Health Information Systems and Registers

Кобринский, Б. А.; Breusov, A V

doi:10.4236/etsn.2019.82002

Cited by 2 publications

(1 citation statement)

References 26 publications

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“…Although there is no perfect health data due to missing values, bias, measurement, transcription, and human entry errors, most of these data problems chiefly occur in developing countries (11)(12)(13)(14). Poor data quality in the health sector can be attributed to various factors, including inadequate training of data managers and healthcare staff, limited access to resources such as technology and reporting tools, and data fragmentation due to disparate systems (2,11,15,16). Data entry errors and lack of supervision and quality control also contribute to inaccuracies, alongside overwhelming workloads and time constraints that lead to rushed data entry (8,9,15).…”

Section: Introductionmentioning

confidence: 99%

Determinants of COVID-19 data quality in the District Health Information Management System version 2 in Ahafo Region, Ghana

Aabebe,

Adjei-Gyamfi,

Asobuno

et al. 2024

Preprint

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Background In ensuring public health efforts in combating pandemics such as coronavirus disease 2019 (COVID-19), transparent data reporting that is of high quality and easily accessible is crucial for tracking epidemic progress and making informed decisions. In Ghana, no published studies have been conducted to evaluate the quality of COVID-19 data submitted onto the national web-based platform, District Health Information Management System version 2 (DHIMS-2) during the COVID-19 period. In this regard, this study seeks to assess the estimates and determinants of COVID-19 data quality in the DHIMS-2 in the Ahafo region of Ghana. Methods A facility-based cross-sectional study design was employed, with a desk review of COVID-19 records in DHIMS-2 and primary data sources (registers and monthly reporting forms). This study involved all 23 different levels of healthcare facilities that reported on COVID-19 in the Ahafo region from March 2020 to December 2022. We assessed COVID-19 data quality using three dimensions of completeness, accuracy, and timeliness according to the World Health Organization data quality guide. Mixed-effect logistic regression was then employed to identify the determinants of COVID-19 data quality at a 95% confidence interval. Results The overall COVID-19 data quality was estimated at 35.9% (95%CI=32.6%, 39.4%) while the rate of the data dimensions of timeliness, completeness, and accuracy were 50.2% (95%CI=46.7%, 53.8%), 50.6% (95%CI=47.1%, 54.2%), and 72.4% (95%CI=69.1%, 75.5%) respectively. It was found that the availability of a functional data validation team at the health facilities (AOR=18.3; 95%CI=1.62, 20.7; p= 0.019), training of data managers in COVID-19 data management (AOR=9.37; 95%CI=2.56, 34.3; p=0.001), and data managers with two-year professional training (certificate background) (AOR=3.42; 95%CI=1.95, 12.2; p=0.025) were independently associated with COVID-19 data quality. Conclusion The overall COVID-19 data quality in the Ahafo region was quite poor. Dimensionally, while the rate of data timeliness was high, that of data completeness, and accuracy were relatively low. The interaction of the independent correlates of COVID-19 data quality requires the healthcare system to identify stringent measures to strengthen the health information system to enhance planning and decision-making, especially during disease outbreaks.

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Section: Introductionmentioning

confidence: 99%

Determinants of COVID-19 data quality in the District Health Information Management System version 2 in Ahafo Region, Ghana

Aabebe,

Adjei-Gyamfi,

Asobuno

et al. 2024

Preprint

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Registers of Healthcare Systems of Northen European Countries

Puhachova¹,

GLADUN²

2021

Demogr. soc. ekon.

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The introduction of electronic register systems for all spheres of state functioning is becoming more widespread in developed countries. It is the systems, not individual registers, that create the conditions for the comprehensive and effective use of available information in the field of state and local government, research, business planning, and so on. In our opinion, health care registries are the most important among other systems, so it is important to study the experience of the most developed countries in the field of creating electronic medical information resources. The use of the experience gained by advanced European countries in this area is especially useful for Ukraine, where such a system is being developed. The purpose of the article is to summarize the experience of Northern European countries in the use of electronic information resources of health care for its implementation in Ukraine. The novelty of the article is a generalized and comparative analysis of health registry systems in Denmark, Norway, the Netherlands, Estonia, Sweden, Finland and a study of the role of medical, statistical and scientific institutions in the development of these systems. The research methodology is based on the application of the following methods: system analysis, scientific generalization, comparative analysis, research methods of complex systems. The article examines the health care systems of six northern European countries, compares the composition and features of these systems. The focus is on electronic information resources, which are introduced only in some countries. It is established that the Danish and Norwegian systems are the most branched among the systems of other studied countries and contain not only a larger number of specialized registers, but also have the largest number of organizations that maintain these registers. The holders of registers and databases in different countries are not only the relevant ministries but also research institutes and universities. In addition, statistical authorities also create registers that are used for society’s statistical information needs. The study thus summarizes the experience of creating and operating electronic information resources in the field of health care in Northern European countries, concludes that it can be used in the implementation of a similar Ukrainian, the process of which began several years ago.

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Health Information Systems and Registers

Cited by 2 publications

References 26 publications

Determinants of COVID-19 data quality in the District Health Information Management System version 2 in Ahafo Region, Ghana

Determinants of COVID-19 data quality in the District Health Information Management System version 2 in Ahafo Region, Ghana

Registers of Healthcare Systems of Northen European Countries

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