Abstract：
OBJECTIVE: To determine the feasibility of integrating Medicare Advantage (MA) admissions into the Centers for Medicare & Medicaid Services (CMS) hospital outcome measures through combining Medicare Advantage Organization (MAO) encounter- and hospital-submitted inpatient claims.
METHODS: Beneficiary enrollment data and inpatient claims from the Integrated Data Repository for 2018 Medicare discharges.
METHODS: We examined timeliness of MA claims, compared diagnosis and procedure codes for admissions with claims submitted both by the hospital and the MAO (overlapping claims), and compared demographic characteristics and principal diagnosis codes for admissions with overlapping claims versus admissions with a single claim.
METHODS: We combined hospital- and MAO-submitted claims to capture MA admissions from all hospitals and identified overlapping claims. For admissions with only an MAO-submitted claim, we used provider history data to match the National Provider Identifier on the claim to the CMS Certification Number used for reporting purposes in CMS outcome measures.
RESULTS: After removing void and duplicate claims, identifying overlapped claims between the hospital- and MAO-submitted datasets, restricting claims to acute care and critical access hospitals, and bundling same admission claims, we identified 5,078,611 MA admissions. Of these, 76.1% were submitted by both the hospital and MAO, 14.2% were submitted only by MAOs, and 9.7% were submitted only by hospitals. Nearly all (96.6%) hospital-submitted claims were submitted within 3 months after a one-year performance period, versus 85.2% of MAO-submitted claims. Among the 3,864,524 admissions with overlapping claims, 98.9% shared the same principal diagnosis code between the two datasets, and 97.5% shared the same first procedure code.
CONCLUSIONS: Inpatient MA data are feasible for use in CMS claims-based hospital outcome measures. We recommend prioritizing hospital-submitted over MAO-submitted claims for analyses. Monitoring, data audits, and ongoing policies to improve the quality of MA data are important approaches to address potential missing data and errors.
METHODS: Beneficiary enrollment data and inpatient claims from the Integrated Data Repository for 2018 Medicare discharges.
METHODS: We examined timeliness of MA claims, compared diagnosis and procedure codes for admissions with claims submitted both by the hospital and the MAO (overlapping claims), and compared demographic characteristics and principal diagnosis codes for admissions with overlapping claims versus admissions with a single claim.
METHODS: We combined hospital- and MAO-submitted claims to capture MA admissions from all hospitals and identified overlapping claims. For admissions with only an MAO-submitted claim, we used provider history data to match the National Provider Identifier on the claim to the CMS Certification Number used for reporting purposes in CMS outcome measures.
RESULTS: After removing void and duplicate claims, identifying overlapped claims between the hospital- and MAO-submitted datasets, restricting claims to acute care and critical access hospitals, and bundling same admission claims, we identified 5,078,611 MA admissions. Of these, 76.1% were submitted by both the hospital and MAO, 14.2% were submitted only by MAOs, and 9.7% were submitted only by hospitals. Nearly all (96.6%) hospital-submitted claims were submitted within 3 months after a one-year performance period, versus 85.2% of MAO-submitted claims. Among the 3,864,524 admissions with overlapping claims, 98.9% shared the same principal diagnosis code between the two datasets, and 97.5% shared the same first procedure code.
CONCLUSIONS: Inpatient MA data are feasible for use in CMS claims-based hospital outcome measures. We recommend prioritizing hospital-submitted over MAO-submitted claims for analyses. Monitoring, data audits, and ongoing policies to improve the quality of MA data are important approaches to address potential missing data and errors.
摘要：
目标：通过结合MedicareAdvantageOrganization(MAO)实施和医院提交的住院索赔，确定将MedicareAdvantage(MA)入院纳入Medicare&Medicaid服务中心(CMS)医院结局指标的可行性。
方法：来自2018年Medicare出院综合数据存储库的受益人登记数据和住院索赔。
方法：我们检查了MA索赔的及时性，将入院的诊断和程序代码与医院和MAO提交的索赔进行比较（重叠索赔），并比较了具有重叠索赔的入院与具有单一索赔的入院的人口统计学特征和主要诊断代码。
方法：我们结合了医院和MAO提交的索赔，以获取所有医院的MA入院情况并确定重叠索赔。对于只有MAO提交的索赔的招生，我们使用提供者历史数据,将声明中的国家提供者标识符与CMS结果衡量标准中用于报告目的的CMS认证号相匹配.
结果：删除无效和重复索赔后，确定医院和MAO提交的数据集之间的重叠索赔，将索赔限制在急性护理和重症监护医院，捆绑相同的承认声明，我们确定了5,078,611MA入院。其中,76.1%由医院和MAO提交，14.2%仅由MAO提交，9.7%仅由医院提交。几乎所有(96.6%)医院提交的索赔都是在一年履约期后的3个月内提交的，与MAO提交的索赔的85.2%相比。在3,864,524份索赔重叠的承认中，98.9%的人在两个数据集之间共享相同的主要诊断代码，和97.5％共享相同的第一个程序代码。
结论：住院患者MA数据可用于基于CMS索赔的医院结局指标。我们建议将医院提交的索赔优先于MAO提交的索赔进行分析。Monitoring,数据审计，和正在进行的提高MA数据质量的政策是解决潜在丢失数据和错误的重要方法。
方法：来自2018年Medicare出院综合数据存储库的受益人登记数据和住院索赔。
方法：我们检查了MA索赔的及时性，将入院的诊断和程序代码与医院和MAO提交的索赔进行比较（重叠索赔），并比较了具有重叠索赔的入院与具有单一索赔的入院的人口统计学特征和主要诊断代码。
方法：我们结合了医院和MAO提交的索赔，以获取所有医院的MA入院情况并确定重叠索赔。对于只有MAO提交的索赔的招生，我们使用提供者历史数据,将声明中的国家提供者标识符与CMS结果衡量标准中用于报告目的的CMS认证号相匹配.
结果：删除无效和重复索赔后，确定医院和MAO提交的数据集之间的重叠索赔，将索赔限制在急性护理和重症监护医院，捆绑相同的承认声明，我们确定了5,078,611MA入院。其中,76.1%由医院和MAO提交，14.2%仅由MAO提交，9.7%仅由医院提交。几乎所有(96.6%)医院提交的索赔都是在一年履约期后的3个月内提交的，与MAO提交的索赔的85.2%相比。在3,864,524份索赔重叠的承认中，98.9%的人在两个数据集之间共享相同的主要诊断代码，和97.5％共享相同的第一个程序代码。
结论：住院患者MA数据可用于基于CMS索赔的医院结局指标。我们建议将医院提交的索赔优先于MAO提交的索赔进行分析。Monitoring,数据审计，和正在进行的提高MA数据质量的政策是解决潜在丢失数据和错误的重要方法。
