Drivers and Barriers to Improved Data Quality and Data-Use Practices: An Interpretative Qualitative Study in Addis Ababa, Ethiopia

Tilahun, Hibret Alemu; Abate, Biruk Beletew; Belay, Hiwot; Gebeyehu, Abebaw; Ahmed, Mohammed; Simanesew, Akiliu; Ayele, Wondimu; Mohammedsanni, Afrah; Knittel, Barbara; Wondarad, Yakob

doi:10.9745/ghsp-d-21-00689

Cited by 4 publications

(4 citation statements)

References 15 publications

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“…Studies have also shown good consistency of reporting on deliveries and livebirths comparing HMIS data and source documents, as was observed in the government facilities veri ed in this study (9,43). The observed data quality problems may also be attributed to factors such as high work load, lack of reporting tools, lack of training and supportive supervision that have been reported eleswhere (21,22,24,25,44).…”

Section: Discussionsupporting

confidence: 70%

“…From the ndings of this study, we recommend tailored support to be provided to private-for-pro t and lower-level (non-EmOC) facilities to report correctly and consistently the services provided and health outcomes. This could be done by linking routine data reviews with on-job mentoring in the different facilities and capacity building among other strategies (31,44). Also, given that majority of facilities were at lower-levels of the system and therefore submit their reports to the district o ces, strengthening the data transmission processes may also help to improve completeness of data.…”

Section: Recommendationsmentioning

confidence: 99%

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Quality of routine data related to facility-based maternal mortality measurement in Kampala City, Uganda

Birabwa,

Banke-Thomas,

Semaan

et al. 2023

Preprint

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Background Routine health facility data are an important source of health information. Regular quality assessments are necessary to improve the reliability of routine data for different purposes, including estimating facility-based maternal mortality. The objective of this study was to assess the quality of routine data on deliveries, livebirths and maternal deaths in Kampala City, Uganda. Methods We reviewed routine data reported by health facilities through the district health information system (DHIS2) from 2016 to 2021. This time period included an upgrade of the DHIS2 resulting in two datasets (2016–2019 and 2020–2021) that were managed separately. We analysed data for all facilities that reported at least one delivery in any of the six years, and for a subset of facilities designated to provide emergency obstetric care (EmOC). We used the World Health Organization data quality review framework to assess completeness and internal consistency of the three data elements, using 2019 and 2021 as reference years. Primary data was collected to verify the accuracy of reporting in four purposively selected EmOC facilities. Descriptive statistics, including frequencies and percentages, were computed using STATA (v14) and Microsoft Excel. Results We included 255 facilities from 2016–2019 and 247 from 2020–2021; of which 30% were EmOC facilities. The overall completeness of data for deliveries and livebirths ranged between 53% and 55%, and was < 2% for maternal deaths (98% of monthly values were zero). Among EmOC facilities, completeness was higher for deliveries and livebirths at 80%; and was < 6% for maternal deaths. For the whole sample, the prevalence of outliers for all three data elements was < 2%. Inconsistencies over time were mostly observed for maternal deaths, and underreporting of maternal deaths was noted in one of the EmOC facilities verified. Conclusion Routine data from facilities providing childbirth services in Kampala were generally suboptimal, but of acceptable quality in EmOC facilities. However, given likely underreporting of maternal deaths, further efforts to verify and count all maternal deaths in health facilities are essential to accurately estimate facility-based maternal mortality. There is still a need to improve facility reporting, especially in non-EmOC facilities.

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Section: Discussionsupporting

confidence: 70%

Section: Recommendationsmentioning

confidence: 99%

Quality of routine data related to facility-based maternal mortality measurement in Kampala City, Uganda

Birabwa,

Banke-Thomas,

Semaan

et al. 2023

Preprint

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“…The study also explored the poor skill and commitment from the leadership as potential barriers to initiating and implementing the HIS accountability framework, which aligns with different research in different parts of the country (23)(24)(25). So, it is recommended that they work on enhancing their skills and commitment by using different modalities like capacity-building, training, and experience-sharing(26).…”

Section: Discussionmentioning

confidence: 99%

The Practice and Barriers of Health Information System Accountability Framework in Northwest Ethiopia, 2023

Tilahun,

Endehabtu,

Minyihun

et al. 2024

Preprint

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Background The government of Ethiopia has designed different initiatives for the Health Information Systems (HIS), including an information revolution transformation agenda by 2015. Various interventions and working documents have also been developed and implemented targeting the different aspects of the HIS program. However, there is no nationally designed accountability framework to govern HIS activities. Besides, how health institutions follow and monitor HIS activities is unknown. Therefore, this study aimed to assess the practice and barriers of HIS accountability framework at the selected public health institutions. Method A descriptive qualitative study design was employed from June 05 to July 12, 2023. Purposively selected informants from public health institutions were recruited for key informant interviews. A prepared pilot-tested semi-structured interview guide was used. The conventional content approach was used to summarize and synthesize the information explored. Findings: The study revealed that the participants better understood the concept and advantages of the HIS accountability framework. The participants believed the HIS accountability framework would help to govern and manage behavioral-related HIS challenges. It was indicated that the framework will help to control the recurrence of HIS errors, enhance the commitment and adherence of health professionals, and improve data handover practice, data security and privacy, data quality, informed decision, and finality quality of care. Lack of national guidelines on the HIS accountability framework, the poor culture of accountability, multiple responsibilities and workload, high staff and leadership turnover, lack of motivation, and security problems were stated barriers to implementation of the HIS accountability framework. It was suggested to create a conducive work environment, engage health professionals and other actors during the intervention development, build the skills on HIS leadership, and have the national HIS accountability framework document to implement the intervention effectively. Conclusions Even if there is a better understanding of the concept and advantage of the HIS accountability framework, its practice across the system is limited. It would be better to design the HIS accountability framework using a human-centered design/approach by engaging the key HIS actors and understanding their working environment.

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“…Together, the articles yield a rich picture of the factors that underpinned early program achievements and how evidence informs strategy to improve data-use practices during the later stages of the program. 33 Worku et al explored whether there were preproject associations between the strength of routine health information systems and maternal health care seeking. 34 The findings suggest patterns and frame hypotheses that Ethiopia Data Use Partnership researchers will explore at later stages of their program.…”

Section: Helping Primary Health Care Systems Bridge the Know-do Gapmentioning

confidence: 99%

Learning Health Systems to Bridge the Evidence-Policy-Practice Gap in Primary Health Care: Lessons From the African Health Initiative

Baynes¹,

Adedokun

Awoonor-Williams

et al. 2022

Glob Health Sci Pract

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Drivers and Barriers to Improved Data Quality and Data-Use Practices: An Interpretative Qualitative Study in Addis Ababa, Ethiopia

Abstract: The Ethiopia government’s implementation of strategies to improve data quality, as outlined in its Information Revolution Roadmap, has led to higher data quality and improved data use, but barriers to optimal data-use practices must be addressed to create a culture of information use.

Cited by 4 publications

References 15 publications

Quality of routine data related to facility-based maternal mortality measurement in Kampala City, Uganda

Quality of routine data related to facility-based maternal mortality measurement in Kampala City, Uganda

The Practice and Barriers of Health Information System Accountability Framework in Northwest Ethiopia, 2023

Learning Health Systems to Bridge the Evidence-Policy-Practice Gap in Primary Health Care: Lessons From the African Health Initiative

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