiates well between M-CHIP and S-CHIP beneficiaries in their state(s) of interest. This can be done by cross-checking CHIP code with eligibility group code and CHIP enrollment days. </p> <p> <a href=\"#footnote-ref-4\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-5\" value=\"8\"> <p class=\"msword-footnote-text\"> <a id=\"_Hlk30510547\"></a> CHIP code of 4 (individual was both Medicaid eligible and S-CHIP eligible during the same month) is not a valid value in later versions of the T-MSIS data dictionary. However, because some states use the code on a small number of records, we included it in tabulations presented in this analysis. </p> <p> <a href=\"#footnote-ref-5\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-6\" value=\"9\"> <p class=\"msword-footnote-text\"> If a state did not report CHIP PI enrollment counts for all months, the average percent difference is calculated based on the months with data. </p> <p> <a href=\"#footnote-ref-6\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-7\" value=\"10\"> <p class=\"msword-footnote-text\"> The difference between TAF and PI enrollment is based on an average of the monthly differences between these two data sources. As a result, it may not equal the difference between the average annual TAF enrollment and average annual PI enrollment. </p> <p> <a href=\"#footnote-ref-7\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"5\"><p class=\"msword-footnote-text\"><a id=\"_Hlk37689908\"></a> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide \u201cProduction of the TAF Research Identifiable Files.\u201d </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"6\"><p class=\"msword-footnote-text\"> More information about the PI data set can be found at <a aria-label=\"View more information about the PI data set\" href=\"https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html\">https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html</a> . <a id=\"_Hlk36815293\"></a> In some cases, the PI data in the Atlas may not match exactly the PI data publicly available on Medicaid.gov, because our analysis uses a version of the data set that may have been updated more recently. </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}, {"number": 4, "content": "<li class=\"footnoteBody\" id=\"footnote-4\" value=\"7\"><p class=\"msword-footnote-text\"> TAF users should check that CHIP code differentiates well between M-CHIP and S-CHIP beneficiaries in their state(s) of interest. This can be done by cross-checking CHIP code with eligibility group code and CHIP enrollment days. </p><p><a href=\"#footnote-ref-4\">\u2191</a></p></li>"}, {"number": 5, "content": "<li class=\"footnoteBody\" id=\"footnote-5\" value=\"8\"><p class=\"msword-footnote-text\"><a id=\"_Hlk30510547\"></a> CHIP code of 4 (individual was both Medicaid eligible and S-CHIP eligible during the same month) is not a valid value in later versions of the T-MSIS data dictionary. However, because some states use the code on a small number of records, we included it in tabulations presented in this analysis. </p><p><a href=\"#footnote-ref-5\">\u2191</a></p></li>"}, {"number": 6, "content": "<li class=\"footnoteBody\" id=\"footnote-6\" value=\"9\"><p class=\"msword-footnote-text\"> If a state did not report CHIP PI enrollment counts for all months, the average percent difference is calculated based on the months with data. </p><p><a href=\"#footnote-ref-6\">\u2191</a></p></li>"}, {"number": 7, "content": "<li class=\"footnoteBody\" id=\"footnote-7\" value=\"10\"><p class=\"msword-footnote-text\"> The difference between TAF and PI enrollment is based on an average of the monthly differences between these two data sources. As a result, it may not equal the difference between the average annual TAF enrollment and average annual PI enrollment. </p><p><a href=\"#footnote-ref-7\">\u2191</a></p></li>"}]}, "summary": {"content": "<p>The TAF eligibility files include information on beneficiaries in both Medicaid and CHIP. CHIP provides coverage to otherwise uninsured children in low-income families whose income exceeds Medicaid eligibility thresholds. States may use CHIP funds to expand their Medicaid program (referred to as M-CHIP), create a separate program (referred to as S-CHIP), or adopt a combination of both approaches. This analysis examines how well the TAF data on total CHIP enrollment align with an external benchmark, the Performance Indicators data set. </p>", "footnotes": []}, "originalIssueBriefId": "4031", "relatedTopics": []} |
5 | {"measureId": 5, "measureName": "Adult Expansion Enrollment", "groupId": 1, "groupName": "Enrollment Benchmarking", "pdfVersionLink": "downloads/background-and-methods/TAF-DQ-Adult-Expansion-Enroll.pdf", "background": {"content": "<p class=\"msword-paragraph\"> Under the Patient Protection and Affordable Care Act of 2010 (the Affordable Care Act), Medicaid eligibility was extended to nearly all adults younger than 65 with an income below 138 percent of the federal poverty level (FPL). <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[1]</a> </sup> </sup> <sup class=\"msword-superscript\"> , </sup> <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[2]</a> </sup> </sup> <sup class=\"msword-superscript\"> , </sup> <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-4\" id=\"footnote-ref-4\">[3]</a> </sup> </sup> In June 2012, the Supreme Court ruled in <em> National Federation of Independent Business v. Sebelius </em> that this Medicaid expansion was not mandatory for states. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-5\" id=\"footnote-ref-5\">[4]</a> </sup> </sup> However, by the end of 2016, 31 states plus the District of Columbia and Puerto Rico (hereafter “states”) had used the authority of the Affordable Care Act to provide Medicaid coverage to low-income adults. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-6\" id=\"footnote-ref-6\">[5]</a> </sup> </sup> <sup> , </sup> <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-7\" id=\"footnote-ref-7\">[6]</a> </sup> </sup> Although the majority of these 33 states expanded Medicaid through an amendment to their Medicaid state plan, about one-quarter of them expanded eligibility through an 1115 demonstration waiver. <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-8\" id=\"footnote-ref-8\">[7]</a> </sup> </sup></p><p class=\"msword-paragraph\"> The Centers for Medicare & Medicaid Services (CMS) requires states to report all Medicaid beneficiaries to a valid eligibility group code in T-MSIS. States that have expanded Medicaid are required to report adult expansion beneficiaries to specific eligibility group codes (codes 72-75). Eligibility group code 72 is designated for newly eligible adult expansion beneficiaries, i.e., those who would not qualify for full Medicaid benefits, benchmark coverage, or benchmark-equivalent coverage under the state’s program rules in place as of December 1, 2009. <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-9\" id=\"footnote-ref-9\">[8]</a> </sup> </sup> Eligibility group codes 73, 74, and 75 are designated for beneficiaries not newly eligible, i.e., those who would qualify under such rules. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-10\" id=\"footnote-ref-10\">[9]</a> </sup> </sup> <sup> , </sup> <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-11\" id=\"footnote-ref-11\">[10]</a> </sup> </sup> However, not all Medicaid expansion states are reporting beneficiaries to these codes. In some cases, this may be a symptom of a broader problem in reporting the new eligibility group code in T-MSIS. This data quality assessment examines the accuracy of the adult expansion enrollment counts derived from the T-MSIS Analytic Files (TAF) by comparing these counts to an external benchmark.</p><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"> <p class=\"msword-footnote-text\"> Adults entitled to Medicare and those pregnant or eligible for Medicaid under another mandatory eligibility group are generally not eligible for the adult expansion group, which includes individuals below 133 percent of the FPL after applying a 5 percent income disregard, equating to an effective coverage limit of 138 percent of the FPL. </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"> <p class=\"msword-footnote-text\"> This expansion population is also known as the VIII Group because the eligibility criteria for this group are defined in Section 1902(10)(VIII) of the Social Security Act. </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-4\" value=\"3\"> <p class=\"msword-footnote-text\"> Paradise, Julia. “Moving Medicaid Forward.” San Francisco, CA: The Kaiser Commission on Medicaid and the Uninsured, March 9, 2015. Available at: <a aria-label=\"View the Moving Medicaid Forward issue brief\" href=\"https://www.kff.org/health-reform/issue-brief/medicaid-moving-forward/\">https://www.kff.org/health-reform/issue-brief/medicaid-moving-forward/</a> . Accessed December 14, 2018. </p> <p> <a href=\"#footnote-ref-4\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-5\" value=\"4\"> <p class=\"msword-footnote-text\"> Rosenbaum, Sara, and Timothy M. Westmoreland. “The Supreme Court’s Surprising Decision on the Medicaid Expansion; How Will the Federal Government and States Proceed?” Health Affairs, vol. 31, no. 8, August 2012. Available at: <a aria-label=\"View the article The Supreme Court’s Surprising Decision On The Medicaid Expansion: How Will The Federal Government And States Proceed?