Background Quality improvement intervention (QI) was implemented from 2018 to 2021 in health facilities of developing regional states of Ethiopia. The main objective of this study was to examine the impact of QI interventions on facility readiness, service availability, quality and usage of health services in these regions.
Methods We used district health information system data of 56 health facilities (HFs). We also used baseline and endline QI monitoring data from 28 HFs. Data were summarised using descriptive statistics and various tests. Regression analysis was employed to examine the impact of QI interventions on various outcomes.
Result The QI intervention improved readiness of HFs, service availability and quality of maternal and child health service delivery. The mean availability of basic amenities increased from 1.89 to 2.89; HF cleanliness score increased from 4.43 to 5.96; family planning method availability increased from 4 to 5.75; score for emergency drugs at labour ward increased from 5.32 to 7.00; and the mean score for basic emergency obstetric and newborn care service availability increased from 5.68 to 6.75; intrauterine contraceptive devices removal service increased from 39.3% to 82.1%; and partograph use increased from 53.6% to 92.9%. HFs that use partograph for labour management increased by 39.3%. The QI intervention increased the quality of antenatal care by 29.3%, correct partograph use by 51.7% and correct active third-stage labour management, a 19.6% improvement from the baseline. The interventions also increased the service uptake of maternal health services, but not significantly associated with improvement in contraceptive service uptake.
Conclusion The integrated QI interventions in HFs could have an impact on facility readiness for service delivery, service accessibility and quality of service delivery. The effectiveness of the QI intervention should be evaluated using robust methods, and efforts to enhance contraceptive services through a QI approach requires further study.
- quality improvement
- maternal health services
- continuous quality improvement
- healthcare quality improvement
Data availability statement
Data are available upon reasonable request. Data will be available upon reasonable request from Yared.Abera@amref.org.
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- quality improvement
- maternal health services
- continuous quality improvement
- healthcare quality improvement
The WHO member states endorsed universal health coverage (UHC) in 2005, aiming to ensure that all people obtain the health services they need with the required quality.1 2 The Sustainable Development Goals have aspired to health-related targets for mothers, newborns and children under UHC by 2030.3 The WHO envisioned that ‘every pregnant woman and newborn will receive quality care throughout pregnancy, childbirth, and the postnatal period’ under the umbrella of UHC. Good quality of care includes provision of effective, efficient, safe care that is accessible, acceptable, patient-centred and equitable4 5 which is often compromised in low-income and middle-income countries. Quality improvement (QI) strategies attempt to close this gap and to strengthening health systems delivery.6–8
QI approaches are being developed to improve the delivery of effective health interventions through long-term, collaborative and cost-effective methods.9–11 Evidence shows that QI interventions have demonstrated success in improving maternal and child health outcomes in low-income countries.12–16 In Ghana, for example, a systems-integrated continuous QI intervention deployed through learning collaborative and QI teams improved skilled delivery, antenatal care (ANC) coverage and reduced under-5 mortality.12 16 A QI intervention deployed in a similar approach in Tanzania, Uganda and Rwanda was also associated with improvements in health outcomes.13 15 In Ethiopia, a prior study demonstrated that QI health systems intervention has improved syphilis testing and health worker adherence to safe childbirth practices.14
Nevertheless, Ethiopia’s commitment to achieving UHC through primary healthcare, expansions of infrastructure and health workforce development has been confronted with delivery of poor quality of care.17 18 Although the country has observed an increase in ANC coverage from 27% in 2000 to 74% in 2019, skilled birth attendance from 5% in 2000 to 50% in 2019, and family planning services from 6.3% in 2000 to 40.5% in 2019, disparities were observed within and between regions.19–21 Whereas much improvement has been observed in major highland regions, the developing regional states (DRS) in Ethiopia—Afar, Benishangul-Gumuz, Gambella and Somali—are lagging. For instance, the under-5 mortality rate in the DRS ranges from 88 per 1000 live births in Gambella to 125 in Afar, compared with the national average of 67 per 1000 live births.19 20 The total fertility rate is highest for women in Somalia (7.2) and Afar (5.5), with 4.6 being the national average. Institutional delivery rates range between 12% (Somali) and 37% (Benishangul-Gumuz) compared with the national average of 66%.19 20
Health system QI is critical to improving the delivery and quality of healthcare.5 10 WHO recommends continuous QI activities to improve maternal and child health outcomes.10 22 As such, the Government of Ethiopia has developed a QI strategy to improve Reproductive, Maternal, Newborn and Child Health (RMNCH) outcomes.23 In line with the government to help the backdrops, since 2018, the USAID Transform: Health in Developing Regions (USAID Transform HDR), in collaboration with Amref Health Africa and subpartners IntraHealth International, Project HOPE and General Electric, has been implementing QI interventions to improve access and demand, strengthening health systems and strategic information for evidence-based decision-making and programme learning on maternal and child health services. The aim of this study is to assess how this QI intervention by USAID Transform HDR (T-HDR) has improved the health facilities readiness, service availability and quality, service delivery and service usage pattern.
