The MONARCH intervention to enhance the quality of antenatal and postnatal primary health services in rural South Africa: Protocol for a stepped-wedge cluster-randomised controlled trial

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Study Justification:
The MONARCH study aims to address gaps in maternal and child health services in rural South Africa, where HIV prevalence among pregnant women is high. By evaluating a Continuous Quality Improvement (CQI) intervention, the study seeks to improve antenatal and postnatal health service outcomes, specifically viral load testing in HIV-positive pregnant women and repeat HIV testing in HIV-negative pregnant women. The study is important because it will provide evidence on the effectiveness of CQI in improving clinic processes in primary care settings in sub-Saharan Africa, and contribute to knowledge on quality improvement interventions in resource-poor settings.
Highlights:
– The MONARCH study is a stepped-wedge cluster-randomised controlled trial conducted in rural KwaZulu-Natal, South Africa.
– The study evaluates the effectiveness of a Continuous Quality Improvement (CQI) intervention on antenatal and postnatal health service outcomes.
– The primary outcome measures are viral load testing in HIV-positive pregnant women and repeat HIV testing in HIV-negative pregnant women.
– The study involves 7 nurse-led primary healthcare clinics, with training and mentoring provided by the University of KwaZulu-Natal Centre for Rural Health.
– Data collection occurred over a period of 19 months, with a total study duration of 25 months.
– The study will provide valuable insights into quality improvement interventions in resource-poor settings and contribute to achieving the Sustainable Development Goals.
Recommendations:
Based on the findings of the MONARCH study, the following recommendations can be made:
1. Implement Continuous Quality Improvement (CQI) interventions in primary healthcare clinics to improve antenatal and postnatal health service outcomes.
2. Provide training and mentoring to healthcare providers on CQI methodology and its application in improving clinic processes.
3. Incorporate real-time data collection and analysis into routine clinic practices to identify gaps and implement targeted interventions.
4. Strengthen collaboration between academic institutions, healthcare providers, and policy makers to support the implementation and sustainability of CQI interventions.
5. Scale up successful CQI interventions to other resource-poor settings to improve maternal and child health outcomes.
Key Role Players:
1. Nurse-led primary healthcare clinics
2. University of KwaZulu-Natal Centre for Rural Health
3. Africa Health Research Institute (AHRI)
4. South African Department of Health
5. Local primary level sub-district hospital (Hlabisa Hospital)
6. Medical officers
7. CQI specialists and mentors
8. Improvement Advisor
9. Scientific Advisor
10. Data manager
Cost Items for Planning Recommendations:
1. Training and mentoring costs for healthcare providers
2. Data collection and analysis tools and software
3. Travel and accommodation expenses for CQI specialists and mentors
4. Administrative support for CQI activities
5. Communication and coordination costs between key role players
6. Evaluation and monitoring costs to assess the effectiveness of CQI interventions
7. Resource allocation for scaling up successful interventions to other settings
Please note that the cost items provided are general categories and not actual cost estimates. The specific budget items would need to be determined based on the context and requirements of the implementation.

The strength of evidence for this abstract is 8 out of 10.
The evidence in the abstract is strong because it describes a well-designed stepped-wedge cluster-randomised controlled trial to evaluate the effectiveness of a Continuous Quality Improvement (CQI) intervention on antenatal and postnatal health service outcomes in rural South Africa. The study provides detailed information on the study design, intervention, data collection, and analysis methods. However, to improve the evidence, the abstract could include more information on the sample size, statistical power, and the specific outcomes measured.

