Assessment of Patient Classification in Appointment System Design

Abstract

T his paper investigates two approaches to patient classification: using patient classification only for sequencing patient appointments at the time of booking and using patient classification for both sequencing and appointment interval adjustment. In the latter approach, appointment intervals are adjusted to match the consultation time characteristics of different patient classes. Our simulation results indicate that new appointment systems that utilize interval adjustment for patient class are successful in improving doctors' idle time, doctors' overtime and patients' waiting times without any trade-offs. Best performing appointment systems are identified for different clinic environments characterized by walk-ins, no-shows, the percentage of new patients, and the ratio of the mean consultation time of new patients to the mean consultation time of return patients. As a result, practical guidelines are developed for managers who are responsible for designing appointment systems.

Fast Evaluation of Appointment Schedules for Outpatients in Health Care

“…Clearly, the results obtained by optimalisation studies highly depends on what criteria are effectively considered in (17). For example, C depends only on W and I in [3,17,20,13], on W and the mean effective session duration τ K +E[W K ] in [22,12], and on W , I, E[X] in [6,14].…”

“…[7]. Other proposed distributions are Cox-type [22], lognormal [6], Weibull [2], uniform and/or exponential [12,13,14,17] and even deterministic consultations [10]. However, patients may also be considered heterogeneous, i.e.…”

“…the fact that they have different known consultation time distributions. In [6] for example, a distinction is made between long and short consultations corresponding to 'new' and 'return' patients respectively. In [13] it is shown that it is beneficial to increase the intervals proportional to the standard deviation of each consultation time.…”

Design of a Patient-Centered Appointment Scheduling with Artificial Neural Network and Discrete Event Simulation

“…Chang, Y.-H. Chang Journal of Service Science and Management etc.) are an important risk factor for cardiovascular, diabetes and other diseases [14]. To keep oral diseases from harming someone's health, carrying out daily oral hygiene and engaging dental examinations and professional dental care regularly is necessary for everyone.…”

Managing urgent care in hospitals

“…Herein they take into account no-shows, as well as walk-ins, which are given a lower priority than appointment patients. They extend upon this study with flexible appointment intervals (based on patient type) [43] and again evaluate several appointment schedules. In our case however, we aim to to find the best possible appointment schedule, and not evaluate several schedule possibilities.…”