Study context and aims of the project
Ethiopia is administratively divided into federal regional states and two city administrations. All the regions are not equally developed as measured by indicators of development, and equity of health service delivery is also not yet attained. Hence, the government has given a special focus to less developed regions and for selected geographical areas of the better developed which are lagging. Those regions that require special attention are grouped together under the name ‘developing regional states (DRS)’.24
The T-HDR project was implemented in 30 health facilities, 22 health centres (health facilities at primary level which provide promotive, preventive, curative and rehabilitative outpatient care including basic laboratory and pharmacy services with the capacity of 10 beds for emergency and delivery services)25 and 8 hospitals (health facilities at secondary and tertiary level that requires diagnostic and imaging facilities and therapeutic interventions with a minimum capacity of 50 beds and at least shall provide specialty care).26 The 30 health facilities are distributed across 23 woredas in the 13 zones of DRS of Ethiopia: Afar, Somali, Benishangul-Gumuz and Gambella. In those regions close to 10 million populations are currently living: Afar, 1.9 million; Somali, 6.2 million; Benishangul-Gumuz, 1.16 million; and Gambella, 0.47 million population.27
The livelihood of Afar and Somali communities are mainly dependent on pastoralism, whereas communities living in Gambella and Benishangul-Gumuz mainly rely on agriculture. In DRS the number of health facilities, access to health facilities, readiness of health facilities to provide services is generally low as compared other regions.21 28 Thus, the T-HDR designed an intervention project with the goal of reducing maternal and under 5 morbidity and mortality with the strategic objectives of increased, access, demand and usage of quality high-impact maternal and child health services, strengthened health systems and improved strategic information for evidence-based decision-making and programme learning in Afar, Benishangul-Gumuz, Gambella and Somali regions by 2021.
The quality improvement intervention approaches
The T-HDR project used a plan, do, study and act (PDSA cycle) as a framework to design evidence-based intervention. The T-HDR used independent but interdependent continuous planning, implementation, evaluation and handover to local organisations. T-HDR, to attain its objectives in QI, has been working closely with the Ethiopian Ministry of Health (MoH) and the four Regional Health Bureaus (RHB). The activity followed the following major phases (figure 1).
In 2018, the T-HDR project conducted a situation analysis and assessed performance and quality data from health facilities in the four developing regional states of Ethiopia. The main objective of this phase was to determine the baseline situation of health facilities, including their capacity to provide quality maternal and child health services and provide inputs to guide project planning, monitoring and evaluation, and to use the results of the baseline assessment to tailor the intervention to the facility-specific contexts. The following are the main activities carried out during the planning phase of the QI intervention.
Set objectives and logic framework (see: online supplemental file 2, Annex 03).
Design intervention plan (see: online supplemental file 2, Annex 03).
Based on the planning document the following activities were implemented for the selected health facilities of the DRS. For more details of project activities (see: online supplemental file 2, Annex 03).
Provision of medical equipment and supplies: based on the assessment the T-HDR provided essential equipment and supplies to the selected health facilities.
Capacity building training on.
QI and specific thematic areas of RMNCH services using the MoH guideline and recommended standards.
Communication skills to improve communication among service providers, between facilities and woreda health offices.
Problem-solving and team working to improve collective work effort.
A QI team was established and trained on the QI at the health facilities.
QI coaching, mentoring and supportive supervision: to strengthen the capacity of health facilities QI implementation and provision of quality of care.
Reward for better performing health facilities annually: to motivate and influence leadership to make decisions on quality-of-service improvement.
Collaborative learning and experience sharing: to strengthen learning and exchange of lessons and promising practices among zonal, regional and national level.
