Impact of a bottom-up community engagement intervention on maternal and child health services utilization in Ghana: A cluster randomised trial

Background: Ghana is among African countries not likely to achieve the Sustainable Development Goal (SDG) three (3) target of reducing maternal mortality to 70 per 100,000 live births by the year 2030 if maternal and child health services utilization are not improved. Community engagement in health is therefore advocated to help address this challenge. This study evaluated the impact of a community engagement intervention on maternal and child health services utilization in Ghana. Methods: This study was a cluster randomised trial among primary healthcare facilities (n = 64) in the Greater Accra and Western regions in Ghana. Multivariate multiple regression analysis and paired-ttest were used to determine impact of the community engagement intervention on maternal and child health indicators at baseline and follow-up. Results: Intervention health facilities recorded significant improvements over control facilities in terms of average spontaneous vaginal deliveries per month per health facility (baseline mean = 15, follow-up mean = 30, p = 0.0013); child immunizations (baseline mean = 270, follow-up mean = 455, p = 0.0642) and female condoms distribution (baseline mean = 0, follow-up mean = 2, p = 0.0628). Other improved indicators in intervention facilities were average number of Human Immunodeficiency Virus (HIV) tests for non-pregnant women (baseline mean = 55, follow-up 104, p = 0.0213); HIV tests for pregnant women (baseline mean = 40, follow-up mean = 119, p = 0.0067) and malaria tests (baseline mean = 43, follow-up mean = 380, p = 0.0174). Control facilities however performed better than intervention facilities in terms of general laboratory tests, voluntary counselling and testing, treatment of sexually transmitted infections, male child circumcisions and other minor surgical procedures. Conclusion: Community engagement in health has the potential of improving utilization of maternal and child health services. There is the need for multi-stakeholder dialogues on complementing existing quality improvement interventions with community engagement strategies.