\" href=\"https://www.healthaffairs.org/doi/abs/10.1377/hlthaff.2012.0766\">https://www.healthaffairs.org/doi/abs/10.1377/hlthaff.2012.0766</a> . Accessed December 14, 2018. </p> <p> <a href=\"#footnote-ref-5\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-6\" value=\"5\"> <p class=\"msword-footnote-text\"> Kaiser Family Foundation. “Status of State Action on the Medicaid Expansion Decision.” April 9, 2019. Available at: <a aria-label=\"View Kaiser Family Foundation's State Health Facts Page on Status of State Action on the Medicaid Expansion Decision\" href=\"https://www.kff.org/health-reform/state-indicator/state-activity-around-expanding-medicaid-under-the-affordable-care-act/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22:%20%22asc%22%7D\">https://www.kff.org/health-reform/state-indicator/state-activity-around-expanding-medicaid-under-the-affordable-care-act/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22: %22asc%22%7D</a> . Accessed April 15, 2019. </p> <p> <a href=\"#footnote-ref-6\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-7\" value=\"6\"> <p class=\"msword-footnote-text\"> In addition, five states—Idaho, Maine, Nebraska, Utah, and Virginia—adopted the Medicaid expansion after 2016. Maine did so in 2017 via a ballot initiative and implemented the program in 2019. Idaho, Nebraska, and Utah also adopted the adult expansion via ballot initiative in 2018. Idaho is scheduled to implement the program on January 1, 2020, Nebraska is planning to do so on October 1, 2020, and Utah implemented a limited expansion in April 2019. Virginia’s legislature voted to adopt the adult expansion in 2018 and began enrollment on January 1, 2019. </p> <p> <a href=\"#footnote-ref-7\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-8\" value=\"7\"> <p class=\"msword-footnote-text\"> Arizona, Arkansas, Iowa, Indiana, Kentucky, Michigan, Montana, and New Hampshire expanded Medicaid through an 1115 demonstration waiver. Pennsylvania initially implemented its adult expansion as an 1115 demonstration in 2015 but shifted to a state plan amendment a few months later. </p> <p> <a href=\"#footnote-ref-8\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-9\" value=\"8\"> <p class=\"msword-footnote-text\"> A beneficiary is also considered “newly eligible” if he or she would have been eligible but could not have been enrolled for these benefits or this coverage because the applicable Medicaid waiver or demonstration had limited or capped enrollment as of December 1, 2009. </p> <p> <a href=\"#footnote-ref-9\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-10\" value=\"9\"> <p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services. “Medicaid and CHIP FAQs: Newly Eligible FMAP and Expansion State FMAP.” February 2013. Available at: <a aria-label=\"View Medicaid and CHIP FAQs: Newly Eligible FMAP and Expansion State FMAP\" href=\"http://www.statecoverage.org/files/ACA-FAQ-BHP.pdf\">http://www.statecoverage.org/files/ACA-FAQ-BHP.pdf</a> . Accessed April 15, 2019. </p> <p> <a href=\"#footnote-ref-10\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-11\" value=\"10\"> <p class=\"msword-footnote-text\"> States that met certain statutory criteria for health benefits coverage, as described in section 1905(z)(3) of the Affordable Care Act, qualified for increased Federal Medical Assistance Percentage (FMAP) rates for a subset of the \"not newly eligible\" population. These states were designated as 1905(z)(3) expansion states. Eligibility group 73 identifies not newly eligible beneficiaries for non-1905(z)(3) states. Eligibility groups 74 and 75 identify not newly eligible beneficiaries for 1905(z)(3) states, with eligibility group 74 specifying parents, caretakers, or relatives of expansion beneficiaries. </p> <p> <a href=\"#footnote-ref-11\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"><p class=\"msword-footnote-text\"> Adults entitled to Medicare and those pregnant or eligible for Medicaid under another mandatory eligibility group are generally not eligible for the adult expansion group, which includes individuals below 133 percent of the FPL after applying a 5 percent income disregard, equating to an effective coverage limit of 138 percent of the FPL. </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"><p class=\"msword-footnote-text\"> This expansion population is also known as the VIII Group because the eligibility criteria for this group are defined in Section 1902(10)(VIII) of the Social Security Act. </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}, {"number": 4, "content": "<li class=\"footnoteBody\" id=\"footnote-4\" value=\"3\"><p class=\"msword-footnote-text\"> Paradise, Julia. \u201cMoving Medicaid Forward.\u201d San Francisco, CA: The Kaiser Commission on Medicaid and the Uninsured, March 9, 2015. Available at: <a aria-label=\"View the Moving Medicaid Forward issue brief\" href=\"https://www.kff.org/health-reform/issue-brief/medicaid-moving-forward/\">https://www.kff.org/health-reform/issue-brief/medicaid-moving-forward/</a> . Accessed December 14, 2018. </p><p><a href=\"#footnote-ref-4\">\u2191</a></p></li>"}, {"number": 5, "content": "<li class=\"footnoteBody\" id=\"footnote-5\" value=\"4\"><p class=\"msword-footnote-text\"> Rosenbaum, Sara, and Timothy M. Westmoreland. \u201cThe Supreme Court\u2019s Surprising Decision on the Medicaid Expansion; How Will the Federal Government and States Proceed?\u201d Health Affairs, vol. 31, no. 8, August 2012. Available at: <a aria-label=\"View the article The Supreme Court\u2019s Surprising Decision On The Medicaid Expansion: How Will The Federal Government And States Proceed?\" href=\"https://www.healthaffairs.org/doi/abs/10.1377/hlthaff.2012.0766\">https://www.healthaffairs.org/doi/abs/10.1377/hlthaff.2012.0766</a> . Accessed December 14, 2018. </p><p><a href=\"#footnote-ref-5\">\u2191</a></p></li>"}, {"number": 6, "content": "<li class=\"footnoteBody\" id=\"footnote-6\" value=\"5\"><p class=\"msword-footnote-text\"> Kaiser Family Foundation. \u201cStatus of State Action on the Medicaid Expansion Decision.\u201d April 9, 2019. Available at: <a aria-label=\"View Kaiser Family Foundation's State Health Facts Page on Status of State Action on the Medicaid Expansion Decision\" href=\"https://www.kff.org/health-reform/state-indicator/state-activity-around-expanding-medicaid-under-the-affordable-care-act/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22:%20%22asc%22%7D\">https://www.kff.org/health-reform/state-indicator/state-activity-around-expanding-medicaid-under-the-affordable-care-act/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22: %22asc%22%7D</a> . Accessed April 15, 2019. </p><p><a href=\"#footnote-ref-6\">\u2191</a></p></li>"}, {"number": 7, "content": "<li class=\"footnoteBody\" id=\"footnote-7\" value=\"6\"><p class=\"msword-footnote-text\"> In addition, five states\u2014Idaho, Maine, Nebraska, Utah, and Virginia\u2014adopted the Medicaid expansion after 2016. Maine did so in 2017 via a ballot initiative and implemented the program in 2019. Idaho, Nebraska, and Utah also adopted the adult expansion via ballot initiative in 2018. Idaho is scheduled to implement the program on January 1, 2020, Nebraska is planning to do so on October 1, 2020, and Utah implemented a limited expansion in April 2019. Virginia\u2019s legislature voted to adopt the adult expansion in 2018 and began enrollment on January 1, 2019. </p><p><a href=\"#footnote-ref-7\">\u2191</a></p></li>"}, {"number": 8, "content": "<li class=\"footnoteBody\" id=\"footnote-8\" value=\"7\"><p class=\"msword-footnote-text\"> Arizona, Arkansas, Iowa, Indiana, Kentucky, Michigan, Montana, and New Hampshire expanded Medicaid through an 1115 demonstration waiver. Pennsylvania initially implemented its adult expansion as an 1115 demonstration in 2015 but shifted to a state plan amendment a few months later. </p><p><a href=\"#footnote-ref-8\">\u2191</a></p></li>"}, {"number": 9, "content": "<li class=\"footnoteBody\" id=\"footnote-9\" value=\"8\"><p class=\"msword-footnote-text\"> A beneficiary is also considered \u201cnewly eligible\u201d if he or she would have been eligible but could not have been enrolled for these benefits or this coverage because the applicable Medicaid waiver or demonstration had limited or capped enrollment as of December 1, 2009. </p><p><a href=\"#footnote-ref-9\">\u2191</a></p></li>"}, {"number": 10, "content": "<li class=\"footnoteBody\" id=\"footnote-10\" value=\"9\"><p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services. \u201cMedicaid and CHIP FAQs: Newly Eligible FMAP and Expansion State FMAP.\u201d February 2013. Available at: <a aria-label=\"View Medicaid and CHIP FAQs: Newly Eligible FMAP and Expansion State FMAP\" href=\"http://www.statecoverage.org/files/ACA-FAQ-BHP.pdf\">http://www.statecoverage.org/files/ACA-FAQ-BHP.pdf</a> . Accessed April 15, 2019. </p><p><a href=\"#footnote-ref-10\">\u2191</a></p></li>"}, {"number": 11, "content": "<li class=\"footnoteBody\" id=\"footnote-11\" value=\"10\"><p class=\"msword-footnote-text\"> States that met certain statutory criteria for health benefits coverage, as described in section 1905(z)(3) of the Affordable Care Act, qualified for increased Federal Medical Assistance Percentage (FMAP) rates for a subset of the \"not newly eligible\" population. These states were designated as 1905(z)(3) expansion states. Eligibility group 73 identifies not newly eligible beneficiaries for non-1905(z)(3) states. Eligibility groups 74 and 75 identify not newly eligible beneficiaries for 1905(z)(3) states, with eligibility group 74 specifying parents, caretakers, or relatives of expansion beneficiaries. </p><p><a href=\"#footnote-ref-11\">\u2191</a></p></li>"}]}, "methods": {"content": "<p class=\"msword-paragraph\"> We used Medicaid Budget and Expenditure System (MBES) enrollment data as the external benchmark to examine the accuracy of the TAF-based enrollment counts for the adult expansion group. <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[11]</a> </sup> </sup> We examined adult expansion population enrollment as a whole and for the subset of newly eligible beneficiaries using the TAF annual Demographic & Eligibility (DE) file. The MBES data are submitted by states to CMS on Form CMS-64 and include aggregated monthly counts of total Medicaid enrollment, enrollment for Medicaid beneficiaries in the adult expansion group, and enrollment for the subsets of newly eligible and not newly eligible adult expansion beneficiaries. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[12]</a> </sup> </sup> Substantial differences between the TAF-based counts and MBES counts raise concerns about the validity of a state’s T-MSIS reporting.</p><p class=\"msword-paragraph\"> To investigate this issue, we obtained a monthly count of beneficiaries with eligibility group codes in the TAF DE file that indicated they were in the adult expansion group (ELGBLTY_GRP_CD_mm = 72, 73, 74, or 75). These codes indicate that individuals were eligible for and enrolled in Medicaid in a given month under one of the adult expansion group categories, in which a value of 72 designates newly eligible beneficiaries, and a value of 73, 74, or 75 designates beneficiaries who are not newly eligible. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-4\" id=\"footnote-ref-4\">[13]</a> </sup> </sup></p><p class=\"msword-paragraph\"> We also obtained a monthly count of the VIII Group enrollees and VIII Group newly eligible enrollees reported by states in the MBES data. For the adult expansion population and for the newly eligible subset in each state and each month, we calculated a percent difference between the TAF-based enrollment counts and the benchmark, and then averaged the monthly percent difference across all 12 months of the calendar year. We also examined the standard deviation of this measure to assess the variation in the difference across months. Because the benchmark data can be viewed as a baseline and the TAF-based calculations as the comparison, we calculated the percent difference as a percent error or change: the difference between the TAF and MBES counts divided by the MBES count.</p><p class=\"msword-paragraph\"> We evaluated the average percent difference against the thresholds listed in Table 1 to categorize the states into levels of concern about data quality according to the alignment between the counts of beneficiaries reported in the TAF DE and the counts in the benchmark. Although we did not assign the level of concern based on the standard deviation, we provide this information in the table, and TAF users may want to consider the monthly variability between TAF and the benchmark when determining whether the data are usable for their analysis.