Service readiness, health facility management practices, and delivery care utilization in five states of Nigeria: A cross-sectional analysis

Background: Existing studies of delivery care in Nigeria have identified socioeconomic and cultural factors as the primary determinants of health facility delivery. However, no study has investigated the association between supply-side factors and health facility delivery. Our study analyzed the role of supply-side factors, particularly health facility readiness and management practices for provision of quality maternal health services. Methods: Using linked data from the 2005 and 2009 health facility and household surveys in the five states in which the Community Participation for Action in the Social Sector (COMPASS) project was implemented, indices of health service readiness and management were developed based on World Health Organization guidelines. Multilevel logistic regression models were run to determine the association between these indices and health facility delivery among 2710 women aged 15-49 years whose last child was born within the five years preceding the surveys and who lived in 51 COMPASS LGAs. Results: The health facility delivery rate increased from 25.4 % in 2005 to 44.1 % in 2009. Basic amenities for antenatal care provision, readiness to deliver basic emergency obstetric and newborn care, and management practices supportive of quality maternal health services were suboptimal in health facilities surveyed and did not change significantly between 2005 and 2009. The LGA mean index of basic amenities for antenatal care provision was more positively associated with the odds of health facility delivery in 2009 than in 2005, and in rural than in urban areas. The LGA mean index of management practices was associated with significantly lower odds of health facility delivery in rural than in urban areas. The LGA mean index of facility readiness to deliver basic emergency obstetric and neonatal care declined slightly from 5.16 in 2005 to 3.98 in 2009 and was unrelated to the odds of health facility delivery. Conclusion: Supply-side factors appeared to play a role in health facility delivery after controlling for socio-demographic factors. Improving uptake of delivery care would require greater attention to rural-urban inequities and health facility management practices, and to increasing the number of health facilities with fundamental elements for delivery of basic emergency obstetric and neonatal care. Data were drawn from the 2005 and 2009 surveys of the Community Participation for Action in the Social Sectors (COMPASS) project in Nigeria. The COMPASS Project was launched in 2004 with the aim of expanding participation, ownership and use of healthcare and education sector services at the community level in 51 local government areas (LGAs) across four states (Bauchi, Lagos, Kano and Nasarawa) and the Federal Capital Territory (FCT) of Nigeria over a period of 5 years. The project was designed with the aim of stimulating and promoting the integration of education and health development across all project activities at all levels. The study was conducted in the 51 COMPASS LGAs and comprised three surveys: household, HF, and school. The household survey used a multi-stage stratified sampling design and collected information on reproductive and MH, child health, and HIV/AIDS-related knowledge and behaviors among women aged 15–49 and men aged 15–64 years. At the first stage of sampling, enumeration areas (EAs) were selected within each state, with probability proportional to the number of LGAs per state as follows: 1:1:2:2:1 for Bauchi, FCT, Kano, Lagos, and Nasarawa, respectively. At the second stage, 25 households were selected within each sample EA using systematic random sampling. Fieldwork was conducted from July-August 2005 and from mid-June to August, 2009. The HF surveys (including comprehensive health care centers; public PHC centers; health, maternity, private, or uniformed services clinics; health posts; and dispensaries and patent medicine vendors (PMVs)) were implemented at the same time as the household surveys. The HF survey was census of all public and primary HFs and PMVs serving the households surveyed. Consequently, the HF survey included some service delivery points that were located outside of the sample EAs and LGAs selected for the household survey. A total of 233 and 286 HFs were surveyed and facility inventories and provider interviews conducted in 2005 and 2009, respectively. The LGA was used to link the HF and household data. The outcome was binary and indicated whether the most recent birth in the past 5 years was delivered in a medical institution. The first two indices of service readiness were constructed based on World Health Organization guidelines on tracer elements for assessment of general service readiness [26]. The third index measured management practices supportive of quality MH services. Each component of the index was binary unless otherwise indicated. This was a 7-item additive index measuring the presence of the following resources in HFs: power (a grid or a functional generator and fuel for it); a protected water source; communication equipment (a working phone or shortwave radio); access to an incinerator for disposal of potentially contaminated waste and items that are not reused such as bandages and syringes; HF assessed to be clean; public transportation within 1 kilometer; and beds for overnight stay. Unfortunately, the HF questionnaire excluded four recommended components – access to computer with email/internet, access to adequate sanitation facilities, availability of emergency transportation, and availability of a room with auditory and visual privacy for patient consultations. The resulting HF index ranged from 0 to 7 and had a Cronbach’s alpha of 0.612 in 2005 and 0.793 in 2009. The LGA-based measure was the mean adapted index of basic amenities per HF surveyed in the LGA. Components of the index were based on WHO (2010) recommendations and covered staff training, equipment and medicines/commodities, and included: availability of guidelines for delivery; staff trained; emergency transportation not considered problematic; examination light; suction apparatus/mucous extractor; vacuum aspirator or dilation and curettage kit; newborn bag and mask; partograph; clean gloves; injectable uterotonic; injectable