Healthcare Scheduling by Data Mining: Literature Review and Future Directions

Rinder, Maria M.; Weckman, Gary; Schwerha, Diana; Snow, Andy; Dreher, Peter A.; Park, Namkyu; Paschold, Helmut; Young, William

doi:https://doi.org/10.1260/2040-2295.3.3.477

Journal of Healthcare Engineering

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Research Article | Open Access

Volume 3 | Article ID 734237 | https://doi.org/10.1260/2040-2295.3.3.477

Healthcare Scheduling by Data Mining: Literature Review and Future Directions

Maria M. Rinder,¹Gary Weckman,¹Diana Schwerha,¹Andy Snow,²Peter A. Dreher,⁴Namkyu Park,¹Helmut Paschold,³and William Young¹

Received01 Aug 2011

Accepted01 Apr 2012

Abstract

This article presents a systematic literature review of the application of industrial engineering methods in healthcare scheduling, with a focus on the role of patient behavior in scheduling. Nine articles that used mathematical programming, data mining, genetic algorithms, and local searches for optimum schedules were obtained from an extensive search of literature. These methods are new approaches to solve the problems in healthcare scheduling. Some are adapted from areas such as manufacturing and transportation. Key findings from these studies include reduced time for scheduling, capability of solving more complex problems, and incorporation of more variables and constraints simultaneously than traditional scheduling methods. However, none of these methods modeled no-show and walk-ins patient behavior. Future research should include more variables related to patient and/or environment.

