How can we elicit health workers' preferences for measures to reduce informal payments? A mixed methods approach to developing a discrete choice experiment in Tanzania.

OBJECTIVE

While discrete choice experiments (DCEs) have been used in other fields as a means of eliciting respondent preferences, these remain relatively new in studying corrupt practices in the health sector. This study documents and discusses the process of developing a DCE to inform policy measures aimed at addressing informal payments for healthcare in Tanzania.

DESIGN

A mixed methods design was used to systematically develop attributes for the DCE. It involved five stages: a scoping literature review, qualitative interviews, a workshop with health providers and managers, expert review and a pilot study.

SETTING

Dar es Salaam and Pwani regions in Tanzania.

PARTICIPANTS

Health workers and health managers.

RESULTS

A large number of factors were identified as driving informal payments in Tanzania and thus represent potential areas for policy intervention. Through iterative process involving different methods (qualitative and quantitative) and seeking consensus views by diverse actors, we derived six attributes for a DCE: mode of payment, supervision at the facility level, opportunity for private practice, awareness and monitoring, disciplinary measures against informal payments and incentive payment for staff if a facility has less informal payments. 12 choice sets were generated and piloted with 15 health workers from 9 health facilities. The pilot study revealed that respondents could easily understand the attributes and levels, answered all the choice sets and appeared to be trading between the attributes. The results from the pilot study had expected signs for all attributes.

CONCLUSIONS

We elicited attributes and levels for a DCE to identify the acceptability and preferences of potential policy interventions to address informal payments in Tanzania through a mixed-methods approach. We argue that more attention is needed to the process of defining attributes for the DCE, which needs to be rigorous and transparent in order to derive reliable and policy-relevant findings.