Hospital services for ill patients in the middle-belt geopolitical zone, Nigeria: Patient’s waiting time and level of satisfaction

An important parameter in the assessment of quality healthcare lies on patient satisfaction. Despite concerted efforts to improve health care services, patient satisfaction couple with the quality of hospital care at disposal remains a significant challenge in Nigeria. The purpose of the study was to determine the perception on factors associated with prolonged waiting time and patient satisfaction at the outpatient department of Ibrahim Badamasi Babangida Specialist Hospital in Nigeria. A mixed method research was utilised. Questionnaire was administered on 95 outpatients along with a focus group discussion (FGD) was held with 8 participants. Statistical analysis was utilized to determine the association between dependent and independent variables. Data from focus group discussion was analysed with NVivo 10. The overall hospital satisfaction was found to be 75.8% among the study population. There was a significant inverse relationship between the level of satisfaction with the doctor and (employment status, and educational level) and direct relationship with (appointment status and type of visits). In FDG, the result shows that patients were satisfied with the neatness of the hospital, doctor’s professionalism and patient-doctor relationship. Dissatisfaction was with extended patient waiting time and the small size infrastructure of the hospital, inefficient handling of patient files by nurse aids and thoroughness of the physicians. The results showed that majority of the patients were dissatisfied with the waiting time for consultation in the hospital. In other words, consultation time positively correlated with the level of patient satisfaction. To improve the overall patient satisfaction the waiting time for consultation should be reduced significantly

Health shock and preference instability: assessing health-state dependency of willingness-to-pay for corrective eyeglasses

Background: Differences in contingent valuation (CV) estimates for identical healthcare goods can cast considerable doubt on the true economic measures of consumer preferences. Hypothetical nature of CV methods can potentially depend on the salience, context and perceived relevance of the good or service under consideration. Thus, the high demand elasticity for healthcare goods warrants careful selection of study population as the contexts of valuation significantly changes after experiencing health shock. Methods: In this study, using triple-bounded dichotomous choice (TBDC) experiments, we test how negative health shock (namely, being diagnosed with refractive errors), can alter preference over a common health good (namely, corrective eyeglasses). We compared elicited WTP of diagnosed patients with a synthetically constructed comparable cohort without the same health shock, controlling for the possible self-selection using a number of matching techniques based on the observable socio-demographic characteristics. Results: The consumers diagnosed with vision problems exhibit a rightward shift in their demand curve compared to observationally identical consumers without such problems resulting in about 17% higher consumer surplus. The consumers without the health shock are willing to pay about BDT 762.4 [95% CI: BDT 709.9 - BDT 814.9] for corrective eyeglasses, which gets 15-30% higher for the matched with-health-shock consumers. Multivariable analyses suggest more educated and wealthier individuals are willing to pay respectively BDT 208 and BDT 119 more for corrective eyeglasses. We have tested the models for different matching protocols. Our results are fairly robust to alternate specifications and various matching techniques. Conclusion: The preferences for healthcare goods, such as eyeglasses, can significantly depend upon the respondent being diagnosed with refractive errors. Our findings have implications for general cost-benefit analyses often relying on WTP, which can vary depending on the contexts. There are also increasing interests in cost recovery models, which require understanding the demand for healthcare goods and services. We find eliciting the demand needs to consider the health status of the population from which the respondents are sampled