A critique of the Uganda district league table using a normative health system performance assessment framework

Exploring variations in the implementation of a health system level policy intervention to improve maternal and child health outcomes in resource limited settings: A qualitative multiple case study from Uganda

BACKGROUND

Despite growing literature, few studies have explored the implementation of policy interventions to reduce maternal and perinatal mortality in low- and middle-income countries (LMICs). Even fewer studies explicitly articulate the theoretical approaches used to understand contextual influences on policy implementation. This under-use of theory may account for the limited understanding of the variations in implementation processes and outcomes. We share findings from a study exploring how a health system-level policy intervention was implemented to improve maternal and child health outcomes in a resource limited LMIC.

METHODS

Our qualitative multiple case study was informed by the Normalization Process Theory (NPT). It was conducted across eight districts and among ten health facilities in Uganda, with 48 purposively selected participants. These included health care workers located at each of the cases, policy makers from the Ministry of Health, and from agencies and professional associations. Data were collected using semi-structured, in-depth interviews to understand uptake and use of Uganda's maternal and perinatal death surveillance and response (MPDSR) policy and were inductively and deductively analyzed using NPT constructs and subconstructs.

RESULTS

We identified six broad themes that may explain the observed variations in the implementation of the MPDSR policy. These include: 1) perception of the implementation of the policy, 2) leadership of the implementation process, 3) structural arrangements and coordination, 4) extent of management support and adequacy of resources, 5) variations in appraisal and reconfiguration efforts and 6) variations in barriers to implementation of the policy.

CONCLUSION AND RECOMMENDATIONS

The variations in sense making and relational efforts, especially perceptions of the implementation process and leadership capacity, had ripple effects across operational and appraisal efforts. Adopting theoretically informed approaches to assessing the implementation of policy interventions is crucial, especially within resource limited settings.

Using normalisation process theory (NPT) to explore implementation of the maternal perinatal death surveillance and response (MPDSR) policy in Uganda: a reflection

BACKGROUND

The implementation of the maternal perinatal death surveillance and response (MPDSR) policy is among the envisaged strategies to reduce the high global burden of maternal and perinatal mortality and morbidity. However, implementation of this policy across various contexts is inconsistent. Theoretically informed approaches to process evaluation can support assessment the implementation of policy interventions such as MPDSR, particularly in understanding what the actors involved actually do. In this article, we reflect on how the normalisation process theory (NPT) was used to explore implementation of the MPDSR policy in Uganda. NPT is a sociological theory concerned with the social organisation of the work (implementation) of making practices routine elements of everyday life (embedding) and of sustaining embedded practices in their social contexts (integration).

METHODS

This qualitative multiple case study conducted across eight districts in Uganda and among 10 health facilities (cases) representing four out of the seven levels of the Uganda health care system. NPT was utilised in several ways including informing the study design, structuring the data collection tools (semi-structured interview guides), providing an organising framework for analysis, interpreting and reporting of study findings as well as making recommendations. Study participants were purposely selected to reflect the range of actors involved in the policy implementation process. This included direct care providers located at each of the cases, the Ministry of Health and from agencies and professional associations. Data were collected using semi-structured, in-depth interviews and were inductively and deductively analysed using NPT constructs and subconstructs.

RESULTS AND CONCLUSION

NPT served useful for process evaluation, particularly in identifying factors that contribute to variations in policy implementation. Considering the NPT focus on the agency of people involved in implementation, additional efforts are required to understand how recipients of the policy intervention influence how the intervention becomes embedded within the various contexts.

Delineating natural catchment health districts with routinely collected health data from women's travel to give birth in Ghana

Background

Health service areas are essential for planning, policy and managing public health interventions. In this study, we delineate health service areas from routinely collected health data as a robust geographic basis for presenting access to maternal care indicators.

