Predicting the place of out-of-hours care--a market simulation based on discrete choice analysis.

BACKGROUND Increasing cost pressure and changing patients' needs in the healthcare sector have led to new delivery models for primary care. Researchers and practitioners need to establish innovative methods to obtain insights into patients' preferences and effectiveness of healthcare services. AIM This study reveals the crucial decision criteria of patients in choosing out-of-hours services and provides a projection of a future market share of the newly established central out-of-hours service, called General Practitioner Cooperative. DESIGN A computer-aided discrete choice experiment. METHOD Respondents were 350 patients in a European city who decided for a service when confronted with a medical emergency in an out-of-hours case; two scenarios called 'adult' and 'child', describing the persons requiring medical assistance, were used to increase generalizability. RESULTS The two most important attributes were 'explanation by the doctor' and 'waiting time' while the others - 'availability of technical equipment', 'ease of access', 'type of consultation' and 'payment method' - were of less importance. The market share projections predict that the new General Practitioner Cooperative will capture about one third of the market ('adult': 39.1%, 'child': 31.3%), ahead of the emergency department, the second most preferred service ('adult': 32.7%, 'child': 30.7%). CONCLUSIONS This study quantifies the adoption of a new medical service. As a result, it extends current research approaches on eliciting and matching patient's needs and assists policy makers in establishing adequate service capacities.

[1]  Jordan J. Louviere,et al.  Using stated preference discrete choice modeling to evaluate health care programs , 2004 .

[2]  Smarter Workflow,et al.  Built to Last , 2007 .

[3]  Richard K. Thomas Marketing Health Services , 2004 .

[4]  Mandy Ryan,et al.  Using discrete choice experiments to value health and health care , 2008 .

[5]  D. Mahr,et al.  Experience: the most critical factor in choosing after-hours medical care , 2010, Quality and Safety in Health Care.

[6]  J. Louviere,et al.  Conducting Discrete Choice Experiments to Inform Healthcare Decision Making , 2012, PharmacoEconomics.

[7]  D. McFadden Conditional logit analysis of qualitative choice behavior , 1972 .

[8]  A. Griffin PDMA Research on New Product Development Practices: Updating Trends and Benchmarking Best Practices , 1997 .

[9]  P. Dolan,et al.  Examining the attitudes and preferences of health care decision-makers in relation to access, equity and cost-effectiveness: a discrete choice experiment. , 2009, Health policy.

[10]  F W Markham,et al.  The Use of Conjoint Analysis to Study Patient Satisfaction , 1999, Evaluation & the health professions.

[11]  J. Lathlean,et al.  The introduction of integrated out‐of‐hours arrangements in England: a discrete choice experiment of public preferences for alternative models of care , 2006, Health expectations : an international journal of public participation in health care and health policy.

[12]  D. Dunt,et al.  Effects of financial disadvantage on use and non-use of after hours care in Australia. , 2006, Health policy.

[13]  David M. Szymanski,et al.  Why Some New Products are More Successful than Others , 2001 .

[14]  S. Thomson,et al.  Choices in health care: the European experience , 2006, Journal of health services research & policy.

[15]  A. Parasuraman,et al.  SERVQUAL: A multiple-item scale for measuring consumer perceptions of service quality. , 1988 .

[16]  M. Ryan,et al.  Using discrete choice modelling in priority setting: an application to clinical service developments. , 2000, Social science & medicine.

[17]  Richard Miller,et al.  Dealing with Product Similarity in Conjoint Simulations , 2007 .

[18]  Sarah Wordsworth,et al.  Sensitivity of Willingness to Pay Estimates to the Level of Attributes in Discrete Choice Experiments , 2000 .

[19]  J. de Haes,et al.  A core questionnaire for the assessment of patient satisfaction in academic hospitals in The Netherlands: development and first results in a nationwide study , 2010, Quality and Safety in Health Care.

[20]  P. Van Royen,et al.  What's the effect of the implementation of general practitioner cooperatives on caseload? Prospective intervention study on primary and secondary care , 2010, BMC health services research.

[21]  A. Scott,et al.  Eliciting preferences of the community for out of hours care provided by general practitioners: a stated preference discrete choice experiment. , 2003, Social science & medicine.

[22]  S. Dovey,et al.  Changes in clinical practice and patient disposition following the introduction of point-of-care testing in a rural hospital. , 2010, Health policy.

[23]  P. Zarembka Frontiers in econometrics , 1973 .

[24]  A. Anell,et al.  Population preferences and choice of primary care models: a discrete choice experiment in Sweden. , 2007, Health policy.

[25]  M Ryan,et al.  Eliciting public preferences for healthcare: a systematic review of techniques. , 2001, Health technology assessment.

[26]  N. Mays,et al.  Can primary care and community-based models of emergency care substitute for the hospital accident and emergency (A & E) department? , 1998, Health policy.

[27]  鄭宇庭 行銷硏究 : Marketing research , 2009 .