title: Contextual Computing: A Bluetooth based approach for tracking healthcare providers in the emergency room.
abstract: Hospital Emergency Departments (EDs) frequently experience crowding. One of the factors that contributes to this crowding is the "door to doctor time", which is the time from a patient's registration to when the patient is first seen by a physician. This is also one of the Meaningful Use (MU) performance measures that emergency departments report to the Center for Medicare and Medicaid Services (CMS). Current documentation methods for this measure are inaccurate due to the imprecision in manual data collection. We describe a method for automatically (in real time) and more accurately documenting the door to physician time. Using sensor-based technology, the distance between the physician and the computer is calculated by using the single board computers installed in patient rooms that log each time a Bluetooth signal is seen from a device that the physicians carry. This distance is compared automatically with the accepted room radius to determine if the physicians are present in the room at the time logged to provide greater precision. The logged times, accurate to the second, were compared with physicians' handwritten times, showing automatic recordings to be more precise. This real time automatic method will free the physician from extra cognitive load of manually recording data. This method for evaluation of performance is generic and can be used in any other setting outside the ED, and for purposes other than measuring physician time.
authors.affiliation: School of Computing, Informatics, and Decision Systems Engineering, Arizona State University, Phoenix, AZ, United States. Electronic address: joshua.frisby@asu.edu.
authors.forename: Joshua
authors.initials: J
authors.lastname: Frisby
authors.affiliation: Department of Emergency Medicine, Mayo Clinic, Phoenix, AZ, United States. Electronic address: smith.vernon@gmail.com.
authors.forename: Vernon
authors.initials: V
authors.lastname: Smith
authors.affiliation: Department of Emergency Medicine, Mayo Clinic, Phoenix, AZ, United States. Electronic address: Traub.Stephen@mayo.edu.
authors.forename: Stephen
authors.initials: S
authors.lastname: Traub
authors.affiliation: Department of Biomedical Informatics, Arizona State University, Phoenix, AZ, United States; Center for Cognitive Studies in Medicine and Public Health, The New York Academy of Medicine, New York, NY, United States. Electronic address: vimla.patel@asu.edu.
authors.forename: Vimla L
authors.initials: VL
authors.lastname: Patel
mesh_terms: D001331:Automation; D003441:Crowding; D003625:Data Collection; D004282:Documentation; D004581:Electronics; D004636:Emergency Service, Hospital; D006801:Humans; D062527:Meaningful Use; D010820:Physicians; D013997:Time Factors
keywords: Clinical workflow; Contextual Computing; Meaningful Use; Patient safety; Sensor-based tracking