How Digital and Physical Care Team Interaction Affect Processing Times: A Case Study of Hospitalists

Abstract

Importance: Hospitalist physicians face increasing pressure to maximize productivity while maintaining high quality of care. Their success, however, depends on the effective exchange of information among a patient’s care team. The latter comprises the digital team (caregivers who document in — not just access — the patient’s electronic health record) and a physical team (caregivers who directly communicate with the hospitalist). Objective: To determine the association between hospitalist total daily processing time per patient and the size and evolution over the patient’s LOS of the digital and physical teams as well as patient-level characteristics. Design: We measured hospitalist daily processing times and captured the physical team through a time-and-motion study of hospitalists. The digital team interactions were extracted from patient Electronic Health Records. Setting: Northwestern Memorial Hospital, a large academic urban hospital in Chicago. Participants Our case study selected four hospitalists at random who cared for 107 inpatient stays over 17 days in June-July 2014 and collaborated with 2046 caregivers: 301 were observed physical collaborators and 1745 were digital-only collaborators. Exposures: Hospitalist activities and patient encounters from observations and electronic health records. Main Outcomes and Measures: Processing time is the total time spent by the hospitalist on a patient’s care per day. Key covariates are patient-level characteristics, interruptions by physical team members, and size and evolution of both the digital and physical teams. Results: Teamwork interaction and patient-level characteristics explain 72% (18.9min) and 28% (7.2min), respectively, of the hospitalist’s average patient processing time of 26.7min per day. Teamwork is further decomposed in two ways: (i) 18.9 = 15.4 3.5 where 15.4min and 3.5min captures the teamwork effect at a macro level (driven by team size and stability variables) and micro level effect (hospitalist workflow interruptions driven by task switches), respectively; (ii) 18.9 = 8.8 10.1 where 8.8min and 10.1min capture digital and physical team variables, respectively. As a benchmark, eliminating interruptions reduces processing times by 3.5min (13%) while minimizing team size and maximizing team stability reduces processing times by 7.8min (29%). The supplementary materials can be found here: http://ssrn.com/abstract=3068197.