Realist evaluation to improve health systems responsiveness to neglected health needs of vulnerable groups in Ghana and Vietnam: Study protocol

PLoS ONE, Volume 16, No. 1 January, Year 2021

Interpretation

Background Socio-economic growth in many low and middle-income countries has resulted in more available, though not equitably accessible, healthcare. Such growth has also increased demands from citizens for their health systems to be more responsive to their needs. This paper shares a protocol for the RESPONSE study which aims to understand, co-produce, implement and evaluate context-sensitive interventions to improve health systems responsiveness to health needs of vulnerable groups in Ghana and Vietnam. Methods We will use a realist mixed-methods theory-driven case study design, combining quantitative (household survey, secondary analysis of facility data) and qualitative (in-depth interviews, focus groups, observations and document and literature review) methods. Data will be analysed retroductively. The study will comprise three Phases. In Phase 1, we will understand actors’ expectations of responsive health systems, identify key priorities for interventions, and using evidence from a realist synthesis we will develop an initial theory and generate a baseline data. In Phase 2, we will co-produce jointly with key actors, the contextsensitive interventions to improve health systems responsiveness. The interventions will seek to improve internal (i.e. intra-system) and external (i.e. people-systems) interactions through participatory workshops. In Phase 3, we will implement and evaluate the interventions by testing and refining our initial theory through comparing the intended design to the interventions’ actual performance. Discussion The study’s key outcomes will be: (1) improved health systems responsiveness, contributing to improved health services and ultimately health outcomes in Ghana and Vietnam and (2) an empirically-grounded and theoretically-informed model of complex contexts-mechanisms- outcomes relations, together with transferable best practices for scalability and generalisability. Decision-makers across different levels will be engaged throughout. Capacity strengthening will be underpinned by in-depth understanding of capacity needs and assets of each partner team, and will aim to strengthen individual, organisational and system level capacities. Our overall health systems research question is: In what way can health systems become more responsive to neglected health needs of vulnerable groups within the contexts of lower-middle-income countries? This study has five objectives, shown in Table 1 alongside the corresponding research questions. Key study’s outcomes will be: (1) improved health systems responsiveness to neglected health needs of vulnerable groups in Ghana and Vietnam, and (2) an empirically-grounded and theoretically-informed model of complex relations between the contexts, mechanisms and outcomes of the interventions, along with transferable best practices for scalability (i.e. expansion within similar contexts) and generalisability (i.e. to different contexts, such as other health areas and countries) for future health systems strengthening. The most widely known framework for health systems responsiveness, developed by the WHO in 2000, comprises seven domains: dignity, autonomy, confidentiality, prompt attention, quality of amenities, access to support networks, and choice of service provider [1, 8, 24]. The WHO framework has been translated into a survey toolkit for self-assessments of patients’ use of healthcare [24–26]. More recent work on the topic stressed that interactions between the people and their health systems are central to understanding this concept [2], and improving responsiveness should therefore address both the ‘people’ and the ‘systems’ sides of such interactions [2, 27, 28]. Evidence also shows that interpretations of responsiveness can be context-sensitive (e.g. expectations of dignity reflect political, democratic and policy climate [5]), and vary across actors (e.g. patients and providers with different powers [7, 29]) and health facilities (e.g. public/private [5, 7]). Responsiveness, therefore, is arguably a socially-constructed, rather than an ‘absolute’ and ‘universally normative’ concept. Adaptations of the seven domains of responsiveness have been proposed for different health areas, such as HIV/AIDS or mental health [26, 30, 31]. Yet, we found no studies which sought to improve health systems responsiveness to health needs of vulnerable groups in LMICs, including to neglected maternal mental health needs. Furthermore, many theoretical and applied questions remain unanswered, such as the following. What does responsiveness mean to different actors on the ‘people’ and the ‘systems’ sides? How do these conceptualisations shape actors’ behaviours and practices? In what way improving responsiveness contributes to other health systems goals? In RESPONSE, we will bridge some of these knowledge gaps while also responding to calls for improved understanding of health systems responsiveness to the needs of diverse health systems actors in LMICs [2, 11, 27, 28]. We approach ‘responsiveness’ as a dynamic social action which is produced via relationships between different actors within contexts of particular socio-economic arrangements as they negotiate experiences of professional, citizen, consumer and patient rights and responsibilities. In our theoretical framework (Fig 2), health systems responsiveness is understood as comprising the socially-constructed processes of external and internal interactions. Experiences of these interactions determine the degree of health systems responsiveness across eight domains: dignity, autonomy, confidentiality, attention, access to networks, quality of amenities, choice of service provider and trust. People’s engagements with health systems (for example, to seek healthcare) and system’s responses to these engagements (for example, service delivery) are shaped by their initial expectations [2]. People’s initial expectations are influenced by their individual’s relations with their families and communities within the context of cultural and societal norms as well as their potential vulnerability. The system’s ability to be responsive is driven by the expectations of frontline service providers of responsive services, in the context of current structures, processes, priorities and targets set by policymakers and managers. Conceptually, health systems responsiveness involves two socially-constructed interactions: People’s interactions with their families and communities are conceptualised as a context which shapes their initial expectations and subsequent engagements with a health system, though these can also be interpreted as a possible third type of interactions. Improving health systems responsiveness should, therefore, target both the internal (within the health systems) and external (between the people and health systems) interactions and be cognisant of the wider context which shapes people’s initial expectations of, and their subsequent engagements with, their health systems. We will conduct the study in two lower-middle-income countries: Ghana and Vietnam. Our choice of these two countries is driven by three considerations. First, their commonalities and diversity provide excellent value for this research. Key similarities are: Data from • Global Burden of Disease Collaborative Network. GBD Study 2017 Socio-Demographic Index (SDI) 1950–2017. Seattle, United States: Institute for Health Metrics and Evaluation (IHME); 2018. • Fullman N, et al. Measuring performance on the Healthcare Access and Quality Index for 195 countries…: a systematic analysis from the GBD Study 2016. The Lancet 2018; 391(10136): 2236–71. • WHO. Global Health Observatory. http://apps.who.int/gho/portal/gho.jsp (accessed 9 May 2019). • WHO. Global Health Expenditure Database. http://apps.who.int/nha (accessed 9 May 2019). The two health systems also have differences. Vietnam’s publicly-dominated system has increasing market competition, but the Ghanaian system has large private not-for-profit sector and a more substantial share of external funding for health (13% compared with 2% in Vietnam) [33]. With regards to decentralisation, in Vietnam most power is consolidated at the province (regional) level whereas in Ghana districts have greater autonomy. While the antenatal care coverage and skilled birth attendance levels are relatively high (over 85%) in each country, maternal mortality in Ghana is higher i.e. 319/100,000 live births compared with 54/100,000 in Vietnam [34]. This may reflect problems with service quality and poorer people-system interactions leading to delays in seeking healthcare. In Ghana, there are dedicated staff for local mental healthcare (e.g. community psychiatric nurses), whereas provision of grassroots level mental healthcare in Vietnam is through mainstream primary health care workers. Our experience shows that in Vietnam, vulnerability often relates to ethnicity and income, but in Ghana it seems to be mostly location and income-related. The second reason which guided the choice of Ghana and Vietnam is that there is high interest from policymakers in making the health systems more responsive to health needs of the most vulnerable. Preliminary discussions with key decision-makers from the Ghana Health Service and Ministries of Health in each country held during the proposal development showed that all key policymakers are committed to improving health systems responsiveness. In each country, maternal health remains a priority [35, 36] with increasing attention to mental health and integrated and responsive services. Psychological well-being of mothers and new-borns is a part of Ghana’s 2014 National Reproductive Health Policy and Standards. In Vietnam, policymakers emphasise ensuring equity in access, integrating mental healthcare (for example, into community programmes [37]) and piloting models of support and rehabilitation for those with mental illnesses. Finally, we have chosen these two countries because we have strong and longstanding academic collaborations between the Universities of Leeds and Ghana [38], and Universities of Leeds and Melbourne with Hanoi University of Public Health [39, 40]. We will leverage and extend these into effective South-South collaborations, exchange and learning, as well as building links amongst policymakers and practitioners in Ghana and Vietnam. In each country, we have purposefully selected one region (in Ghana) or province (in Vietnam) with some of the largest inequities disproportionately affecting vulnerable groups. Within each region and province, we have further selected a rural and an urban district to allow comparisons between rural-urban contexts. In Ghana, we will work in Greater Accra Region located in the Coastal zone. It is 90% urban with highest maternal mortality of 336/100,000 live births as compared with the national average of 310/100,000 live births according to the 2017 Maternal Health Survey, growing squatter urban slums and some of the most deprived rural communities. In Vietnam, we will work in Bắc Giang, a mountainous Province 50km to the east of the capital Hanoi, with large vulnerable groups and 12% of the population comprising ethnic minorities. In each country, we have selected two district health systems as our case studies, based on consultations with policymakers and their demographic and health indicators (Table 3) and leadership’s commitment to and opportunities for change. We have selected a purely rural (Shai Osudoku and Yên Thế), a rural with urbanised periphery (Ningo Prampram) and urban (Hiệp Hoà) districts, to allow learning across rural-urban settings. Data from national health information systems Both districts in Ghana have a Demographic Surveillance System run by the Dodowa Health Research Centre, thus giving a useful link to an existing dataset. The Vietnam’s MOH has identified the Bắc Giang Province to pilot models of support and rehabilitation