scholarly journals Data quality assessment and associated factors in the health management information system among health centers of Southern Ethiopia

PLoS ONE ◽  
2021 ◽  
Vol 16 (10) ◽  
pp. e0255949
Author(s):  
Mastewal Solomon ◽  
Mesfin Addise ◽  
Berhan Tassew ◽  
Bahailu Balcha ◽  
Amene Abebe

Background A well designed Health management information system is necessary for improving health service effectiveness and efficiency. It also helps to produce quality information and conduct evidence based monitoring, adjusting policy implementation and resource use. However, evidences show that data quality is poor and is not utilized for program decisions in Ethiopia especially at lower levels of the health care and it remains as a major challenge. Method Facility based cross sectional study design was employed. A total of 18 health centers and 302 health professionals were selected by simple random sampling using lottery method from each selected health center. Data was collected by health professionals who were experienced and had training on HMIS tasks after the tools were pretested. Data quality was assessed using accuracy, completeness and timeliness dimensions. Seven indicators from national priority area were selected to assess data accuracy and monthly reports were used to assess completeness and timeliness. Statistical software SPSS version 20 for descriptive statistics and binary logistic regression was used for quantitative data analysis to identify candidate variable. Result A total of 291 respondents were participated in the study with response rate of 96%. Overall average data quality was 82.5%. Accuracy, completeness and timeliness dimensions were 76%, 83.3 and 88.4 respectively which was lower than the national target. About 52.2% respondents were trained on HMIS, 62.5% had supervisory visits as per standard and only 55.3% got written feedback. Only 11% of facilities assigned health information technicians. Level of confidence [AOR = 1.75, 95% CI (0.99, 3.11)], filling registration or tally completely [AOR = 3.4, 95% CI (1.3, 8.7)], data quality check, supervision AOR = 1.7 95% CI (0.92, 2.63) and training [AOR = 1.89 95% CI (1.03, 3.45)] were significantly associated with data quality. Conclusion This study found that the overall data quality was lower than the national target. Over reporting of all indicators were observed in all facilities. It needs major improvement on supervision quality, training status to increase confidence of individuals to do HMIS activities.

2016 ◽  
Vol 1 (2) ◽  
pp. 98 ◽  
Author(s):  
Ermias Abera ◽  
Kidist Daniel ◽  
Taye Letta ◽  
Desalegn Tsegaw

<p><strong><em>Background:</em></strong><em> Health Information systems are increasingly important for measuring and </em><em>improving the quality and coverage of health services. Reliable and timely health information </em><em>is vital for operational and strategic decision making that save lives and enhances health. In Ethiopia information quality and use remain weak, particularly at district health offices and </em><em>primary health care facilities to facilitate decision making. Therefore this study will be designed to greatly signal the current status of Health Management Information System (HMIS) in study area.</em></p><p><strong><em>Objective:</em></strong><em> </em><em>To assess the utilization of health management information systems and associated factors at health centers in Hadiya zone, </em><em>Southern Ethiopia, 2014.</em></p><p><strong><em>Methods:</em></strong><em> A cross sectional study was conducted in health institutions by interviewing </em><em>units/departments of health centers from </em><em>April to June, 2014. Quantitative data was collected using structured </em><em>questionnaires, check lists, observation and interview guide by trained data collectors. Data </em><em>was analyzed using SPSS version 20 and descriptive and logistic regression analysis was carried out.</em></p><p><strong><em>Results:</em></strong><em> The finding of the study revealed that utilization of health management information was 242(69.3%) in all the study units/departments of health centers. Health center units/department had key indicators (AOR=3.67; 95%CI: 2.11, 6.39), completeness of data format (AOR=3.42; 95%CI: 1.65, 7.08), consistency of data (AOR=1.91; 95%CI: 1.05, 3.48)</em><em> were found to be significantly associated with utilization of health information system at 95% level of significance. </em></p><p class="Default"><strong><em>Conclusion:</em></strong><em> Health center units/departments </em><em>had key indicators, completeness of data and consistency of data were predictors of utilization of health management information</em><em> </em><em>system. Therefore, in-service training and updating of staff involved in Health Management Information System (HMIS) at district, strengthening health information system inputs, timely and concrete feedbacks with establishment of functional Health Management Information System (HMIS).</em></p><strong><em></em></strong>


2020 ◽  
Author(s):  
SUSAN F. RUMISHA ◽  
EMANUEL P. LYIMO ◽  
IRENE R. MREMI ◽  
PATRICK K. TUNGU ◽  
VICTOR S. MWINGIRA ◽  
...  

