Determinants of facility readiness for integration of family planning with HIV testing and counseling services: Evidence from the Tanzania service provision assessment survey, 2014-2015

Background: Global policy reports, national frameworks, and programmatic tools and guidance emphasize the integration of family planning and HIV testing and counseling services to ensure universal access to reproductive health care and HIV prevention. However, the status of integration between these two services in Tanzanian health facilities is unclear. This study examined determinants of facility readiness for integration of family planning with HIV testing and counseling services in Tanzania. Methods: Data from the 2014-2015 Tanzania Service Provision Assessment Survey were analyzed. Facilities were considered ready for integration of family planning with HIV testing and counseling services if they scored ≥ 50% on both family planning and HIV testing and counseling service readiness indices as identified by the World Health Organization. All analyses were adjusted for clustering effects, and estimates were weighted to correct for non-responses and disproportionate sampling. Descriptive, bivariate, and multivariate logistic regression analyses were performed. Results: A total of 1188 health facilities were included in the study. Of all of the health facilities, 915 (77%) reported offering both family planning and HIV testing and counseling services, while only 536 (45%) were considered ready to integrate these two services. Significant determinants of facility readiness for integrating these two services were being government owned [AOR = 3.2; 95%CI, 1.9-5.6], having routine management meetings [AOR = 1.9; 95%CI, 1.1-3.3], availability of guidelines [AOR = 3.8; 95%CI, 2.4-5.8], in-service training of staff [AOR = 2.6; 95%CI, 1.3-5.2], and availability of laboratories for HIV testing [AOR = 17.1; 95%CI, 8.2-35.6]. Conclusion: The proportion of facility readiness for the integration of family planning with HIV testing and counseling in Tanzania is unsatisfactory. The Ministry of Health should distribute and ensure constant availability of guidelines, availability of rapid diagnostic tests for HIV testing, and the provision of refresher training to health providers, as these were among the determinants of facility readiness. This study used data from the Tanzania Service Provision Assessment (Tanzania SPA) Survey, conducted between 20 October 2014 and 21 February 2015. The survey was undertaken by Tanzania’s National Bureau of Statistics (NBS) and the Office of the Chief Government Statistician (OCGS) in collaboration with the Ministry of Health and Social Welfare (MoHSW) – Mainland, and the Ministry of Health (MoH) – Zanzibar. This survey is the second facility-based survey conducted in Tanzania, following the one conducted in 2006. The survey, funded by the United States Agency for International Development (USAID) [60], was designed to provide information on the availability of basic and essential health care services and on service readiness. It assessed the presence and functioning of components essential for quality service delivery for child health, maternal and newborn care, FP, antenatal care, sexually transmitted infections, HIV/AIDS, and non-communicable diseases [60]. The methodology of this survey is reported elsewhere, but briefly, from a list of 7102 verified (active) health facilities as a sampling frame; 1200 facilities were randomly selected for inclusion in the survey. The sample was designed to provide nationally representative results according to facility type and managing authority, and regionally representative results for all 25 Tanzania mainland regions and five Zanzibar regions [60]. However, of the 1200 health facilities sampled, seven refused to participate in the survey, four had closed down, and one facility could not be reached. Finally, a total of 1188 facilities took part in this survey. The 2014–2015 Tanzania SPA survey data were collected between 20 October 2014 and 21 February 2015, and some facilities that were not covered previously were revisited from 2 to 13 March 2015. The survey used four main types of data collection tools: Facility Inventory questionnaire; Health Provider Interview questionnaire; Observation Protocols for antenatal care (ANC), FP, and services for sick children; and Exit Interview questionnaires for ANC and FP clients and for caregivers of sick children whose consultations were observed [60]. An online DHS website request for permission to access the Tanzania SPA survey dataset was performed by the first author on 29 October 2016. Two days later, the authors received full online access to all four (Facility, Health Provider, Observation, and Client Exit) files of Tanzania SPA survey dataset. Most of the data analyzed in this study were obtained from the Facility Inventory file, but one variable regarding staff that had received refresher training was obtained from the Health Provider file. The data in these file were edited, cleaned, and recoding was performed for variables of interest to obtain meaningful information for addressing our research questions. Data cleaning was performed by calculating the frequencies and sorting. Finally, these two files were merged in Stata together into new file (dataset) using facility identification as a unique identifier of these two files. As the Facility Inventory was used as the master file and Provider was used as the using file, the merge command in Stata was performed at 1:1; therefore, the unit of analysis of the new file remained at the facility level. After merging, 12 cases from the Facility Inventory file were not matched. This was because 12 facilities sampled were not interviewed. Therefore, they were regarded as missing variables and were excluded from further analysis. As the facilities sampled were not evenly distributed and the response rate may be very different between regions or facility type, over- and under-sampling were performed in the regions with fewer and more facilities, respectively, prior to data collection. Before analysis, therefore, facility weight was applied to restore the actual representativeness and corrected for sampled data. Facility readiness: defined in this study as the willingness or state of the health facility to provide FP and HTC as integrated services. Refresher training: defined as on-the-job training provided to health providers without taking into consideration their roles to update their