References

Bureau of Labor Statistics 2009, Estimated quarterly revenue for employer firms, seasonally adjusted, www.census.gov/qss, Accessed September 2009.
Plunkett Research Ltd, Industry statistics, trends and in-depth analysis of top companies, http://www.plunkettresearch.com/Industries/HealthCare/HealthCareTrends/tabid/294/Default.aspx, Accessed September 2009.
A. Gupta and B. Denton, “Appointment scheduling in health care: challenges and opportunities,” IIE Transactions, vol. 40, pp. 800–819, 2008.
View at: Google Scholar
D. R. Sweeney, “Your office: a lot of things will have to change,” Medical Economics, vol. 73, no. 7, pp. 97–102, 1996.
View at: Google Scholar
P. D. Wright, K. M. Bretthauer, and M. J. Coté, “Reexamining the nurse scheduling problems: staffing ratios and nursing shortages,” Decision Science, vol. 37, no. 1, pp. 39–70, 2006.
View at: Google Scholar
A. Turkan, B. Zeng, K. Muthuraman, and M. Lawley, “Sequential clinical scheduling with service criteria,” European Journal of Operational Research, vol. 214, pp. 780–795, 2011.
View at: Google Scholar
H. Fei, N. Meskens, and C. Chu, “A planning and scheduling problem for an operating theatre using an open scheduling strateg,” Computers and Industrial Engineering, vol. 58, pp. 221–230, 2010.
View at: Google Scholar
S. Ceschia and A. Schaerf, “Local search and lower bounds for the patient admission scheduling problem,” Computers and Operations Research, vol. 38, pp. 1452–1463, 2011.
View at: Google Scholar
X. Huang, “Patients Attitude towards waiting in an outpatient clinic and its applications,” Health Services Management Research, vol. 7, pp. 2–8, 1994.
View at: Google Scholar
A. R. Jackson, “A waiting time survey in general practice,” Australian Family Physician, vol. 20, no. 12, pp. 1744–1750, 1991.
View at: Google Scholar
M. Wojtys, L. S. Edward, K. A. Overgaard, and J. Agbabian, “Applying lean techniques to improve the patient scheduling process,” Journal for Healthcare Quality, vol. 31, pp. 10–16, 2009.
View at: Google Scholar
X. Qu and J. Shi, “Modeling the effect of patient choice on the performance of open access scheduling,” International Journal of Production Economics, vol. 129, pp. 314–327, 2011.
View at: Google Scholar
M. Murray and D. M. Berwick, “Advanced access: reducing waiting and delays in primary care,” Journal of American Medical Association, vol. 289, pp. 1035–1040, 2003.
View at: Google Scholar
S. K. Kachhal, “Industrial engineering Applications in Health Care Systems,” in Handbook of Industrial Engineering. Technology and Operations Management, John Wiley and Sons, Inc., New York, 3rd edition, 2001.
View at: Google Scholar
D. V. Lindley, “The theory of queues with a single server,” Proceedings Cambridge Philosophy Society, vol. 48, pp. 277–289, 1952.
View at: Google Scholar
N. T. J. Bailey, “A study of queues and appointment systems in hospital out-patient departments, with special reference to waiting-time,” Journal of Royal Statistical Society, vol. A 14, pp. 185–199, 1952.
View at: Google Scholar
B. Jansson, “Choosing a good appointment system: a study of queues of type (D/M/1),” Operations Research, vol. 14, pp. 292–312, 1966.
View at: Google Scholar
A. Soriano, “Comparison of two scheduling systems,” Operations Research, vol. 14, pp. 388–397, 1966.
View at: Google Scholar
A. Mercer, “A queuing problem in which arrival times of the customers are scheduled,” Journal of the Royal Statistical Society Series B, vol. 22, pp. 108–113, 1960.
View at: Google Scholar
B. Fries and V. Marathe, “Determination of optimal variable-sized multiple-block appointment systems,” Operations Research, vol. 29, no. 2, pp. 324–345, 1981.
View at: Google Scholar
M. Brahimi and D. J. Worthington, “The finite capacity multi-Server queue with inhomogeneous arrival rate and discrete service time distribution and its application to continuous service time problems,” European Journal of Operational Research, vol. 50, no. 30, pp. 310–324, 1991.
View at: Google Scholar
L. Liu and X. Liu, “Block appointment systems for outpatient clinics with multiple doctors,” Journal of Operational Research Society, vol. 49, no. 12, pp. 1254–1259, 1998.
View at: Google Scholar
B. Denton and D. Gupta, “A sequential bounding approach for optimal appointments scheduling,” IIE Transactions, vol. 35, pp. 1003–1016, 2003.
View at: Google Scholar
J. D. Welch and N. T. J. Bailey, “Appointment systems in hospital outpatient departments,” Lancet, vol. 259, pp. 1105–1109, 1952.
View at: Google Scholar
J. D. Welch, “Appointment systems in hospital outpatient departments,” Operational Research Quarterly, vol. 15, no. 3, pp. 224–232, 1954.
View at: Google Scholar
R. Fetter and J. Thompson, “Patients' waiting time and doctors' idle time in the outpatient setting,” Health Services Research, vol. 1, pp. 66–90, 1966.
View at: Google Scholar
Vissers and J. Wijngaard, “The outpatient appointment system: design of a simulation study,” European Journal of Operational Research, vol. 3, no. 6, pp. 459–463, 1979.
View at: Google Scholar
C. Ho and H. Lau, “Minimizing total cost in scheduling outpatient appointments,” Management Science, vol. 38, no. 12, pp. 1750–1764, 1992.
View at: Google Scholar
