G2TT
来源类型Publication
来源IDT-MSIS Analytic Files Data Quality Brief #5042
Using the Type of Bill to Classify Institutional Claims in 2017 (Brief)
Allison Barrett; Laura Nolan; Mary Allison Geibel; Kimberly Proctor; and Jessie Parker
发表日期2019-10-24
出版者Baltimore, MD: Centers for Medicare & Medicaid Services
出版年2019
语种英语
概述This analysis focused on 46 states, the District of Columbia, and Puerto Rico. Mississippi, Missouri, Montana, and Nebraska were excluded from the analysis.",
摘要

Key Findings:

  • In the T-MSIS Analytic Files, the type of bill field can be used to differentiate between institutional and professional claims, and to provide information about the type of facility and services being billed on institutional claims. This brief identifies states with concerning rates of missing or unexpected type of bill values in the IP, OT and LT files in 2017.
  • The information in the type of bill field is complete and reliable in the IP file in 37 states. In Georgia and Virginia, however, the information captured in this field suggests that the states may have erroneously submitted outpatient claims in their IP file instead of in the OT file.
  • Thirty-three states submitted nearly all LT records with a type of bill value for an expected provider type, such as nursing facilities and intermediate care facilities for individuals with intellectual or developmental disabilities. Missing and invalid type of bill values were a larger problem in the LT file than in the IP file.
  • Because the OT file contains a mixture of institutional and professional claims, it is difficult to evaluate the completeness and quality of the information in the type of bill field in this file. However, California, Illinois, Washington, and Wyoming had high rates of unexpected or invalid type of bill values in their OT records, indicating problems in the quality of the data.
URLhttps://www.mathematica.org/our-publications-and-findings/publications/using-the-type-of-bill-to-classify-institutional-claims-in-2017-brief
来源智库Mathematica Policy Research (United States)
资源类型智库出版物
条目标识符http://119.78.100.153/handle/2XGU8XDN/489748
推荐引用方式
GB/T 7714
Allison Barrett,Laura Nolan,Mary Allison Geibel,et al. Using the Type of Bill to Classify Institutional Claims in 2017 (Brief). 2019.
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