</p><p class=\"msword-table-title\"> Table 1. Criteria for DQ assessment of enrollment in adult expansion group</p><table aria-label=\"Table 1. Criteria for DQ assessment of enrollment in adult expansion group \" class=\"dq-assessment-table\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Average monthly percent difference between TAF and MBES enrollment counts </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Level of alignment with between TAF and MBES enrollment counts </p> </th> <th class=\"msword-table-header-center dq-assessment-col\"> <p class=\"msword-table-header-center\"> DQ assessment </p> </th> </tr> </thead> <tbody> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x ≤ 5 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> High </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 5 percent < x ≤ 10 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Moderate </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 10 percent < x ≤ 20 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level medium\"> <p class=\"msword-table-text-centered\"> Medium concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 20 percent < x ≤ 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level high\"> <p class=\"msword-table-text-centered\"> High concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x > 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level unusable\"> <p class=\"msword-table-text-centered\"> Unusable </p> </td> </tr> </tbody></table><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"11\"> <p class=\"msword-footnote-text\"> <a id=\"_Hlk37689908\"></a> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide “Production of the TAF Research Identifiable Files.” </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"12\"> <p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services. “Medicaid Enrollment Data Collected Through MBES.” November 2018. Available at <a aria-label=\"View Medicaid Enrollment Data Collected Through MBES\" href=\"https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/enrollment-mbes/index.html\">https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/enrollment-mbes/index.html</a> . Accessed December 24, 2018. </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-4\" value=\"13\"> <p class=\"msword-footnote-text\"> <a id=\"_Hlk35496373\"></a> In early years of T-MSIS reporting, at least one state (Pennsylvania) reported its adult expansion beneficiaries using eligibility group code 71 (other expansions under 1115 authority). Because other states use this eligibility group code to identify non-expansion populations covered under the 1115 authority, it was not used in this analysis to calculate TAF-based counts of the adult expansion population. </p> <p> <a href=\"#footnote-ref-4\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"11\"><p class=\"msword-footnote-text\"><a id=\"_Hlk37689908\"></a> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide \u201cProduction of the TAF Research Identifiable Files.\u201d </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"12\"><p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services. \u201cMedicaid Enrollment Data Collected Through MBES.\u201d November 2018. Available at <a aria-label=\"View Medicaid Enrollment Data Collected Through MBES\" href=\"https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/enrollment-mbes/index.html\">https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/enrollment-mbes/index.html</a> . Accessed December 24, 2018. </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}, {"number": 4, "content": "<li class=\"footnoteBody\" id=\"footnote-4\" value=\"13\"><p class=\"msword-footnote-text\"><a id=\"_Hlk35496373\"></a> In early years of T-MSIS reporting, at least one state (Pennsylvania) reported its adult expansion beneficiaries using eligibility group code 71 (other expansions under 1115 authority). Because other states use this eligibility group code to identify non-expansion populations covered under the 1115 authority, it was not used in this analysis to calculate TAF-based counts of the adult expansion population. </p><p><a href=\"#footnote-ref-4\">\u2191</a></p></li>"}]}, "summary": {"content": "<p>Under the Affordable Care Act, some states elected to expand coverage to all low-income adults with an income below 138 percent of the federal poverty level. This analysis examines how well the TAF data on enrollment in the adult expansion group align with an external benchmark, the Medicaid Budget and Expenditure System.</p>", "footnotes": []}, "originalIssueBriefId": "4041", "relatedTopics": [{"measureId": 6, "measureName": "Newly Eligible Adult Enrollment", "groupId": 1, "groupName": "Enrollment Benchmarking", "order": 1}]} |
6 | {"measureId": 6, "measureName": "Newly Eligible Adult Enrollment", "groupId": 1, "groupName": "Enrollment Benchmarking", "pdfVersionLink": "downloads/background-and-methods/TAF-DQ-Newly-Elig-Adult-Enroll.pdf", "background": {"content": "<p class=\"msword-paragraph\"> Under the Patient Protection and Affordable Care Act of 2010 (the Affordable Care Act), Medicaid eligibility was extended to nearly all adults younger than 65 with an income below 138 percent of the federal poverty level (FPL). <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[1]</a> </sup> </sup> <sup class=\"msword-superscript\"> , </sup> <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[2]</a> </sup> </sup> <sup class=\"msword-superscript\"> , </sup> <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-4\" id=\"footnote-ref-4\">[3]</a> </sup> </sup> In June 2012, the Supreme Court ruled in <em> National Federation of Independent Business v. Sebelius </em> that this Medicaid expansion was not mandatory for states. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-5\" id=\"footnote-ref-5\">[4]</a> </sup> </sup> However, by the end of 2016, 31 states plus the District of Columbia and Puerto Rico (hereafter “states”) had used the authority of the Affordable Care Act to provide Medicaid coverage to low-income adults. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-6\" id=\"footnote-ref-6\">[5]</a> </sup> </sup> <sup> , </sup> <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-7\" id=\"footnote-ref-7\">[6]</a> </sup> </sup> Although the majority of these 33 states expanded Medicaid through an amendment to their Medicaid state plan, about one-quarter of them expanded eligibility through an 1115 demonstration waiver. <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-8\" id=\"footnote-ref-8\">[7]</a> </sup> </sup></p><p class=\"msword-paragraph\"> The Centers for Medicare & Medicaid Services (CMS) requires states to report all Medicaid beneficiaries to a valid eligibility group code in T-MSIS. States that have expanded Medicaid are required to report adult expansion beneficiaries to specific eligibility group codes (codes 72-75). Eligibility group code 72 is designated for newly eligible adult expansion beneficiaries, i.e., those who would not qualify for full Medicaid benefits, benchmark coverage, or benchmark-equivalent coverage under the state’s program rules in place as of December 1, 2009. <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-9\" id=\"footnote-ref-9\">[8]</a> </sup> </sup> Eligibility group codes 73, 74, and 75 are designated for beneficiaries not newly eligible, i.e., those who would qualify under such rules. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-10\" id=\"footnote-ref-10\">[9]</a> </sup> </sup> <sup> , </sup> <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-11\" id=\"footnote-ref-11\">[10]</a> </sup> </sup> However, not all Medicaid expansion states are reporting beneficiaries to these codes. In some cases, this may be a symptom of a broader problem in reporting the new eligibility group code in T-MSIS. This data quality assessment examines the accuracy of the adult expansion enrollment counts derived from the T-MSIS Analytic Files (TAF) by comparing these counts to an external benchmark.</p><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"> <p class=\"msword-footnote-text\"> Adults entitled to Medicare and those pregnant or eligible for Medicaid under another mandatory eligibility group are generally not eligible for the adult expansion group, which includes individuals below 133 percent of the FPL after applying a 5 percent income disregard, equating to an effective coverage limit of 138 percent of the FPL. </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"> <p class=\"msword-footnote-text\"> This expansion population is also known as the VIII Group because the eligibility criteria for this group are defined in Section 1902(10)(VIII) of the Social Security Act. </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-4\" value=\"3\"> <p class=\"msword-footnote-text\"> Paradise, Julia. “Moving Medicaid Forward.” San Francisco, CA: The Kaiser Commission on Medicaid and the Uninsured, March 9, 2015. Available at: <a aria-label=\"View the Moving Medicaid Forward issue brief\" href=\"https://www.kff.org/health-reform/issue-brief/medicaid-moving-forward/\">https://www.kff.org/health-reform/issue-brief/medicaid-moving-forward/</a> . Accessed December 14, 2018. </p> <p> <a href=\"#footnote-ref-4\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-5\" value=\"4\"> <p class=\"msword-footnote-text\"> Rosenbaum, Sara, and Timothy M. Westmoreland. “The Supreme Court’s Surprising Decision on the Medicaid Expansion; How Will the Federal Government and States Proceed?” Health Affairs, vol. 31, no. 8, August 2012. Available at: <a aria-label=\"View the article The Supreme Court’s Surprising Decision On The Medicaid Expansion: How Will The Federal Government And States Proceed?