knowledge, skills, and technical competence to improve health care related to the services offered to clients. The FRIFHS was measured based on the scores of FP and HTC service readiness indices. The scores were determined using the WHO approach, and FP and HTC readiness indicators were identified according to the WHO Service Availability and Readiness Assessment (SARA) Manual [38]. Using this approach, the FP service readiness index was categorized into three domains; staff and guidelines, equipment and medicines/commodities. The first domain consisted of staff and guidelines, which had two indicators, i.e., guidelines on FP and staff trained in FP. The facilities with guidelines and at least one staff member that had received refresher training in FP within 24 months were categorized as “Yes,” while those without such guidelines or at least one staff member receiving refresher training in FP within 24 months were categorized as “No.” The second domain was equipment, which had one indicator, i.e., the presence of blood pressure (BP) apparatus. Facilities with BP apparatus were categorized as “Yes,” while those without were categorized as “No.” The third domain was medicine and commodities, which had four indicators, i.e., the availabilities of progestin-only pills, combined oral pills, injectable contraceptives (combined or progestin-only), and condoms. Facilities with the availability of these means of contraception were categorized as “Yes,” while those without were categorized as “No.” The HTC service readiness index was categorized into three domains. The first domain was staff and guidelines, which had two indicators, i.e., guidelines and staff trained in HTC. Facilities with guidelines and at least one staff member that had received refresher training in HTC within 24 months were categorized as “Yes,” while those without such guidelines and no staff members receiving HTC refresher training within 24 months were categorized as “No.” The second domain was laboratory capacity. Facilities with the capability to perform rapid diagnostic tests or ELISA for HIV were categorized as “Yes,” while those without were categorized as “No.” The third domain was supplies/commodities, which had one indicator; facilities with the availability of condoms at testing and counseling sites were categorized as “Yes,” while those without were categorized as “No.” Each index (FP and HTC service readiness) was then totaled by adding the presence of each indicator, with equal weight given to each of the domains and each of the indicators within the domains. As the target was 100%, each domain accounted for 33.3% (100%/3) of the index. The percentage for each indicator within the domain was equal to 33.3% divided by the number of indicators in that domain. The FP and HTC service readiness indices for each facility were then calculated by summing the percentages. Facilities with scores of at least 50% for the FP service readiness index and 50% for the HTC service readiness index were considered to be ready for the integration of FP with HTC services (i.e., FRIFHS), while those that scored less than 50% for each index were not considered to be ready (i.e., not FRIFHS) [38, 61]. An additional table in word document file summarizes this measurement procedure in more details [see Additional file 1]. Facility type was coded as “1” for a hospital, “2” for a health center, and “3” for a clinic or dispensary. The residence was coded as “0” for urban and “1” for rural. Managing authority was coded as “0” for a private facility and “1” for the public facility. Routine management meetings were coded as “Yes” for facilities reporting that they performed routine management meetings at least on a quarterly basis and “No” for those that reported having no such meetings at least on the quarterly basis. External supervision was coded as “Yes” for facilities reporting having receiving external supervision in the past 3 months and “No” for those without such supervision. Location was categorized as “0” for Zanzibar and “1” for the mainland. FP and HTC guidelines were categorized as “0” for facilities without guidelines for both FP and HTC and “1” for facilities with guidelines for both FP and HTC. Staff trained in FP and HTC were categorized as “0” for facilities without staff trained in both FP and HTC and “1” for facilities with staff trained in both FP and HTC. Laboratory capacity was categorized as “0” or “1” for facilities without and with laboratory capacity to test for HIV, respectively. Data were analyzed using Stata 14 (StataCorp, College Station, TX). For all analyses, the “svy” set command in Stata was used to adjust for the complex sampling design used by Tanzania SPA survey. All estimates were weighted to correct for non- responses and disproportionate sampling. In descriptive analyses, categorical variables were summarized using proportions and then presented in tables and graphs. An unadjusted logistic regression model was fitted to examine whether there were any associations between the dependent variable (FRIFHS) and the independent (health facility) variables (location, residence, facility type, managing authorities, management meetings, FP and HTC guidelines, staff trained in FP and HTC, laboratory capacity for HIV testing, and external supervision) using multilevel modeling. All variables with P < 0.2 were fitted into the multiple logistic regression models using the stepwise (backward elimination) method to test for the association of each variable with the dependent variable using a 5% significance level. The resulting final model included all of the variables that determined the FRIFHS. The P-value and 95% confidence interval (CI) for the odds ratio (OR) were used to confirm the significance of the associations. In all analyses, P < 0.05 was taken to indicate statistical significance. The 2014–2015 Tanzania SPA survey was approved by Tanzania’s National Institute for Medical Research (NIMR), the Zanzibar Medical Ethics and Research Committee (ZAMREC), and the Institutional Review Board of ICF International in the USA. Before interviews were performed, informed consent was obtained from the manager, the person-in-charge of the facility, or the most senior health worker responsible for client services present at the facility. The respondents were adequately informed regarding all relevant aspects of the study, including its aim and interview procedures. Respondents that accepted for their facilities to participate in the study signed informed consent.