What Patients Want From Primary Care Consultations: A Discrete Choice Experiment to Identify Patients’ Priorities

Understanding patients’ priorities is essential in designing services to meet patient needs and desires, and the discrete choice method is clearly a useful and powerful tool for measuring priorities (1). However, if information about patients’ priorities is to be used to inform service design and provision, we need to be aware that measuring attribute importance is a complex issue with many unresolved questions.

Cheraghi-Sohi et al (1) acknowledge in their paper that discrete choice methods can be criticised for not reflecting patients’ choices and priorities in ‘real life’. The discrete choice method rests on assumptions of rational choice; the authors’ tests of this assumption showed that while most respondents made consistent choices, a substantial proportion were unwilling to trade between attributes. In reality people’s decisions are often based on habit and heuristics (cognitive ‘shortcuts’), rather than a weighing up of alternatives. In addition, patients’ priorities in reality may depend on their expectations or experiences of the services available. For example, technical quality of care emerges as a pivotal attribute from the discrete choice study, but if in ‘real life’ patients assume there is little variation in technical quality, they may instead place more weight on other attributes which vary more between different service providers. If service delivery is designed solely around the priorities identified through experimental studies such as discrete choice studies, then this may not acknowledge and reflect the priorities that people actually have in accessing and evaluating services.

The discrete choice method is one of many methods of identifying patients’ priorities, others include open-ended questions and rating of attributes. There is evidence that the type of method used can influence the order of ranking of priorities (2), and different methods may tap into different dimensions of importance. There are at least three different dimensions of attribute importance: salience (how immediately an attribute comes to mind), relevance (how well the attribute fits with an individual’s values and desires), and determinance (an attribute’s contribution to choice) (3), with discrete choice analysis argued to measure determinance. It may be that different methods of measuring the importance of service attributes are appropriate in different contexts, for example, in measuring patients’ priorities when they make consulting decisions, as compared to when they evaluate the quality of their care.

These complexities highlight the need for a clearer understanding of how patients actually formulate their priorities in real life, and how their priorities impact on their consulting decisions and their evaluation of care. This would provide a valuable context within which to interpret the findings of empirical studies.

1. Cheraghi-Sohi S, Risa Hole A, 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; 6:107-115.

2. Phillips KA, Johnson FR, Maddala T (2002). Measuring what people value: A comparison of "attitude" and "preference" surveys. Health Services Research;37(6):1659–1679.

3. Myers JH, Alpert MI (1977). Semantic confusion in attitude research: salience vs. importance vs. determinance. Adv Consum Res;4:106–110.

Competing interests:   None declared