Background: Gaps in maternal and child health services can slow progress towards achieving the Sustainable Development Goals. The Management and Optimization of Nutrition, Antenatal, Reproductive, Child Health & HIV Care (MONARCH) study will evaluate a Continuous Quality Improvement (CQI) intervention targeted at improving antenatal and postnatal health service outcomes in rural South Africa where HIV prevalence among pregnant women is extremely high. Specifically, it will establish the effectiveness of CQI on viral load (VL) testing in pregnant women who are HIV-positive and repeat HIV testing in pregnant women who are HIV-negative. Methods: This is a stepped-wedge cluster-randomised controlled trial (RCT) of 7 nurse-led primary healthcare clinics to establish the effect of CQI on selected routine antenatal and postnatal services. Each clinic was a cluster, with the exception of the two smallest clinics, which jointly formed one cluster. The intervention was applied at the cluster level, where staff received training on CQI methodology and additional mentoring as required. In the control exposure state, the clusters received the South African Department of Health standard of care. After a baseline data collection period of 2 months, the first cluster crossed over from control to intervention exposure state; subsequently, one additional cluster crossed over every 2 months. The six clusters were divided into 3 groups by patient volume (low, medium and high). We randomised the six clusters to the sequences of crossing over, such that both the first three and the last three sequences included one cluster with low, one with medium, and one with high patient volume. The primary outcome measures were (i) viral load testing among pregnant women who were HIV-positive, and (ii) repeat HIV testing among pregnant women who were HIV-negative. Consenting women ≥18 years attending antenatal and postnatal care during the data collection period completed outcome measures at delivery, and postpartum at three to 6 days, and 6 weeks. Data collection started on 15 July 2015. The total study duration, including pre- and post-exposure phases, was 19 months. Data will be analyzed by intention-to-treat based on first booked clinic of study participants. Discussion: The results of the MONARCH trial will establish the effectiveness of CQI in improving antenatal and postnatal clinic processes in primary care in sub-Saharan Africa. More generally, the results will contribute to our knowledge on quality improvement interventions in resource-poor settings. Trial registration: This trial was registered on 10 December 2015: www.clinicaltrials.gov, identifier NCT02626351.

