Volume 7, Issue 26 (3-2017)                   jemr 2017, 7(26): 7-40 | Back to browse issues page


XML Persian Abstract Print


Download citation:
BibTeX | RIS | EndNote | Medlars | ProCite | Reference Manager | RefWorks
Send citation to:

sobhanian S M H, mehrara M. Study of Factors inFluencing Physician Decision to Enter the Family Physician Program; A Case Study of Tehran. jemr. 2017; 7 (26) :7-40
URL: http://jemr.khu.ac.ir/article-1-1376-en.html
Abstract:   (1167 Views)

One of the main issues and challenges of managing health care system in Iran, is the issue of inequities in access to health services. Theoretical studies and empirical evidences indicate that implementation of the referral system and family physician plan is one of the main strategies to overcome inequity in the health and appropriate using of scarce resources in this area. But for successful execution of the family physician, it is necessary to identify important determinants affecting the decisions of participants in this plan using scientific methods and studying, and health policy makers should design a program pack that matches preferences of the target population to increase the possibility of its successful implementation. This study used Discrete Choice Experiment (DCE) to identify important determinants affecting the decisions of physicians.
Results show that increase in net payments to general practitioners, nearer workplace to residence, allocation of quota to get the degree of expertise, existence of housing facilities and deadheading pay, less covered population and paying to physicians in less period of time may increase the utility and satisfaction of physicians and therefore, possibility of their participation and entry to the plan, as expected.
According to the results, the attribute "place of work" are significantly more important than the other attributes.

Full-Text [PDF 1861 kb]   (453 Downloads)    
Type of Study: Applicable | Subject: بخش عمومی
Received: 2016/02/24 | Accepted: 2017/01/3 | Published: 2017/03/1

