Data-driven modeling of diabetes care teams using social network analysis

Mina Ostovari · Charlotte Joy Steele-Morris · Paul M. Griffin · Denny Yu

14 citations0/0 files storedJournal of the American Medical Informatics Association

No readable copy stored yet — this record is metadata only.

No open-access location is known for this record yet.

Literature note Cite in a project Citation map

Healthcare Systems and Technology Healthcare Policy and Management Complex Network Analysis Techniques

Abstract

OBJECTIVE: We assess working relationships and collaborations within and between diabetes health care provider teams using social network analysis and a multi-scale community detection. MATERIALS AND METHODS: Retrospective analysis of claims data from a large employer over 2 years was performed. The study cohort contained 827 patients diagnosed with diabetes. The cohort received care from 2567 and 2541 health care providers in the first and second year, respectively. Social network analysis was used to identify networks of health care providers involved in the care of patients with diabetes. A multi-scale community detection was applied to the network to identify groups of health care providers more densely connected. Social network analysis metrics identified influential providers for the overall network and for each community of providers. RESULTS: Centrality measures identified medical laboratories and mail-order pharmacies as the central providers for the 2 years. Seventy-six percent of the detected communities included primary care physicians, and 97% of the communities included specialists. Pharmacists were detected as central providers in 24% of the communities. DISCUSSION: Social network analysis measures identified the central providers in the network of diabetes health care providers. These providers could be considered as influencers in the network that could enhance the implication of promotion programs through their access to a large number of patients and providers. CONCLUSION: The proposed framework provides multi-scale metrics for assessing care team relationships. These metrics can be used by implementation experts to identify influential providers for care interventions and by health service researchers to determine impact of team relationships on patient outcomes.

Paper brief

Loading…

Cite this work

Citation unavailable for this work.

BibTeX RIS CSL-JSON

No public copy is stored for this record, so only the metadata is cited.

Citations in this library

Citation map →

Stored only when both papers are in the corpus — 14 citations exist upstream.

References

1953Who Shall Survive? Foundations of Sociometry, Group Psychotherapy and Sociodrama 2011Health professional networks as a vector for improving healthcare quality and safety: a systematic review 2012Variation in Patient-Sharing Networks of Physicians Across the United States 2011Mapping Physician Networks with Self-Reported and Administrative Data 2012Physician Patient-sharing Networks and the Cost and Intensity of Care in US Hospitals 1953Who Shall Survive? Foundations of Sociometry, Group Psychotherapy and Sociodrama 2009Understanding communication networks in the emergency department 2012Patient Sharing Among Physicians and Costs of Care: A Network Analytic Approach to Care Coordination Using Claims Data

Cited by

2022Using social network analysis methods to identify networks of physicians responsible for the care of specific patient populations

Explore the map →

Papers that cite the same references — the relational fallback while embeddings are still backfilling.

Imported from OpenAlex (CC0) — nothing here is generated.