A Universal Appointment Rule with Patient Classification for Service Times, No-Shows, and Walk-Ins

This study evaluates patient classification for scheduling and sequencing appointments for patients differentiated by their mean and standard deviation of service times, no-show, and walk-in probabilities. Alternative appointment systems are tested through simulation using a universal Dome rule and some of the best traditional appointment rules in the literature. Our findings show that the universal Dome rule performs better in terms of reducing the total cost of patient’s waiting time, doctor’s idle time, and overtime, and its performance improves further with the right sequencing of patient groups. Although it is a challenge to find the best sequence, we propose a heuristic rule that successfully identifies the best sequence with an accuracy level of 98% for the universal Dome rule. Sensitivity analyses further confirm that our findings are valid even when assumptions on patient punctuality and service time distributions are relaxed. To facilitate the use of our proposed appointment system, an open source online tool is developed to support practitioners in designing their appointment schedules for real clinics.

[1]  J. Wijngaard,et al.  The outpatient appointment system: Design of a simulation study , 1979 .

[2]  Emre A. Veral,et al.  Assessment of patient classification in appointment system design , 2008 .

[3]  James R. Wilson,et al.  Modeling patient arrivals in community clinics , 2008 .

[4]  Matthew Rosenshine,et al.  Scheduling arrivals to queues , 1990, Comput. Oper. Res..

[5]  P. Patrick Wang,et al.  Static and dynamic scheduling of customer arrivals to a single‐server system , 1993 .

[6]  Kenneth J. Klassen,et al.  Strategies for Appointment Policy Design with Patient Unpunctuality , 2014, Decis. Sci..

[7]  Lawrence W. Robinson,et al.  Scheduling doctors' appointments: optimal and empirically-based heuristic policies , 2003 .

[8]  S. D. Walter A comparison of appointment schedules in a hospital radiology department. , 1973, British journal of preventive & social medicine.

[9]  T. Rohleder,et al.  Outpatient appointment scheduling with urgent clients in a dynamic, multi‐period environment , 2004 .

[10]  Kurt M. Bretthauer,et al.  The Impact of Variability and Patient Information on Health Care System Performance , 2011 .

[11]  Brian T. Denton,et al.  Bi‐Criteria Scheduling of Surgical Services for an Outpatient Procedure Center , 2011 .

[12]  Thomas R. Rohleder,et al.  Scheduling outpatient appointments in a dynamic environment , 1996 .

[13]  Brian Lehaney,et al.  A case of an intervention in an outpatients department , 1999, J. Oper. Res. Soc..

[14]  C. Dennis Pegden,et al.  PLANNING TIMELY ARRIVALS TO A STOCHASTIC PRODUCTION OR SERVICE SYSTEM , 1988 .

[15]  R. O'keefe,et al.  Investigating Outpatient Departments: Implementable Policies and Qualitative Approaches , 1985, The Journal of the Operational Research Society.

[16]  Emre A. Veral,et al.  Designing appointment scheduling systems for ambulatory care services , 2006, Health care management science.

[17]  John Fontanesi,et al.  Stochastic Modeling of Patient Arrival Offset Times in Scheduled Visits , 2012 .

[18]  Stephen R. Lawrence,et al.  Appointment Overbooking in Health Care Clinics to Improve Patient Service and Clinic Performance , 2012 .

[19]  Evrim Didem Günes,et al.  Outpatient appointment scheduling in presence of seasonal walk-ins , 2014, J. Oper. Res. Soc..

[20]  Martin L. Puterman,et al.  Improving resource utilization for diagnostic services through flexible inpatient scheduling: A method for improving resource utilization , 2007, J. Oper. Res. Soc..

[21]  G. Swartzman,et al.  The patient arrival process in hospitals: statistical analysis. , 1970, Health services research.

[22]  Maurice Queyranne,et al.  Appointment Scheduling with Discrete Random Durations , 2009, Math. Oper. Res..

[23]  Rainer Kolisch,et al.  Providing radiology health care services to stochastic demand of different customer classes , 2008, OR Spectr..

[24]  Kumar Muthuraman,et al.  A stochastic overbooking model for outpatient clinical scheduling with no-shows , 2008 .

[25]  Refael Hassin,et al.  Scheduling Arrivals to Queues: A Single-Server Model with No-Shows , 2008, Manag. Sci..