\" href=\"https://www.healthaffairs.org/doi/abs/10.1377/hlthaff.2012.0766\">https://www.healthaffairs.org/doi/abs/10.1377/hlthaff.2012.0766</a> . Accessed December 14, 2018. </p> <p> <a href=\"#footnote-ref-5\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-6\" value=\"5\"> <p class=\"msword-footnote-text\"> Kaiser Family Foundation. “Status of State Action on the Medicaid Expansion Decision.” April 9, 2019. Available at: <a aria-label=\"View Kaiser Family Foundation's State Health Facts Page on Status of State Action on the Medicaid Expansion Decision\" href=\"https://www.kff.org/health-reform/state-indicator/state-activity-around-expanding-medicaid-under-the-affordable-care-act/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22:%20%22asc%22%7D\">https://www.kff.org/health-reform/state-indicator/state-activity-around-expanding-medicaid-under-the-affordable-care-act/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22: %22asc%22%7D</a> . Accessed April 15, 2019. </p> <p> <a href=\"#footnote-ref-6\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-7\" value=\"6\"> <p class=\"msword-footnote-text\"> In addition, five states—Idaho, Maine, Nebraska, Utah, and Virginia—adopted the Medicaid expansion after 2016. Maine did so in 2017 via a ballot initiative and implemented the program in 2019. Idaho, Nebraska, and Utah also adopted the adult expansion via ballot initiative in 2018. Idaho is scheduled to implement the program on January 1, 2020, Nebraska is planning to do so on October 1, 2020, and Utah implemented a limited expansion in April 2019. Virginia’s legislature voted to adopt the adult expansion in 2018 and began enrollment on January 1, 2019. </p> <p> <a href=\"#footnote-ref-7\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-8\" value=\"7\"> <p class=\"msword-footnote-text\"> Arizona, Arkansas, Iowa, Indiana, Kentucky, Michigan, Montana, and New Hampshire expanded Medicaid through an 1115 demonstration waiver. Pennsylvania initially implemented its adult expansion as an 1115 demonstration in 2015 but shifted to a state plan amendment a few months later. </p> <p> <a href=\"#footnote-ref-8\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-9\" value=\"8\"> <p class=\"msword-footnote-text\"> A beneficiary is also considered “newly eligible” if he or she would have been eligible but could not have been enrolled for these benefits or this coverage because the applicable Medicaid waiver or demonstration had limited or capped enrollment as of December 1, 2009. </p> <p> <a href=\"#footnote-ref-9\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-10\" value=\"9\"> <p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services. “Medicaid and CHIP FAQs: Newly Eligible FMAP and Expansion State FMAP.” February 2013. Available at: <a aria-label=\"View Medicaid and CHIP FAQs: Newly Eligible FMAP and Expansion State FMAP\" href=\"http://www.statecoverage.org/files/ACA-FAQ-BHP.pdf\">http://www.statecoverage.org/files/ACA-FAQ-BHP.pdf</a> . Accessed April 15, 2019. </p> <p> <a href=\"#footnote-ref-10\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-11\" value=\"10\"> <p class=\"msword-footnote-text\"> States that met certain statutory criteria for health benefits coverage, as described in section 1905(z)(3) of the Affordable Care Act, qualified for increased Federal Medical Assistance Percentage (FMAP) rates for a subset of the \"not newly eligible\" population. These states were designated as 1905(z)(3) expansion states. Eligibility group 73 identifies not newly eligible beneficiaries for non-1905(z)(3) states. Eligibility groups 74 and 75 identify not newly eligible beneficiaries for 1905(z)(3) states, with eligibility group 74 specifying parents, caretakers, or relatives of expansion beneficiaries. </p> <p> <a href=\"#footnote-ref-11\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"><p class=\"msword-footnote-text\"> Adults entitled to Medicare and those pregnant or eligible for Medicaid under another mandatory eligibility group are generally not eligible for the adult expansion group, which includes individuals below 133 percent of the FPL after applying a 5 percent income disregard, equating to an effective coverage limit of 138 percent of the FPL. </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"><p class=\"msword-footnote-text\"> This expansion population is also known as the VIII Group because the eligibility criteria for this group are defined in Section 1902(10)(VIII) of the Social Security Act. </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}, {"number": 4, "content": "<li class=\"footnoteBody\" id=\"footnote-4\" value=\"3\"><p class=\"msword-footnote-text\"> Paradise, Julia. \u201cMoving Medicaid Forward.\u201d San Francisco, CA: The Kaiser Commission on Medicaid and the Uninsured, March 9, 2015. Available at: <a aria-label=\"View the Moving Medicaid Forward issue brief\" href=\"https://www.kff.org/health-reform/issue-brief/medicaid-moving-forward/\">https://www.kff.org/health-reform/issue-brief/medicaid-moving-forward/</a> . Accessed December 14, 2018. </p><p><a href=\"#footnote-ref-4\">\u2191</a></p></li>"}, {"number": 5, "content": "<li class=\"footnoteBody\" id=\"footnote-5\" value=\"4\"><p class=\"msword-footnote-text\"> Rosenbaum, Sara, and Timothy M. Westmoreland. \u201cThe Supreme Court\u2019s Surprising Decision on the Medicaid Expansion; How Will the Federal Government and States Proceed?\u201d Health Affairs, vol. 31, no. 8, August 2012. Available at: <a aria-label=\"View the article The Supreme Court\u2019s Surprising Decision On The Medicaid Expansion: How Will The Federal Government And States Proceed?\" href=\"https://www.healthaffairs.org/doi/abs/10.1377/hlthaff.2012.0766\">https://www.healthaffairs.org/doi/abs/10.1377/hlthaff.2012.0766</a> . Accessed December 14, 2018. </p><p><a href=\"#footnote-ref-5\">\u2191</a></p></li>"}, {"number": 6, "content": "<li class=\"footnoteBody\" id=\"footnote-6\" value=\"5\"><p class=\"msword-footnote-text\"> Kaiser Family Foundation. \u201cStatus of State Action on the Medicaid Expansion Decision.\u201d April 9, 2019. Available at: <a aria-label=\"View Kaiser Family Foundation's State Health Facts Page on Status of State Action on the Medicaid Expansion Decision\" href=\"https://www.kff.org/health-reform/state-indicator/state-activity-around-expanding-medicaid-under-the-affordable-care-act/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22:%20%22asc%22%7D\">https://www.kff.org/health-reform/state-indicator/state-activity-around-expanding-medicaid-under-the-affordable-care-act/?currentTimeframe=0&sortModel=%7B%22colId%22:%22Location%22,%22sort%22: %22asc%22%7D</a> . Accessed April 15, 2019. </p><p><a href=\"#footnote-ref-6\">\u2191</a></p></li>"}, {"number": 7, "content": "<li class=\"footnoteBody\" id=\"footnote-7\" value=\"6\"><p class=\"msword-footnote-text\"> In addition, five states\u2014Idaho, Maine, Nebraska, Utah, and Virginia\u2014adopted the Medicaid expansion after 2016. Maine did so in 2017 via a ballot initiative and implemented the program in 2019. Idaho, Nebraska, and Utah also adopted the adult expansion via ballot initiative in 2018. Idaho is scheduled to implement the program on January 1, 2020, Nebraska is planning to do so on October 1, 2020, and Utah implemented a limited expansion in April 2019. Virginia\u2019s legislature voted to adopt the adult expansion in 2018 and began enrollment on January 1, 2019. </p><p><a href=\"#footnote-ref-7\">\u2191</a></p></li>"}, {"number": 8, "content": "<li class=\"footnoteBody\" id=\"footnote-8\" value=\"7\"><p class=\"msword-footnote-text\"> Arizona, Arkansas, Iowa, Indiana, Kentucky, Michigan, Montana, and New Hampshire expanded Medicaid through an 1115 demonstration waiver. Pennsylvania initially implemented its adult expansion as an 1115 demonstration in 2015 but shifted to a state plan amendment a few months later. </p><p><a href=\"#footnote-ref-8\">\u2191</a></p></li>"}, {"number": 9, "content": "<li class=\"footnoteBody\" id=\"footnote-9\" value=\"8\"><p class=\"msword-footnote-text\"> A beneficiary is also considered \u201cnewly eligible\u201d if he or she would have been eligible but could not have been enrolled for these benefits or this coverage because the applicable Medicaid waiver or demonstration had limited or capped enrollment as of December 1, 2009. </p><p><a href=\"#footnote-ref-9\">\u2191</a></p></li>"}, {"number": 10, "content": "<li class=\"footnoteBody\" id=\"footnote-10\" value=\"9\"><p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services. \u201cMedicaid and CHIP FAQs: Newly Eligible FMAP and Expansion State FMAP.\u201d February 2013. Available at: <a aria-label=\"View Medicaid and CHIP FAQs: Newly Eligible FMAP and Expansion State FMAP\" href=\"http://www.statecoverage.org/files/ACA-FAQ-BHP.pdf\">http://www.statecoverage.org/files/ACA-FAQ-BHP.pdf</a> . Accessed April 15, 2019. </p><p><a href=\"#footnote-ref-10\">\u2191</a></p></li>"}, {"number": 11, "content": "<li class=\"footnoteBody\" id=\"footnote-11\" value=\"10\"><p class=\"msword-footnote-text\"> States that met certain statutory criteria for health benefits coverage, as described in section 1905(z)(3) of the Affordable Care Act, qualified for increased Federal Medical Assistance Percentage (FMAP) rates for a subset of the \"not newly eligible\" population. These states were designated as 1905(z)(3) expansion states. Eligibility group 73 identifies not newly eligible beneficiaries for non-1905(z)(3) states. Eligibility groups 74 and 75 identify not newly eligible beneficiaries for 1905(z)(3) states, with eligibility group 74 specifying parents, caretakers, or relatives of expansion beneficiaries. </p><p><a href=\"#footnote-ref-11\">\u2191</a></p></li>"}]}, "methods": {"content": "<p class=\"msword-paragraph\"> We used Medicaid Budget and Expenditure System (MBES) enrollment data as the external benchmark to examine the accuracy of the TAF-based enrollment counts for the adult expansion group. <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[11]</a> </sup> </sup> We examined adult expansion population enrollment as a whole and for the subset of newly eligible beneficiaries using the TAF annual Demographic & Eligibility (DE) file. The MBES data are submitted by states to CMS on Form CMS-64 and include aggregated monthly counts of total Medicaid enrollment, enrollment for Medicaid beneficiaries in the adult expansion group, and enrollment for the subsets of newly eligible and not newly eligible adult expansion beneficiaries. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[12]</a> </sup> </sup> Substantial differences between the TAF-based counts and MBES counts raise concerns about the validity of a state’s T-MSIS reporting.</p><p class=\"msword-paragraph\"> To investigate this issue, we obtained a monthly count of beneficiaries with eligibility group codes in the TAF DE file that indicated they were in the adult expansion group (ELGBLTY_GRP_CD_mm = 72, 73, 74, or 75). These codes indicate that individuals were eligible for and enrolled in Medicaid in a given month under one of the adult expansion group categories, in which a value of 72 designates newly eligible beneficiaries, and a value of 73, 74, or 75 designates beneficiaries who are not newly eligible. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-4\" id=\"footnote-ref-4\">[13]</a> </sup> </sup></p><p class=\"msword-paragraph\"> We also obtained a monthly count of the VIII Group enrollees and VIII Group newly eligible enrollees reported by states in the MBES data. For the adult expansion population and for the newly eligible subset in each state and each month, we calculated a percent difference between the TAF-based enrollment counts and the benchmark, and then averaged the monthly percent difference across all 12 months of the calendar year. We also examined the standard deviation of this measure to assess the variation in the difference across months. Because the benchmark data can be viewed as a baseline and the TAF-based calculations as the comparison, we calculated the percent difference as a percent error or change: the difference between the TAF and MBES counts divided by the MBES count.