Franklin Dexter1, Hyun-Soo Ahn, Richard H Epstein. 1. Department of Anesthesia, Division of Management Consulting, University of Iowa, 200 Hawkins Dr., 6JCP, Iowa City, IA 52242, USA. Franklin-Dexter@UIowa.ed
Abstract
BACKGROUND: When a practitioner in a preanesthesia evaluation clinic is not evaluating a patient because no patient is waiting to be seen, the practitioner often has other responsibilities such as reviewing charts of patients. When practitioners differ in how quickly they complete evaluations, multiple scenarios can be created wherein the slowest practitioner would only evaluate patients when the number of patients waiting exceeds a threshold (e.g., at least 2 patients are waiting). METHODS: Review of operations research studies identified conditions for which such management of the queue can be beneficial (e.g., mean evaluation time of the fastest practitioner is less than half that of the slowest practitioner). These conditions were compared with the actual completion rates of certified registered nurse practitioners at a hospital's clinic. The 99.9% confidence intervals (CI) were calculated for ratios of mean evaluation times. RESULTS: The fastest practitioner was typically 1.23 times faster than the second fastest practitioner (CI 1.22-1.23) and 1.61 times faster than the slowest of three practitioners (1.59-1.61). These are significantly less than the 3 times and 2 times faster, respectively, that would be sufficiently large to warrant managing queue discipline. Practitioners with longer mean evaluation times had larger percentage utilizations of working time (Kendall τb = 0.56, P = 0.0001), inconsistent with preferential assignment of patients to the fastest practitioner(s) available. CONCLUSIONS: Practitioners' speeds in evaluating patients do not differ sufficiently for information systems to be used routinely to choose who evaluates the next patient (i.e., state-dependent assignment policy). Clinics aiming to reduce patient waiting should focus on reducing the overall mean evaluation time (e.g., by chart review ahead), appropriately scheduling patients, and having the right numbers of nursing assistants and practitioners.
BACKGROUND: When a practitioner in a preanesthesia evaluation clinic is not evaluating a patient because no patient is waiting to be seen, the practitioner often has other responsibilities such as reviewing charts of patients. When practitioners differ in how quickly they complete evaluations, multiple scenarios can be created wherein the slowest practitioner would only evaluate patients when the number of patients waiting exceeds a threshold (e.g., at least 2 patients are waiting). METHODS: Review of operations research studies identified conditions for which such management of the queue can be beneficial (e.g., mean evaluation time of the fastest practitioner is less than half that of the slowest practitioner). These conditions were compared with the actual completion rates of certified registered nurse practitioners at a hospital's clinic. The 99.9% confidence intervals (CI) were calculated for ratios of mean evaluation times. RESULTS: The fastest practitioner was typically 1.23 times faster than the second fastest practitioner (CI 1.22-1.23) and 1.61 times faster than the slowest of three practitioners (1.59-1.61). These are significantly less than the 3 times and 2 times faster, respectively, that would be sufficiently large to warrant managing queue discipline. Practitioners with longer mean evaluation times had larger percentage utilizations of working time (Kendall τb = 0.56, P = 0.0001), inconsistent with preferential assignment of patients to the fastest practitioner(s) available. CONCLUSIONS: Practitioners' speeds in evaluating patients do not differ sufficiently for information systems to be used routinely to choose who evaluates the next patient (i.e., state-dependent assignment policy). Clinics aiming to reduce patient waiting should focus on reducing the overall mean evaluation time (e.g., by chart review ahead), appropriately scheduling patients, and having the right numbers of nursing assistants and practitioners.
Authors: Jonathan F Bard; Zhichao Shu; Douglas J Morrice; Dongyang Ester Wang; Ramin Poursani; Luci Leykum Journal: Health Care Manag Sci Date: 2014-08-26