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Published in: Health Economics Review 1/2016

Open Access 01-12-2016 | Research

Heterogeneity in general practitioners’ preferences for quality improvement programs: a choice experiment and policy simulation in France

Authors: Mehdi Ammi, Christine Peyron

Published in: Health Economics Review | Issue 1/2016

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Abstract

Despite increasing popularity, quality improvement programs (QIP) have had modest and variable impacts on enhancing the quality of physician practice. We investigate the heterogeneity of physicians’ preferences as a potential explanation of these mixed results in France, where the national voluntary QIP – the CAPI – has been cancelled due to its unpopularity. We rely on a discrete choice experiment to elicit heterogeneity in physicians’ preferences for the financial and non-financial components of QIP. Using mixed and latent class logit models, results show that the two models should be used in concert to shed light on different aspects of the heterogeneity in preferences. In particular, the mixed logit demonstrates that heterogeneity in preferences is concentrated on the pay-for-performance component of the QIP, while the latent class model shows that physicians can be grouped in four homogeneous groups with specific preference patterns. Using policy simulation, we compare the French CAPI with other possible QIPs, and show that the majority of the physician subgroups modelled dislike the CAPI, while favouring a QIP using only non-financial interventions. We underline the importance of modelling preference heterogeneity in designing and implementing QIPs.
Appendix
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Footnotes
1
The CAPI was replaced in 2012 by a P4P program (the ROSP) where physicians are enrolled automatically, but can request to opt out.
 
2
The number of considered attributes should not be so high as to allow respondent to make trade-offs. If there are no clear recommendations on the maximum number, the DCE health economics literature generally uses at most eight attributes [21].
 
3
Caussade et al. [25] showed that setting between 6 and 13 choice situations minimizes the error variance of the estimates.
 
4
We restricted ourselves to the region of Bourgogne because of prior relationships with the regional health professional’s union who facilitated the constitution of the focus-group and offered logistic support for the survey. The restriction to one region is also due to monetary and time constraints. The fund obtained from the Conseil Regional de Bourgogne did not allow for a survey of more than one region.
 
5
This point is, however, not particularly concerning as the regional and national values are derived from an administrative database (système national d’information inter-régimes – SNIIR) known to underestimate physicians’ activity. The SNIIR includes the very low activity physicians, pulling down the average number of acts.
 
6
Beyond the choice exercise, supplementary choices and follow-up questions were introduced in the DCE in order to test the internal validity of the data collected. More information on the test procedures used is available upon request.
 
7
This random part is precisely why RUT can deal with axiomatic violations. The “errors” may come from this stochastic part, which is unexplained by the researcher.
 
8
Because of the qualitative nature of the majority of our attributes, there is no reason to think that one level should be preferred to another a priori. It is therefore difficult to select the sign of the distribution. MXL with log-normal distribution are run for sensitivity analyses and do not exhibit large differences in the fit. Results are available from the authors.
 
9
The simplest way to account for heterogeneity of preferences is to incorporate the personal characteristics of the respondents in the models. It can be done with interaction terms in the MXL and to explain class membership probability in the LCM. We argue these individual characteristics have to considerably improve the fit of the models in order to be worth keeping for final analysis, which is not the case with our data (results available upon request). Most of the personal characteristics are found to be insignificant in the MXL, the integration of these characteristics does not drastically improve the fit to the data in MXL, and even worsens the fit of the LCM. As a result and following Hole [39], we focus only on the more parsimonious models in our analyses.
 
10
The maximal satisfaction policy is designed for all GPs. Our goal is to compare different nationally uniform policies such as the CAPI.
 
11
In this paragraph, when talking about greater CV, we do not take the maximum satisfaction into account and only concentrate on the reliably implantable policies.
 
12
This is partly because only two attributes are found significant for this latent class and enter the calculation of the CV. Their presence or absence therefore has a disproportionate impact on the CV for each policy.
 
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Metadata
Title
Heterogeneity in general practitioners’ preferences for quality improvement programs: a choice experiment and policy simulation in France
Authors
Mehdi Ammi
Christine Peyron
Publication date
01-12-2016
Publisher
Springer Berlin Heidelberg
Published in
Health Economics Review / Issue 1/2016
Electronic ISSN: 2191-1991
DOI
https://doi.org/10.1186/s13561-016-0121-7

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