Assessing the effect of SGHPs on access to quality of PCH and cost of care.
malaria
MALARIA, DISEASES
When the initiative was planned in 2018, the Bugesera District had 50 cells, the administrative unit between the sector and a village. Each cell contained several villages with a combined population of ∼6,500 persons. The district was served by the district hospital and health centers. In addition, most cells had health posts operated by a nongovernmental organization or the government. However, 16 cells had no health posts. The Ministry of Health selected eight cells without health posts and located somewhat remotely from their health center as locations for SGHPs. To evaluate this initiative, we developed a prospective, controlled cluster study design in which the cell was the unit of analysis. The eight cells selected for SGHPs constituted the intervention cells whereas the remaining eight cells without official health posts were control cells. Twelve health centers served the 16 study cells (We used multiple data sources to estimate the effect of SGHPs on access to health care, including administrative data compiled by the Society for Family Health (SFH), an analysis of patient registration records from health centers serving the study cells, two rounds of household surveys, and qualitative data from focus group discussions (FGDs). In addition, we conducted interviews with key stakeholders (Dr. William Rutagengwa, Bugesera District Medical Director; and Dr. Diana Mutamba, Manager of SFH) to inform the interpretation of findings. We also used published statistical information to compare the Bugesera District with other parts of Rwanda, and conducted four FGDs (see All household survey data were collected initially by interviewers circling responses on paper questionnaires. Each data collector then entered the response into a 2019 version Excel (Microsoft Corp., Redmond, WA) spreadsheet. Researchers then merged these spreadsheets into a single Excel workbook and conducted logic checks, such as checking whether each entry fell within the item’s valid range. Missing or out-of-range entries were corrected by reference to the original paper questionnaire. We next performed descriptive analyses of frequencies and means of key variables by study arm. These included receipt of antenatal care (ANC) visit, travel time, quality indexes, and services indexes.Last, to quantify the effect of SGHPs on key outcome variables, we used a difference-in-differences (DIDs) approach to perform the analysis. The mathematical expression of the DIDs model is as follows:Study variables and the expected sign of the interaction term signifying the effect of SGHPsSGHPs = second-generation health posts. The study’s service index (on a 0- to 100-poing scale) for pregnant women is the average number of recommended services reported during the first antenatal care visit, including a blood test to confirm pregnancy, and laboratory tests for malaria, HIV/AIDS, and other diseases.All the analyses were conducted using Stata 17 (StataCorp, LLC, College Station, TX), with We used Rwanda’s Health Management Information System (HMIS) to capture the increase in routine primary care visits. The HMIS tallies the number of visits by month, site, and diagnosis at all participating health facilities, including health posts and health centers.