antibiotic; and intravenous solution with infusion set. Data were not collected on three recommended components: manual vacuum extractor, antibiotic eye ointment for the newborn, and magnesium sulphate. HFs that did not provide delivery/newborn care were assigned the value “0” on this indicator. The resulting 22-item additive index represented the cumulative availability of components required to provide BEmONC, had a Cronbach’s alpha of 0.925 in 2005 and 0.939 in 2009, and ranged from 0 to 21 for HFs in the sample. The LGA-based measure was the unweighted average number of items present in the HFs that provided delivery and newborn care in the LGA. This index measured the routine use of quality assurance methods by the HF; the occurrence and content of supervisory visits in the past six months; the availability of systems for client feedback; the presence of up-to-date client and birth registers; and the availability of a skilled provider. Questions on use of quality assurance methods asked non-PMVs whether any of the following methods of quality assurance were routinely used by the facility: (a) supervisory checklist for health system components (e.g., service-specific equipment, medications and records) based on standard and protocol; (b) supervisory checklist for health service provision (e.g., observation checklist) based on standards and protocol; (c) system for identifying and addressing quality of care that is implemented by staff or specific service level; (d) facility-wide review of mortality; (e) periodic audit of medical records or service registers; (f) quality assurance committee/team; (g) regional/district health management teams; and (h) other method. Components pertaining to supervision were asked separately for ANC/postpartum care and delivery/newborn care and measured (h) number of times in the last six months the provider’s delivery/newborn care was supervised and for the most recent supervisory visit, whether the supervisor (i) checked the provider’s records/reports; (j) observed his/her work; (k) provided feedback on his/her performance; (l) provided updates on administrative or technical issues related to his/her work; (m) discussed problems the provider had encountered; (n) discussed job expectations; and (n) anything else. Components pertaining to the availability of systems for client feedback asked whether the HF had the following systems for determining client opinion about the HF or its services: (o) suggestion box; (p) client survey form; (q) client interview; (r) other system. The variable measuring up-to-date birth registers consisted of four categories: no register, register not seen, register seen – last entry more than 7 days ago, and register seen – entry in past 7 days. One component of the index measured whether a skilled birth attendant (doctor, nurse or midwife) was present at the facility or on call 24 h a day, including weekends to provide delivery care and their actual involvement in conducting deliveries. This variable was coded as follows: 4 if a skilled attendant was present and always conducted deliveries; 3 if a skilled attendant was present but deliveries were sometimes conducted by primary- or auxiliary-level staff; 2 if a skilled attendant was on call and always conducted deliveries; 1 if a skilled attendant was on call but deliveries were sometimes conducted by primary or auxiliary level staff; and 0 if a skilled attendant was not present or on call 24 h a day, including weekends, to provide delivery care. The resulting 28-item HF index ranged from 0 to 31, with a Cronbach’s alpha of 0.8834 in 2005 and 0.895 in 2009. We calculated the LGA-level mean index based on the scores of all non-PMVs that provided MH services in the LGA. The analysis controlled for the following individual-level variables: year of survey (2009 versus 2005); duration of residence in the area (years); age as reported; number of children ever born; education (none, primary, secondary/higher); marital status (married, living with a partner, not in union); type of place of residence (urban, semi-urban, or rural); state (Bauchi, Kano, FCT, Lagos, Nasarawa); counseling about pregnancy complications (no ANC from a health professional, not counseled, counseled about pregnancy complications and where to go); and household wealth (low, medium, high). Household wealth represented by tertile of an index constructed from the household ownership of the following amenities/items, using principal components analysis: refrigerator, electricity, piped water, flush toilet, bicycle, motorcycle, car, television, radio, and telephone/cellular phone). The index was based on the first component, which explained 44.2 % of the common variances of all ten components. Scree plot inspection revealed a distinct one-factor solution. The Kaiser-Meyer Olkin measure of sampling adequacy was 0.867. The analysis was based on women whose most recent birth occurred in the five years preceding the survey. Descriptive statistics were calculated for all variables of interest. We computed F-tests to investigate the association between the HF delivery rate and LGA measures of service readiness, taking into consideration the multi-stage sampling design. Two-level random-intercept logistic regression models that offered simultaneous consideration of i women (Level 1) nested in j LGAs (Level 2) were estimated to take into consideration the hierarchical clustered structure of the data, which if ignored, could generate improper standard errors, and to incorporate random effects at the LGA and individual levels to account for unobserved factors. Adjusted odds ratios (AORs) and 95 % confidence intervals (CIs) were estimated from regression statistics using the generalized latent and mixed model command in Stata 12.1.0.15 Variance inflation factors (VIFs) suggested that multicollinearity was not a major concern: the mean VIF was 1.82 and the highest was 2.80. Intra-class correlation coefficients (ICC) were used to evaluate how the odds of HF delivery varied between LGAs and were calculated as: where σ2 μ is the intercept variance and π2/3 = 3.29 and represents the level-1 residual variance for a logit model. The analytical sample consisted of 51 LGAs and 2710 mothers whose last birth occurred in the past five years and who had no missing data on variables of interest. No significant differences between missing and non-missing cases were detected.