C. Ho, H. Lau, and J. Li, “Introducing variable-interval appointment scheduling in service systems,” International Journal of Production & Operations Management, vol. 15, no. 6, pp. 59–69, 1995.
View at: Google Scholar
C. Ho and H. Lau, “Evaluating the impact of operating conditions on the performance of appointment scheduling rules in service systems,” European Journal of Operational Research, vol. 112, no. 3, pp. 542–553, 1999.
View at: Google Scholar
K. J. Klassen and T. R. Rohleder, “Scheduling outpatient appointments in a dynamic environment,” Journal of Operations Management, vol. 14, no. 2, pp. 83–101, 1996.
View at: Google Scholar
T. R. Rohleder and K. J. Klassen, “Using client-variance information to improve dynamic appointment scheduling performance,” Omega, vol. 28, no. 3, pp. 293–302, 2000.
View at: Google Scholar
A. M. Genaidy, Cancer risk among firefighters: Epidemiologic evidence [PhD dissertation], University of Cincinnati, 2010.
V. Podgorelec and P. Kokol, “Genetic algorithm based system for patient scheduling in highly constrained situations,” Journal of Medical Systems, vol. 21, no. 6, pp. 417–427, 1997.
View at: Google Scholar
M. W. Isken and B. Rajagopalan, “Data mining to support simulation modeling of patient flow in hospitals,” Journal of Medical Systems, vol. 26, no. 2, pp. 179–197, 2002.
View at: Google Scholar
G. C. Kaandorp and G. Koole, “Optimal outpatient appointment scheduling,” Health Care Management Science, vol. 10, pp. 217–229, 2007.
View at: Google Scholar
C.-F. Chien, F.-T. Tseng, and C.-H. Chen, “An evolutionary approach to rehabilitation patient scheduling: a case study,” European Journal of Operational Research, vol. 189, pp. 1234–1253, 2008.
View at: Google Scholar
S. N. Ogulata, M. Koyuncu, and E. Karakas, “Personnel and patient scheduling in the high demand hospital services: a case study in the physiotherapy service,” Journal of Medical Systems, vol. 32, pp. 221–228, 2008.
View at: Google Scholar
S. Chakraborty, K. Muthuraman, and M. Lawley, “Sequential clinical scheduling with patient no-shows and general service time distributions,” IIE Transactions, vol. 42, pp. 354–366, 2010.
View at: Google Scholar
H. Beaulieu, J. A. Ferland, B. Gendron, and P. Michelon, “A mathematical programming approach for scheduling physicians in the emergency room,” Health Care Management Science, vol. 3, pp. 193–2000, 2000.
View at: Google Scholar
U. Aickelin and K. A. Dowsland, “An indirect genetic algorithm for a nurse scheduling problem,” Computers and Operations Research, vol. 31, no. 5, pp. 761–778, 2004.
View at: Google Scholar
M. L. DeGrano, D. J. Medeiros, and D. Eitel, “Accommodating individual preferences in nurse scheduling via auction and optimization,” Health Care Management Science, vol. 12, pp. 228–242, 2009.
View at: Google Scholar
K. Muthuraman and M. Lawley, “A stochastic overbooking model for outpatient clinical scheduling with no-shows,” IIE Transactions, vol. 40, no. 9, pp. 820–837, 2008.
View at: Google Scholar
B. Zeng, A. Turkcan, J. Lin, and M. Lawley, “Clinic scheduling models with overbooking for patients with heterogeneous no-show probabilities,” Annals of Operations Research, vol. 178, pp. 121–144, 2010.
View at: Google Scholar
R. Hall, “Patient flow: the new queuing theory for healthcare,” OR/MS Today, vol. 33, pp. 36–40, 2006.
View at: Google Scholar
T. Nolan, M. Schall, D. Berwick, and J. Roessner, Reducing delays and waiting times throughout healthcare system, Institute for Healthcare Improvement, Boston, MA, 1996.
K. J. Bennett and E. Baxley, “The effect of a carve-out advanced access scheduling system on no-show rates,” Family Medicine, vol. 41, no. 1, pp. 51–56, 2009.
View at: Google Scholar
R. A. Deyo and T. S. Inui, “Dropouts and broken appointments: a literature review and agenda for future research,” Medical Care, vol. 18, pp. 1146–1157, 1980.
View at: Google Scholar
W. M. Barron, “Failed appointments: who misses them, why they are missed, and what can be done,” Primary Care, vol. 7, pp. 563–574, 1980.
View at: Google Scholar
J. Daggy, M. Lawley, D. Willis et al., “Using no-show modeling to improve clinic performance,” Health Informatics Journal, vol. 16, no. 4, pp. 246–259, 2010.
View at: Google Scholar
W. M. Macharia, G. Leon, B. H. Rowe, B. J. Stephenson, and B. Haynes, “An overview of interventions to improve compliance with appointments keeping for medical services,” Journal of the American Medical Association, vol. 267, pp. 1813–1817, 1992.
View at: Google Scholar
Organization for Economic co-operation and development, http://www.oecd.org/home/0,3305,en_2649_201185_1_1_1_1_1,00.html, Accessed 2011.
U. S. Census Bureau, http://www.census.gov/, Accessed 2011.
L. LaGanga and S. R. Lawrence, “Clinic overbooking to improve patient access and increase provider productivity,” Decision Sciences, vol. 38, no. 2, pp. 251–276, 2007.
View at: Google Scholar
D. Sitompul and S. U. Randhawa, “Nurse scheduling models: a state-of-the-art review,” Journal of Society for Health Systems, vol. 2, no. 1, pp. 62–72, 1990.
View at: Google Scholar

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Copyright © 2012 Hindawi Publishing Corporation. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

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