for those with mental illnesses (including pregnant women), which provides an excellent opportunity and timing for our results to inform on-going reforms. In each district, we will implement interventions in the district hospital, 2–4 public and private primary health care facilities and within respective communities. As we explain later in the paper, the interventions will aim to improve external interactions (i.e. between people and health systems) as well as internal interactions within health systems (i.e. between healthcare staff and managers). Simultaneously, in Ghana we will engage with Greater Accra Regional Health Directorate and Ghana Health Service, in Vietnam we will engage with Province Health Department, and national Ministry of Health. The project co-investigator Dr Ashinyo is Deputy Director in the Directorate of Clinical Care of the Ghana Health Service and therefore has direct links with national policymakers. In Vietnam, we will leverage project co-investigator Professor Bui’s strong research-policy links. This will ensure sustainability, replication and scaling up of the interventions. We will use a mixed-methods realist theory-driven case study design, utilising our expertise in realist evaluations [41–46] and established standards for reporting realist evaluations [43]. Health systems comprise heterogeneous interconnected actors (e.g. patients and providers) operating at multiple levels within a complex dynamic system. Ensuring systems responsiveness requires aligning multiple interpretations from actors with different powers and resources. A realist approach helps make sense of such complexity by identifying how the multiple components interact in non-linear ways [47, 48]. It recognises micro, meso and macro contexts (Cs) in triggering the mechanisms (Ms) to produce outcomes (Os) [47, 48], known as CMO configurations, to explore what works, in which circumstances, for whom and why [47], and therefore suits this study. Realist researchers develop, test and refine middle-range theories which show causal pathways of how interventions work. Such an approach is similar to studies guided by theories of change or even initial hypotheses. Our draft initial theory, to be further developed, tested and refined is: Context-sensitive interventions for better recognition of initial expectations of key actors, if co-produced by these actors to target internal and external interactions and implemented within favourable policy contexts, will improve health systems responsiveness to neglected health needs of vulnerable groups, ultimately contributing to better health outcomes for all. This 42-months study will comprise three Phases as shown in Fig 3 (methods are in italics) and set out in detail in the following three sub-sections. In phase 1 (first year) we will understand actors’ expectations of responsive health systems, identify key priorities for fine-tuning interventions, develop initial theory (using evidence from a realist synthesis) and generate a baseline of data (through primary data collection and analysis). This phase will particularly address the study’s objective 1 and will include two broad parts: We will rigorously synthesise knowledge on systems responsiveness in LMICs using realist synthesis, a “…systematic, theory-driven interpretative technique… to help make sense of heterogeneous evidence about complex interventions applied in diverse contexts” [51 p.2]. This review approach is well suited for explaining disparate data and conceptualisations across the academic disciplines [52] and unpacking specific pathways of how particular contexts may trigger (or interfere with) mechanisms to produce intended or unintended outcomes [53]. The realist synthesis will help understand how specific micro-meso-macro contexts shape certain pathways through which responsiveness works. While there is a substantial knowledge base on assessing health systems responsiveness using adaptations of the WHO survey toolkit, published literature on improving systems responsiveness is scarce. Therefore, in addressing key issues from Phase 1 and fine-tuning the interventions (in Phase 2), we will draw on broader relevant knowledge of health systems strengthening–for example, accountability [6, 54, 55], integration of mental and maternal services [20, 22, 23] and staff support [56–58]–and will relate these to our understanding of vulnerability [14–17], our understanding of responsiveness in our framework and our initial theory. Our realist synthesis will utilise a four-step process [59], which will run alongside other components of the wider RESPONSE study, and will comprise: A detailed protocol for the realist synthesis is available from the International Prospective Register of Systematic Reviews, PROSPERO registration CRD42020200353 (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=200353). The aim of collecting and analysing primary data during Phase 1, will be to answer research questions 1a and 1b (see Table 1 earlier) through exploring: We will collect data using: (i) reviews of policy and facility documentation including analysis of facility records of service provision and use; (ii) in-depth interviews and focus group discussions with key actors from local communities and health systems and (iii) a community survey. Data will be analysed retroductively, meaning both inductively and deductively. We will draw upon established processes for data analysis such as thematic analysis of qualitative data, and regression models for analysis of quantitative data. We will begin with a comprehensive review of policy and facility documentation to deepen our understanding of policy, regulatory and systems environments and healthcare practices—relating all back to the conceptualisations of health systems responsiveness. We will qualitatively review two purposefully-identified types of documents: key national-level policies, plans and guidelines; and relevant local-level documents within health facilities, such as minutes of management meetings, clinical reviews, and staff management and performance appraisal records. We will adopt a semi-structured template to summarise insights on the underlying conceptualisations, values and ideas around responsiveness, and approaches to ensuring health systems responsiveness. We will also quantitatively assess patterns of provision and utilisation of maternal and mental health services. To do so, we will analyse facility records for the last 2–3 years disaggregated by key dimensions of intersectionality such as age, income and residence. Using the IDIs, we will understand what responsiveness means to different health systems actors including its importance, underlying principles, components, mechanisms and intended outcomes. We will also explore the actors’ framing of underlying fundamental issues (e.g. rights, agency) and practices (management, service provision, health-seeking), relating them to our continuously refined understanding of responsiveness. From our experience, 20–25 IDIs should sufficiently represent views of key actor groups in each district, with further 10–15 IDIs at the province and national levels each (total 60–80 IDIs per country). This may decrease if we reach data saturation earlier, i.e. when no major new themes will be emerging from subsequent IDIs. We will also conduct 4–6 FGDs with key actors in each country. These will explore their understanding and expectations of responsive health systems, their framing of underlying fundamental issues and will understand group norms and dynamics. The FGDs will be conducted at the community, facility and province levels (1–2 at each level). Each group will comprise 6–8 participants to maximise engagement, will comprise similar participants (in terms of age, staff category) and separate FGDs may be conducted to reduce gender-related bias. The participants for IDIs and FGDs will be identified through purposive sampling and will include: (a) patients and public across their intersectionality dimensions (such as different genders, incomes and social strata); (b) health facility staff including service providers and support staff; and (c) health policymakers and managers. An initial participant list will be drawn by month 3 and we will identify further ones through snowballing. All FGDs and IDIs will be guided by a semi-structured topic guide to explore causal pathways of responsiveness [42]. Questions will be adapted to specific individuals’ backgrounds and roles. All IDIs and FGDs will be conducted in local languages as appropriate, audio-recorded, transcribed and either translated verbatim to English for thematic analysis or analysed in local languages with relevant extracts to be translated for cross-country comparisons. We will conduct a baseline community survey to help us understand which attributes of responsive health systems community members value and expect most, and which drivers determine health-seeking behaviours of vulnerable groups. These attributes will be based on the WHO’s seven domains of health systems responsiveness: dignity, autonomy, confidentiality, prompt attention, quality of amenities, access to support networks, and choice of service provider [1, 8, 24]. We will explore how the values and expectations that respondents hold about these attributes, differ across key characteristics, such as users vs non-users of the health system, and across their different intersectionality dimensions, such as gender and socio-economic status. We will use insights from the preceding qualitative methods to guide the design of the survey questionnaire. We will measure how much relative importance respondents place on the different attributes of responsiveness, that is how much they value and expect each attribute, using Likert scales or discretely coded visual analogue scales. We will pilot test the questionnaire among a small number of purposively selected respondents to explore its acceptability and their understanding of a range of different scales, to allow us to select the most suitable scale. During the pilot we will also explore respondents’ understanding of the rest of the questionnaire, along with the feasibility and acceptability of the survey methodology to data collectors. We will also collect a range of key socio-demographic details from respondents on factors that are likely related to their access and use of the health system and their experiences of engaging with the health system, and which will allow us to categorise them in terms of key determinants of intersectionality like gender and socio-economic status. Depending on the sampling frame data that is available in each country, we will use a multi-stage clustered household survey sampling approach [63] to allow us to select a statistically representative population sample from the relevant communities around our intervention facilities. Sample size: To understand respondents’ views on the importance of the different attributes of responsiveness, we will treat each discrete point on our chosen responsiveness attribute “importance scale” as a binary outcome and estimate the percentage of respondents selecting that point on the given scale (accounting for the complex survey design). We estimate that for the survey in each country we will require 562 respondents (assuming a response rate of 95%) to estimate the percentage of respondents selecting each point on the scale (assuming the most conservative percentage of 50% when estimating the sample size for a binary outcome based on precision) with a margin of error of ± 6 percentage points (95% confidence intervals), which we judged to be a suitable balance between precision and resources, and assuming a moderate design effect of 2 given we have no existing data (the mean design effect in the Ghana Demographic and Health Survey 2014 was 1.5). We will aim to understand the relationships between the socio-economic factors and respondents’ views on the relative importance of the different attributes of responsiveness, such as differences between men and women. In doing so, we will use appropriate