ArticleJournal of general internal medicine2019
Comparing Shared Patient Networks Across Payers.
Article in Journal of general internal medicine, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
18 citing papers in PubMed, 28 citations in OpenAlex.
- A Scoping Review of Multilevel Patient-Sharing Network Measures in Health Services Research.Medical care research and review : MCRR · 2025Article
- Considerations for Social Networks and Health Data Sharing: An Overview.Annals of epidemiology · 2025Review
- Catchment area and cancer population health research through a novel population-based statewide database: a scoping review.JNCI cancer spectrum · 2024Article
- The segregation of physician networks providing care to black and white patients with heart disease: Concepts, measures, and empirical evaluation.Social science & medicine (1982) · 2024Article
- A flexible approach to measure care coordination based on patient-sharing networks.BMC medical research methodology · 2024Article
- Within-Physician Differences in Patient Sharing Between Primary Care Physicians and Cardiologists Who Treat White and Black Patients With Heart Disease.Journal of the American Heart Association · 2023Article
- Can peer effects explain prescribing appropriateness? a social network analysis.BMC medical research methodology · 2023Article
- Physician patient sharing relationships within insurance plan networks.Health services research · 2023Article
- Characteristics of Specialty Mental Health Provider Networks in Oregon Medicaid.Psychiatric services (Washington, D.C.) · 2023Article
- Team Relationships and Performance: Evidence from Healthcare Referral Networks.Management science · 2022Article
- Physician network connections to specialists and HIV quality of care.Health services research · 2021Article
- Physician Network Connections Associated With Faster De-Adoption of Dronedarone for Permanent Atrial Fibrillation.Circulation. Cardiovascular quality and outcomes · 2021Article
- The association of insurance plan characteristics with physician patient-sharing network structure.International journal of health economics and management · 2021Article
- The impact of sampling patients on measuring physician patient-sharing networks using Medicare data.Health services research · 2020Article
- Care coordination for severe mental health disorders: an analysis of healthcare provider patient-sharing networks and their association with quality of care in a French region.BMC health services research · 2020Article
- Article
- Improving Network Science in Health Services Research.Journal of general internal medicine · 2019Article
- Referral Network Increases Physicians' Adoption of Active Surveillance for Localized Prostate Cancer: A Cross-Sectional Study Using SEER-Medicare.Inquiry : a journal of medical care organization, provision and financingArticle
Corrections and comments
- Commented on by
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
backgroundMeasuring care coordination in administrative data facilitates important research to improve care quality.
objectiveTo compare shared patient networks constructed from administrative claims data across multiple payers.
designSocial network analysis of pooled cross sections of physicians treating prevalent colorectal cancer patients between 2003 and 2013.
participantsSurgeons, medical oncologists, and radiation oncologists identified from North Carolina Central Cancer Registry data linked to Medicare claims (N = 1735) and private insurance claims (N = 1321). MAIN MEASURES: Provider-level measures included the number of patients treated, the number of providers with whom they share patients (by specialty), the extent of patient sharing with each specialty, and network centrality. Network-level measures included the number of providers and shared patients, the density of shared-patient relationships among providers, and the size and composition of clusters of providers with a high level of patient sharing.
resultsFor 24.5% of providers, total patient volume rank differed by at least one quintile group between payers. Medicare claims missed 14.6% of all shared patient relationships between providers, but captured a greater number of patient-sharing relationships per provider compared with the private insurance database, even after controlling for the total number of patients (27.242 vs 26.044, p < 0.001). Providers in the private network shared a higher fraction of patients with other providers (0.226 vs 0.127, p < 0.001) compared to the Medicare network. Clustering coefficients for providers, weighted betweenness, and eigenvector centrality varied greatly across payers. Network differences led to some clusters of providers that existed in the combined network not being detected in Medicare alone.
conclusionMany features of shared patient networks constructed from a single-payer database differed from similar networks constructed from other payers' data. Depending on a study's goals, shortcomings of single-payer networks should be considered when using claims data to draw conclusions about provider behavior.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.