Survey and sampling techniques
Data for the present study were obtained from the latest demographic and health survey in Ghana (GDHS, 2014). The primary objective of the survey was to generate recent reliable information on fertility, family planning, infant and child mortality, maternal and child health, and nutrition. This information will enhance informed policy decisions and will be used for planning, monitoring, and evaluating programs related to reproductive health and health in general. The survey was implemented by the Ghana Statistical Service (GSS), the Ghana Health Service (GHS), and the National Public Health Reference Laboratory (NPHRL) of the GHS as part of the International Demographic and Health Survey program known as MEASURE DHS, which is currently active in 90 countries. The survey was conducted under the auspices of the United States Agency for International Development (USAID) with the technical assistance of ICF International, based in the USA. The Demographic and Health Surveys (DHSs) are free, public datasets, though researchers must register with MEASURE DHS and submit a request before access to DHS data is granted. This data request system ensures that all users understand and agree to basic data usage ethics standards.
The survey lasted from early September to mid-December of 2014. Sampling technique involved a two-stage clustering encompassing both urban and rural areas across all ten administrative regions in the country. The first stage involved selecting clusters which are collections of enumeration areas (EAs). A total of 427 clusters were selected (216 in urban areas and 211 in rural areas). In the second stage, households were selected systematically from each EAs. A total of 12,831 households were selected for the survey and 11,835 households were finally interviewed successfully with a response rate of 99%. Further details are provided in the final report of the Ghana DHS 2014 report (GDHS 2014).
Variables selection and measurement
The explanatory variables of primary interest were economic status, whereas patient satisfaction on various aspects of healthcare services in relation to area of residence (Rural and Urban areas), was entered as a dependent variable.
A set of 13 items pertinent to the quality assessment of PHCs were extracted from the GDHS data set. The participants were inquired about their satisfaction on the following components to which they could answer as either YES or NO: 1) Satisfaction with the time to wait for your turn, 2) Satisfaction with the time spent in the consulting/examination room, 3) Satisfaction with the time to wait for tests to be performed, 4) Satisfaction with the time to wait for test results, 5) Satisfaction with the time at pharmacy/dispensary, 6) Satisfaction with staff when they listened to the respondent, 7) Satisfaction with staff when they explained what was wanted, 8) Satisfaction with staff when they gave advice on treatment, 9) Satisfaction with the cleanliness of the facility, 10) Satisfaction with the easiness of finding where to go, 11) Satisfaction with comfort and safety while waiting, 12) Satisfaction with privacy during the examination, 13) Satisfaction with confidentiality and protection of personal information. The scoring procedure involved summing the 13 items measuring satisfaction for a respondent to generate total satisfaction level. The mean was obtained and the variable was dichotomized to “satisfied” if a respondent scored at least the mean or “not satisfied” if a respondent scored below the mean respectively.
Covariates
Several covariates were included based on their relevance to the outcome variable: age (years) of respondents which are grouped in the interval; 15–19, 20–24, 25–29, 30–34, 35–39, 40–44 and 45–49.Geographical regions include; Western, Central, Greater Accra, Volta, Eastern, Ashanti, Brong Ahafo, Northern, Upper East and Upper West.
In addition, educational attainment was measured as No education, Primary, Secondary and Higher.The wealth status was measure as: poorest, poorer, middle, richer and richest.
Calculation of Wealth status: DHS provide no direct information on personal income; however, DHS employs a special technique to measure household wealth index and classify them into five groups: richest, richer, middle, poorer, and poorest. DHS programs employ wealth index as a proxy indicator for personal income status which is representative of an individual’s ability to afford personal healthcare needs. The process involves assigning wealth scores to household possessions e.g. floor, wall and roof material; type of cooking fuel; access to potable water and sanitation, ownership of radio, TV, refrigerator, motorcycle and others. Scoring is performed by principal components analysis, and based on their weighted wealth scores, households fall into five wealth quintiles ranging from poorest to richest. Measurement of wealth index is explained in detail elsewhere [1].
Educational attainment: Based on total years of completion of formal education, the following categories were used: No education, Primary, Secondary, and Higher.
Ethics statement
Before each interview, all participants gave informed consent to take part in the survey. The DHS program maintains strict standards for ensuring data anonymity and protecting the privacy of all participants. ICF International ensures that the survey complies with the U.S. Department of Health and Human Services regulations for the protection of human subjects, whilst the host country ensures that the survey complies with local laws and norms. Further approval for this study was not required since the data is secondary and is available in the public domain. More details regarding DHS data and ethical standards are available at: https://dhsprogram.com/What-We-Do/Protecting-the-Privacy-of-DHS-Survey-Respondents.cfm.
Data analysis
Summary statistics in percentages was used to present respondents’ demographic and socioeconomic characteristics. Chi-square test was used to find association between urban-rural differentials with socio-economic variables. Multiple logistic regression was performed to measure the association of being satisfied with primary healthcare services with study variables. Model fitness was tested by pseudo R2. Statistical significance was set at 95% confidence interval. Data were analyzed using STATA (StataCorp, College Station, TX, USA) version 12 and SPSS version 21.