multiple linear regression models that treat the “importance scale” outcomes as continuous variables (and which adjust for any complex survey design features such as clustering, stratification and weighting). Based on this approach, the above sample size (562) would also allow us to detect differences between binary subgroups, such as men and women (assuming a maximum between-subgroup size ratio of ≤6:1), of 0.65 or greater points in their responses to any of the “importance scale” questions with 80% power (based on two-sided hypothesis testing at the 5% significance level, assuming t-distributed data, a response rate of 95%, a design effect of 2). The outcome of Phase 1 will be an initial theoretical model explaining how health systems responsiveness works. It will explain how different contexts shape and trigger the mechanisms through which health systems responsiveness is enacted (or not) by the different actors to produce the intended and unintended outcomes. In Phase 2 (months 13–18) we will co-produce the context-sensitive interventions to improve health systems responsiveness, addressing study objective 2. The co-production will be through 2–3 meetings in each district involving key actors (communities, service providers, facility managers, regional/province and national-level actors). These meetings themselves can also be seen as interventions, and will therefore involve elements of capacity strengthening and knowledge uptake. The meetings will be led by district (or regional) health leadership and facilitated by researchers who will present evidence from Phase 1, document causal pathways of how the interventions are intended to work (i.e. refine initial theory) and using participant observations following a semi-structured template reflect on the co-production processes in terms of clarity, inclusivity, transparency and effectiveness. In each country, the interventions will seek to improve two key components of responsiveness: The rationale is that these two components, when combined, will ultimately contribute to improving people’s experiences across the different domains of health systems responsiveness specified in our theoretical framework. Our focus on the processes of interaction is also driven by our intention to enact systemic change rather than target specific individual domains in a discreet manner. The overall design of the interventions is shown in Table 4. During the intervention co-production meetings we will fine-tune this general design (i.e. finalise themes, refine facilitation guidance and produce required materials), to be informed by better understanding of people’s initial expectations of responsive health systems which inform their interactions with their health systems from Phase 1. In fine-tuning the interventions, we will consolidate, adapt and extend our work in Health Workers for Change (HWFC) workshops [58, 64], Continuous Quality Improvement (CQI) [65, 66], patient feedback systems [61, 67] and acceptability of maternal healthcare by vulnerable groups [39, 40]. Relevant published and unpublished results will be presented during intervention co-production meetings as a possible ‘menu’ of interventions for considerations by the key stakeholders. To improve internal interactions, in each district we will conduct sets of six thematic workshops, following the HWFC approach, comprising frontline health workers and managers in the district hospital and PHC facilities. These are participatory, interactive 2-hour workshops, moderated by a skilled facilitator–usually a social scientist with experience in moderating group discussions. The workshop series stems from Paulo Freire’s work on transformational learning [68] and aims to help staff surface and critically reflect on their experiences, strengths and constraints in delivering responsive and quality healthcare. From these reflections, staff are then encouraged and supported, to develop relevant and feasible local solutions [69]. The six workshops are usually titled: “why I am a health worker”; “how do our clients see us”; “women’s status in society”; “unmet needs”; “overcoming obstacles at work” and “solutions”. The manual for the HWFC series was developed from initial work in South Africa and then refined following experiences in other African contexts. During co-production, we will align the themes with our initial theory of systems responsiveness specifically targeting the internal (and external) interactions and adapt facilitation guidance as appropriate. Experiences of using HFWC approach in Ghana and other countries, show them as an effective platform for institutionalising a process of Continuous Quality Improvement (CQI) in healthcare facilities [58, 64]. Evidence from Vietnam also shows that similar facilitated stakeholder groups can contribute towards improved health outcomes [70]. The CQI emphasises the process of systemic change underpinned by gradual optimisation and improvement and organisational learning; and that healthcare quality needs to be satisfied for both service users and providers [65, 66]. Both CQI and HWFC have been shown to improve communication within health facilities [58, 65] and thus focus on both the people and the systems sides of health systems responsiveness. To improve external interactions, to establish group consensus during these workshops, we will use a Nominal Group Technique (NGT)–a structured, multistep, group consensus building technique which comprises 6 steps: (a) individual writing of ideas; (b) group review and feedback; and (c) discussion, clarification and evaluation of each idea (d) ranking ideas in order of their significance; (e) discussion of the preliminary vote; and (f) final individual voting on significance of each idea. We will draw upon the NGT’s documented effects on consensus building, including in Ghana and in Vietnam [71, 72], to improve external interactions through empowering people to engage with their health systems. To raise people’s awareness of possible options, we will utilise our knowledge of improving patient feedback (as channels for people to convey their expectations from and reflections on, systems performance [61, 67]) and improving use of maternal healthcare [39, 40]. Evidence shows that effective interventions to improve feedback systems should target all three steps in the process: collection of feedback (e.g. raising patients’ awareness), analysis within facilities (e.g. improving staff skills), and acting on the information (e.g. integrating learning into service quality improvement) [67]. We will also draw upon the knowledge that use of available healthcare by vulnerable groups requires people’s cultural acceptance of these services [39]–and which can be improved through raising awareness about, and increasing confidence in, health workers [40]. The interventions are intentionally designed as low-cost activities to be embedded within the current structures and processes to ensure their sustainability, replication and scaling up. Although the HFWC workshops and NGT intend to improve internal and external interactions respectively, each is also likely to bridge the external-internal boundaries. We also anticipate that cumulatively these two intervention components will raise awareness and empower health workers and communities, and consequently will provide a sustainable platform for problem analysis and solution seeking. Such a platform will contribute to systemic improvements in responsiveness as a key attribute of health systems strengthening. In Phase 3 (months 19–42) we will implement and evaluate the interventions within local contexts. The interventions will be implemented for one full year and through existing systems’ structures and processes. Such duration should help embed the interventions within annual health planning and budgeting cycles and thus ensure their integration within routine practices and longer-term sustainability. Using realist evaluation [47, 73] we will test and refine our initial theory and intended intervention pathways from Phases 1 and 2. These will be compared to the actual performance of the interventions in improving internal and external interactions. We will relate results to any changes in key domains of responsiveness from our theoretical framework (e.g. dignity), within the complex context of vulnerability and assessed against the baseline. We will repeat our community survey within the same areas and asking the same questions. See Phase 1 section for proposed details of the survey design, questionnaire topics and format, and sample size/analysis. With the baseline and follow-up community surveys we can then explore whether respondents’ views on the relative importance of different attributes of responsiveness have changed subsequent to the intervention. This will be done using appropriate multiple linear regression models that adjust for the complex survey design, and also control for likely important confounding variables. We will also assess the interventions’ feasibility and acceptability by key actors and processes within and between Ghana and Vietnam, utilising the UK Medical Research Council’s framework for process evaluation of complex interventions [74]. In doing so, we will modify, extend and reuse the Phase 1 methods. Our intra- and cross-country comparative analyses will allow us to develop transferable best practices for other areas and LMICs which also experience similar socio-economic growth and face pressures to effectively address the needs of vulnerable groups. These best practices will be in a form of a theory-informed and empirically-grounded model of health systems responsiveness to neglected health needs of vulnerable groups, specifically addressing the study objectives 3 and 4. The model will guide a deeper understanding of how the contexts shape and trigger specific mechanisms through which health systems responsiveness works for different actors. We will also produce detailed practical guidance notes on further adaptations of this model to inform future policy and practice on improving health systems responsiveness in LMICs. Ethics approvals for this study were obtained from the University of Leeds School of Medicine Research Ethics Committee (ref: MREC19-051), Ghana Health Service Ethics Review Committee (ref GHS-ERC 012/03/20) and Hanoi University of Public Health Institutional Review Board (ref 020-149/DD-YTCC). All primary data will be collected after obtaining written informed consent (or thumb print for those who can’t write) and while preserving participants’ anonymity and confidentiality. The project will be carried out with full respect of current relevant legislation such as the General Data Protection Regulation. The methods development, data collection and analysis will consider: The project will be implemented according to established robust research governance practice standards at the University of Leeds for implementing collaborative projects. This includes ensuring: regular communication between the partners and engagement with policymakers and practitioners; quality assurance through regular peer-review both within and between the teams; appropriate mentoring and coaching support to early career researchers; and equal opportunities as part of the Leeds University’s commitment to the Athena Swan equal opportunities initiative. We will embed the research into policy and practice working with facility, district, regional and national actors, and through extending our academic collaborations into South-South research and policy partnerships. Engagements of decision-makers will facilitate implementation and scaling-up of these and similar interventions within and across Ghana and Vietnam. We will communicate research findings through combinations of: There is a high interest from key policymakers in this topic, some of whom are the members of the project team. We will maintain equal research-policy partnerships [75] and will embed research into policy and practice to facilitate integrating interventions within district health systems and ensure their sustainability.