Methods

A zone design algorithm was adapted to delineate health service areas through a cross-sectional, ecological study design. Health sub-districts were merged into health service areas such that patient flows across boundaries were minimised. Delineated zones and existing administrative boundaries were used to provide estimates of access to maternal health services. We analysed secondary data comprising routinely collected health records from 32,921 women attending 27 hospitals to give birth, spatial demographic data, a service provision assessment on the quality of maternal healthcare and health sub-district boundaries from Eastern Region, Ghana.

Results

Clear patterns of cross border movement to give birth emerged from the analysis, but more women originated closer to the hospitals. After merging the 250 sub-districts in 33 districts, 11 health service areas were created. The minimum percent of internal flows of women giving birth within any health service area was 97.4%. Because the newly delineated boundaries are more “natural” and sensitive to observed flow patterns, when we calculated areal indicator estimates, they showed a marked improvement over the existing administrative boundaries, with the inclusion of a hospital in every health service area.

Conclusion

Health planning can be improved by using routine health data to delineate natural catchment health districts. In addition, data-driven geographic boundaries derived from public health events will improve areal health indicator estimates, planning and interventions.

Healthworker preparedness for COVID-19 management and implementation experiences: a mixed methods study in Uganda's refugee-hosting districts

Background

The negative impact of COVID-19 on population health outcomes raises critical questions on health system preparedness and resilience, especially in resource-limited settings. This study examined healthworker preparedness for COVID-19 management and implementation experiences in Uganda’s refugee-hosting districts.

Methods

A cross sectional, mixed-method descriptive study in 17 health facilities in 7 districts from 4 major regions. Total sample size was 485 including > 370 health care workers (HCWs). HCW knowledge, attitude and practices (KAP) was assessed by using a pre-validated questionnaire. The quantitative data was processed and analysed using SPSS 26, and statistical significance assumed at p < 0.05 for all statistical tests. Bloom's cutoff of 80% was used to determine threshold for sufficient knowledge level and practices with scores classified as high (80.0–100.0%), average (60.0–79.0%) and low (≤ 59.0%). HCW implementation experiences and key stakeholder opinions were further explored qualitatively using interviews which were audio-recorded, coded and thematically analysed.

Results

On average 71% of HCWs were knowledgeable on the various aspects of COVID-19, although there is a wide variation in knowledge. Awareness of symptoms ranked highest among 95% (p value < 0.0001) of HCWs while awareness of the criteria for intubation for COVID-19 patients ranked lowest with only 35% (p value < 0.0001). Variations were noted on falsehoods about COVID-19 causes, prevention and treatment across Central (p value < 0.0356) and West Nile (p value < 0.0161) regions. Protective practices include adequate ventilation, virtual meetings and HCW training. Deficient practices were around psychosocial and lifestyle support, remote working and contingency plans for HCW safety. The work environment has immensely changed with increased demands on the amount of work, skills and variation in nature of work. HCWs reported moderate control over their work environment but with a high level of support from supervisors (88%) and colleagues (93%).

Conclusions

HCWs preparedness is inadequate in some aspects. Implementation of healthcare interventions is constrained by the complexity of Uganda’s health system design, top-down approach of the national response to COVID-19 and longstanding health system bottlenecks. We recommend continuous information sharing on COVID-19, a design review with capacity strengthening at all health facility levels and investing in community-facing strategies.

Can routine health facility data be used to monitor subnational coverage of maternal, newborn and child health services in Uganda?

Background

Routine health facility data are a critical source of local monitoring of progress and performance at the subnational level. Uganda has been using district health statistics from facility data for many years. We aimed to systematically assess data quality and examine different methods to obtain plausible subnational estimates of coverage for maternal, newborn and child health interventions.

Methods

Annual data from the Uganda routine health facility information system 2015–2019 for all 135 districts were used, as well as national surveys for external comparison and the identification of near-universal coverage interventions. The quality of reported data on antenatal and delivery care and child immunization was assessed through completeness of facility reporting, presence of extreme outliers and internal data consistencies. Adjustments were made when necessary. The denominators for the coverage indicators were derived from population projections and health facility data on near-universal coverage interventions. The coverage results with different denominators were compared with the results from household surveys.