Performance assessment and monitoring
Dashboard and audit tool for each of the selected health facilities developed to monitor the implementation of the project during the implementation period (see: online supplemental file 1). Moreover, quarterly review meetings, baseline, midline and endline assessment and root cause analysis were conducted to identify causes for low performance, maternal and child health services uptake and client satisfaction.29–31
Handover and sustainability
The established QI team at each health facility with the T-HDR had been making continuous changes to customise the local needs, and redesign interventions based on the findings of midline and quarterly review meetings. At the end of the project the T-HDR provided recommendations and lessons learnt to the woreda health offices, regional health bureau and the health facility. The handover of the project with its lessons and recommendations was conducted officially to the governing body of the health facilities. The closeout sessions conducted at regional and national level relevant stakeholders including regional health bureau heads, state minister delegates and other relevant stakeholders participated in the official event organised to handover related to the project.31–34
Study design and period for the current study
Baseline and endline programme monitoring data from the T-HDR health facility QI project was used to determine the effect of intervention. Selected outcomes (ANC-1, ANC-4, skilled birth attendant and contraceptive prevalence rate) across intervention and non-interventions health facilities were compared. The baseline data was collected from June to December in 2018, and the endline data was collected from May to July in 2021.
The T-HDR project used purposive sampling technique to select 30 intervention health facilities from 23 woredas in the 4 developing regions. The selection of facilities for QI intervention was guided by availability of health workers in the facility, and recommendation of regional health bureau. We have included 21 health facilities in 21 woredas and 7 hospitals as QI intervention facilities for this assessment. From each of the selected health facilities, we randomly selected 10 ANC and 10 delivery charts using lists of chart numbers as a sampling frame, resulting in a total of 420 medical charts. The non-intervention facilities were randomly selected from the lists of the facilities in the same zones where intervention facilities were selected in the respective regions. Random number generator used to select the required number of charts and health facilities.
Data sources and variable definitions
There are two types of data sources: the T-HDR project monitoring data and the service usage data obtained from district health information system (DHIS). The programme monitoring data captures all necessary information of intervention facilities at baseline and endline. It contains information on the availability of specific items of medical equipment and supplies, facility infrastructure and amenities such as toilet, electric and water and cleanliness of service delivery environment.
Moreover, the service availability, provision and components of the services at baseline and at the end of the intervention were captured. The T-HDR programme collected monitoring data using: (1) medical chart review, (2) health worker interviews and (3) observation using a semi-structured questionnaire. The service usage data of intervention and non-intervention facilities were extracted from the national DHIS. The following (table 1) are reported variables which are measured in baseline and endline in the same health facility. The constructs of each composite variable are coded as ‘1’ and ‘0’ and added up to create a composite variable (table 1).
Data management and analysis
Both the programme monitoring and service usage data were extracted in Excel formats. Variable selection, and cleaning of the data were conducted using Excel. The variables both at baseline and endline have similar name, with exception of prefix added to baseline (b_) and endline (f_). Then we merged the two Excel data sets after taking care of the variable naming. The service delivery data from QI intervention and non-intervention facilities were extracted using Excel from national DHIS databases. Then the Excel data sets were exported to Stata V.16.1 for further cleaning and analysis.
Data were organised and summarised using descriptive statistics. To compare baseline and endline results among the QI health facilities, bar graphs, proportion and paired t-test were used as appropriate. While displaying mean scores or proportions, we reported 95% CI around the estimates. Moreover, we used line graph to show the trend of service usage across QI and non-QI health facilities. Linear regression was fitted to assess the impact of the QI intervention among the QI health facilities compared with the non-QI health facilities. During regression analysis we tested interaction between month and QI variable (coded as QI facility and non-QI facility). If the interaction was significant, we reported the regression result separately for the QI group and non-QI group with the 95% CI.
T-HDR had an agreement with federal MoH and concerned regional government offices for implementing the intervention programme. Such programmes are not required to go through an ethical approval process in Ethiopia if they are reviewed and endorsed by the MoH. Permission letters from all concerned authorities (MoH and RHB) were received prior to visit of health facilities.
The QI interventions were performed in 28 health facilities in 13 zones distributed across 4 regions. Out of the 28 facilities 7 are hospitals. To compare the selected equal number of non-QI facilities in each category (table 2).
The following sections describe the effect of the QI interventions by comparing the results before and after interventions within the QI health facilities and comparing the service usage data between the QI and non-QI health facilities.
Impact of QI intervention on facilities readiness
Although there is no statistically significant difference, QI intervention increased the facilities readiness for service provision as compared with the baseline. The mean availability of basic amenities increased from 1.89 to 2.89 out of 3, the mean cleanliness of health facilities increased from 4.43 to 5.96 out of 7 (table 3).
Impact of QI intervention on service availability
In relative terms the QI intervention increased the availability of FP (family planning) methods, maternal service usage and integrated mobile outreach services among QI health facilities during the implementation period as compared with the baseline. The mean availability of FP methods increased from 4 to 5.75 out of 7, availability of emergency drugs at the labour ward increased from 5.32 to 7 out of 8 (table 4).