</p><p class=\"msword-paragraph\"> We evaluated the average percent difference against the thresholds listed in Table 1 to categorize the states into levels of concern about data quality according to the alignment between the counts of beneficiaries reported in the TAF DE and the counts in the benchmark. Although we did not assign the level of concern based on the standard deviation, we provide this information in the table, and TAF users may want to consider the monthly variability between TAF and the benchmark when determining whether the data are usable for their analysis.</p><p class=\"msword-table-title\"> Table 1. Criteria for DQ assessment of enrollment in adult expansion group</p><table aria-label=\"Table 1. Criteria for DQ assessment of enrollment in adult expansion group \" class=\"dq-assessment-table\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Average monthly percent difference between TAF and MBES enrollment counts </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Level of alignment with between TAF and MBES enrollment counts </p> </th> <th class=\"msword-table-header-center dq-assessment-col\"> <p class=\"msword-table-header-center\"> DQ assessment </p> </th> </tr> </thead> <tbody> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x ≤ 5 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> High </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 5 percent < x ≤ 10 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Moderate </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 10 percent < x ≤ 20 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level medium\"> <p class=\"msword-table-text-centered\"> Medium concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 20 percent < x ≤ 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level high\"> <p class=\"msword-table-text-centered\"> High concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x > 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level unusable\"> <p class=\"msword-table-text-centered\"> Unusable </p> </td> </tr> </tbody></table><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"11\"> <p class=\"msword-footnote-text\"> <a id=\"_Hlk37689908\"></a> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide “Production of the TAF Research Identifiable Files.” </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"12\"> <p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services. “Medicaid Enrollment Data Collected Through MBES.” November 2018. Available at <a aria-label=\"View Medicaid Enrollment Data Collected Through MBES\" href=\"https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/enrollment-mbes/index.html\">https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/enrollment-mbes/index.html</a> . Accessed December 24, 2018. </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-4\" value=\"13\"> <p class=\"msword-footnote-text\"> <a id=\"_Hlk35496373\"></a> In early years of T-MSIS reporting, at least one state (Pennsylvania) reported its adult expansion beneficiaries using eligibility group code 71 (other expansions under 1115 authority). Because other states use this eligibility group code to identify non-expansion populations covered under the 1115 authority, it was not used in this analysis to calculate TAF-based counts of the adult expansion population. </p> <p> <a href=\"#footnote-ref-4\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"11\"><p class=\"msword-footnote-text\"><a id=\"_Hlk37689908\"></a> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources page</a> , and a crosswalk of variable names can be found in the guide \u201cProduction of the TAF Research Identifiable Files.\u201d </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"12\"><p class=\"msword-footnote-text\"> Centers for Medicare & Medicaid Services. \u201cMedicaid Enrollment Data Collected Through MBES.\u201d November 2018. Available at <a aria-label=\"View Medicaid Enrollment Data Collected Through MBES\" href=\"https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/enrollment-mbes/index.html\">https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/enrollment-mbes/index.html</a> . Accessed December 24, 2018. </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}, {"number": 4, "content": "<li class=\"footnoteBody\" id=\"footnote-4\" value=\"13\"><p class=\"msword-footnote-text\"><a id=\"_Hlk35496373\"></a> In early years of T-MSIS reporting, at least one state (Pennsylvania) reported its adult expansion beneficiaries using eligibility group code 71 (other expansions under 1115 authority). Because other states use this eligibility group code to identify non-expansion populations covered under the 1115 authority, it was not used in this analysis to calculate TAF-based counts of the adult expansion population. </p><p><a href=\"#footnote-ref-4\">\u2191</a></p></li>"}]}, "summary": {"content": "<p>Under the Affordable Care Act, some states elected to expand coverage to all low-income adults with an income below 138 percent of the federal poverty level. Individuals in the adult expansion group are considered \"newly eligible\" if they would not have qualified for Medicaid coverage under the eligibility rules in place as of December 1, 2009. This analysis examines how well the TAF data on newly eligible adult enrollment align with an external benchmark, the Medicaid Budget and Expenditure System.</p>", "footnotes": []}, "originalIssueBriefId": "4041", "relatedTopics": [{"measureId": 5, "measureName": "Adult Expansion Enrollment", "groupId": 1, "groupName": "Enrollment Benchmarking", "order": 0}]} |
7 | {"measureId": 7, "measureName": "Total Medicaid and CHIP Enrollment", "groupId": 1, "groupName": "Enrollment Benchmarking", "pdfVersionLink": "downloads/background-and-methods/TAF-DQ-Total-Enroll.pdf", "background": {"content": "<p class=\"msword-paragraph\"> The research-ready T\u2011MSIS Analytic Files (TAF), are an enhanced set of data on beneficiaries in Medicaid and the Children’s Health Insurance Program (CHIP), their claims, and the participating managed care plans and providers that serve them. The TAF eligibility files contain beneficiaries enrolled in Medicaid or CHIP at any point during the year, including beneficiaries who qualify for comprehensive medical coverage as well as those who only qualify for limited benefits. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[1]</a> </sup> </sup> Analyses that require a relatively complete record of an individual’s service use often need to be restricted to Medicaid beneficiaries with comprehensive benefits at a minimum.</p><p class=\"msword-paragraph\"> Five variables in the annual Demographic and Eligibility (DE) TAF can be used to identify Medicaid and CHIP beneficiaries who have comprehensive benefits (Table 1).</p><p class=\"msword-table-title\"> Table 1. Potential TAF DE variables for identifying Medicaid and CHIP beneficiaries</p><table aria-label=\"Table 1. Potential TAF DE variables for identifying Medicaid and CHIP beneficiaries\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Data element </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Use for identifying Medicaid and CHIP beneficiaries </p> </th> </tr> </thead> <tbody> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> CHIP_CD </p> </td> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> Identifies individuals in Medicaid (CHIP_CD = 1), Medicaid Expansion CHIP (M-CHIP) (CHIP_CD = 2), and Separate CHIP (S-CHIP) (CHIP_CD = 3). </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> MDCD_ENRLMT_DAYS and CHIP_ENRLMT_DAYS </p> </td> <td> <p class=\"msword-table-text-left\"> Built from T-MSIS enrollment date and enrollment type variables (ENROLLMENT-EFF-DATE, ENROLLMENT-END-DATE, and ENROLLMENT-TYPE). </p> <p class=\"msword-table-text-left\"> The beneficiary will have at least one day of Medicaid or M-CHIP enrollment (MDCD_ENRLMT_DAYS > 0) if he or she had an enrollment span that covered at least one day in the month and the enrollment span was classified as ENROLLMENT-TYPE = 1 (Medicaid or M-CHIP). </p> <p class=\"msword-table-text-left\"> The beneficiary will have at least one day of S-CHIP enrollment (CHIP_ENRLMT_DAYS > 0) if he or she had an enrollment span that covered at least one day in the month and the enrollment span was classified as S-CHIP (ENROLLMENT-TYPE = 2 [Separate Title XXI CHIP]). </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> ELGBLTY_GRP_CD </p> </td> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> Contains the eligibility group applicable to the individual based on the state’s eligibility determination process. Can be used to distinguish S-CHIP and M-CHIP (ELGBLTY_GRP_CD = 61–68) from Medicaid (ELGBLTY_GRP_CD = 1-9, 11-56, 59–60, or 69–75) enrollment. </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> RSTRCTD_BNFTS_CD </p> </td> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> Indicates the scope of Medicaid or CHIP benefits to which a beneficiary is entitled during the month. Can be used to distinguish between individuals not eligible for Medicaid or CHIP benefits during the month (value of 0); those enrolled with full or comprehensive benefits (values of 1, 4, 5, 7, A, B, or D); <sup class=\"msword-superscript\"> a </sup> and those enrolled with limited benefits (values of 2, 3, 6, C, E, or F). Beneficiaries with a restricted benefits code of 4 (restricted benefits for pregnancy-related services) have benefits that meet the Minimum Essential Coverage (MEC) requirements in all states except Arkansas, Idaho, and South Dakota. Beneficiaries with a restricted benefits code of 4 in those three states have limited benefits. </p> </td> </tr> </tbody></table><p class=\"msword-table-source\"> Note: \tThese five data elements are available monthly in the TAF DE, with the number of each month appended to the end of the data element name (for instance, CHIP_CD_01 for January, CHIP_CD_02 for February, and so on). For simplicity, we did not list the monthly indicators in this table because this analysis used all months of data. A list of valid values and descriptions of these data elements can be found in the TAF Demographic and Eligibility Codebook at <a aria-label=\"View the TAF Claims Codebook on the Chronic Conditions Data Warehouse Data Dictionaries page\" href=\"https://www2.ccwdata.org/web/guest/data-dictionaries\">https://www2.ccwdata.org/web/guest/data-dictionaries</a> .</p><p class=\"msword-table-source\"> Maintenance assistance status and basis of eligibility (MASBOE_CD), which was constructed from T-MSIS data elements MAINTENANCE-ASSISTANCE-STATUS and MEDICAID-BASIS-OF-ELIGIBILITY, has been phased out in favor of the new, more detailed eligibility group code; MASBOE_CD is not recommended for use.