ArticleJournal of the American Medical Informatics Association : JAMIA2017
Identifying collaborative care teams through electronic medical record utilization patterns.
Article in Journal of the American Medical Informatics Association : JAMIA, 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers, 1 of them a synthesis that pooled it.
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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.
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Who cites it
21 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Using electronic health record audit logs to study clinical activity: a systematic review of aims, measures, and methods.Journal of the American Medical Informatics Association : JAMIA · 2020Pooled it
- Electronic health record activity changes around new decision support implementation: monitoring using audit logs and topic modeling.JAMIA open · 2025Article
- An electronic health record metadata-mining approach to identifying patient-level interprofessional clinician teams in the intensive care unit.Journal of the American Medical Informatics Association : JAMIA · 2025Article
- Reimagining clinical AI: from clickstreams to clinical insights with EHR use metadata.npj health systems · 2025Review
- Familiarity Among Nurses: The Key to ICU Patient Outcomes?American journal of respiratory and critical care medicine · 2023Article
- Characterizing intensive care unit rounding teams using meta-data from the electronic health record.Journal of critical care · 2022Article
- Examining Diurnal Differences in Multidisciplinary Care Teams at a Pediatric Trauma Center Using Electronic Health Record Data: Social Network Analysis.Journal of medical Internet research · 2022Article
- Assessing Neonatal Intensive Care Unit Structures and Outcomes Before and During the COVID-19 Pandemic: Network Analysis Study.Journal of medical Internet research · 2021Article
- Measuring Collaboration Through Concurrent Electronic Health Record Usage: Network Analysis Study.JMIR medical informatics · 2021Article
- An Analysis of Electronic Health Record Work to Manage Asynchronous Clinical Messages among Breast Cancer Care Teams.Applied clinical informatics · 2021Article
- Hyperpolarized Magnetic Resonance and Artificial Intelligence: Frontiers of Imaging in Pancreatic Cancer.JMIR medical informatics · 2021Review
- Collaboration Structures in COVID-19 Critical Care: Retrospective Network Analysis Study.JMIR human factors · 2021Article
- Artificial Intelligence Algorithm with ICD Coding Technology Guided by the Embedded Electronic Medical Record System in Medical Record Information Management.Journal of healthcare engineering · 2021Article
- Provider Networks in the Neonatal Intensive Care Unit Associate with Length of Stay.... IEEE Conference on Collaboration and Internet Computing. IEEE Conference on Collaboration and Internet Computing · 2019Article
- Modeling Care Team Structures in the Neonatal Intensive Care Unit through Network Analysis of EHR Audit Logs.Methods of information in medicine · 2019Article
- Evaluation of multidisciplinary collaboration in pediatric trauma care using EHR data.Journal of the American Medical Informatics Association : JAMIA · 2019Article
- Obstetric Patients with Repetitious Hospital Location Transfers Have Prolonged Stays.Proceedings. IEEE International Conference on Healthcare Informatics · 2019Article
- Interaction patterns of trauma providers are associated with length of stay.Journal of the American Medical Informatics Association : JAMIA · 2018Article
- Learning bundled care opportunities from electronic medical records.Journal of biomedical informatics · 2018Article
- Using telephony data to facilitate discovery of clinical workflows.Applied clinical informatics · 2017Article
Corrections and comments
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Authors and funding
5 authors.
Funding
Abstract
objectiveThe goal of this investigation was to determine whether automated approaches can learn patient-oriented care teams via utilization of an electronic medical record (EMR) system. MATERIALS AND
methodsTo perform this investigation, we designed a data-mining framework that relies on a combination of latent topic modeling and network analysis to infer patterns of collaborative teams. We applied the framework to the EMR utilization records of over 10 000 employees and 17 000 inpatients at a large academic medical center during a 4-month window in 2010. Next, we conducted an extrinsic evaluation of the patterns to determine the plausibility of the inferred care teams via surveys with knowledgeable experts. Finally, we conducted an intrinsic evaluation to contextualize each team in terms of collaboration strength (via a cluster coefficient) and clinical credibility (via associations between teams and patient comorbidities).
resultsThe framework discovered 34 collaborative care teams, 27 (79.4%) of which were confirmed as administratively plausible. Of those, 26 teams depicted strong collaborations, with a cluster coefficient > 0.5. There were 119 diagnostic conditions associated with 34 care teams. Additionally, to provide clarity on how the survey respondents arrived at their determinations, we worked with several oncologists to develop an illustrative example of how a certain team functions in cancer care. DISCUSSION: Inferred collaborative teams are plausible; translating such patterns into optimized collaborative care will require administrative review and integration with management practices.
conclusionsEMR utilization records can be mined for collaborative care patterns in large complex medical centers.
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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.