The study setting is rural KwaZulu-Natal, South Africa, in the community participating in the population health research carried out by the Africa Health Research Institute (AHRI) which was previously known as the Africa Centre for Health and Population Studies. AHRI is located within a 438 km2 area in the mostly rural Hlabisa sub-district of northern KwaZulu-Natal (Fig. 1). As a Wellcome Trust-Howard Hughes Medical Institute major overseas programme, the AHRI Population Intervention Platform Surveillance Area (PIPSA) South has collected comprehensive longitudinal population and HIV surveillance data on consenting individuals ≥15 years old (approximately 90,000 people in 11,000 households) since 2003. HIV prevalence amongst women of reproductive age is ~ 37% [36]. Overall fertility has been stabile since 2000, at about three children per woman, with an average of 2200 live births per year [37]. The Africa Health Research Institute study site at Somkhele. Location of the MONARCH study. Based on: Tanser et al. 2008 [46] There are 6 nurse-led Department of Health (DoH) primary healthcare clinics (PHCs) of varying size within the geographic bounds of PIPSA South. The clinic immediately outside the PIPSA South geographic bounds located in the market town of Mtubatuba, adjoins a major highway and is often visited by PIPSA residents regardless of proximity. It was thus added to the 6 clinics within PIPSA South for this study. Oversight of these 7 clinics is led by the local primary level sub-district hospital, Hlabisa Hospital. Medical officer support is provided weekly where possible. The CQI intervention in this study was delivered by the University of KwaZulu-Natal (UKZN) Centre for Rural Health (CRH) CQI specialist team who travelled from Durban, KwaZulu-Natal, to the study site. They worked collaboratively with PHC staff to implement changes in clinical practice through training and mentorship using real-time clinic data. The CRH team consisted of two isiZulu-speaking South African professional nurses (CRH CQI mentors) and a data capturer who carried out field activities, with close support from an Improvement Advisor (a consultant obstetrician with CQI experience), a Scientific Advisor and a data manager. CQI field activities for the entire project were scheduled in advance of the first intervention step and are described in detail below. The study, a stepped-wedge cluster RCT, was carried out from 15 July 2015 to 30 January 2017, at the 7 DoH PHCs described above: Mtubatuba, KwaMsane, Mpukunyoni, Somkhele, Machibini, Esiyembeni and Gunjaneni. All clusters crossed over from control to intervention exposure according to the stepped-wedge study design (Fig. 2). The six clusters were randomised to the calendar sequences of crossing over. The stepped-wedge study design was selected because (i) it was considered unethical to withhold the intervention from some clinics as CQI has known efficacy in resource-rich settings; (ii) the participation of all clinics both during the control and the intervention exposure state was thought to be better if it was known that during the course of the trial all clinics would receive the intervention; (iii) the field implementers of CQI were a small team of three people, making simultaneous rollout in all clusters impracticable; and (iv) it allows adjustment for secular trends in outcomes. Data collection occurred at all 7 DoH PHCs and Hlabisa Hospital maternity ward as the majority of deliveries from the sub-district occur at Hlabisa Hospital. The MONARCH stepped wedge study design. Clinics provided baseline (pre-intervention) data until each rolled over to the intervention in random order. All clinics provided data continuously throughout the study period. Baseline data collection across all clinics occurred from 15 July 2015 to 28 September 2015 (Step 0). As data extraction on antenatal visits was retrospective from the point of delivery, the baseline observation period covered an additional ~ 6 months for the first recruited participants – thus Step 0 covered a duration of ~ 8 months The clusters were pre-defined and included the 6 PHCs within the PIPSA South area plus Mtubatuba clinic. Antenatal care providers within clusters participated in the CQI activities based on availability. Efforts were made to recruit providers in leadership roles (e.g. Operational Managers, Professional Nurses) to increase likelihood of sustainability of the intervention and dissemination of skills. Based on clinic size (and staffing) approximately five participants from each clinic constituted a facility-level CQI team, which ideally included at least one person in a leadership position. All women aged 18 years or older were overall eligible for outcome and exposure assessment at three time points independent of previous or prospective recruitment status: at delivery, at the 3–6 day postnatal visit, and at the 6-week postnatal visit. Recruitment occurred continuously at all clinics and Hlabisa Hospital over the entire study period regardless of the clinic’s randomisation status. Women who had just delivered a baby at Hlabisa Hospital or any of the 7 study clinics were recruited for outcome and exposure assessment if they had attended any of the 7 study clinics for antenatal care (ANC) or resided in PIPSA South during their pregnancy. Consenting women attending a 3–6 day or 6-week postnatal visit at a study clinic with their infant (aged < 8 days or 5–8 weeks respectively) were recruited regardless of ANC clinic attended or where they resided during pregnancy. We hypothesized that this CQI intervention would bring about