title: Non-punctual patients: planning for variability in appointment arrival times.
abstract: Tighter competition and rationed resources place a premium on health clinic management of patient arrival times to maximize smooth workflow dynamics and consistency in patient processes. Early efforts to analyze patient arrival characteristics relied on assumptions that may have been too simplistic. For instance, it was assumed that a scheduled patient's arrival was likely to fit a bell-shaped curve in terms of being early, late, or on time and that any one patient's likelihood of being "on time" was purely a random event. However, our analysis of patient arrival times, obtained from detailed workflow observations in nine community clinics, indicates that the likelihood of a patient arriving early, late, or on time is neither entirely random nor does the pattern of arrivals fit a bell-shaped curve. Rather, patients tend to arrive in "clumps," possibly due to factors such as traffic patterns and parking availability. These findings are important with respect to 1) clinic practice management, 2) scheduling optimization strategies, and 3) computer simulation and analysis of clinic processes.
authors.affiliation: Department of Pediatrics, University of California, San Diego, 9500 Gilman Drive, La Jolla, CA 92093-0927, USA. jfontanesi@ucsd.edu
authors.forename: John
authors.initials: J
authors.lastname: Fontanesi
authors.forename: Christos
authors.initials: C
authors.lastname: Alexopoulos
authors.forename: David
authors.initials: D
authors.lastname: Goldsman
authors.forename: Michelle
authors.initials: M
authors.lastname: DeGuire
authors.forename: David
authors.initials: D
authors.lastname: Kopald
authors.forename: Kathy
authors.initials: K
authors.lastname: Holcomb
authors.forename: Mark H
authors.initials: MH
authors.lastname: Sawyer
mesh_terms: D001071:Appointments and Schedules; D016009:Chi-Square Distribution; D003625:Data Collection; D010818:Practice Patterns, Physicians' / Q000458:organization & administration*; D013997:Time Factors