Expectations of healthcare quality: A cross-sectional study of internet users in 12 low- and middle-income countries

Author summaryWhy was this study done? Expectations of healthcare quality are believed to influence how patients experience and rate healthcare; however, little is known about expectations in low- and middle-income countries (LMICs). High satisfaction with poor-quality care is common in LMICs; one possible explanation is that expectations of care are low. This study was conducted to better understand expectations of healthcare quality in LMICs. What did the researchers do and find? We used an innovative internet sampling methodology to collect information from 17,996 individuals in 12 LMICs. Vignettes describing poor-quality care were used to elicit expectations of healthcare; good ratings for poor-quality care approximate low expectations. Over half of respondents (53%) rated the poor-quality care vignettes as good quality or better; low expectations were more likely if respondents were less educated, were male, reported good personal health, or had experienced discrimination during a healthcare visit in the past. What do these findings mean? Internet users in LMICs are a relatively privileged subgroup in our study countries, limiting the generalizability of our findings. Populations with low expectations are more likely to be satisfied with poor-quality care, reducing the demand-side pressure that health systems experience to deliver high-quality care. Raising expectations of quality may be one approach to improving the quality of healthcare in LMICs. Background High satisfaction with healthcare is common in low- and middle-income countries (LMICs), despite widespread quality deficits. This may be due to low expectations because people lack knowledge about what constitutes good quality or are resigned about the quality of available services. Methods and findings We fielded an internet survey in Argentina, China, Ghana, India, Indonesia, Kenya, Lebanon, Mexico, Morocco, Nigeria, Senegal, and South Africa in 2017 (N = 17,996). It included vignettes describing poor-quality services-inadequate technical or interpersonal care-for 2 conditions. After applying population weights, most of our respondents lived in urban areas (59%), had finished primary school (55%), and were under the age of 50 (75%). Just over half were men (51%), and the vast majority reported that they were in good health (73%). Over half (53%) of our study population rated the quality of vignettes describing poor-quality services as good or better. We used multilevel logistic regression and found that good ratings were associated with less education (no formal schooling versus university education; adjusted odds ratio [AOR] 2.22, 95% CI 1.90-2.59, P < 0.001), better self-reported health (excellent versus poor health; AOR 5.19, 95% CI 4.33-6.21, P < 0.001), history of discrimination in healthcare (AOR 1.47, 95% CI 1.36-1.57, P < 0.001), and male gender (AOR 1.32, 95% CI 1.23-1.41, P < 0.001). The survey did not reach nonusers of the internet thus only representing the internet-using population. Conclusions Majorities of the internet-using public in 12 LMICs have low expectations of healthcare quality as evidenced by high ratings given to poor-quality care. Low expectations of health services likely dampen demand for quality, reduce pressure on systems to deliver quality care, and inflate satisfaction ratings. Policies and interventions to raise people's expectations of the quality of healthcare they receive should be considered in health system quality reforms.