Medicaid, Medicare, and the Michigan Tumor Registry: A Linkage Strategy

Author:

Bradley Cathy J.1,Given Charles W.2,Luo Zhehui3,Roberts Caralee4,Copeland Glenn5,Virnig Beth A.6

Affiliation:

1. Virginia Commonwealth University, Department of Health Administration and Massey Cancer Center, Grant House, Richmond, VA,

2. Department of Family Practice and Michigan State Univ. East Lansing

3. Department of Epidemiology Michigan State University, East Lansing

4. Roberts Research Associates, East Lansing, MI

5. Michigan Cancer Surveillance Program, Michigan Department of Community Health, Lansing

6. Department of Health Services Research and Policy, School of Public Health, University of Minnesota, Minneapolis

Abstract

The study of health outcomes and the reduction in health disparities is at the forefront of the nation's health care agenda. A theme in the disparities literature is the call for a data infrastructure that can track progress toward goals aimed at reducing differences in health outcomes. This article describes a strategy for linking Medicaid, Medicare, and Michigan Tumor Registry data for the purposes of studying disparities in cancer diagnosis, quality of care, and survival. The authors review their procedures for ensuring that a correct match between files occurred and offer guidance for merging and assessing the quality of these complex linked data sets. A cohort of 113,604 subjects (90%) from a population of 125,900 subjects was correctly linked from the Michigan Tumor Registry to Medicare and Medicaid files. Using probabilistic and deterministic methods, the prediction rate of the Medicaid match to the Michigan Tumor Registry was 93%. Approximately 13% of the subjects were dually eligible for Medicare and Medicaid. An expansive data set reflecting the Medicare and Medicaid medical service utilization and outcomes for a cohort of individuals age 65 years and older when diagnosed with cancer was created. This data set serves as a cornerstone of a health outcomes data infrastructure. The methodology described may serve as a model for other researchers seeking to create a similar data set in their state.

Publisher

SAGE Publications

Subject

Health Policy

Cited by 30 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

1. Building Data Infrastructure for Disease-Focused Health Economics Research;Medical Care;2023-11-09

2. Blockchain Application to the Cancer Registry Database;International Journal of Healthcare Information Systems and Informatics;2020-10

3. Development and Evaluation of a Process to Link Cancer Patients in the SEER Registries to National Medicaid Enrollment Data;JNCI Monographs;2020-05-01

4. Data Linkage Methods for Big Data Management in Industry 4.0;Optimizing Big Data Management and Industrial Systems With Intelligent Techniques;2019

5. Balancing Privacy and Information Disclosure in Interactive Record Linkage with Visual Masking;Proceedings of the 2018 CHI Conference on Human Factors in Computing Systems;2018-04-21

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3