There is a significant change in service availability among health facilities included in the QI programme notably IUCD (intrauterine contraceptive devices) removal service, partograph use and availing PPFP (postpartum family planning) in delivery room. IUCD removal service increased from 39.3% health facilities to 82.1% of health facilities, partograph use increased from 53.6% health facilities to 92.9% health facilities (figure 2).
Impact of QI intervention on facilities service delivery
The QI intervention programme increased the quality of RMNCH service delivery among the QI health facilities. The quality of ANC service, which is getting all essential ANC components of care, increased from 28.1% to 57.4%. Correct use of partograph, which is measuring and documenting essential indicators, increased from 33.4% to 85.1% of health facilities among QI sites (figure 3).
The following table depicts the effect of the QI intervention on the QI of quality of RMNCH service delivery. The results at the end of the QI intervention are significantly different from the baseline data. The highest effect is observed in the use of partograph for labour management, with 51.7% improvement from the baseline (table 5).
Impact of QI intervention on service usage pattern
Results from descriptive analysis
In general, the QI health facilities were better in terms of performance as compared with the non-QI health facilities during the implementation periods. The performance gap between QI and non-QI health institutions widened over time. The performance of QI health facilities has a positive pattern on ANC-1, ANC-4, SBA (skilled birth attendant) and PNC (postnatal care) during the implementation period of the interventions (figure 4).
Even though the QI interventions have a positive pattern on ANC, SBA and PNC service uptake, it did not have a significant effect on the service uptake of contraceptive service. The pattern of new and repeat contraceptive acceptors did not vary over time despite the QI intervention; however, the QI facilities were better performers initially (figure 5).
Results from regression analysis
The QI interventions have a positive impact on increasing the service uptake of ANC, SBA and PNC within 7 days during the intervention periods among QI health facilities as compared with the non-QI facilities. The average rate of ANC-1 service usage in QI health facilities increased on average by 0.47% per month from 2018 to 2021, but the average rate in non-QI health facilities decreased on average by 0.24% per month. ANC-4 increases with a mean of 0.35% among QI health facilities, whereas it decreases with a mean of 0.15% among non-QI health facilities. The QI intervention at QI health facilities contributed to 55% ANC-1 (from 53.6% to 97.7%), 59% ANC-4 (from 25.3% to 42.9%), 54% SBA (from 32.5% to 60%), 50% PNC (from 31.3% to 62.6%), 54% new contraceptive acceptors (from 21.4% to 38.1%) and 39% repeat contraceptive acceptors (from 16.9% to 43.5%) from baseline in January 2018 to June 2021. The SBA and PNC within 7 days have a positive pattern in both QI and non-QI facilities, but the rate of difference is higher among QI facilities. The highest impact of QI intervention is observed in PNC service usage (table 6).
The effects of QI interventions on contraceptive services uptake are not statistically significant. The only observed difference between QI and non-QI facilities is the baseline difference. The baseline difference between the QI and non-QI health facilities is statistically significant (table 7).
The T-HDR project implemented a comprehensive QI intervention between 2018 and 2021 in selected public health facilities in four of Ethiopia developing regions to improve service delivery and coverage. The QI intervention was found to be effective in improving the readiness of health facilities to provide services; increasing the availability of RMNCH services, particularly the availability of FP methods, the use of maternal services and integrated mobile outreach services; and improving the quality of RMNCH service delivery among QI compared with the baseline. In addition, the impact of these changes at QI health facilities increased service usage of ANC, SBA and PNC compared with users at non-QI facilities. However, there was no significant effect on the uptake of contraceptive services.
The QI intervention improved the readiness of health facilities to provide services by increasing the mean availability of basic amenities from 1.89 to 2.89 out of 3, the mean cleanliness of health facilities from 4.43 to 5.96 out of 7 and the availability of newborn commodities from 5.21 to 6.75. The mean availability of FP methods increased from 4 to 5.75 out of 7, availability of emergency drugs during labour and delivery increased from 5.32 to 7 out of 8 and partograph use increased from 53.6% to 92.9%. Similar QI studies in India and Ethiopia revealed an increase in the availability of essential medicines and supplies for maternal and newborn care following QI interventions.14 35 The results of this study, which are consistent with other studies, suggest that improving facility readiness is critical for service delivery and increasing service uptake.21 28 Health facilities in developing regional states have low service availability because of different barriers like inadequate equipment or poor infrastructure.21 28 36 37 Addressing these barriers is necessary to increase service availability. Thus, stakeholders need to address these barriers to improve the service availability of maternal and newborn healthcare and potentially reduce maternal and newborn morbidity and mortality.