[26]  Paul R. Harper,et al.  Reduced outpatient waiting times with improved appointment scheduling: a simulation modelling approach , 2003, OR Spectr..

[27]  Brant E. Fries,et al.  Determination of Optimal Variable-Sized Multiple-Block Appointment Systems , 1981, Oper. Res..

[28]  N. Bailey A Study of Queues and Appointment Systems in Hospital Out‐Patient Departments, with Special Reference to Waiting‐Times , 1952 .

[29]  Dennis C. Dietz,et al.  Minimizing expected waiting in a medical appointment system , 2000 .

[30]  Hon-Shiang Lau,et al.  Evaluating the impact of operating conditions on the performance of appointment scheduling rules in service systems , 1999, Eur. J. Oper. Res..

[31]  F Dexter,et al.  Design of appointment systems for preanesthesia evaluation clinics to minimize patient waiting times: a review of computer simulation and patient survey studies. , 1999, Anesthesia and analgesia.

[32]  Thomas R. Rohleder,et al.  Using client-variance information to improve dynamic appointment scheduling performance , 2000 .

[33]  Kenneth J. Klassen,et al.  Improving Performance in Outpatient Appointment Services with a Simulation Optimization Approach , 2009 .

[34]  Diwakar Gupta,et al.  A Sequential Bounding Approach for Optimal Appointment Scheduling , 2003 .

[35]  Ger Koole,et al.  Optimal outpatient appointment scheduling , 2007, Health care management science.

[36]  Ronald E. Giachetti,et al.  A Stochastic Mathematical Appointment Overbooking Model for Healthcare Providers to Improve Profits , 2006, IEEE Transactions on Systems, Man, and Cybernetics - Part A: Systems and Humans.

[37]  Ben Wang,et al.  Managing Patient Service in a Diagnostic Medical Facility , 2006, Oper. Res..

[38]  Edward J. Rising,et al.  A Systems Analysis of a University-Health-Service Outpatient Clinic , 1973, Oper. Res..

[39]  Kum Khiong Yang,et al.  A universal appointment rule in the presence of no-shows and walk-ins , 2012 .

[40]  A. Soriano,et al.  Comparison of Two Scheduling Systems , 1966, Oper. Res..

[41]  Elliott N. Weiss,et al.  Models for Determining Estimated Start Times and Case Orderings In Hospital Operating Rooms , 1990 .

[42]  Peter Williams,et al.  Optimization of scheduling patient appointments in clinics using a novel modelling technique of patient arrival , 2012, Comput. Methods Programs Biomed..

[43]  Xiaoming Liu,et al.  Block appointment systems for outpatient clinics with multiple doctors , 1998, J. Oper. Res. Soc..

[44]  Maurice Queyranne,et al.  Dynamic Multipriority Patient Scheduling for a Diagnostic Resource , 2008, Oper. Res..

[45]  Joseph Fong,et al.  Hybrid Learning and Continuing Education , 2013, Lecture Notes in Computer Science.

[46]  Maqbool Dada,et al.  Patient punctuality and clinic performance: observations from an academic-based private practice pain centre: a prospective quality improvement study , 2014, BMJ Open.

[47]  R. Fetter,et al.  Patients' waiting time and doctors' idle time in the outpatient setting. , 1966, Health services research.

[48]  P. Patrick Wang,et al.  Sequencing and scheduling N customers for a stochastic server , 1999, Eur. J. Oper. Res..

[49]  Stephen R. Lawrence,et al.  Clinic Overbooking to Improve Patient Access and Increase Provider Productivity , 2007, Decis. Sci..

[50]  Emre A. Veral,et al.  OUTPATIENT SCHEDULING IN HEALTH CARE: A REVIEW OF LITERATURE , 2003 .

[51]  T. Cox,et al.  Optimising the queuing system for an ear, nose and throat outpatient clinic , 1985 .

[52]  M. Pike,et al.  Appointment Systems in Out-patients?? Clinics and the Effect of Patients?? Unpunctuality , 1964 .

[53]  Kum Khiong Yang,et al.  A new appointment rule for a single-server, multiple-customer service system , 1998 .

[54]  Brian Denton,et al.  Optimization of surgery sequencing and scheduling decisions under uncertainty , 2007, Health care management science.