AI Digest

Study Justification:

– The study aims to improve health systems responsiveness to neglected health needs of vulnerable groups in Ghana and Vietnam.
– Socio-economic growth in these countries has increased demands for more responsive health systems.
– The study will contribute to improved health services and health outcomes in these countries.
– There is a lack of research on improving health systems responsiveness in low and middle-income countries (LMICs), particularly for neglected health needs of vulnerable groups.

Study Highlights:

– The study will use a realist mixed-methods theory-driven case study design.
– It will combine quantitative (household survey, secondary analysis of facility data) and qualitative (interviews, focus groups, observations) methods.
– The study will comprise three phases: understanding actors’ expectations, co-producing interventions, and implementing and evaluating the interventions.
– The interventions will target both internal (within the health systems) and external (between people and health systems) interactions.
– The study will generate an empirically-grounded and theoretically-informed model of complex relations between contexts, mechanisms, and outcomes.
– Decision-makers at different levels will be engaged throughout the study.

Study Recommendations:

– Improve health systems responsiveness to neglected health needs of vulnerable groups in Ghana and Vietnam.
– Develop an empirically-grounded and theoretically-informed model of complex relations between contexts, mechanisms, and outcomes.
– Provide transferable best practices for scalability and generalizability to other health areas and countries.
– Strengthen individual, organizational, and system level capacities.

Key Role Players:

– Actors involved in the study include policymakers, health service providers, facility managers, researchers, and community members.
– Policymakers at the national, regional, and district levels will play a crucial role in implementing and scaling up the interventions.
– Health service providers and facility managers will participate in co-producing the interventions and implementing them within their facilities.
– Researchers will lead the study and provide guidance throughout the process.
– Community members, particularly vulnerable groups, will be engaged in the study to ensure their needs and perspectives are considered.

Cost Items for Planning Recommendations:

– Budget items to consider include research personnel salaries, data collection and analysis costs, travel expenses for meetings and workshops, communication and dissemination activities, and capacity strengthening initiatives.
– Other potential cost items may include materials and resources for interventions, training and capacity building programs, and administrative support.
Please note that the above information is a summary of the study and its components. For more detailed information, please refer to the full publication in PLoS ONE, Volume 16, No. 1, January, Year 2021.

Strength of Evidence

The strength of evidence for this abstract is 7 out of 10.
The evidence in the abstract is based on a study protocol, which outlines the research design and methods. While the protocol provides a clear plan for the study, it does not present any findings or results. To improve the strength of the evidence, the study should be completed and the results should be analyzed and reported.