This was a cluster randomised trial in 64 primary health facilities (32 intervention and 32 control) and their catchment area, as detailed in previous related publications by the lead author [5–8]. Primary health facilities in this context are clinics and health centres as per the Ghana Health Service (GHS) categorizations and pyramidal levels of healthcare. Private and public health facilities categorized as clinics or health centres were considered eligible for inclusion in this study. Moreover, health facilities credentialed by the National Health Insurance Authority (NHIA) in Ghana were included in the study. Health facilities with same or similar NHIA credentialed scores were included to ensure homogeneity among the control and intervention facilities. The NHIA is an agency under the Ministry of Health (MoH) established in 2003 by Parliamentary Act (650) and amended Act (852) in 2012. The NHIA is mandated to implement the NHIS, determine scheme membership contributions, registration, issuance of membership cards and regulation of private health insurance schemes in Ghana. This study setting and population are the same as previous publications by the lead author using the same research design and approach (see Alhassan et al. [5–8]). The study was thus conducted in the Greater Accra and Western regions of Ghana in 16 administrative districts. Greater Accra region is a coastal region which also hosts the capital of Ghana (Accra); it is predominantly urban and cosmopolitan with a population of about 4 million people [7, 9]. Out of the nearly 3593 credentialed health facilities in Ghana in 2018, a total of 419 were in Greater Accra region [7, 9]. Western region which is also a coastal region has a population of a little over 2 million with 439 NHIS-credentialed health facilities as at 2018 [9]. In both regions over 50% of the credentialed facilities are primary level facilities (i.e. clinics and health centres). Randomisation and sampling procedure for this study are same as previous publications by the lead author [5–8] where the sample frame entailed list of primary health facilities credentialed by the NHIA. Primary health facilities were purposively selected for this study because they are relatively less complex in terms of health service delivery and could easily be monitored for impact of the implemented intervention [7]. Moreover, these cadres of health facilities are closer to their communities in terms of service delivery and are often the first port of call in terms of formal healthcare delivery [7]. The cluster randomization involved randomly sampling eight (8) NHIS-district offices, analogous to administrative districts, from each of the two regions same as the approach used in Alhassan et al. [7]. The focus was on districts which had NHIS membership enrolment and NHIS credentialed health facilities at the time of conducting the study. NHIS districts were selected because these districts were analogous to the administrative districts in the two regions at the time of conducting the study. Also, the study focused on all facilities accredited by the NHIA at the time of conducting this study hence, the need to consider districts which had NHIS membership enrolment and NHIS accredited health facilities [5–8]. Next, four (4) health facilities were randomly picked without replacement as cluster sites from each district; two (2) facilities were then randomly assigned to intervention and control groups, making a total of 32 intervention and 32 control facilities (see Additional file 1). Prior to the randomization, Principal Component Analysis (PCA) was performed on the NHIA credentialed data in all the sixteen (16) districts to select the most homogeneous health facilities. The PCA scores allowed for comparability in the 64 sampled facilities (32 from each region), prior to randomization into control and intervention groups [5–8]. A profile of health facilities involved in the cluster randomised trial is detailed in Table 1. Profile of health facilities involved in cluster randomized trial n = 64 Source: Field Data Greater Accra and Western Regions (2014); Legend: aAttrition of one health facility which was rural by location and private by ownership; f (Frequency) Detailed description of the SCE intervention has been published in previous articles by the lead author [5–8]. Nonetheless, an overview of the SCE intervention is presented in this paper for the purposes of emphasis. The community engagement intervention was implemented in 32 primary health facilities for nearly one year (from June, 2013 to March, 2014) and evaluated over three months [7]. Baseline study was conducted in 2012 and the follow-up conducted in 2014 after the intervention implementation. The bottom-up intervention involved using existing community groups/associations to identify service delivery gaps in healthcare facilities through a systematic community engagement process (see Additional file. 2) [7]. Comprehensive reports on the community engagement intervention have been published by Alhassan et al. [5–8]. The SCE intervention was implemented using a bottom-up approach to promote community participation in the healthcare quality improvement value chain guided by predetermined healthcare quality proxies. The first step of the engagement process involved recruitment and training of 52 facilitators, and identification of existing community groups/associations. As part of the engagement process, one facilitator was assigned to each of the 52 community groups in the two study regions, thus 26 in each region [7]. The second step of the intervention entailed evaluation of the quality of healthcare services in the intervention health facilities by community members. The assessment was done based on the clients’ most recent encounter with the service providers, in the last six (6) months [7]. Healthcare quality proxies assessed by the community members were non-technical components of service delivery such as staff attitude towards clients, staff punctuality to work, feedback from staff to clients on their health conditions, staff providing right information to clients during service delivery and ability of health facility to dispense all prescribed medications to clients. As part of the assessment process, community members were expected to express their satisfaction or disappointment with these healthcare quality proxies. The community scoring was guided by “cartoon illustrated” five-point Likert Scale score card that ranged from 1 = “Very disappointing” to 5 = “Very Satisfactory”. Assessment scores by community members are published in Alhassan et al. [8]; besides, the focus of this paper is on impact of the community engagement activities on utilization of maternal and child health services in health facilities that benefited from the implemented interventions. The third step of the intervention implementation involved a validation of the community members assessment scores with the relevant stakeholders such as health managers, NHIS managers, clients and traditional authorities. The validation and feedback sessions were held separately in the regional capitals of the two regions. The aim was to enable service providers address identified service quality gaps and agree with clients and other stakeholders on timelines for addressing these gaps [7]. The fourth step was a follow-up on the intervention health facilities by community facilitators also called “community quality care champions” to ensure action plans were implemented by health managers in the intervention health facilities as agreed during the validation and feedback sessions. The follow-up was done by the “community quality care champions” approximately three (3) months after the third implementation step [7]. The final step involved recognition of health facilities which were perceived by community members to have improved in the quality of their services to clients after the series of engagements with community members. The community members adjudged the best health facilities themselves to promote transparency, ownership and accountability of health providers to clients. Reward for best health facilities in service quality was an inscription of recognition displayed at the outpatient department (OPD) of the facility in addition to a cash amount of approximately US$ 280 given in Ghana Cedis (GHC) equivalence. The aim of this recognition was to stimulate health competition among peer health facilities to render client-centered quality services. See details of all the intervention implementation steps in Additional file 3 and in Alhassan et al. [7]. Data was collected using a tool called Situational Analysis Plus (SA+) which has four main sections namely: Facility Information, Access to Care, Clinic Activities/Services, and Personnel/Vacancies. SA+ was developed by the PharmAccess Foundation and SafeCare Initiative in the Netherlands and has been tested in a number of African countries including Ghana. Details of the SA+ tool can be found in Alhassan et al. [5]. Only data from primary health facilities contacted at baseline and follow-up was used for the final analysis in line with the protocol for evaluating effectiveness of interventions [10]. STATA statistical software version 12.0 (StataCorp, College Station. Texas USA) was used for all analysis. Multivariate multiple regression analysis and paired t-test were used to determine true impact of the community engagement intervention on the key outcome variables of interest after testing for multicollinearity and controlling effects of relevant covariates. Main outcome variables were: number of spontaneous vaginal deliveries; number of child immunizations conducted; number of female condoms distributed; number of HIV tests for non-pregnant women, number of HIV tests for pregnant women, and number of malarial tests. These outcome variables were recorded on “per month per health facility” basis.

• alhassan, robert kaba
• nketiah-amponsah, edward
• ayanore, martin amogre
• afaya, agani
• salia, solomon mohammed
• japiong, milipaak
• ansah, evelyn k.
• owusu-agyei, seth