Protective Effects of Increased EHR-Mediated Information Sharing Within- and Between-Healthcare Teams on Patient Outcomes
Tu, S.-P.; Sewell, D.; Garcia, B.; Stoddard-O'Neill, Q.; Hogarth, M.; Shuffler, M.; Boussina, A.; Chew, H.; Cooke, D.; Romano, P.; Elmore, J.; Dow, A.; Zhu, X.
Show abstract
Electronic Health Records (EHRs) provide a common repository for patient information, and while many challenges persist, EHRs allow asynchronous coordination among healthcare professionals (HCPs). Such coordination is inherently challenging, as large multidisciplinary teams, or teams-of-teams, of HCPs jointly manage complex patient care. These teams-of-teams naturally fit under the Multiteam System (MTS) framework, where evidence suggests that both stronger within- and between-team communication improves overall team performance. Yet little is known how about these patterns of information sharing mediated through the EHR correlate with patient outcomes. We extracted over 53.9 million EHR access logs for 482 patients to construct novel within- and between-team information sharing measures which were then used to predict future emergency department (ED) visits and hospitalizations admitted through the ED. These network measures showed both statistical and practical significance, suggesting that this modifiable dimension of teamwork-information sharing through the EHR-could reduce acute care utilization.
Matching journals
The top 2 journals account for 50% of the predicted probability mass.
Similar papers in this journal
- Large language models improve transferability of electronic health record-based predictions across countries and coding systems 91%
- Aggregating Multiple Real-World Data Sources using a Patient-Centered Health Data Sharing Platform: an 8-week Cohort Study among Patients Undergoing Bariatric Surgery or Catheter Ablation of Atrial Fibrillation 90%
- Development and assessment of a machine learning tool for predicting emergency admission in Scotland 89%
Similar papers in this journal
- Diagnostic Codes in AI prediction models and Label Leakage of Same-admission Clinical Outcomes 89%
- Crowdfunding Medical Care: A Comparison of Online Medical Fundraising in Canada, the United Kingdom, and the United States 89%
- Estimating the Burden of Influenza on Daily Activity at Population Scale Using Commercial Wearable Sensors 88%
Similar papers in this journal
- Eleven key measures for monitoring general practice clinical activity during COVID-19 using federated analytics on 48 million adults’ primary care records through OpenSAFELY 88%
- Ten months of temporal variation in the clinical journey of hospitalised patients with COVID-19: an observational cohort 87%
- Disentangling the rhythms of human activity in the built environment for airborne transmission risk: a large-scale analysis of mobility data 87%
"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.