Abstract

Our overall health systems research question is: In what way can health systems become more responsive to neglected health needs of vulnerable groups within the contexts of lower-middle-income countries? This study has five objectives, shown in Table 1 alongside the corresponding research questions. Key study’s outcomes will be: (1) improved health systems responsiveness to neglected health needs of vulnerable groups in Ghana and Vietnam, and (2) an empirically-grounded and theoretically-informed model of complex relations between the contexts, mechanisms and outcomes of the interventions, along with transferable best practices for scalability (i.e. expansion within similar contexts) and generalisability (i.e. to different contexts, such as other health areas and countries) for future health systems strengthening. The most widely known framework for health systems responsiveness, developed by the WHO in 2000, comprises seven domains: dignity, autonomy, confidentiality, prompt attention, quality of amenities, access to support networks, and choice of service provider [1, 8, 24]. The WHO framework has been translated into a survey toolkit for self-assessments of patients’ use of healthcare [24–26]. More recent work on the topic stressed that interactions between the people and their health systems are central to understanding this concept [2], and improving responsiveness should therefore address both the ‘people’ and the ‘systems’ sides of such interactions [2, 27, 28]. Evidence also shows that interpretations of responsiveness can be context-sensitive (e.g. expectations of dignity reflect political, democratic and policy climate [5]), and vary across actors (e.g. patients and providers with different powers [7, 29]) and health facilities (e.g. public/private [5, 7]). Responsiveness, therefore, is arguably a socially-constructed, rather than an ‘absolute’ and ‘universally normative’ concept. Adaptations of the seven domains of responsiveness have been proposed for different health areas, such as HIV/AIDS or mental health [26, 30, 31]. Yet, we found no studies which sought to improve health systems responsiveness to health needs of vulnerable groups in LMICs, including to neglected maternal mental health needs. Furthermore, many theoretical and applied questions remain unanswered, such as the following. What does responsiveness mean to different actors on the ‘people’ and the ‘systems’ sides? How do these conceptualisations shape actors’ behaviours and practices? In what way improving responsiveness contributes to other health systems goals? In RESPONSE, we will bridge some of these knowledge gaps while also responding to calls for improved understanding of health systems responsiveness to the needs of diverse health systems actors in LMICs [2, 11, 27, 28]. We approach ‘responsiveness’ as a dynamic social action which is produced via relationships between different actors within contexts of particular socio-economic arrangements as they negotiate experiences of professional, citizen, consumer and patient rights and responsibilities. In our theoretical framework (Fig 2), health systems responsiveness is understood as comprising the socially-constructed processes of external and internal interactions. Experiences of these interactions determine the degree of health systems responsiveness across eight domains: dignity, autonomy, confidentiality, attention, access to networks, quality of amenities, choice of service provider and trust. People’s engagements with health systems (for example, to seek healthcare) and system’s responses to these engagements (for example, service delivery) are shaped by their initial expectations [2]. People’s initial expectations are influenced by their individual’s relations with their families and communities within the context of cultural and societal norms as well as their potential vulnerability. The system’s ability to be responsive is driven by the expectations of frontline service providers of responsive services, in the context of current structures, processes, priorities and targets set by policymakers and managers. Conceptually, health systems responsiveness involves two socially-constructed interactions: People’s interactions with their families and communities are conceptualised as a context which shapes their initial expectations and subsequent engagements with a health system, though these can also be interpreted as a possible third type of interactions. Improving health systems responsiveness should, therefore, target both the internal (within the health systems) and external (between the people and health systems) interactions and be cognisant of the wider context which shapes people’s initial expectations of, and their subsequent engagements with, their health systems. We will conduct the study in two lower-middle-income countries: Ghana and Vietnam. Our choice of these two countries is driven by three considerations. First, their commonalities and diversity provide excellent value for this research. Key similarities are: Data from • Global Burden of Disease Collaborative Network. GBD Study 2017 Socio-Demographic Index (SDI) 1950–2017. Seattle, United States: Institute for Health Metrics and Evaluation (IHME); 2018. • Fullman N, et al. Measuring performance on the Healthcare Access and Quality Index for 195 countries…: a systematic analysis from the GBD Study 2016. The Lancet 2018; 391(10136): 2236–71. • WHO. Global Health Observatory. http://apps.who.int/gho/portal/gho.jsp (accessed 9 May 2019). • WHO. Global Health Expenditure Database. http://apps.who.int/nha (accessed 9 May 2019). The two health systems also have differences. Vietnam’s publicly-dominated system has increasing market competition, but the Ghanaian system has large private not-for-profit sector and a more substantial share of external funding for health (13% compared with 2% in Vietnam) [33]. With regards to decentralisation, in Vietnam most power is consolidated at the province (regional) level whereas in Ghana districts have greater autonomy. While the antenatal care coverage and skilled birth attendance levels are relatively high (over 85%) in each country, maternal mortality in Ghana is higher i.e. 319/100,000 live births compared with 54/100,000 in Vietnam [34]. This may reflect problems with service quality and poorer people-system interactions leading to delays in seeking healthcare. In Ghana, there are dedicated staff for local mental healthcare (e.g. community psychiatric nurses), whereas provision of grassroots level mental healthcare in Vietnam is through mainstream primary health care workers. Our experience shows that in Vietnam, vulnerability often relates to ethnicity and income, but in Ghana it seems to be mostly location and income-related. The second reason which guided the choice of Ghana and Vietnam is that there is high interest from policymakers in making the health systems more responsive to health needs of the most vulnerable. Preliminary discussions with key decision-makers from the Ghana Health Service and Ministries of Health in each country held during the proposal development showed that all key policymakers are committed to improving health systems responsiveness. In each country, maternal health remains a priority [35, 36] with increasing attention to mental health and integrated and responsive services. Psychological well-being of mothers and new-borns is a part of Ghana’s 2014 National Reproductive Health Policy and Standards. In Vietnam, policymakers emphasise ensuring equity in access, integrating mental healthcare (for example, into community programmes [37]) and piloting models of support and rehabilitation for those with mental illnesses. Finally, we have chosen these two countries because we have strong and longstanding academic collaborations between the Universities of Leeds and Ghana [38], and Universities of Leeds and Melbourne with Hanoi University of Public Health [39, 40]. We will leverage and extend these into effective South-South collaborations, exchange and learning, as well as building links amongst policymakers and practitioners in Ghana and Vietnam. In each country, we have purposefully selected one region (in Ghana) or province (in Vietnam) with some of the largest inequities disproportionately affecting vulnerable groups. Within each region and province, we have further selected a rural and an urban district to allow comparisons between rural-urban contexts. In Ghana, we will work in Greater Accra Region located in the Coastal zone. It is 90% urban with highest maternal mortality of 336/100,000 live births as compared with the national average of 310/100,000 live births according to the 2017 Maternal Health Survey, growing squatter urban slums and some of the most deprived rural communities. In Vietnam, we will work in Bắc Giang, a mountainous Province 50km to the east of the capital Hanoi, with large vulnerable groups and 12% of the population comprising ethnic minorities. In each country, we have selected two district health systems as our case studies, based on consultations with policymakers and their demographic and health indicators (Table 3) and leadership’s commitment to and opportunities for change. We have selected a purely rural (Shai Osudoku and Yên Thế), a rural with urbanised periphery (Ningo Prampram) and urban (Hiệp Hoà) districts, to allow learning across rural-urban settings. Data from national health information systems Both districts in Ghana have a Demographic Surveillance System run by the Dodowa Health Research Centre, thus giving a useful link to an existing dataset. The Vietnam’s MOH has identified the Bắc Giang Province to pilot models of support and rehabilitation for those with mental illnesses (including pregnant women), which provides an excellent opportunity and timing for our results to inform on-going reforms. In each district, we will implement interventions in the district hospital, 2–4 public and private primary health care facilities and within respective communities. As we explain later in the paper, the interventions will aim to improve external interactions (i.e. between people and health systems) as well as internal interactions within health systems (i.e. between healthcare staff and managers). Simultaneously, in Ghana we will engage with Greater Accra Regional Health Directorate and Ghana Health Service, in Vietnam we will engage with Province Health Department, and national Ministry of Health. The project co-investigator Dr Ashinyo is Deputy Director in the Directorate of Clinical Care of the Ghana Health Service and therefore has direct links with national policymakers. In Vietnam, we will leverage project co-investigator Professor Bui’s strong research-policy links. This will ensure sustainability, replication and scaling up of the interventions. We will use a mixed-methods realist theory-driven case study design, utilising our expertise in realist evaluations [41–46] and established standards for reporting realist evaluations [43]. Health systems comprise heterogeneous interconnected actors (e.g. patients and providers) operating at multiple levels within a complex dynamic system. Ensuring systems responsiveness requires aligning multiple interpretations from actors with different powers and resources. A realist