the desired changes in clinical processes by providing a supportive and motivating environment alongside real-time data to PHC-level healthcare providers. The CRH team supported PHC staff to implement simple workable solutions to gaps identified through collaborative root-cause analyses. Furthermore, CQI may have increased job satisfaction and empowerment through reduced workload and better patient outcomes. Implicit in these assumptions were staff availability to participate in CQI activities and the ability to continue normal clinical duties in parallel to CQI activities. Each intervention step was of 2 months’ duration with a 2-month pre-exposure data collection period and a 4.5-month endline (Fig. ​(Fig.2).2). We refer to the first 2-month intervention step as the ‘transition’ phase – this was the start of the intervention, in which ‘intensive’ CQI was delivered. The maintenance phase occurred after this transition phase for each cluster and included support and maintenance CQI visits in approximately monthly intervals. Visit types and planned activities are described in Table 1. Description of CQI intervention visit types and activities CQI Continuous Quality Improvement, CRH Centre for Rural Health, PDSA Plan-Do-Study-Act CQI field activities for the entire project were scheduled in advance of the first intervention step. Clinic-based CQI activities occurred over 3 days of a given week, and administrative work scheduled for a separate day each week. CQI tools and principles (Tables 1 & 2) included Action Learning Sessions at the end of each transition phase to consolidate skills and share experiences. The intervention was based on the Institute for Healthcare Improvement (IHI) breakthrough collaborative CQI model [38]. Given time constraints imposed by the study design, activities mainly targeted the primary endpoint indicators: repeat HIV screening and HIV viral load (VL) testing according to South African PMTCT guidelines (Additional file 1: Text S1). Additional study endpoint indicators were addressed as time permitted. Description of CQI tools used in the intervention CQI Continuous Quality Improvement, CRH Centre for Rural Health, PDSA Plan-Do-Study-Act Prior to transition-phase CQI activities, a 2-week lead-in period (approximately 4 visits) was planned, to introduce the newly randomised cluster to the CRH team and CQI concepts. A standardized ‘dose’ of intensive CQI of ~ 19 visits, was planned for each transition step. A schedule of monthly follow-up (CQI maintenance) visits was also planned thereafter and varied by cluster due to order of randomisation. Efforts to prevent cross-contamination whilst enabling buy-in for sustainability of CQI were made: only randomised clinics were invited to attend Action Learning Sessions, and PHC supervisors were excluded from these events during the intervention period (unlike ‘real-world’ implementation of CQI) as they supervise multiple clinics. However after the final transition step was complete, a final joint Action Learning Session with staff from all 7 clinics, PHC supervisors, sub-district and district DoH staff was held. In order to reduce bias the AHRI study investigators (evaluators) refrained from intervening in CQI clinic processes, although some operational co-involvement was required (e.g. introducing the CRH team to clinic staff). During the control exposure state, maternal and child healthcare providers continued providing DoH standard of care to ANC and PNC attendees as usually implemented. The South African maternal and child health strategic plan outlines the maternal package of services to be provided, including basic antenatal care. Usual training for staff involves weekly 1 hour in-service training on current evidence-based guidelines applied to primary healthcare services and may include training on ANC or PNC. The usual training, however, does not contain a mentoring component and is not a data driven process to evaluate the implementation of evidence-based guidelines. Additional background details on DoH standard of care are provided (Additional file 1: Text S1). All eligible women had their Maternity Case Record (MCR) photographed at delivery, excluding the intrapartum section, based on UKZN Biomedical Research Ethics Committee waiver of requirement for consent to access routine DoH data. All consenting women were interviewed at delivery and their infant’s Road-to-Health Booklet (RtHB) photographed. The structured interview covered themes on demographics, satisfaction with services, obstetric history, pregnancy intention, healthcare expenditures, access to care, and knowledge (infant feeding and HIV). At the 3–6 day and 6-week postnatal visits all consenting women were interviewed and their infant’s RtHB photographed. The structured interview at the 3–6 day visit was identical to the delivery visit. The 6-week structured interview covered themes on demographics, satisfaction with services, knowledge and uptake of services (HIV, PMTCT services, adherence to ART, contraception, self-reported infant feeding practices), healthcare expenditures, and access to care. All questionnaires contained questions in English with isiZulu translations and were conducted in isiZulu. Structured interviews of consenting healthcare providers at the 7 study clinics were undertaken in English covering themes on job satisfaction, motivation and antenatal care practices, at study mid-point and study end. Process evaluation data sources included semi-structured healthcare provider interviews undertaken in English, and detailed CQI implementation records from CRH for each PHC. The latter