References
1.  Adamowicz, W., Boxall, P., Williams, M. & Louviere, J. (1998). Stated preference Approaches for Measuring Passive Use Values: Choice Experiments and Contingent valuation, American Jornal of Agricaltureral Economics, 80(1): 64-75.
2.  Alpizar, F. (2007). Using Choice Experiments for Non-Market Valuation, Transprot, 8(1).
3.  Anderson, G., Hurst, J., Hussey, PS. & Jee-Hughes, M. (2000). Trends: health spending and out comes: trends in OECD countries 1960-1998, Health Aff, 19(3): 150-17.
4.  Bennett, J., and V. Adamowicz. (2001). Some Fundamental of Environmental Choice Modelling. In The Choice Modelling Approach to Environmental Valuation, edited by J. Bennett and R. Blamey. Cheltenham, UK: Edward Elgar.
5.  Ben-Akiva, M. & Morikawa, T. (1990). Estimation of Switching Models from Revealed Preferences and Stated Intentions, Transportation Research Part A-Policy and Practice, 24(6): 485-495.
6.  Bryan, S., Buxton, M., Sheldon, R. & Grant, A. (1998). Magnetic resonance imaging for the investigation of knee injuries: an investigation of preferences, Health Economics, 7(7): 595-603.
7.  Chen, T.T., Chung, H.P., Huang, H.C., Man, L.N. & Lai, M.S. (2010). Using discrete choice experiment to elicit doctors' preferences for the report card design of diabetes care in Taiwan - a pilot study, Journal of Evaluation in Clinical Practice, 16(1): 14-20.
8.  Cheraghi-Sohi, S., Hole, A.R., Mead, N., McDonald, R., Whalley, D., Bower, P. & Roland, M. (2008). What patients want from primary care consultations: a discrete choice experiment to identify patients' priorities, Ann Fam Med, 6(2): 107-115.
9.  Coast, J., Flynn, T.N., Salisbury, C., Louviere, J. & Peters, T.J. (2006). Maximizing responses to discrete choice experiments: A randomized trial, Applied Health Economics and Health, 5(4): 249-260.
10.  Freemantle, N. (1999). Does the UK National Health Service need a fourth hurdle for pharmaceutical reimbursement to encourage the more efficient prescribing of pharmaceuticals?, Health Policy, 46(3): 255-265.
11.  Guyatt, G., Haynes, B.R., Jaeschke, R.Z., Cook, D.J., Green, L., Naylor, C.D., Wilson, M.C. & Richardson, W.S. (2000). Users' guides to the medical literature: XXV, Evidence-based medicine: principles for applying the users' guide to patient care, JAMA, 284(10): 1290-1296.
12.  Hall, J., Viney, R., Haas, M. & Louviere, J. (2004). Using stated preference discrete choice modeling to evaluate health care programs, Journal of Business Research, 57, 1026-1032.
13.  Hall, J. & Viney, R. (2000). The political economy of health sector reform, In: Bloom AL, editor, Health reform in Australia and New Zealand, Melbourne: Oxford Univ. Press, 39-53.
14.  Hauber, A.B., Mohamed, A.F., Johnson, F.R. & Falvey, H. (2009). Treatment preferences and medication adherence of people with Type 2 diabetes using oral glucose-lowering agents, Diabetic medicine, 26(4): 416-424.
15.  Hensher, D., Louviere, J. & Swait, J. (1999). Combining sources of preference data, Journal of Econometrics, 89(1-2): 197-221.
16.  Hitchock, W., Mellon, M., Memran, M., Parasuraman, B., Ramachendran, S. & Walzer, S. (2007). Caregiver preferences for pediatric asthma treatment delivery system, Advances in Therapy, 24(6): 1240-1253.
17.  Kjær, T. & Gyrd-Hansen, D. (2010). Preference heterogeneity and choice of cardiac rehabilitation program: Results from a discrete choice experiment, Health Policy, 85(1): 124-132.
18.  Kleinman, L., McIntosh, E., Ryan, M., Schmier, J., Crawley, J., Locke, G.R. & De Lissovoy, G. (2002). Willingness to pay for Complete Symptom relief of Gastroesophagael Reflux Disease (GERD), Archives of Internal Medicine, 162(12): 1361-1366.
19.  Lancaster, K.J. (1966). A new approach to consumer theory, Journal of Political Economy, 74(2): 132-157.
20.  Lancsar, E.J., Hall, J.P., King, M., Kenny, P., Louviere, J., Fiebing, D.G., Hossain, I., Thien, F.C.K., Reddel, H.K. & Jenkins, CR. (2007). Using discrete choice experiments to investigate subject preferences for preventive asthma medication, Respirology, 12(1): 127-136.
21.  Louviere, J., Hensher, D.A. & Swait, J. (2000). Stated Choice Methods, analysis and application, Cambride University Press, U.K.
22.  Louviere, J. J. & Woodworth, G. 1983, "Design and Analysis of Simulated onsumer Choice Or Allocation Experiments - An Approach Based on Aggregate Data", Journal of Marketing Research, vol. 20, no. 4, 350-367.
23.  McFadden, D. 1974, "Conditional logit analysis of qualitative choice behaviour," in Frontiers of Econometrics, P. Zarembka, ed., Academic Press, London, U.K., 105-142.
24.  McFadden, D. & Train, K. (2000). Mixed MNL models for discrete response, Journal of Applied Econometrics, 15, 447- 470.
25. ♣ Morgan, S. & Hurley, J. (2004). Influences on the health care technology cost driver, In: Forst, PG., McIntosh, T., Marchildon, G. (eds.), Selected discussion papers from the commission on the future of health care in Canada, University of Toronto Press, Toronto, 27-50.
26.  Peter, A. & Berman, A. (2000). Decade of Health Sector Reform in Developing Countries: What Have We Learned?, Harvard School of Public Health, 15.
27.  Ratcliffe, J., Buxton, M., McGarry, T., Sheldon, R. & Chanellor, J. (2004). Patients' preferences for characteristics associated with treatments for osteoarthritis, Reumatology, 43(3): 337-345.
28.  Revelt, D. & Train, K. (1998). Mixed logit with repeated choices: households' choices of appliance efficiency level, Review of Economics and Statistics, 80(4): 647-657.Salkeld, G., Ryan, M. & Short, L. (2000). The veil of experience: do consumers prefer what they know best?, Health Economics, 9(3): 267-270.
29.  Thurstone, L. (1927). A Law of Comparative Judgment, Psychological Review, 34, 273- 286.
30.  Train, K. (2003). Discrete choice methods with simulation, Cam-bridge University Press, UK.
31.  Train, K. E. 1998, "Recreation demand models with taste differences over people", Land Economics, vol. 74, no. 2, pp. 230-239.
32.  Ubach, C., Scott, A., French, F., Awramenko, M., Needham, G.(2004). What do hospital consultants valu about their jobs? A discrete choice experiment. BMJ, vol. 326.
33.  Van der Pol, M. & Cairns, J. (1998). Estabilishing patient preferences for blood transfusion support: an application or conjoint analysis, Health Serv Res Policy, 3(2): 70-76.
34.  Viney, R., Lancasar, E. & Louviere, J. (2002). Discrete choice experiment to measure consumer preferences for health and health care, Expert Review of Pharmacoeconomics Outcomes Research, 2(4): 319-326.
35.  Vojáček O, Pecáková I. (2010). Comparison of discrete choice models for economic environmental research. Prague Economic Papers. (1). 35-53. [DOI:10.18267/j.pep.363]
36.  Walzer S, Zweifel P. (2007). Willingness-to-pay for caregivers of children with asthma or wheezing conditions. Therapeutics and Clinical Risk Management, 3(1): 157-165 [DOI:10.2147/tcrm.2007.3.1.157]
37. ♣ Walzer S. What do parents want from their child's asthma treatment? Therapeutics and Clinical Risk Management, 3(1): 167-175 [DOI:10.2147/tcrm.2007.3.1.167]
38.  Wordsworth S., Skåtun D., Scott A., French F. (2004). Preferences for general practice jobs: a survey of principals and sessional GPs. British Journal of General Practice
39.  World Health Organisation (2002). The world health report.
40.  World Health Organisation (2012). How to conduct a discrete choice experiment for heath workforce recruitment and retention in remote and rural areas

Add your comments about this article : Your username or Email:
CAPTCHA code

Send email to the article author


© 2018 All Rights Reserved | Journal of Economic Modeling Research

Designed & Developed by : Yektaweb