approach helps make sense of such complexity by identifying how the multiple components interact in non-linear ways [47, 48]. It recognises micro, meso and macro contexts (Cs) in triggering the mechanisms (Ms) to produce outcomes (Os) [47, 48], known as CMO configurations, to explore what works, in which circumstances, for whom and why [47], and therefore suits this study. Realist researchers develop, test and refine middle-range theories which show causal pathways of how interventions work. Such an approach is similar to studies guided by theories of change or even initial hypotheses. Our draft initial theory, to be further developed, tested and refined is: Context-sensitive interventions for better recognition of initial expectations of key actors, if co-produced by these actors to target internal and external interactions and implemented within favourable policy contexts, will improve health systems responsiveness to neglected health needs of vulnerable groups, ultimately contributing to better health outcomes for all. This 42-months study will comprise three Phases as shown in Fig 3 (methods are in italics) and set out in detail in the following three sub-sections. In phase 1 (first year) we will understand actors’ expectations of responsive health systems, identify key priorities for fine-tuning interventions, develop initial theory (using evidence from a realist synthesis) and generate a baseline of data (through primary data collection and analysis). This phase will particularly address the study’s objective 1 and will include two broad parts: We will rigorously synthesise knowledge on systems responsiveness in LMICs using realist synthesis, a “…systematic, theory-driven interpretative technique… to help make sense of heterogeneous evidence about complex interventions applied in diverse contexts” [51 p.2]. This review approach is well suited for explaining disparate data and conceptualisations across the academic disciplines [52] and unpacking specific pathways of how particular contexts may trigger (or interfere with) mechanisms to produce intended or unintended outcomes [53]. The realist synthesis will help understand how specific micro-meso-macro contexts shape certain pathways through which responsiveness works. While there is a substantial knowledge base on assessing health systems responsiveness using adaptations of the WHO survey toolkit, published literature on improving systems responsiveness is scarce. Therefore, in addressing key issues from Phase 1 and fine-tuning the interventions (in Phase 2), we will draw on broader relevant knowledge of health systems strengthening–for example, accountability [6, 54, 55], integration of mental and maternal services [20, 22, 23] and staff support [56–58]–and will relate these to our understanding of vulnerability [14–17], our understanding of responsiveness in our framework and our initial theory. Our realist synthesis will utilise a four-step process [59], which will run alongside other components of the wider RESPONSE study, and will comprise: A detailed protocol for the realist synthesis is available from the International Prospective Register of Systematic Reviews, PROSPERO registration CRD42020200353 (https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=200353). The aim of collecting and analysing primary data during Phase 1, will be to answer research questions 1a and 1b (see Table 1 earlier) through exploring: We will collect data using: (i) reviews of policy and facility documentation including analysis of facility records of service provision and use; (ii) in-depth interviews and focus group discussions with key actors from local communities and health systems and (iii) a community survey. Data will be analysed retroductively, meaning both inductively and deductively. We will draw upon established processes for data analysis such as thematic analysis of qualitative data, and regression models for analysis of quantitative data. We will begin with a comprehensive review of policy and facility documentation to deepen our understanding of policy, regulatory and systems environments and healthcare practices—relating all back to the conceptualisations of health systems responsiveness. We will qualitatively review two purposefully-identified types of documents: key national-level policies, plans and guidelines; and relevant local-level documents within health facilities, such as minutes of management meetings, clinical reviews, and staff management and performance appraisal records. We will adopt a semi-structured template to summarise insights on the underlying conceptualisations, values and ideas around responsiveness, and approaches to ensuring health systems responsiveness. We will also quantitatively assess patterns of provision and utilisation of maternal and mental health services. To do so, we will analyse facility records for the last 2–3 years disaggregated by key dimensions of intersectionality such as age, income and residence. Using the IDIs, we will understand what responsiveness means to different health systems actors including its importance, underlying principles, components, mechanisms and intended outcomes. We will also explore the actors’ framing of underlying fundamental issues (e.g. rights, agency) and practices (management, service provision, health-seeking), relating them to our continuously refined understanding of responsiveness. From our experience, 20–25 IDIs should sufficiently represent views of key actor groups in each district, with further 10–15 IDIs at the province and national levels each (total 60–80 IDIs per country). This may decrease if we reach data saturation earlier, i.e. when no major new themes will be emerging from subsequent IDIs. We will also conduct 4–6 FGDs with key actors in each country. These will explore their understanding and expectations of responsive health systems, their framing of underlying fundamental issues and will understand group norms and dynamics. The FGDs will be conducted at the community, facility and province levels (1–2 at each level). Each group will comprise 6–8 participants to maximise engagement, will comprise similar participants (in terms of age, staff category) and separate FGDs may be conducted to reduce gender-related bias. The participants for IDIs and FGDs will be identified through purposive sampling and will include: (a) patients and public across their intersectionality dimensions (such as different genders, incomes and social strata); (b) health facility staff including service providers and support staff; and (c) health policymakers and managers. An initial participant list will be drawn by month 3 and we will identify further ones through snowballing. All FGDs and IDIs will be guided by a semi-structured topic guide to explore causal pathways of responsiveness [42]. Questions will be adapted to specific individuals’ backgrounds and roles. All IDIs and FGDs will be conducted in local languages as appropriate, audio-recorded, transcribed and either translated verbatim to English for thematic analysis or analysed in local languages with relevant extracts to be translated for cross-country comparisons. We will conduct a baseline community survey to help us understand which attributes of responsive health systems community members value and expect most, and which drivers determine health-seeking behaviours of vulnerable groups. These attributes will be based on the WHO’s seven domains of health systems responsiveness: dignity, autonomy, confidentiality, prompt attention, quality of amenities, access to support networks, and choice of service provider [1, 8, 24]. We will explore how the values and expectations that respondents hold about these attributes, differ across key characteristics, such as users vs non-users of the health system, and across their different intersectionality dimensions, such as gender and socio-economic status. We will use insights from the preceding qualitative methods to guide the design of the survey questionnaire. We will measure how much relative importance respondents place on the different attributes of responsiveness, that is how much they value and expect each attribute, using Likert scales or discretely coded visual analogue scales. We will pilot test the questionnaire among a small number of purposively selected respondents to explore its acceptability and their understanding of a range of different scales, to allow us to select the most suitable scale. During the pilot we will also explore respondents’ understanding of the rest of the questionnaire, along with the feasibility and acceptability of the survey methodology to data collectors. We will also collect a range of key socio-demographic details from respondents on factors that are likely related to their access and use of the health system and their experiences of engaging with the health system, and which will allow us to categorise them in terms of key determinants of intersectionality like gender and socio-economic status. Depending on the sampling frame data that is available in each country, we will use a multi-stage clustered household survey sampling approach [63] to allow us to select a statistically representative population sample from the relevant communities around our intervention facilities. Sample size: To understand respondents’ views on the importance of the different attributes of responsiveness, we will treat each discrete point on our chosen responsiveness attribute “importance scale” as a binary outcome and estimate the percentage of respondents selecting that point on the given scale (accounting for the complex survey design). We estimate that for the survey in each country we will require 562 respondents (assuming a response rate of 95%) to estimate the percentage of respondents selecting each point on the scale (assuming the most conservative percentage of 50% when estimating the sample size for a binary outcome based on precision) with a margin of error of ± 6 percentage points (95% confidence intervals), which we judged to be a suitable balance between precision and resources, and assuming a moderate design effect of 2 given we have no existing data (the mean design effect in the Ghana Demographic and Health Survey 2014 was 1.5). We will aim to understand the relationships between the socio-economic factors and respondents’ views on the relative importance of the different attributes of responsiveness, such as differences between men and women. In doing so, we will use appropriate multiple linear regression models that treat the “importance scale” outcomes as continuous variables (and which adjust for any complex survey design features such as clustering, stratification and weighting). Based on this approach, the above sample size (562) would also allow us to detect differences between binary subgroups, such as men and women (assuming a maximum between-subgroup size ratio of ≤6:1), of 0.65 or greater points in their responses to any of the “importance scale” questions with 80% power (based on two-sided hypothesis testing at the 5% significance level, assuming t-distributed data, a response rate of 95%, a design effect of 2). The outcome of Phase 1 will be an initial theoretical model explaining how health systems responsiveness works. It will explain how different