Analysis of the Effect of Patients’ Clinical Conditions on No-Shows

Sangbok Lee, Kitaek Park, Kwanghun Chung

Abstract


This study focuses on analyzing no-shows associated with patients’ clinical characteristicsdescribed by diagnoses in their medical data. A dataset of 7,055 patient-records from a Veterans hospital in the United States was used to test if there is difference on no-shows along with each patient’s diagnosed diseases and the number of diagnoses. Patients with mental diseases such as drug dependence abuse and major depression, and chronic diseases such as hypertension are more likely to no-show. In comparisons with the number of diagnoses, the no-show decreases as the number of diagnoses increases up to four and doesn’t change significantly afterwards. We provide managerial insights on clinical operations problems from statistical analysis. We believe that our results can be used to develop appropriate solutions on no-shows in clinics.


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References


Atun, A. R., Sittampalam S. R., and Mohan, A., “Uses and Benefits of SMS in Healthcare Delivery,” Centre for Health Management, Imperial College London, UK, 2005.

Belardi, F. G., Weir S., and Craig F. W., “A controlled trial of an advanced access appointment system in a residency family medicine center,” Family Medicine, Vol.36, No. 5, pp. 341-345, 2004.

Chung, K. and Min, D., “Staffing a service system with appointment-based customer arrivals,” Journal of the Operational Research Society, Vol. 65, No. 10, pp. 1533-1543, 2014.

Daggy et al., “Using no-show modeling to improve clinic performance,” Health Informatics Journal, Vol. 16, No. 4, pp. 246-259, 2010.

Davis et al., “Large-scale no- show patterns and distributions for clinic operational research,” Healthcare, Vol. 4, No. 1, p. 15, 2016.

George, A. and Rubin, G., “Non-attendance in general practice: A systematic review and its implications for access to primary health care,” Family Practice, Vol. 20, No. 2, pp. 178-184, 2003.

Hamilton, W., Round, A., and Sharp, D., “Patient, hospital, and general practitioner characteristics associated with non- attendance: A cohort study,” British Journal of General Practice, Vol. 52, No. 477, pp. 317-319, 2002.

Hwang, J. I., “Factors influencing consultation time and waiting time of ambulatory patients in a tertiary teaching hospital,” Quality Improvement in Health Care, Vol. 12, No. 1, pp. 6-16, 2006.

Kang, H. J., “National-level use of health care big data and its policy implications,” Health and Welfare Policy Forum, Vol. 8, pp. 55-71, 2016.

Kim, S. and Giachetti, R., “A stochastic mathematical appointment overbooking model for healthcare providers to improve profits,” IEEE Transactions on Systems, Man, and Cyberbetics-Part A: Systems and Humans, Vol. 36, No. 6, pp. 1211-1219, 2006.

Kopach et al., “Effect of clinical characteristics on successful open access scheduling,” Health Care Management Science, Vol. 10, No. 2, pp. 111-124, 2007.

Kwon, S. T., Lee, Y. S., Han, E., and Kim, T. H., “Factors associated with no- show in an academic medical center,” Korean Public Health Research, Vol. 41, No. 2, pp. 29-46, 2015.

Lacy, N. L., Paulman, A., Reuter, M. D., and Lovejoy, B., “Why we don’t come: Patient perceptions on no-shows,” Annals of Family Medicine, Vol. 2, No. 6, pp. 541-545, 2004.

LaGanga L. and Lawrence S., “Appointment overbooking in health care clinics to improve patient service and clinic performance,” Production and Operations Management, Vol. 21, No. 5, pp. 874-888, 2012.

Lasser, K. E., Mintzer, I. L., Lambert, A., Cabral, H., and Bor, D. H., “Missed appointment rates in primary care: the importance of site of care,” Journal of Health Care for the Poor and Undeserved, Vol. 16, No. 3, pp. 475-486, 2005.

Lee, S. and Yih, Y., “Analysis of an open access scheduling system in outpatient clinics: A simulation study,” Simulation: Transactions of The Society for Modeling and Simulation International, Vol. 86, No. 8-9, pp. 503-518, 2010.

Lee, S., Min, D., Ryu, J., and Yih, Y., “A simulation study of appointment scheduling in outpatient clinics: open access and overbooking,” Simulation: Transactions of The Society for Modeling and Simulation International., Vol. 89, No. 12, pp. 1459-1473, 2013.

Min, D. and Koo, H., “no-show related factors for outpatients at a hospital,” The Journal of Society for e-Business Studies, Vol. 22, No. 1, pp. 37-49, 2017.

Murray, M. and Tantau, C., “Same-day appointments: Exploding the access paradigm,” Family Practice Management, Vol. 7, No. 8, pp. 45-50, 2000.

Nguyen, D. L., Dejesus, R. S., and Wieland, M. L., “Missed appointments in resident continuity clinic: Patient characteristics and health care outcomes,” Journal of Graduate Medical Education, Vol. 3, No. 3, pp. 350-355, 2011.

O’Hare C. D. and Corlett, J., “The outcomes of open-access scheduling,” Family Practice Management, Vol. 11, No. 2, pp. 35-38, 2004.

Parikh et al., “The effectiveness of outpatient appointment reminder systems in reducing no-show rates,” American Journal of Medicine, Vol. 123, No. 6, pp. 542-548, 2010.

Paul, J. and Hanna, J. B., “Applying the marketing concept in health care: the no-show problem,” Health Marketing Quarterly, Vol. 14, No. 3, pp. 3-17, 1997.

Peeters, F. P. and Bayer, H., “no-show for initial screening at a community mental health centre: Rate, reasons, and further help-seeking,” Social Psychiatry and Psychiatric Epidemiology, Vol. 34, No. 6, pp. 323-327, 1999.

Samuels et al., “Missed appointments factors contributing to high no-show rates in an urban pediatrics primary care clinic,” Clinic Pediatrics, Vol. 54, No. 10, pp. 976-982, 2015.

United States Department of Veterans Affairs, “Audit of Veterans Health Administration’s Efforts to Reduce Unused Outpatient Appointments,” U.S. Department of Venterans Affairs Office of Inspector General, Washington, DC, USA, 2008.

Yoon, J., “Waste of the worth of 2.5 trillion KRW in clinical resources by no- shows,” The Hospital Newspaper, April 27, 2016.


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