</p><p class=\"msword-table-source\"> A restricted benefits code value of 1 indicates full-scope Medicaid or CHIP benefits; value 4 indicates that the individual is eligible for Medicaid or CHIP but only entitled to restricted benefits for pregnancy-related services; value 5 indicates that the individual is eligible for Medicaid or CHIP, but for reasons other than alien, dual-eligibility, or pregnancy-related status, is only entitled to restricted benefits that meet the MEC standard; value 7 indicates Medicaid enrollment in an alternative package of benchmark-equivalent Medicaid coverage; value A indicates entitlement to Medicaid benefits under the Psychiatric Residential Treatment Facilities Demonstration Grant; value B indicates entitlement to Medicaid benefits using a Health Opportunity Account; and value D indicates entitlement to Medicaid benefits under a Money Follows the Person rebalancing demonstration.</p><p class=\"msword-paragraph-continued\"> Analyses conducted on the 2016 TAF data (results not shown) found that using the restricted benefits code alone is the most reliable approach for counting the number of Medicaid and CHIP beneficiaries with comprehensive benefits. This analysis evaluates whether this data element can be used to accurately count enrollment for this group in each state.</p><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"> <p class=\"msword-footnote-text\"> States can offer limited Medicaid benefits to individuals based on alien status, dual eligibility, or pregnancy-related status. In addition, some beneficiaries are eligible for family planning or emergency services only. These benefit packages do not meet the Minimum Essential Coverage threshold and are therefore not considered comprehensive benefits. </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"><p class=\"msword-footnote-text\"> States can offer limited Medicaid benefits to individuals based on alien status, dual eligibility, or pregnancy-related status. In addition, some beneficiaries are eligible for family planning or emergency services only. These benefit packages do not meet the Minimum Essential Coverage threshold and are therefore not considered comprehensive benefits. </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}]}, "methods": {"content": "<p class=\"msword-paragraph\"> We used Eligibility and Enrollment Performance Indicator (PI) data as the external benchmark to examine the accuracy of TAF-based enrollment counts for the Medicaid and CHIP population with comprehensive benefits. <sup class=\"msword-superscript\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[2]</a> </sup> </sup> Although some states’ PI data contain quality issues prior to 2017 that may affect their accuracy, these data are the best source available for use as an external benchmark for the Medicaid and CHIP population because many of the data quality issues are known, and the data provide a consistent benchmark across multiple data quality assessments. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[3]</a> </sup> </sup></p><p class=\"msword-paragraph\"> In the TAF, we identified Medicaid and CHIP beneficiaries with comprehensive benefits by selecting records where the restricted benefits code was equal to 1, 4, 5, 7, A, B, or D in all states but Arkansas, Idaho and South Dakota, which do not provide comprehensive benefits to Medicaid beneficiaries who are eligible because of pregnancy. In these states, we calculated TAF-based enrollment counts for beneficiaries with comprehensive benefits using a restricted benefits code equal to 1, 5, 7, A, B, or D. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-4\" id=\"footnote-ref-4\">[4]</a> </sup> </sup></p><p class=\"msword-paragraph\"> Using the restricted benefits code to create TAF-based counts has the effect of including all individuals enrolled for one or more days (“ever enrolled”) in the month. We compared the PI and TAF-based counts by (1) evaluating the percent difference between TAF-based enrollment counts and the benchmark, averaged across all 12 months; and (2) examining the standard deviation of this measure to assess variation in the difference across months. <a id=\"_Hlk30513451\"></a> The average monthly TAF enrollment count is calculated as the sum of the monthly TAF counts divided by 12, and the average monthly PI enrollment count is calculated as the sum of the monthly PI counts divided by 12. Because the benchmark data can be viewed as a baseline and the TAF-based calculations as the comparison, the percent difference between the two is calculated as a percent error or change: the difference between the TAF and PI counts divided by the PI count and multiplied by 100. <a id=\"_Hlk30513473\"></a> The average monthly percent difference is calculated as the sum of the monthly percent differences, divided by 12. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-5\" id=\"footnote-ref-5\">[5]</a> </sup> </sup> The standard deviation of the monthly percent differences between the TAF-based count and the PI count is calculated as the square root of the sum of the squared differences between the monthly percent differences and the average percent difference, divided by 12.</p><p class=\"msword-paragraph\"> Table 2 shows the level of concern for the TAF Medicaid enrollment counts based on both the percent difference and the level of alignment between the TAF and the PI enrollment counts. Although we did not assign the level of concern based on the standard deviation, we provide this information in the tables, and TAF users may want to consider the monthly variability between TAF and the benchmark when determining whether the data are usable for their analysis and whether all months are of similar quality.</p><p class=\"msword-table-title\"> Table 2. Criteria for DQ assessment of Medicaid and CHIP enrollment</p><table aria-label=\"Table 2. Criteria for DQ assessment of Medicaid and CHIP enrollment \" class=\"dq-assessment-table\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Average monthly percent difference between TAF and PI enrollment counts </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Level of alignment between TAF and PI enrollment counts </p> </th> <th class=\"msword-table-header-center dq-assessment-col\"> <p class=\"msword-table-header-center\"> DQ assessment </p> </th> </tr> </thead> <tbody> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x ≤ 5 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> High </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 5 percent < x ≤ 10 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Moderate </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 10 percent < x ≤ 20 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level medium\"> <p class=\"msword-table-text-centered\"> Medium concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 20 percent < x ≤ 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level high\"> <p class=\"msword-table-text-centered\"> High concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x > 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level unusable\"> <p class=\"msword-table-text-centered\"> Unusable </p> </td> </tr> </tbody></table><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"2\"> <p class=\"msword-footnote-text\"> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources</a> page, and a crosswalk of variable names can be found in the guide “Production of the TAF Research Identifiable Files.” </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"3\"> <p class=\"msword-footnote-text\"> More information about the PI data set can be found at <a aria-label=\"View more information about the PI data set\" href=\"https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html\">https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html</a> . <a id=\"_Hlk36815293\"></a> In some cases, the PI data in the Atlas may not match exactly the PI data publicly available on Medicaid.gov, because our analysis uses a version of the data set that may have been updated more recently. </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-4\" value=\"4\"> <p class=\"msword-footnote-text\"> As of 2020, the restricted benefits code value of 5 (the individual is eligible for Medicaid or Medicaid-Expansion CHIP but, for reasons other than alien, dual-eligibility, or pregnancy-related status, is entitled to restricted benefits only) should be used only if the coverage meets the MEC standard and a new valid value of E should be used if the coverage does not meet the MEC standard. For years prior to 2020, we did not include the code 5 group for any state because it represented a more heterogenous mix of beneficiaries (some of whom had limited benefits in some states). </p> <p> <a href=\"#footnote-ref-4\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-5\" value=\"5\"> <p class=\"msword-footnote-text\"> <a id=\"_Hlk30514575\"></a> The difference between TAF and PI enrollment is based on an average of the monthly differences between these two data sources. As a result, it may not equal the difference between the average annual TAF enrollment and average annual PI enrollment. </p> <p> <a href=\"#footnote-ref-5\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"2\"><p class=\"msword-footnote-text\"> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources</a> page, and a crosswalk of variable names can be found in the guide \u201cProduction of the TAF Research Identifiable Files.\u201d </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"3\"><p class=\"msword-footnote-text\"> More information about the PI data set can be found at <a aria-label=\"View more information about the PI data set\" href=\"https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html\">https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html</a> . <a id=\"_Hlk36815293\"></a> In some cases, the PI data in the Atlas may not match exactly the PI data publicly available on Medicaid.gov, because our analysis uses a version of the data set that may have been updated more recently. \u00a0 </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}, {"number": 4, "content": "<li class=\"footnoteBody\" id=\"footnote-4\" value=\"4\"><p class=\"msword-footnote-text\"> As of 2020, the restricted benefits code value of 5 (the individual is eligible for Medicaid or Medicaid-Expansion CHIP but, for reasons other than alien, dual-eligibility, or pregnancy-related status, is entitled to restricted benefits only) should be used only if the coverage meets the MEC standard and a new valid value of E should be used if the coverage does not meet the MEC standard. For years prior to 2020, we did not include the code 5 group for any state because it represented a more heterogenous mix of beneficiaries (some of whom had limited benefits in some states). </p><p><a href=\"#footnote-ref-4\">\u2191</a></p></li>"}, {"number": 5, "content": "<li class=\"footnoteBody\" id=\"footnote-5\" value=\"5\"><p class=\"msword-footnote-text\"><a id=\"_Hlk30514575\"></a> The difference between TAF and PI enrollment is based on an average of the monthly differences between these two data sources. As a result, it may not equal the difference between the average annual TAF enrollment and average annual PI enrollment. </p><p><a href=\"#footnote-ref-5\">\u2191</a></p></li>"}]}, "summary": {"content": "<p>The TAF eligibility files include information on beneficiaries in both Medicaid and CHIP. This analysis examines how well the TAF data on the number of Medicaid and CHIP beneficiaries align with an external benchmark, the Performance Indicators data set.</p>", "footnotes": []}, "originalIssueBriefId": "4051", "relatedTopics": []} |