contexts shape and trigger the mechanisms through which health systems responsiveness is enacted (or not) by the different actors to produce the intended and unintended outcomes. In Phase 2 (months 13–18) we will co-produce the context-sensitive interventions to improve health systems responsiveness, addressing study objective 2. The co-production will be through 2–3 meetings in each district involving key actors (communities, service providers, facility managers, regional/province and national-level actors). These meetings themselves can also be seen as interventions, and will therefore involve elements of capacity strengthening and knowledge uptake. The meetings will be led by district (or regional) health leadership and facilitated by researchers who will present evidence from Phase 1, document causal pathways of how the interventions are intended to work (i.e. refine initial theory) and using participant observations following a semi-structured template reflect on the co-production processes in terms of clarity, inclusivity, transparency and effectiveness. In each country, the interventions will seek to improve two key components of responsiveness: The rationale is that these two components, when combined, will ultimately contribute to improving people’s experiences across the different domains of health systems responsiveness specified in our theoretical framework. Our focus on the processes of interaction is also driven by our intention to enact systemic change rather than target specific individual domains in a discreet manner. The overall design of the interventions is shown in Table 4. During the intervention co-production meetings we will fine-tune this general design (i.e. finalise themes, refine facilitation guidance and produce required materials), to be informed by better understanding of people’s initial expectations of responsive health systems which inform their interactions with their health systems from Phase 1. In fine-tuning the interventions, we will consolidate, adapt and extend our work in Health Workers for Change (HWFC) workshops [58, 64], Continuous Quality Improvement (CQI) [65, 66], patient feedback systems [61, 67] and acceptability of maternal healthcare by vulnerable groups [39, 40]. Relevant published and unpublished results will be presented during intervention co-production meetings as a possible ‘menu’ of interventions for considerations by the key stakeholders. To improve internal interactions, in each district we will conduct sets of six thematic workshops, following the HWFC approach, comprising frontline health workers and managers in the district hospital and PHC facilities. These are participatory, interactive 2-hour workshops, moderated by a skilled facilitator–usually a social scientist with experience in moderating group discussions. The workshop series stems from Paulo Freire’s work on transformational learning [68] and aims to help staff surface and critically reflect on their experiences, strengths and constraints in delivering responsive and quality healthcare. From these reflections, staff are then encouraged and supported, to develop relevant and feasible local solutions [69]. The six workshops are usually titled: “why I am a health worker”; “how do our clients see us”; “women’s status in society”; “unmet needs”; “overcoming obstacles at work” and “solutions”. The manual for the HWFC series was developed from initial work in South Africa and then refined following experiences in other African contexts. During co-production, we will align the themes with our initial theory of systems responsiveness specifically targeting the internal (and external) interactions and adapt facilitation guidance as appropriate. Experiences of using HFWC approach in Ghana and other countries, show them as an effective platform for institutionalising a process of Continuous Quality Improvement (CQI) in healthcare facilities [58, 64]. Evidence from Vietnam also shows that similar facilitated stakeholder groups can contribute towards improved health outcomes [70]. The CQI emphasises the process of systemic change underpinned by gradual optimisation and improvement and organisational learning; and that healthcare quality needs to be satisfied for both service users and providers [65, 66]. Both CQI and HWFC have been shown to improve communication within health facilities [58, 65] and thus focus on both the people and the systems sides of health systems responsiveness. To improve external interactions, to establish group consensus during these workshops, we will use a Nominal Group Technique (NGT)–a structured, multistep, group consensus building technique which comprises 6 steps: (a) individual writing of ideas; (b) group review and feedback; and (c) discussion, clarification and evaluation of each idea (d) ranking ideas in order of their significance; (e) discussion of the preliminary vote; and (f) final individual voting on significance of each idea. We will draw upon the NGT’s documented effects on consensus building, including in Ghana and in Vietnam [71, 72], to improve external interactions through empowering people to engage with their health systems. To raise people’s awareness of possible options, we will utilise our knowledge of improving patient feedback (as channels for people to convey their expectations from and reflections on, systems performance [61, 67]) and improving use of maternal healthcare [39, 40]. Evidence shows that effective interventions to improve feedback systems should target all three steps in the process: collection of feedback (e.g. raising patients’ awareness), analysis within facilities (e.g. improving staff skills), and acting on the information (e.g. integrating learning into service quality improvement) [67]. We will also draw upon the knowledge that use of available healthcare by vulnerable groups requires people’s cultural acceptance of these services [39]–and which can be improved through raising awareness about, and increasing confidence in, health workers [40]. The interventions are intentionally designed as low-cost activities to be embedded within the current structures and processes to ensure their sustainability, replication and scaling up. Although the HFWC workshops and NGT intend to improve internal and external interactions respectively, each is also likely to bridge the external-internal boundaries. We also anticipate that cumulatively these two intervention components will raise awareness and empower health workers and communities, and consequently will provide a sustainable platform for problem analysis and solution seeking. Such a platform will contribute to systemic improvements in responsiveness as a key attribute of health systems strengthening. In Phase 3 (months 19–42) we will implement and evaluate the interventions within local contexts. The interventions will be implemented for one full year and through existing systems’ structures and processes. Such duration should help embed the interventions within annual health planning and budgeting cycles and thus ensure their integration within routine practices and longer-term sustainability. Using realist evaluation [47, 73] we will test and refine our initial theory and intended intervention pathways from Phases 1 and 2. These will be compared to the actual performance of the interventions in improving internal and external interactions. We will relate results to any changes in key domains of responsiveness from our theoretical framework (e.g. dignity), within the complex context of vulnerability and assessed against the baseline. We will repeat our community survey within the same areas and asking the same questions. See Phase 1 section for proposed details of the survey design, questionnaire topics and format, and sample size/analysis. With the baseline and follow-up community surveys we can then explore whether respondents’ views on the relative importance of different attributes of responsiveness have changed subsequent to the intervention. This will be done using appropriate multiple linear regression models that adjust for the complex survey design, and also control for likely important confounding variables. We will also assess the interventions’ feasibility and acceptability by key actors and processes within and between Ghana and Vietnam, utilising the UK Medical Research Council’s framework for process evaluation of complex interventions [74]. In doing so, we will modify, extend and reuse the Phase 1 methods. Our intra- and cross-country comparative analyses will allow us to develop transferable best practices for other areas and LMICs which also experience similar socio-economic growth and face pressures to effectively address the needs of vulnerable groups. These best practices will be in a form of a theory-informed and empirically-grounded model of health systems responsiveness to neglected health needs of vulnerable groups, specifically addressing the study objectives 3 and 4. The model will guide a deeper understanding of how the contexts shape and trigger specific mechanisms through which health systems responsiveness works for different actors. We will also produce detailed practical guidance notes on further adaptations of this model to inform future policy and practice on improving health systems responsiveness in LMICs. Ethics approvals for this study were obtained from the University of Leeds School of Medicine Research Ethics Committee (ref: MREC19-051), Ghana Health Service Ethics Review Committee (ref GHS-ERC 012/03/20) and Hanoi University of Public Health Institutional Review Board (ref 020-149/DD-YTCC). All primary data will be collected after obtaining written informed consent (or thumb print for those who can’t write) and while preserving participants’ anonymity and confidentiality. The project will be carried out with full respect of current relevant legislation such as the General Data Protection Regulation. The methods development, data collection and analysis will consider: The project will be implemented according to established robust research governance practice standards at the University of Leeds for implementing collaborative projects. This includes ensuring: regular communication between the partners and engagement with policymakers and practitioners; quality assurance through regular peer-review both within and between the teams; appropriate mentoring and coaching support to early career researchers; and equal opportunities as part of the Leeds University’s commitment to the Athena Swan equal opportunities initiative. We will embed the research into policy and practice working with facility, district, regional and national actors, and through extending our academic collaborations into South-South research and policy partnerships. Engagements of decision-makers will facilitate implementation and scaling-up of these and similar interventions within and across Ghana and Vietnam. We will communicate research findings through combinations of: There is a high interest from key policymakers in this topic, some of whom are the members of the project team. We will maintain equal research-policy partnerships [75] and will embed research into policy and practice to facilitate integrating interventions within district health systems and ensure their sustainability.

