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Abstract 15: Quantifying Teamwork at Hospital Discharge for Readmissions Reduction: A Network Analytics Approach

Authors :
Matthew B Carson
Denise M Scholtens
Conor N Frailey
Gayle S Kricke
Corrine Benacka
Faraz Ahmad
R. Kannan Mutharasan
Preeti Kansal
Allen S Anderson
Clyde W Yancy
Nicholas D Soulakis
Source :
Circulation: Cardiovascular Quality and Outcomes. 9
Publication Year :
2016
Publisher :
Ovid Technologies (Wolters Kluwer Health), 2016.

Abstract

Background: The vulnerable period for hospital readmission begins upon hospital discharge, a complex, interdisciplinary process that necessitates close teamwork for accurate execution of the discharge plan. Thus, better understanding of the quality of teamwork throughout the discharge process may inform strategies to reduce hospital readmissions rates. Novel methods using a network analytics approach to quantify teamwork may better characterize this critical clinical process, facilitate quality improvement (QI), and become an important tool in learning healthcare systems. Methods: We extracted three years of patient, provider, and activity data related to discharge planning for an inpatient cardiology unit from Northwestern Medicine’s Enterprise Data Warehouse. We then created a provider-patient network to identify providers who shared patients and calculated readmissions rates for provider pairs. Using these data, we calculated a novel parameter, the Shared Positive Outcome Ratio (SPOR), an objective composite measure that quantifies the concentration of positive outcomes over a set of shared patients. To identify significant low-readmission and high-readmission collaborative relationships, we compared the observed network to 1000 sample networks containing randomized readmission values. Results: We identified 133,927 actions distributed among 38 discharge activity types performed during 13,720 patient encounters. The collaborative network was composed of 1,542 providers including 503 nurses, 432 residents, 207 physicians, 111 physical and occupational therapists, 59 medical students, 32 dieticians, and other medical and administrative staff. The average encounter involved 4 providers performing 10 discharge-related actions. After pruning the network to include only provider pairs with 6 or more shared patients, we found that 6% of collaborative interactions had a significantly low SPOR, indicating lower than expected readmission rates. Conversely, 12% of collaborative interactions had a significantly high SPOR, indicating higher than expected readmission rates. We identified 21 providers who had a low SPOR for a significant percentage of their collaborations, indicating potential top performers in the teamwork domain. Conclusions: Readmission rates appear to vary across different teams of providers. Team collaboration can be quantified using a composite measure of collaboration across provider pairs. Tracking provider pair outcomes over a sufficient set of shared encounters may inform various QI strategies, such as optimizing team staffing, identifying high-performing teams who can share their best practices, and redesigning discharge care processes. Ongoing work on this model is focused on accurately risk-adjusting outcomes, which will increase the robustness of this method.

Details

ISSN :
19417705 and 19417713
Volume :
9
Database :
OpenAIRE
Journal :
Circulation: Cardiovascular Quality and Outcomes
Accession number :
edsair.doi...........648aaf234b8a7a97d5a5b228bbef013b