8 | {"measureId": 8, "measureName": "Medicaid-Only Enrollment", "groupId": 1, "groupName": "Enrollment Benchmarking", "pdfVersionLink": "downloads/background-and-methods/TAF-DQ-Medicaid-Only-Enroll.pdf", "background": {"content": "<p class=\"msword-paragraph\"> The research-ready T\u2011MSIS Analytic Files (TAF), are an enhanced set of data on beneficiaries in Medicaid and the Children’s Health Insurance Program (CHIP), their claims, and the participating managed care plans and providers that serve them. The TAF eligibility files include beneficiaries enrolled in Medicaid, Medicaid expansion CHIP (referred to as M-CHIP) and separate CHIP (referred to as S-CHIP). <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[1]</a> </sup> </sup> Many data users will want to identify and study only beneficiaries in non-CHIP (Title XIX-funded) Medicaid (and for analyses requiring a relatively complete record of individuals’ service use, particularly those with comprehensive benefits <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[2]</a> </sup> </sup> ) and will need to know whether these beneficiaries are completely reported in a state’s TAF data.</p><p class=\"msword-paragraph\"> Three variables in the annual Demographic and Eligibility (DE) TAF can be used in combination to identify Title XIX Medicaid beneficiaries (which does not include M-CHIP) who have comprehensive benefits (Table 1). These variables are CHIP code (CHIP_CD), eligibility group code (ELGBLTY_GRP_CD), and restricted benefits code (RSTRCTD_BNFTS_CD). The CHIP code (CHIP_CD) is most useful for distinguishing beneficiaries enrolled in a Title XIX Medicaid program, from those enrolled in the Title XXI M-CHIP, and from those enrolled in Title XXI S-CHIP. It is the only variable that can be used to identify the entire Title XXI CHIP population. TAF users cannot identify Title XIX Medicaid enrollment by using the Medicaid enrollment days variable (MDCD_ENRLMT_DAYS) because that variable also includes days during the month in which the beneficiary was enrolled in M-CHIP. While eligibility group code (ELGBLTY_GRP_CD) is most useful for obtaining detailed information on the eligibility group through which a beneficiary is enrolled in Medicaid or CHIP, it cannot be used alone to identify all beneficiaries enrolled in Title XXI CHIP or to separate Title XXI M-CHIP from Title XXI S-CHIP beneficiaries due to overlap in the use of certain eligibility groups.</p><p class=\"msword-table-title\"> Table 1. Potential TAF DE variables for identifying Title XIX Medicaid beneficiaries</p><table aria-label=\"Table 1. Potential TAF DE variables for identifying Title XIX Medicaid beneficiaries\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Data element </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Use for identifying Medicaid and CHIP beneficiaries </p> </th> </tr> </thead> <tbody> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> CHIP_CD </p> </td> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> Identifies individuals in Medicaid (CHIP_CD = 1), Medicaid expansion CHIP (M-CHIP) (CHIP_CD = 2), and Separate CHIP (S-CHIP) (CHIP_CD = 3). </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> ELGBLTY_GRP_CD </p> </td> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> Contains the eligibility group applicable to the individual based on the state’s eligibility determination process. When CHIP_CD is missing, ELGBLTY_GRP_CD can be used to indicate CHIP enrollment (ELGBLTY_GRP_CD = 61–68, with 61 used for both M-CHIP and S-CHIP and 62–68 exclusive to S-CHIP) and Medicaid enrollment (ELGBLTY_GRP_CD = 1–60 or 69–76). </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> RSTRCTD_BNFTS_CD </p> </td> <td> <p class=\"msword-table-text-left\"> Indicates the scope of Medicaid benefits to which a beneficiary is entitled during the month. </p> <p class=\"msword-table-text-left\"> Can be used to distinguish between individuals not eligible for Medicaid or CHIP benefits during the month (value of 0); those enrolled with full or comprehensive benefits (values of 1, 4, 5, 7, A, B, or D); and those enrolled with limited or partial benefits (values of 2, 3, 6, C, E, or F). Beneficiaries with a restricted benefits code of 4 (restricted benefits for pregnancy-related services) have benefits that meet the Minimum Essential Coverage (MEC) requirements in all states except Arkansas, Idaho, and South Dakota. Beneficiaries with a restricted benefits code of 4 in those three states have limited benefits. </p> </td> </tr> </tbody></table><p class=\"msword-table-source\"> Note:\tThese three data elements are available monthly in the TAF DE, with the number of each month appended to the end of the data element name (for instance, CHIP_CD_01 for January, CHIP_CD_02 for February, and so on). For simplicity, we did not list the monthly indicators in this brief because we used all months of data. A list of valid values and descriptions of these data elements can be found in the TAF Demographic and Eligibility Codebook at <a aria-label=\"View the TAF Claims Codebook on the Chronic Conditions Data Warehouse Data Dictionaries page\" href=\"https://www2.ccwdata.org/web/guest/data-dictionaries\">https://www2.ccwdata.org/web/guest/data-dictionaries</a> .</p><p class=\"msword-table-source\"> Maintenance assistance status and basis of eligibility (MASBOE_CD), which was constructed from T-MSIS data elements MAINTENANCE-ASSISTANCE-STATUS and MEDICAID-BASIS-OF-ELIGIBILITY, has been phased out in favor of the new, more detailed T-MSIS eligibility group code; MASBOE_CD is not recommended for use.</p><p class=\"msword-table-source\"> We also do not include Medicaid enrollment days (MDCD_ENRLMT_DAYS) or CHIP enrollment days (CHIP_ENRLMT_DAYS) because they cannot be used to distinguish the Medicaid-only population funded through Title XIX. The Medicaid enrollment days variable combines Medicaid with M-CHIP; CHIP enrollment days is just for S-CHIP. In addition, the TAF DE equivalent of the T-MSIS enrollment type variable (ENROLLMENT-TYPE) is enrollment type flag (ENRL_TYPE_FLAG), which groups beneficiaries in the same manner as Medicaid and CHIP enrollment days and therefore cannot be used to identify the Medicaid-only population.</p><p class=\"msword-table-source\"> A restricted benefits code value of 1 indicates full-scope Medicaid or CHIP benefits; value 4 indicates that the individual, although eligible for Medicaid or CHIP, is entitled to only restricted benefits for pregnancy-related services; value 5 indicates that the individual is eligible for Medicaid or CHIP, but for reasons other than alien, dual-eligibility, or pregnancy-related status, is only entitled to restricted benefits that meet the MEC standard; value 7 indicates Medicaid enrollment in an alternative package of benchmark-equivalent Medicaid coverage; value A indicates entitlement to Medicaid benefits under the Psychiatric Residential Treatment Facilities Demonstration Grant; value B indicates entitlement to Medicaid benefits using a Health Opportunity Account; and value D indicates entitlement to Medicaid benefits under a Money Follows the Person rebalancing demonstration.</p><p class=\"msword-paragraph-continued\"> Analyses conducted on the 2016 TAF data found that using a combination of all three data elements is the most reliable approach for counting the number of beneficiaries enrolled in Title XIX Medicaid who qualify for comprehensive benefits (results not shown). This analysis evaluates whether these data elements can be used to accurately count enrollment among Title XIX Medicaid beneficiaries with comprehensive benefits in each state.</p><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"> <p class=\"msword-footnote-text\"> States may use CHIP funds to expand their Medicaid program (M-CHIP), create a program separate from their existing Medicaid program (S-CHIP), or adopt a combination of both approaches. Medicaid beneficiaries qualify for Title XIX funding, M-CHIP beneficiaries qualify for enhanced Title XXI finding, and S-CHIP beneficiaries qualify for Title XXI funding. </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"> <p class=\"msword-footnote-text\"> Comprehensive benefits refers to coverage that is comparable to that provided to categorically needy Medicaid beneficiaries and considered Minimum Essential Coverage under the Affordable Care Act. In addition, states can offer restricted Medicaid benefits to individuals on the basis of alien status, dual eligibility, or pregnancy-related status; some beneficiaries are eligible for only limited benefits such as family planning or emergency services. </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"1\"><p class=\"msword-footnote-text\"> States may use CHIP funds to expand their Medicaid program (M-CHIP), create a program separate from their existing Medicaid program (S-CHIP), or adopt a combination of both approaches. Medicaid beneficiaries qualify for Title XIX funding, M-CHIP beneficiaries qualify for enhanced Title XXI finding, and S-CHIP beneficiaries qualify for Title XXI funding. </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"2\"><p class=\"msword-footnote-text\"> Comprehensive benefits refers to coverage that is comparable to that provided to categorically needy Medicaid beneficiaries and considered Minimum Essential Coverage under the Affordable Care Act. In addition, states can offer restricted Medicaid benefits to individuals on the basis of alien status, dual eligibility, or pregnancy-related status; some beneficiaries are eligible for only limited benefits such as family planning or emergency services. </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}]}, "methods": {"content": "<p class=\"msword-paragraph\"> We used Eligibility and Enrollment Performance Indicator (PI) data as the external benchmark to examine the accuracy of TAF-based enrollment counts for the Medicaid population with comprehensive benefits. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-2\" id=\"footnote-ref-2\">[3]</a> </sup> </sup> Although some states’ PI data contain quality issues prior to 2017 that may affect their accuracy, these data are the best source available for use as an external benchmark for the Medicaid population because many of the data quality issues are known, and the data provide a consistent benchmark across multiple data quality assessments. