ArticleAMIA ... Annual Symposium proceedings. AMIA Symposium2018
Identifying Key Players in the Care Process of Patients with Diabetes Using Social Network Analysis and Administrative Data.
Article in AMIA ... Annual Symposium proceedings. AMIA Symposium, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 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
7 citing papers in PubMed, 14 citations in OpenAlex.
- Transcriptomic Profiling Identifies Potential Prognostic Genes in Vietnamese Patients with Non-Small-Cell Lung Cancer.Current issues in molecular biology · 2026Article
- A Scoping Review of Multilevel Patient-Sharing Network Measures in Health Services Research.Medical care research and review : MCRR · 2025Article
- Article
- Assessing Association Between Team Structure and Health Outcome and Cost by Social Network Analysis.Journal of the American Geriatrics Society · 2020Article
- Data-driven modeling of diabetes care teams using social network analysis.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Determining networks of healthcare providers quantitatively can identify impactful care processes that improve health outcomes for a high-risk populations such as elderly people with multiple chronic conditions. By applying social network analysis to health claim data of a large university in the Midwest, we measured healthcare provider networks of patients with diabetes for two consecutive years. Networks were built based on the assumption that having common patients may indicate potential working relationships between providers. Measures of the social network analysis including degree and betweenness centrality were utilized to identify healthcare providers with an important role in the care process. Both degree and betweenness centrality measures identified a supply center and three laboratories as the central providers of the network for both years. This study can positively impact informed decision-making of policymakers and insurance companies to better design their insurance coverage plans based on the collaboration patterns of the healthcare providers.
Indexed as
Identifiers
30815188PMC6371373W2941147924What 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.