The effects of free prescriptions on community pharmacy selection: A discrete choice experiment.

ABSTRACT

BACKGROUND: Little is known about preferences for community pharmacies, particularly the influence of prescription co-payments, and for New Zealand's priority populations, Maori and Pacific Peoples. Improving understanding of community pharmacy preferences will enable tailoring services to meet community needs. OBJECTIVES: This study aims to investigate New Zealanders' preferences for community pharmacies when collecting prescriptions. Additionally, variations in preferences for community pharmacy attributes between different latent and demographic groups were examined. METHODS: Focus group discussions with various community groups were thematically analyzed to develop six attributes location, wait time, customer service, prescription co-payments, parking availability, and nearby businesses. Participants were asked to complete an online survey involving 12 choice tasks, where they had to choose their preferred option of 3 unlabeled pharmacies along with demographic questions. A mixed multinomial logit model and latent classes analysis were used to assess and compare the participant preferences. RESULTS: The sample of 553 participants, representative of the New Zealand population, resulted in 19,908 observations for analysis. The most attractive pharmacy attribute was its proximity, being within a 10-min travel distance from home or work. The importance of prescription co-payments is evident, with free prescriptions being the second most attractive attribute level and $15 NZD prescription co-payments being the least appealing. Different classes placed importance on different attributes, the largest of which prioritized prescription co-payments. Including demographic characteristics did not improve model accuracy nor predict class membership. CONCLUSIONS: Under current policy, the most effective way for pharmacies to attract business is by offering free prescriptions. However, the trend of adopting lower-cost models may reduce the quality of care they deliver. Policy decision-makers must decide if they are comfortable with this potential impact.