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-3\" id=\"footnote-ref-3\">[4]</a> </sup> </sup></p><p class=\"msword-paragraph\"> To create the TAF-based counts, we included individuals enrolled at any point (“ever enrolled”) in the month. Specifically, we used CHIP code of 1 to identify the Title XIX Medicaid population. If the CHIP code was missing, we counted beneficiaries with an eligibility group code that indicated they were eligible for Medicaid benefits (eligibility group code of 1–60 or 69–76). We then used restricted benefits code of 1, 4, 5, 7, A, B, or D to identify those with comprehensive benefits. We excluded the restricted benefits code 4 group in the three states that do not extend comprehensive benefits to women in the pregnancy group (Arkansas, Idaho, and South Dakota). <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-4\" id=\"footnote-ref-4\">[5]</a> </sup> </sup></p><p class=\"msword-paragraph\"> We compared the performance of different variables by (1) evaluating the percent difference between TAF-based enrollment counts and the benchmark, averaged across all 12 months, and (2) examining the standard deviation of this measure to assess variation in the difference across months. The average monthly TAF enrollment count is calculated as the sum of the monthly TAF counts divided by 12, and the average monthly PI enrollment count is calculated as the sum of the monthly PI counts divided by 12. Because the benchmark data can be viewed as a baseline and the TAF-based calculations as the comparison, the percent difference is calculated as a percent error or change: the difference between the TAF and PI counts divided by the PI count and multiplied by 100. The average monthly percent difference is calculated as the sum of the monthly percent differences, divided by 12. <sup class=\"msword-footnote-reference\"> <sup> <a class=\"footnoteRef\" href=\"#footnote-5\" id=\"footnote-ref-5\">[6]</a> </sup> </sup> The standard deviation of the monthly percent differences between the TAF-based count and the PI count is calculated as the square root of the sum of the squared differences between the monthly percent differences and the average percent difference, divided by 12.</p><p class=\"msword-paragraph\"> Table 2 shows the level of concern for the TAF Title XIX Medicaid enrollment counts based on both the percent difference and the level of alignment between the TAF and the PI enrollment counts. Although we did not assign the level of concern based on the standard deviation, we provide this information in the tables, and TAF users may want to consider the monthly variability between TAF and the benchmark when determining whether the data are usable for their analysis and whether all months are of similar quality.</p><p class=\"msword-table-title\"> Table 2. Criteria for DQ assessment of Title XIX Medicaid enrollment</p><table aria-label=\"Table 2. Criteria for DQ assessment of Title XIX Medicaid enrollment\" class=\"dq-assessment-table\" tabindex=\"0\"> <thead> <tr> <th class=\"msword-table-header-left\"> <p class=\"msword-table-header-left\"> Average monthly percent difference between TAF and PI enrollment counts </p> </th> <th class=\"msword-table-header-center\"> <p class=\"msword-table-header-center\"> Level of alignment between TAF and PI enrollment counts </p> </th> <th class=\"msword-table-header-center dq-assessment-col\"> <p class=\"msword-table-header-center\"> DQ assessment </p> </th> </tr> </thead> <tbody> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x ≤ 5 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> High </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 5 percent < x ≤ 10 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Moderate </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level low\"> <p class=\"msword-table-text-centered\"> Low concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 10 percent < x ≤ 20 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level medium\"> <p class=\"msword-table-text-centered\"> Medium concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> 20 percent < x ≤ 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level high\"> <p class=\"msword-table-text-centered\"> High concern </p> </td> </tr> <tr> <td class=\"msword-table-text-left\"> <p class=\"msword-table-text-left\"> x > 50 percent </p> </td> <td class=\"msword-table-text-centered\"> <p class=\"msword-table-text-centered\"> Very low </p> </td> <td class=\"msword-table-text-centered dq-assessment-col dq-level unusable\"> <p class=\"msword-table-text-centered\"> Unusable </p> </td> </tr> </tbody></table><ol> <li class=\"footnoteBody\" id=\"footnote-2\" value=\"3\"> <p class=\"msword-footnote-text\"> <a id=\"_Hlk37699725\"></a> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources</a> page, and a crosswalk of variable names can be found in the guide “Production of the TAF Research Identifiable Files.” </p> <p> <a href=\"#footnote-ref-2\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-3\" value=\"4\"> <p class=\"msword-footnote-text\"> More information about the PI data set can be found at <a aria-label=\"View more information about the PI data set\" href=\"https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html\">https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html</a> . <a id=\"_Hlk36815293\"></a> In some cases, the PI data in the Atlas may not match exactly the PI data publicly available on Medicaid.gov, because our analysis uses a version of the data set that may have been updated more recently. </p> <p> <a href=\"#footnote-ref-3\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-4\" value=\"5\"> <p class=\"msword-footnote-text\"> As of 2020, the restricted benefits code value of 5 (the individual is eligible for Medicaid or Medicaid-Expansion CHIP but, for reasons other than alien, dual-eligibility, or pregnancy-related status, is entitled to restricted benefits only) should be used only if the coverage meets the MEC standard and a new valid value of E should be used if the coverage does not meet the MEC standard. For years prior to 2020, we did not include the code 5 group for any state because it represented a more heterogenous mix of beneficiaries (some of whom had limited benefits in some states). </p> <p> <a href=\"#footnote-ref-4\">↑</a> </p> </li> <li class=\"footnoteBody\" id=\"footnote-5\" value=\"6\"> <p class=\"msword-footnote-text\"> The difference between TAF and PI enrollment is based on an average of the monthly differences between these two data sources. As a result, it may not equal the difference between the average annual TAF enrollment and average annual PI enrollment. </p> <p> <a href=\"#footnote-ref-5\">↑</a> </p> </li></ol>", "footnotes": [{"number": 2, "content": "<li class=\"footnoteBody\" id=\"footnote-2\" value=\"3\"><p class=\"msword-footnote-text\"><a id=\"_Hlk37699725\"></a> This analysis used the TAF data that were released as TAF Research Identifiable Files (RIF). During the transformation into RIF, some TAF data elements were suppressed, changed, or renamed. Additional details are available on the <a aria-label=\"View additional details on the DQ Atlas Resources page\" class=\"bgm-relative-link\" href=\"landing/resources\">DQ Atlas Resources</a> page, and a crosswalk of variable names can be found in the guide \u201cProduction of the TAF Research Identifiable Files.\u201d </p><p><a href=\"#footnote-ref-2\">\u2191</a></p></li>"}, {"number": 3, "content": "<li class=\"footnoteBody\" id=\"footnote-3\" value=\"4\"><p class=\"msword-footnote-text\"> More information about the PI data set can be found at <a aria-label=\"View more information about the PI data set\" href=\"https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html\">https://www.medicaid.gov/medicaid/program-information/medicaid-and-chip-enrollment-data/report-highlights/index.html</a> . <a id=\"_Hlk36815293\"></a> In some cases, the PI data in the Atlas may not match exactly the PI data publicly available on Medicaid.gov, because our analysis uses a version of the data set that may have been updated more recently. </p><p><a href=\"#footnote-ref-3\">\u2191</a></p></li>"}, {"number": 4, "content": "<li class=\"footnoteBody\" id=\"footnote-4\" value=\"5\"><p class=\"msword-footnote-text\"> As of 2020, the restricted benefits code value of 5 (the individual is eligible for Medicaid or Medicaid-Expansion CHIP but, for reasons other than alien, dual-eligibility, or pregnancy-related status, is entitled to restricted benefits only) should be used only if the coverage meets the MEC standard and a new valid value of E should be used if the coverage does not meet the MEC standard. For years prior to 2020, we did not include the code 5 group for any state because it represented a more heterogenous mix of beneficiaries (some of whom had limited benefits in some states). </p><p><a href=\"#footnote-ref-4\">\u2191</a></p></li>"}, {"number": 5, "content": "<li class=\"footnoteBody\" id=\"footnote-5\" value=\"6\"><p class=\"msword-footnote-text\"> The difference between TAF and PI enrollment is based on an average of the monthly differences between these two data sources. As a result, it may not equal the difference between the average annual TAF enrollment and average annual PI enrollment. </p><p><a href=\"#footnote-ref-5\">\u2191</a></p></li>"}]}, "summary": {"content": "<p>The TAF eligibility files include information on beneficiaries in both Medicaid and CHIP. This analysis examines how well the TAF data on the number of total Medicaid beneficiaries align with an external benchmark, the Performance Indicators data set. </p>", "footnotes": []}, "originalIssueBriefId": "4061", "relatedTopics": []} |
9 | "{\"measureId\": 9, \"measureName\": \"Dually Enrolled in Medicare\", \"groupId\": 1, \"groupName\":(...TRUNCATED) |
10 | "{\"measureId\": 10, \"measureName\": \"Number of Enrollment Spans\", \"groupId\": 2, \"groupName\":(...TRUNCATED) |
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in Data Studio
implAuto_measure_backgroundAndMethods
Description
This is a dataset created for use by the DQ Atlas website, and is not intended for use outside that application. For more information on the DQ Atlas and the information contained in this dataset see https://www.medicaid.gov/dq-atlas/welcome
Dataset Details
- Publisher: Centers for Medicare & Medicaid Services
- Last Modified: 2025-01-15
- Contact: DataConnect Support Team ([email protected])
Source
Original data can be found at: https://healthdata.gov/d/a9zs-s4k3
Usage
You can load this dataset using:
from datasets import load_dataset
dataset = load_dataset('HHS-Official/implautomeasurebackgroundandmethods')
License
This dataset is licensed under http://opendefinition.org/licenses/odc-odbl/
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