included actual visit dates, visit type, and descriptions of the successes and challenges the CRH CQI mentors encountered in implementing CQI. Data collection from clusters commenced on 15 July 2015 and concluded on 30 January 2017. Each cluster contributed pre-exposure data until rolled over to the CQI intervention. Data collection continued from all clusters throughout the study until project end, providing pre-exposure, transition phase and post-exposure outcome data on all clusters. As women were recruited at delivery or thereafter starting on 15 July 2015 – with retrospective capturing of their routine antenatal care data – the 2-month baseline data collection period contributed an additional observation period of ~ 6 months, resulting in a total data collection period of ~ 19 months and total observation period of ~ 25 months. The final post-exposure period (after all clusters had received the intervention) was 4.5 months (Fig. ​(Fig.22). Eleven data clerks trained in International Conference on Harmonisation (ICH) Good Clinical Practice (GCP) guidelines were based at either Hlabisa Hospital or the 7 PHCs throughout the study. All data collected in clinics and Hlabisa Hospital, including cameras, were returned daily to the AHRI data centre for secure storage and capturing. A data capturing team of five trained in ICH GCP, including research nurses and quality controllers, captured clinical and laboratory data from digital photographs of MCRs and infant RtHB, and all information from structured questionnaires onto a REDCap™ study database [39]. Each clinic was a cluster, with the exception of the two smallest clinics, which jointly formed one cluster. After a baseline data collection period of 2 months, the first cluster crossed over from control to intervention exposure state on 29 September 2015; subsequently, one additional cluster crossed over every 2 months (Fig. ​(Fig.2).2). The six clusters were divided into 3 groups by patient volume (low, medium and high). To increase the likelihood that the sample sizes in intervention and control exposure states were similar, and to improve balance, we then randomised the clusters to the six calendar sequences of crossing over, such that both the first three and the last three sequences included one small, one medium, and one large cluster. A senior biostatistician performed randomisation for all clusters prior to the first intervention step. All study implementers, evaluators and clinic health workers were blinded to the initial randomisation status. Two weeks prior to each scheduled intervention step crossover date, the custodian of the randomisation list (AHRI Chief Information Officer) revealed the randomised cluster to the AHRI study team. The AHRI study team then introduced the CRH team to the randomised cluster for CQI training to commence. For our baseline power calculation, we assumed – based on local routine primary care data – that without the MONARCH intervention viral load testing would be carried out in 40% of all pregnant women who were HIV-positive and repeat HIV testing would be carried out in 65% of all pregnant women who were HIV-negative. Based on local routine primary care data, we further assumed that half of all pregnant women would be HIV-positive and that pregnant women would make three ANC visits. We assumed an intracluster correlation coefficient (ICC) of 0.10. This coefficient is conservative compared to ICCs that we empirically measured in a similar setting (PHCs in sub-Saharan Africa providing ANC and HIV treatment and care), which ranged from 0.00 to 0.07 [40]. Finally, we assumed that we could not use information from 15% of enrolled women because of missing data. Given these assumptions, we estimated that we would have 80% power to detect at least a 15 percentage point increase in our two primary endpoints at the 5% significance level if we enrolled a total of 1260 pregnant women (i.e., 630 women who were HIV-positive and 630 women who were HIV-negative). Additional file 1: Table S1 shows the minimum detectable differences for this sample size with a number of alternative ICCs and endpoint values in the control exposure state. The data will be analyzed by intention-to-treat (ITT). For ITT analyses, patient outcomes will be analyzed by the exposure status of the clinic attended at the first antenatal booking visit, independent of later clinic switches. We will analyse the CQI effect using mixed effects generalized linear regression models. In the main analysis, we will include a fixed effect for the time step and a random effect for clinic, following Hussey and Hughes [41], as well as adjust for clustering of standard errors at the clinic level. For the analyses of our two primary endpoints, which are binary, we will use modified Poisson regression [42] within the generalized linear regression framework. Our main results will thus be expressed as risk ratios. In sensitivity analyses, we will adjust for patient pre-exposure characteristics, and we will assess effect modification by secular time and time since intervention start in a clinic [43]. Stata (version 15.0, StataCorp, College Station, Texas) will be used for all analyses. For the Process Evaluation we will use a logic framework to explore the relationship between (i) input factors or resources that guide; (ii) activities needed to transform inputs into outputs processes; (iii) output elements comprising health service products produced with the inputs and activities; and (iv) the outcomes of this change process. A SPIRIT checklist pertaining to this protocol is attached (Additional file 2).

