RFID-Enabled Analysis of Care Coordination and Patient Flow in Ambulatory Care

Healthcare is primarily delivered in the ambulatory care setting. The high variability in service delivery encountered in this environment negatively impacts efficiency, quality of care, costs, patient satisfaction and safety. Care coordination, a process to manage dependencies between clinicians who provide care to a patient, has been proposed as a critical and challenging step in improving care delivery and health outcomes. In this study, we develop optimal care coordination models and policies for the ambulatory care delivery environment that optimize important service delivery metrics using a novel data collection strategy that employs RFID technology. Time and location stamped data is collected using RTLS-based Gen2IR/RFID-enabled badges worn by patients, clinicians, and staff as they complete each clinic visit. This data is mapped to facility and personnel resources and specific tasks associated with each visit to track patient flow. We analyze process variability using discrete event simulation and sequential pattern analysis, and formulate a Markov decision process model to identify best practice plans that improve care coordination. 389 office visit records associated with 327 unique patients and 12 clinicians and staff, collected over a 2-month period, are used to instantiate our models and identify optimal policies. The results also highlight the value of RTLS solutions and the challenges in deploying them to understand variability in patient care and opportunities to re-engineer services to improve service delivery in the ambulatory care environment. These methods and approaches are generalizeable to other care delivery settings and have the potential to improve healthcare services significantly.