Materials

N/A

Innovations

Based on the information provided, here are some potential innovations that could be used to improve access to maternal health:

1. Mobile Health (mHealth) Solutions: Develop and implement mobile applications or text messaging services to provide pregnant women with important health information, appointment reminders, and access to healthcare providers.

2. Telemedicine: Use telecommunication technology to provide remote consultations and monitoring for pregnant women in rural or underserved areas, allowing them to access healthcare services without having to travel long distances.

3. Community Health Workers: Train and deploy community health workers to provide education, support, and basic healthcare services to pregnant women in their own communities, bridging the gap between healthcare facilities and remote areas.

4. Transportation Solutions: Develop transportation programs or partnerships to ensure that pregnant women have access to reliable and affordable transportation to healthcare facilities for prenatal care, delivery, and postnatal care.

5. Financial Incentives: Implement financial incentives, such as conditional cash transfers or vouchers, to encourage pregnant women to seek and utilize maternal health services.

6. Maternal Health Clinics: Establish dedicated maternal health clinics or centers that provide comprehensive care for pregnant women, including prenatal care, delivery services, and postnatal care, all in one location.

7. Health Education Programs: Develop and implement targeted health education programs that focus on maternal health, including topics such as nutrition, breastfeeding, and safe delivery practices, to empower women with knowledge and promote healthy behaviors.

8. Public-Private Partnerships: Foster collaborations between public and private sectors to improve access to maternal health services, leveraging the resources and expertise of both sectors to expand service delivery and reach more women.

9. Task-Shifting: Train and empower non-physician healthcare providers, such as nurses or midwives, to take on additional responsibilities and tasks traditionally performed by doctors, increasing the availability of skilled healthcare providers for maternal health services.

10. Quality Improvement Initiatives: Implement quality improvement initiatives in healthcare facilities to ensure that maternal health services are delivered in a safe, effective, and patient-centered manner, improving the overall experience and outcomes for pregnant women.

These are just a few examples of innovations that could be considered to improve access to maternal health. The specific context and needs of the target population should be taken into account when selecting and implementing these innovations.

AI Innovations Description

The recommendation to improve access to maternal health is to develop context-sensitive interventions that target both internal and external interactions within health systems. These interventions should be co-produced with key actors, such as communities, service providers, and policymakers, and implemented within favorable policy contexts. The interventions should focus on improving the quality of amenities, access to support networks, choice of service provider, dignity, autonomy, confidentiality, prompt attention, and trust. By addressing these domains of health systems responsiveness, the interventions aim to improve people’s experiences and ultimately contribute to better health outcomes for vulnerable groups. The interventions should be low-cost, embedded within existing structures and processes, and implemented for a sufficient duration to ensure integration and sustainability. The effectiveness of the interventions should be evaluated using a realist evaluation approach, comparing the intended design to the actual performance and assessing changes in key domains of responsiveness. The findings from the evaluation can inform the development of transferable best practices for improving health systems responsiveness in other low- and middle-income countries.

AI Innovations Methodology

The study protocol described in the provided text aims to improve health systems responsiveness to neglected health needs of vulnerable groups in Ghana and Vietnam. The study will utilize a realist mixed-methods theory-driven case study design, combining quantitative and qualitative methods. The methodology includes three phases:

Phase 1: In this phase, the study will understand actors’ expectations of responsive health systems, identify key priorities for interventions, and develop an initial theory. This will be done through a realist synthesis of existing knowledge on health systems responsiveness in low- and middle-income countries (LMICs), as well as primary data collection through document review, interviews, focus groups, and a community survey.

Phase 2: In this phase, the study will co-produce context-sensitive interventions to improve health systems responsiveness. This will involve participatory workshops with key actors, including communities, service providers, and health system managers. The interventions will target both internal (within the health system) and external (between people and health systems) interactions to improve responsiveness.

Phase 3: In this phase, the study will implement and evaluate the interventions. The interventions will be implemented for one year and evaluated using realist evaluation methods. The study will compare the intended design of the interventions to their actual performance in improving internal and external interactions. The study will also conduct a follow-up community survey to assess changes in respondents’ views on the importance of different attributes of responsiveness.

The study aims to achieve two key outcomes: improved health systems responsiveness to neglected health needs of vulnerable groups in Ghana and Vietnam, and the development of a model of complex relations between contexts, mechanisms, and outcomes of the interventions. The study will also provide transferable best practices for scalability and generalizability to other health areas and countries.

The methodology described in the study protocol utilizes a realist approach, which focuses on understanding how interventions work in specific contexts and under what conditions. This approach allows for a deeper understanding of the complex interactions between different actors within health systems and how these interactions contribute to health systems responsiveness. The study will engage with key decision-makers throughout the research process to ensure the integration of findings into policy and practice.

Authors & Co-Authors

Statistics:

Citations: 4

Authors: 17

Identifiers:

DOI: 10.1371/journal.pone.0245755

Research Areas:

Community Interventions, Disability, Disparities, Health System and Policy, Infectious Diseases, Maternal Access, Maternal and Child Health, Mental Health, Quality of Care, Sexual and Reproductive Health, Social Determinants

Study Countries:

Ghana, Multi-Countries, South Africa

Study Design:

Case Study, Cohort Study, Cross Sectional Study, Grounded Theory, Phenomenological Study, randomised-control-trial

Study Approach:

Mixed-methods, Qualitative, Quantitative, Systematic Review

Participants Gender:

Male & Female