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Using a real-time location system to measure patient flow in a radiation oncology outpatient clinic
Kevin Conley1, Chester Chambers2, Shereef Elnahal1
1Johns Hopkins School of Medicine, Department of Radiation Oncology and Molecular Radiation Sciences, Baltimore, Maryland.
Purpose:
Common performance metrics for outpatient clinics define the time between patient arrival and entry into an examination room as "waiting time." Time spent in the room is considered processing time. This characterization systematically ignores time spent in the examination room waiting for service. If these definitions are used, performance will consistently understate total waiting times and overstate processing times. Correcting such errors will provide a better understanding of system behavior.
Methods And Materials:
In a radiation oncology service in an urban academic clinic, we collected data from a patient management system for 84 patients with 4 distinct types of visits: consultations, follow-ups, on-treatment visits, and nurse visits. Examination room entry and exit times were collected with a real-time location system for relevant care team members. Novel metrics of clinic performance were created, including the ratio of face time (ie, time during which the patient is with a practitioner) to total cycle time, which we label face-time efficiency. Attending physician interruptions occurred when the attending is called out of the room during a patient visit, and coordination-related delays are defined as waits for another team member.
Results:
Face-time efficiency levels for consults, follow-ups, on-treatment visits, and nurse visits were 30.1%, 22.9%, 33.0%, and 25.6%, respectively. Attending physician interruptions averaged 6.7 minutes per patient. If these interruptions were eliminated, face-time efficiencies would rise to 33.2%, 29.2%, 34.4%, and 25.6%, respectively. Eliminating all coordination-related delays would increase these values to 41.3%, 38.9%, 54.7%, and 38.7%, respectively.
Conclusions:
A real-time location system can be used to augment a patient management system and automate data collection to provide improved descriptions of clinic performance.
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