Yevgeniy Feyman PhD, Jose Figueroa MD, MPH, Melissa Garrido PhD, Gretchen Jacobson PhD, Michael Adelberg MA, MPP, Austin Frakt PhD
{"title":"医疗保险优势医疗服务提供者网络对各专科医师的限制性","authors":"Yevgeniy Feyman PhD, Jose Figueroa MD, MPH, Melissa Garrido PhD, Gretchen Jacobson PhD, Michael Adelberg MA, MPP, Austin Frakt PhD","doi":"10.1111/1475-6773.14308","DOIUrl":null,"url":null,"abstract":"<div>\n \n \n <section>\n \n <h3> Objective</h3>\n \n <p>The objective was to measure specialty provider networks in Medicare Advantage (MA) and examine associations with market factors.</p>\n </section>\n \n <section>\n \n <h3> Data Sources and Study Setting</h3>\n \n <p>We relied on traditional Medicare (TM) and MA prescription drug event data from 2011 to 2017 for all Medicare beneficiaries in the United States as well as data from the Area Health Resources File.</p>\n </section>\n \n <section>\n \n <h3> Study Design</h3>\n \n <p>Relying on a recently developed and validated prediction model, we calculated the provider network restrictiveness of MA contracts for nine high-prescribing specialties. We characterized network restrictiveness through an observed-to-expected ratio, calculated as the number of unique providers seen by MA beneficiaries divided by the number expected based on the prediction model. We assessed the relationship between network restrictiveness and market factors across specialties with multivariable linear regression.</p>\n </section>\n \n <section>\n \n <h3> Data Collection/Extraction Methods</h3>\n \n <p>Prescription drug event data for a 20% random sample of beneficiaries enrolled in prescription drug coverage from 2011 to 2017.</p>\n </section>\n \n <section>\n \n <h3> Principal Findings</h3>\n \n <p>Provider networks in MA varied in restrictiveness. OB-Gynecology was the most restrictive with enrollees seeing 34.5% (95% CI: 34.3%–34.7%) as many providers as they would absent network restrictions; cardiology was the least restrictive with enrollees seeing 58.6% (95% CI: 58.4%–58.8%) as many providers as they otherwise would. Factors associated with less restrictive networks included the county-level TM average hierarchical condition category score (0.06; 95% CI: 0.04–0.07), the county-level number of doctors per 1000 population (0.04; 95% CI: 0.02–0.05), the natural log of local median household income (0.03; 95% CI: 0.007–0.05), and the parent company's market share in the county (0.16; 95% CI: 0.13–0.18). Rurality was a major predictor of more restrictive networks (−0.28; 95% CI: −0.32 to −0.24).</p>\n </section>\n \n <section>\n \n <h3> Conclusions</h3>\n \n <p>Our findings suggest that rural beneficiaries may face disproportionately reduced access in these networks and that efforts to improve access should vary by specialty.</p>\n </section>\n </div>","PeriodicalId":55065,"journal":{"name":"Health Services Research","volume":null,"pages":null},"PeriodicalIF":3.1000,"publicationDate":"2024-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Restrictiveness of Medicare Advantage provider networks across physician specialties\",\"authors\":\"Yevgeniy Feyman PhD, Jose Figueroa MD, MPH, Melissa Garrido PhD, Gretchen Jacobson PhD, Michael Adelberg MA, MPP, Austin Frakt PhD\",\"doi\":\"10.1111/1475-6773.14308\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div>\\n \\n \\n <section>\\n \\n <h3> Objective</h3>\\n \\n <p>The objective was to measure specialty provider networks in Medicare Advantage (MA) and examine associations with market factors.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Data Sources and Study Setting</h3>\\n \\n <p>We relied on traditional Medicare (TM) and MA prescription drug event data from 2011 to 2017 for all Medicare beneficiaries in the United States as well as data from the Area Health Resources File.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Study Design</h3>\\n \\n <p>Relying on a recently developed and validated prediction model, we calculated the provider network restrictiveness of MA contracts for nine high-prescribing specialties. We characterized network restrictiveness through an observed-to-expected ratio, calculated as the number of unique providers seen by MA beneficiaries divided by the number expected based on the prediction model. We assessed the relationship between network restrictiveness and market factors across specialties with multivariable linear regression.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Data Collection/Extraction Methods</h3>\\n \\n <p>Prescription drug event data for a 20% random sample of beneficiaries enrolled in prescription drug coverage from 2011 to 2017.</p>\\n </section>\\n \\n <section>\\n \\n <h3> Principal Findings</h3>\\n \\n <p>Provider networks in MA varied in restrictiveness. OB-Gynecology was the most restrictive with enrollees seeing 34.5% (95% CI: 34.3%–34.7%) as many providers as they would absent network restrictions; cardiology was the least restrictive with enrollees seeing 58.6% (95% CI: 58.4%–58.8%) as many providers as they otherwise would. Factors associated with less restrictive networks included the county-level TM average hierarchical condition category score (0.06; 95% CI: 0.04–0.07), the county-level number of doctors per 1000 population (0.04; 95% CI: 0.02–0.05), the natural log of local median household income (0.03; 95% CI: 0.007–0.05), and the parent company's market share in the county (0.16; 95% CI: 0.13–0.18). 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Restrictiveness of Medicare Advantage provider networks across physician specialties
Objective
The objective was to measure specialty provider networks in Medicare Advantage (MA) and examine associations with market factors.
Data Sources and Study Setting
We relied on traditional Medicare (TM) and MA prescription drug event data from 2011 to 2017 for all Medicare beneficiaries in the United States as well as data from the Area Health Resources File.
Study Design
Relying on a recently developed and validated prediction model, we calculated the provider network restrictiveness of MA contracts for nine high-prescribing specialties. We characterized network restrictiveness through an observed-to-expected ratio, calculated as the number of unique providers seen by MA beneficiaries divided by the number expected based on the prediction model. We assessed the relationship between network restrictiveness and market factors across specialties with multivariable linear regression.
Data Collection/Extraction Methods
Prescription drug event data for a 20% random sample of beneficiaries enrolled in prescription drug coverage from 2011 to 2017.
Principal Findings
Provider networks in MA varied in restrictiveness. OB-Gynecology was the most restrictive with enrollees seeing 34.5% (95% CI: 34.3%–34.7%) as many providers as they would absent network restrictions; cardiology was the least restrictive with enrollees seeing 58.6% (95% CI: 58.4%–58.8%) as many providers as they otherwise would. Factors associated with less restrictive networks included the county-level TM average hierarchical condition category score (0.06; 95% CI: 0.04–0.07), the county-level number of doctors per 1000 population (0.04; 95% CI: 0.02–0.05), the natural log of local median household income (0.03; 95% CI: 0.007–0.05), and the parent company's market share in the county (0.16; 95% CI: 0.13–0.18). Rurality was a major predictor of more restrictive networks (−0.28; 95% CI: −0.32 to −0.24).
Conclusions
Our findings suggest that rural beneficiaries may face disproportionately reduced access in these networks and that efforts to improve access should vary by specialty.
期刊介绍:
Health Services Research (HSR) is a peer-reviewed scholarly journal that provides researchers and public and private policymakers with the latest research findings, methods, and concepts related to the financing, organization, delivery, evaluation, and outcomes of health services. Rated as one of the top journals in the fields of health policy and services and health care administration, HSR publishes outstanding articles reporting the findings of original investigations that expand knowledge and understanding of the wide-ranging field of health care and that will help to improve the health of individuals and communities.