The QI intervention programme also increased the quality of RMNCH service delivery. The quality of ANC service, which includes all essential components of ANC care, increased by 29.3%, the correct use of the partograph increased by 51.7% and correct active third stage management of labour increased by 19.6% from baseline. These results tell us that there is a significant change in the quality-of-service delivery. Those improvements are mainly because of the QI coaching, mentoring and supportive supervision to strengthen the capacity of health facilities. Other studies in Ethiopia38 and abroad16 35 39 have shown that QI interventions are associated with improved quality of maternal health services. The findings suggest that QI interventions through continued follow-up, mentoring and learning have a positive impact on quality of care that will contribute to reducing preventable morbidities and mortalities in resource-limited settings.
Addressing service availability or facility readiness improves service quality and coverage. but there is no significant effect on usage of contraceptive services. The QI health facilities showed an increase of 0.47% for ANC-1, 0.35% for ANC-4, 0.53% for SBA and 0.45% for PNC every month from 2018 to 2021, while the non-QI health facilities showed a decreasing rate of these services. However, there is no significant effect on usage of contraceptive services among QI and non-QI health facilities. Various studies evaluating QI interventions showed that such types of interventions helped the health system to improve service uptake.40–42 These studies showed that comprehensive interventions that focus on multiple service delivery problems have a significant impact on increasing service coverage. This suggests that the health sector transformation plan in quality should focus on improving facility readiness for service delivery, availability and care to improve service uptake in facilities in four developing regions of Ethiopia. The effect of the QI intervention on contraceptive usage is not significant due to the strong cultural and religious influence in Afar and Somali regions.
The response of the health facilities to the QI improvement programme varies. The main reason for the variability is that the participating health facilities are poorly equipped with relevant equipment and supplies. Some other facilities faced challenges such as high turnover of trained health workers, security issues, hot weather conditions in some areas like Afar and administrative challenges. The wide disparities in equity and quality of healthcare between and within regions can be addressed by focusing on improving the readiness of health facilities and availability of RMNCH services. Thus, the quality and equity pillars of the Health Sector Transformation Plan II24 could be realised through adopting evidence based QI interventions.
Despite many strengths of the study, there were inherent limitations. The health facilities included for the QI programme were relatively better performing than the non-QI health facilities. Although the QI facilities are better, we tried to see the impact of the intervention using regression. Differences in leadership, human resources related issues and infrastructure differences between districts and facilities may also have affected the processes and outcomes. The study did not include the perceptions and opinions of clients, QI was not separately studied for hospitals and health centres. The study did not show the direct impact of the project in reducing maternal or child mortalities, but it is known that increasing access, availability and quality of health services will contribute to reduced mortality. The T-HDR used the PDSA cycle during design and implementation as a framework for implementation, however this paper used data generated from the project implementation. The methods and contents of the QI intervention can be expandable and applicable in other similar settings.
Conclusion and recommendations
In the developing regional states of Ethiopia, the QI intervention increased health facility readiness to provide services, service accessibility and service quality from the baseline. Compared with non-QI facilities, these positive improvements had a positive impact on service uptake for ANC, SBA and PNC in QI health facilities, but did not have a statistically significant impact on the service uptake of contraceptive services. The results suggest that integrated QI interventions at health facilities could have an impact health facility could have an impact on how society uses services. The intervention programmes can be scaled up for use in facilities with similar settings. However, the effectiveness of the QI intervention should be evaluated in the low performing health facilities, and efforts to improve contraceptive services require other culturally appropriate interventions.
Data availability statement
Data are available upon reasonable request. Data will be available upon reasonable request from Yared.Abera@amref.org.
Patient consent for publication
We would like to acknowledge AMREF Health Africa through Transform HDR project, for allowing us to use their resources and also providing necessary support that was necessary to generate the data and write the manuscript. MERQ Consultancy coordinated and supervised the write-up of the manuscript. We would have successfully collected the data if we did not receive support from Afar and Somali Regional Health Bureau, Dubti, Harshin, and Awbare Health Bureau. Our deepest gratitude goes to community workers and the interview participants for their time and participation.
Contributors TLD and TAA drafted the whole manuscript equally. GM, AY, Derebe Tadesse, YA, MDW, Daniel Tadesse, ST and MJG reviewed and edited the manuscript. GM and Derebe Tadesse are guarnter.
Funding The authors have not declared a specific grant for this research from any funding agency in the public, commercial or not-for-profit sectors.
Competing interests None declared.
Patient and public involvement Patients and/or the public were not involved in the design, or conduct, or reporting, or dissemination plans of this research.
Provenance and peer review Not commissioned; externally peer reviewed.
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