Literature DB >> 32412071

Sensitivity of Medicare Data to Identify Oncologists.

Joan L Warren1, Michael J Barrett2, Dolly P White1, Robert Banks2, Susannah Cafardi3, Lindsey Enewold1.   

Abstract

BACKGROUND: Health services researchers have studied how care from oncologists impacts treatment and outcomes for cancer patients. These studies frequently identify physician specialty using files from the Center for Medicare and Medicaid Services (CMS) or the American Medical Association (AMA). The completeness of the CMS data resources, individually or combined, to identify oncologists is unknown. This study assessed the sensitivity of CMS data to capture oncologists included in the AMA Physician Masterfile.
METHODS: Oncologists were identified from three CMS data resources: physician claims, the National Plan and Provider Enumeration System Registry, and the Medicare Data on Provider Practice and Specialty file. CMS files and AMA data were linked using a unique physician identifier. Sensitivity to identify any oncologists, radiation oncologists (ROs), surgical oncologists (SOs), and medical oncologists (MOs) was calculated for individual and combined CMS files. For oncologists in the AMA data not identified as oncologists in the CMS data, their CMS specialty was assessed.
RESULTS: Individual CMS files each captured approximately 83% of the 17 934 oncologists in the AMA Masterfile; combined CMS files captured 90.4%. By specialty, combined CMS data captured 98.2% of ROs, 89.3% of MOs, and 70.1% of SOs. For ROs and SOs in the AMA data not identified as oncologists in the CMS data, their CMS specialty was usually similar to the AMA subspecialty; ROs were radiologists and SOs were surgeons.
CONCLUSION: Using combined files from CMS identified most ROs and MOs found in the AMA, but not most SOs. Determining whether to use the AMA data or CMS files for a particular research project will depend on the specific research question and the type of oncologist included in the study. Published by Oxford University Press 2020. This work is written by US Government employees and is in the public domain in the US.

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Year:  2020        PMID: 32412071      PMCID: PMC7868031          DOI: 10.1093/jncimonographs/lgz030

Source DB:  PubMed          Journal:  J Natl Cancer Inst Monogr        ISSN: 1052-6773


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