Center for Medicare and Medicaid Innovation, Centers for Medicare & Medicaid Services, Baltimore, Maryland, USA.
Health Serv Res. 2023 Dec;58(6):1303-1313. doi: 10.1111/1475-6773.14211. Epub 2023 Aug 16.
To compare the Encounter Data System (EDS) and Medicare Provider Analysis and Review (MedPAR) completeness and medical coding of Medicare Advantage hospitalizations.
FY 2016-FY 2019 data limited to hospitals paid under Medicare's Inpatient Prospective Payment System.
Secondary data analysis.
DATA COLLECTION/EXTRACTION METHODS: Completeness of EDS and MedPAR data was estimated using the total number of unique hospitalizations in both data sources as denominator. Deriving this denominator involved matching cases in the EDS and MedPAR by MA enrollee, discharge date, and hospital. The higher the match rate, the more informative the comparison of EDS and MedPAR medical coding of the same hospitalization. EDS and MedPAR codes were assessed for similarity on six measures of Medicare Severity Diagnosis-Related Group (MS-DRG) assignment and identical diagnosis and procedure codes.
EDS hospitalizations' completeness increased steadily each year from 90% to 93%, driven by the 23 largest Medicare Advantage Organizations, which account for 83% of total cases. MedPAR completeness was relatively stable (89%) and benefited from 91% completeness among the largest hospitals, which are often teaching hospitals and account for 63% of MedPAR cases. By 2019, 97% of medical cases were assigned the same MS-DRG, indicating the high consistency of the severity level coding, since 98% were assigned the same base MS-DRGs, which include all severity levels for the same condition. Without chart reviews, medical cases with identical diagnosis codes increased from 87% to 92%.
The EDS has a completeness advantage over MedPAR for studies of non-teaching disproportionate share (DSH) hospitals and individual hospitals generally. MedPAR is only slightly less complete for hospitalizations of teaching DSH hospitals and large hospitals in general. A highly consistent EDS and MedPAR medical coding of matched cases is an important finding since the matched cases are 88% of EDS and 90% of MedPAR cases.
比较医疗保险优势住院患者的遭遇数据系统（EDS）和医疗保险提供者分析和审查（MedPAR）的完整性和医疗编码。
2016 财年至 2019 财年的数据仅限于在医疗保险的住院患者前瞻性支付系统下支付的医院。
二次数据分析。
数据收集/提取方法：使用两个数据源中唯一住院患者的总数作为分母来估计 EDS 和 MedPAR 数据的完整性。得出这个分母涉及通过医疗保险优势参保人、出院日期和医院匹配 EDS 和 MedPAR 中的病例。匹配率越高，比较同一住院患者的 EDS 和 MedPAR 医疗编码的信息就越丰富。对 EDS 和 MedPAR 代码进行了六项医疗保险严重程度诊断相关组（MS-DRG）分配和相同诊断和程序代码的相似性评估。
EDS 住院患者的完整性每年稳步提高，从 90%提高到 93%，这得益于占总病例数 83%的 23 家最大的医疗保险优势组织。MedPAR 的完整性相对稳定（89%），并受益于最大医院中 91%的完整性，这些医院通常是教学医院，占 MedPAR 病例的 63%。到 2019 年，97%的医疗病例被分配了相同的 MS-DRG，表明严重程度编码的一致性很高，因为 98%被分配了相同的基础 MS-DRG，其中包括同一疾病的所有严重程度。如果没有病历审查，具有相同诊断代码的医疗病例从 87%增加到 92%。
对于非教学不成比例份额（DSH）医院和一般医院的研究，EDS 比 MedPAR 具有完整性优势。对于教学 DSH 医院和一般大型医院的住院患者，MedPAR 的完整性略低。对于匹配病例，EDS 和 MedPAR 的医疗编码高度一致是一个重要的发现，因为匹配病例占 EDS 的 88%，占 MedPAR 的 90%。