Results

Uganda’s completeness of reporting by facilities was near 100% and extreme outliers were rare. Inconsistencies in reported events, measured by annual fluctuations and between intervention consistency, were common and more among the 135 districts than the 15 subregions. The reported numbers of vaccinations were improbably high compared to the projected population of births or first antenatal visits – and especially so in 2015–2016. There were also inconsistencies between the population projections and the expected target population based on reported numbers of antenatal visits or immunizations. An alternative approach with denominators derived from facility data gave results that were more plausible and more consistent with survey results than based on population projections, although inconsistent results remained for substantive number of subregions and districts.

Conclusion

Our systematic assessment of the quality of routine reports of key events and denominators shows that computation of district health statistics is possible with transparent adjustments and methods, providing a general idea of levels and trends for most districts and subregions, but that improvements in data quality are essential to obtain more accurate monitoring.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12913-021-06554-6.

District Health Teams' Readiness to Institutionalize Integrated Community Case Management in the Uganda Local Health Systems: A Repeated Qualitative Study

District health teams failed to transition from partner-supported integrated community case management (iCCM) programs to locally-run and fully-institutionalized programs. Successful iCCM institutionalization requires local ownership with increased coordination among governmental and nongovernmental actors at the national and district levels.

Introduction:

Several countries have adopted integrated community case management (iCCM) as a strategy for improved health service delivery in areas with poor health facility coverage. Early implementation of iCCM is often run by nongovernmental organizations financed by donors through projects. Such projects risk failure to transition into programs run by the local health system upon project closure. Engagement of subnational health authorities such as district health teams (DHTs) is essential for a smooth transition.

Methods:

We used a repeated qualitative study design to assess the readiness of and progress made by DHTs in institutionalizing iCCM into the functions of locally decentralized health systems in 9 western Uganda districts. Readiness data were derived from structured group interviews with DHTs before iCCM policy adoption in 2010 and again in 2015. Progressive institutionalization achievements were assessed through key informant interviews with targeted DHT members and local government district planners in the same areas.

Findings:

In the readiness study, DHTs expressed commitment to institutionalize iCCM into the local health system through the development of district-specific iCCM activity work plans and budgets. The DHTs further suggested that they would implement district-led training, motivation, and supervision of community health workers; procurement of iCCM medicines and supplies; and advocacy activities for inclusion of iCCM indicators into the national health information systems. After iCCM policy adoption, follow-up study data findings showed that iCCM was largely not institutionalized into the local district health system functions. The poor institutionalization was attributed to lack of stewardship on how to transition from externally supported implementation to district-led programming, conflicting guidelines on community distribution of medicines, poor community-level accountability systems, and limited decision-making autonomy at the district level.

Conclusion:

Successful institutionalization of iCCM requires local ownership with increased coordination and cooperation among governmental and nongovernmental actors at both the national and district levels.

Generating statistics from health facility data: the state of routine health information systems in Eastern and Southern Africa

Health facility data are a critical source of local and continuous health statistics. Countries have introduced web-based information systems that facilitate data management, analysis, use and visualisation of health facility data. Working with teams of Ministry of Health and country public health institutions analysts from 14 countries in Eastern and Southern Africa, we explored data quality using national-level and subnational-level (mostly district) data for the period 2013-2017. The focus was on endline analysis where reported health facility and other data are compiled, assessed and adjusted for data quality, primarily to inform planning and assessments of progress and performance. The analyses showed that although completeness of reporting was generally high, there were persistent data quality issues that were common across the 14 countries, especially at the subnational level. These included the presence of extreme outliers, lack of consistency of the reported data over time and between indicators (such as vaccination and antenatal care), and challenges related to projected target populations, which are used as denominators in the computation of coverage statistics. Continuous efforts to improve recording and reporting of events by health facilities, systematic examination and reporting of data quality issues, feedback and communication mechanisms between programme managers, care providers and data officers, and transparent corrections and adjustments will be critical to improve the quality of health statistics generated from health facility data.