The MONARCH intervention is a Continuous Quality Improvement (CQI) program aimed at improving antenatal and postnatal health services in rural South Africa, specifically targeting pregnant women with HIV. The study is a stepped-wedge cluster-randomized controlled trial involving 7 nurse-led primary healthcare clinics. Here are some key innovations and recommendations from the study:

1. Continuous Quality Improvement (CQI): The MONARCH intervention utilizes CQI methodology to improve the quality of antenatal and postnatal services. This involves training healthcare staff on CQI principles and providing ongoing mentoring and support.

2. Real-time clinic data: The intervention uses real-time clinic data to identify gaps and implement changes in clinical practice. This data-driven approach helps healthcare providers make informed decisions and improve patient outcomes.

3. Collaborative root-cause analyses: The MONARCH intervention includes collaborative root-cause analyses to identify the underlying causes of gaps in service delivery. This approach involves engaging healthcare providers in problem-solving and finding practical solutions to improve care.

4. Action Learning Sessions: The intervention includes Action Learning Sessions at the end of each transition phase to consolidate skills and share experiences. These sessions provide a supportive and motivating environment for healthcare providers to learn from each other and improve their practices.

5. Randomized controlled trial design: The study utilizes a stepped-wedge cluster-randomized controlled trial design, which allows for the evaluation of the effectiveness of the intervention while ensuring that all clinics eventually receive the intervention. This design helps to minimize ethical concerns and allows for adjustment of secular trends in outcomes.

6. Inclusion of patient perspectives: The study collects data on patient satisfaction with services, knowledge, and access to care. This patient-centered approach helps to ensure that the intervention addresses the needs and preferences of pregnant women.

Overall, the MONARCH intervention combines CQI methodology, real-time data, collaborative problem-solving, and a patient-centered approach to improve access to maternal health services in rural South Africa. The results of this study will contribute to our knowledge on quality improvement interventions in resource-poor settings.
AI Innovations Description
The MONARCH intervention is a Continuous Quality Improvement (CQI) program aimed at improving antenatal and postnatal health services in rural South Africa, where HIV prevalence among pregnant women is high. The intervention involves training healthcare staff on CQI methodology and providing additional mentoring as needed. The study is a stepped-wedge cluster-randomized controlled trial, with 7 nurse-led primary healthcare clinics participating. The intervention is applied at the cluster level, with one cluster crossing over from control to intervention every 2 months. The primary outcomes being measured are viral load testing among HIV-positive pregnant women and repeat HIV testing among HIV-negative pregnant women. The study is being conducted in rural KwaZulu-Natal, South Africa, within the population health research carried out by the Africa Health Research Institute. The study duration is 19 months, including pre- and post-exposure phases. The results of the MONARCH trial will provide valuable insights into the effectiveness of CQI in improving antenatal and postnatal clinic processes in resource-poor settings.
AI Innovations Methodology
The MONARCH study is a stepped-wedge cluster-randomized controlled trial that aims to evaluate the effectiveness of a Continuous Quality Improvement (CQI) intervention in improving antenatal and postnatal health service outcomes in rural South Africa, where HIV prevalence among pregnant women is high. The study focuses on improving viral load testing in HIV-positive pregnant women and repeat HIV testing in HIV-negative pregnant women.

The methodology of the study involves the following steps:

1. Study Setting: The study is conducted in rural KwaZulu-Natal, South Africa, within the population health research carried out by the Africa Health Research Institute (AHRI). The study site includes 7 nurse-led primary healthcare clinics and a sub-district hospital.

2. Cluster Randomization: The 7 clinics are divided into 3 groups based on patient volume (low, medium, and high). Randomization is done to determine the order in which the clusters will receive the CQI intervention.

3. Stepped-Wedge Design: The study uses a stepped-wedge design, where each cluster transitions from a control exposure state to an intervention exposure state at different time points. The first cluster crosses over to the intervention exposure state, followed by one additional cluster every 2 months.

4. CQI Intervention: The CQI intervention is delivered by a specialist team from the University of KwaZulu-Natal (UKZN) Centre for Rural Health. The team provides training and mentorship to the healthcare staff at the clinics, focusing on implementing changes in clinical practice based on real-time clinic data.

5. Data Collection: Data collection occurs at all 7 clinics and the sub-district hospital. Baseline data is collected for 2 months before the first cluster transitions to the intervention exposure state. Data is collected continuously throughout the study period, including pre-exposure, transition phase, and post-exposure data.

6. Outcome Measures: The primary outcome measures are viral load testing among HIV-positive pregnant women and repeat HIV testing among HIV-negative pregnant women. Other secondary outcome measures are also assessed, including satisfaction with services, knowledge, and uptake of services.

7. Data Analysis: The data will be analyzed using intention-to-treat analysis, where patient outcomes will be analyzed based on the exposure status of the clinic attended at the first antenatal booking visit. Mixed effects generalized linear regression models will be used to assess the effect of the CQI intervention.

The results of the MONARCH study will provide valuable insights into the effectiveness of CQI in improving antenatal and postnatal clinic processes in resource-poor settings. The study aims to contribute to the knowledge on quality improvement interventions in maternal health in sub-Saharan Africa.

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