Severity: Warning
Message: file_get_contents(https://...@pubfacts.com&api_key=b8daa3ad693db53b1410957c26c9a51b4908&a=1): Failed to open stream: HTTP request failed! HTTP/1.1 429 Too Many Requests
Filename: helpers/my_audit_helper.php
Line Number: 176
Backtrace:
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 176
Function: file_get_contents
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 250
Function: simplexml_load_file_from_url
File: /var/www/html/application/helpers/my_audit_helper.php
Line: 3122
Function: getPubMedXML
File: /var/www/html/application/controllers/Detail.php
Line: 575
Function: pubMedSearch_Global
File: /var/www/html/application/controllers/Detail.php
Line: 489
Function: pubMedGetRelatedKeyword
File: /var/www/html/index.php
Line: 316
Function: require_once
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.
Download full-text PDF |
Source |
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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC11250170 | PMC |
http://dx.doi.org/10.1111/1475-6773.14308 | DOI Listing |
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