Understanding what women want: eliciting preference for delivery health facility in a rural sub-County in Kenya, a discrete choice experiment

Objective: To identify what women want in a delivery health facility and how they rank the attributes that influence the choice of a place of delivery. Design: A Discrete Choice Experiment was conducted to elicit rural women’s preferences for choice of delivery health facility. Data were analyzed using both a conditional logit model to evaluate relative importance of the selected attributes. A mixed multinomial model evaluated how interactions with sociodemographic variables influence the choice of the selected attributes. Setting: Six health facilities in a rural sub-County. Participants: Women aged 18-49 years who had delivered within six weeks. Primary outcome: The DCE required women to select from hypothetical health facility A or B or opt-out alternative. Results: A total of 474 participants were sampled, 466 participants completed the survey (response rate 98%).The attribute with the strongest association with health facility preference was having a kind and supportive healthcare worker (β=1.184, p<0.001), second availability of medical equipment and drug supplies (β=1.073, p<0.001) and third quality of clinical services (β=0.826, p<0.001). Distance, availability of referral services and costs were ranked 4th, 5th and 6th respectively (β=0.457, p<0.001), (β=0.266 p<0.001), and (β=0.000018, p<0.001). The opt-out alternative ranked last suggesting a disutility for home delivery. (β=-0.849, p<0.001). Conclusion: The most highly valued attribute was a process indicator of quality of care followed by technical indicators. Policy makers need to consider women’s preferences to inform strategies that are person-centered and lead to improvements in quality of care during delivery. A Discrete Choice Experiment was conducted to elicit rural women’s preferences for choice of delivery health facility. Data were analyzed using both a conditional logit model to evaluate relative importance of the selected attributes. A mixed multinomial model evaluated how interactions with sociodemographic variables influence the choice of the selected attributes.