ArticlePloS one2019
Impact of care provider network characteristics on patient outcomes: Usage of social network analysis and a multi-scale community detection.
Article in PloS one, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
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Who cites it
14 citing papers in PubMed.
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- Understanding Collaborative CT and MRI Utilization Through Network Analysis: Retrospective Study Using Administrative Claims Data.JMIR formative research · 2026Observational
- A Scoping Review of Multilevel Patient-Sharing Network Measures in Health Services Research.Medical care research and review : MCRR · 2025Article
- Collaborative networks in community-based health and social care services: insights from Blackpool and the Fylde Coast (United Kingdom).Health research policy and systems · 2025Article
- Article
- Cardiac interventions in Wales: A comparison of benefits between NHS Wales specialties.PloS one · 2024Article
- Effectiveness of a targeted telephone-based case management service on activity in an Emergency Department in the UK: a pragmatic difference-in-differences evaluation.BMC health services research · 2022Article
- Article
- Regional medical inter-institutional cooperation in medical provider network constructed using patient claims data from Japan.PloS one · 2022Article
- The Effect of Interdependences of Referral Behaviors on the Quality of Ambulatory Care: Evidence from Taiwan.Risk management and healthcare policy · 2021Article
- What Types of Networks Do Professionals Build, and How Are They Affected by the Results of Network Evaluation?Frontiers in public health · 2021Article
- Assessing Association Between Team Structure and Health Outcome and Cost by Social Network Analysis.Journal of the American Geriatrics Society · 2020Article
- A Social Network Analysis Approach for Contact Tracing in the Hospital Setting.Delaware journal of public health · 2020Article
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Authors and funding
2 authors.
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No grant is acknowledged in the PubMed record.
Abstract
objectiveWe assess healthcare provider collaboration and the impact on patient outcomes using social network analysis, a multi-scale community detection algorithm, and generalized estimating equations. MATERIAL AND
methodsA longitudinal analysis of health claims data of a large employer over a 3 year period was performed to measure how provider relationships impact patient outcomes. The study cohort included 4,230 patients with 167 providers. Social network analysis with a multi-scale community detection algorithm was used to identify groups of healthcare providers more closely working together. Resulting measures of provider collaboration were: 1) degree, 2) betweenness, and 3) closeness centrality. The three patient outcome measures were 1) emergency department visit, 2) inpatient hospitalization, and 3) unplanned hospitalization. Relationships between provider collaboration and patient outcomes were assessed using generalized estimating equations. General practitioner, family practice, and internal medicine were labeled as primary care. Cardiovascular, endocrinologists, etc. were labeled as specialists, and providers such as radiology and social workers were labeled as others.
resultsHigher connectedness (degree) and higher access (closeness) to other providers in the community were significant for reducing inpatient hospitalization and emergency department visits. Patients of specialists (e.g. cardiovascular) and providers specified as others (e.g. social worker) had higher rate of hospitalization and emergency department visits compared to patients of primary care providers.
conclusionApplication of social network analysis for developing healthcare provider networks can be leveraged by community detection algorithms and predictive modeling to identify providers' network characteristics and their impacts on patient outcomes. The proposed framework presents multi-scale measures to assess characteristics of healthcare providers and their impact on patient outcomes. This approach can be used by implementation experts for informed decision-making regarding the design of insurance coverage plans, and wellness promotion programs. Health services researchers can use the study approach for assessment of provider collaboration and impacts on patient outcomes.
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