Patient Choice in Acute Care

Consumer healthcare information plays a critical role in informing patients who participate in or make healthcare decisions for themselves without direct supervision of a healthcare professional. One such example is the choice of facility for acute care, prototypically between a fully equipped emergency care department (ED) at a hospital and a more convenient but less capable urgent care (UC) or retail clinic. We model a strategic patient making this decision taking into account the limited medical information and convenience factors that affect the patient’s decision. This model is then used to inform the pricing decision made by the manager of the UC. We show that a separating equilibrium, in which all patients self-triaged as noncritical choose to go to the UC first, dominates pooling equilibria for moderate error rates in self-triage. We analyze the separating equilibrium to examine the effect of consumer health information (CHI) systems, and show that as the quality of the CHI decreases and the error rates go up, the co-pay for an UC decreases, the facility is smaller, and makes less profit. Keywords-consumer health information systems, classification error, Nash equilibrium, emergency room, urgent care

[1]  D. Padgett,et al.  Psychosocial factors influencing non-urgent use of the emergency room: a review of the literature and recommendations for research and improved service delivery. , 1992, Social science & medicine.

[2]  Edieal J. Pinker,et al.  Reserving Capacity for Urgent Patients in Primary Care , 2011 .

[3]  Brant E. Fries,et al.  Bibliography of Operations Research in Health-Care Systems , 1976, Oper. Res..

[4]  Nan Liu,et al.  Dynamic Scheduling of Outpatient Appointments Under Patient No-Shows and Cancellations , 2010, Manuf. Serv. Oper. Manag..

[5]  D. Aronsky,et al.  Systematic review of emergency department crowding: causes, effects, and solutions. , 2008, Annals of emergency medicine.

[6]  Ateev Mehrotra,et al.  Many emergency department visits could be managed at urgent care centers and retail clinics. , 2010, Health affairs.

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

[8]  Michael Pinedo,et al.  Appointment scheduling with no-shows and overbooking , 2014 .

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

[10]  Diwakar Gupta,et al.  Revenue Management for a Primary-Care Clinic in the Presence of Patient Choice , 2008, Oper. Res..

[11]  K. Siddharthan,et al.  A priority queuing model to reduce waiting times in emergency care. , 1996, International journal of health care quality assurance.

[12]  Martin L. Puterman,et al.  Dynamic multi-appointment patient scheduling for radiation therapy , 2012, European Journal of Operational Research.

[13]  Ronald L. Rardin,et al.  Matching daily healthcare provider capacity to demand in advanced access scheduling systems , 2007, Eur. J. Oper. Res..

[14]  Ji Lin,et al.  Clinic scheduling models with overbooking for patients with heterogeneous no-show probabilities , 2010, Ann. Oper. Res..

[15]  Nan Liu,et al.  Appointment Scheduling Under Patient Preference and No-Show Behavior , 2014, Oper. Res..

[16]  J. Nyman,et al.  Excess demand, consumer rationality, and the quality of care in regulated nursing homes. , 1989, Health services research.

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

[18]  L. Baker,et al.  Use of the Internet and e-mail for health care information: results from a national survey. , 2003, JAMA.

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

[20]  Lawrence W. Robinson,et al.  A Comparison of Traditional and Open-Access Policies for Appointment Scheduling , 2010, Manuf. Serv. Oper. Manag..

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

[22]  James R. Jackson,et al.  An Improved Stochastic Model for Occupancy-Related Random Variables in General-Acute Hospitals , 1973, Oper. Res..

[23]  E. Hing,et al.  Wait time for treatment in hospital emergency departments: 2009. , 2012, NCHS data brief.