Abstract Background: Effective planning for disease prevention and control requiresaccurate, adequately-analysed, interpreted and communicated data. This study assessed the quality of routine Health Management Information System (HMIS) data at healthcare facility (HF) and district levels in Tanzania. Methods: HMIS tools used at primary health care facilities (dispensary, health centre, hospital) and district office were reviewed to assess their availability, completeness, and accuracy of collected data. The assessment involved seven health service areas namely, Outpatient department, Inpatient department, Antenatal care, Family Planning, Post-natal care, Labour and Delivery and Provider-initiated Testing and Counselling.Results: A total of 115 HFs in 11 districts were assessed. Registers (availability rate=91.1%; interquartile range (IQR):66.7%-100%) and reportforms (86.9%;IQR:62.2%-100%) were the most utilized tools. There was a limited use of tally-sheets (77.8%;IQR:35.6%-100%). Tools availability at dispensary was 91.1%, health-centre 82.2% and hospital 77.8%, and was poor in urban districts. The availability rate atthe district level was 65% (IQR:48%-75%). Reports were highly over-represented in comparison to registers’ records, with large differences observed at HF phase of the data journey and more profound in hospitals.Tool availability and data quality varied by service-areas, indicators, facility level, and districts, however, with a remarkable improvement over the years.Conclusion: There are high variations and improvements in the tool utilisation and data accuracy at facility and district levels. The routine HMIS is weak and data at district level inaccurately reflects what is available at the HFs. These results highlight the need to design tailored and inter-service strategies for improving data quality.


2016 ◽  
Vol 18 (1) ◽  
Author(s):  
Kidist Teklegiorgis ◽  
Kidane Tadesse ◽  
Gebremeskel Mirutse ◽  
Wondwossen Terefe

Background: A Health Information System (HIS) is a system that integrates data collection, processing, reporting, and use of the information necessary for improving health service effectiveness and efficiency through better management at all levels of health services. Despite the credible use of HIS for evidence-based decision-making, countries with the highest burden of ill health and the most in need of accurate and timely data have the weakest HIS in the vast majority of world’s poorest countries. Although a Health Management Information System (HMIS) forms a backbone for strong health systems, most developing countries still face a challenge in strengthening routine HIS. The main focus of this study was to assess the current HIS performance and identify factors affecting data quality in a resource-limited setting, such as Ethiopian health facilities.Methods: A cross-sectional study was conducted by using structured questionnaires in Dire Dawa Administration health facilities. All unit and/or department heads from all government health facilities were selected. The data was analysed using STATA version 11. Frequency and percentages were computed to present the descriptive findings. Association between variables was computed using binary logistic regression.Results: Over all data quality was found to be 75.3% in unit and/or departments. Trained staff to fill format, decision based on supervisor directives and department heads seek feedback were significantly associated with data quality and their magnitudes were (AOR = 2.253, 95% CI [1.082, 4.692]), (AOR = 2.131, 95% CI [1.073, 4.233]) and (AOR = 2.481, 95% CI [1.262, 4.876]), respectively.Conclusion: Overall data quality was found to be below the national expectation level. Low data quality was found at health posts compared to health centres and hospitals. There was also a shortage of assigned HIS personnel, separate HIS offices, and assigned budgets for HIS across all units and/or departments.


2021 ◽  
Vol 9 (2) ◽  
pp. 210-219
Author(s):  
Prince Olueseh Ezekiel

The National Health Management Information System (NHMIS) Was Designed To Provide Timely And Reliable Health Service Delivery Information. The Efficiency And Effectiveness Of Health Service Delivery Is Assessed By The Availability Of Quality, Complete And Timely Data. The NHMIS Policy Review Was Initiated By A Consortium Of Relevant Stake Holders Led By The Department Of Planning, Research And Statistics (DPRS) Of The Federal Ministry Of Health (FMOH) And The National Primary Health Care Development Agency (NPHCDA). The Emphasis Of The NHMIS Is To Strengthen The Health Information System-HIS In The Country And Promote The Use Of Quality Information For Evidence-Based Decision-Making At The Community, LGA, And National Levels. In Spite Of Substantial Investments, The Health Sector In Nigeria Has Made Slow Progress In Improving Its Health Indices. Thus The Nigeria State Health Investment Project(NSHIP), Through Support From WHO, Introduced The Performance-Based Financing –PBF Currently Rolled Out In Three States- Adamawa, Nasarawa, And The Ondo States To Deliver A Result-Based Approach To Improve Quantity And Quality Of Health Services Especially In The Area Of Maternal Health. Health Centers Receive Funds Directly Based On The Number Of Essential Services They Delivered And The Improved Quality Of Care. This Encouraged Health Centers To Focus On Delivering Results, And The New Funds Enabled Them To Improve Their Services. This Study Compared Data Reported Using The NHMIS And Declared Validated On The PBF Declaration Forms In Funding Health Facilities In Nasarawa State For Quarter 1 (Jan.- Mar.)2018 And Quarter 2 (Apr. – June) 2018.


2020 ◽  
Author(s):  
Tahmina Begum ◽  
Shaan Muberra Khan ◽  
Bridgit Adamou ◽  
Jannatul Ferdous ◽  
Muhammad Masud Parvez ◽  
...  

Abstract Background: Accurate and high-quality data are important for improving program effectiveness and informing policy. Bangladesh’s health management information system adopted the District Health Information Software, Version 2 (DHIS2) in 2009 to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality. We aimed to understand the facilitators and barriers of implementing DHIS2 as a way to retrieve meaningful and accurate data for reproductive, maternal and child health (RMCAH) services. Methods: This qualitative study was conducted in two districts of Bangladesh from September 2017 to 2018. Data collection included key informant interviews (n=11), in-depth interviews (n=23), and focus group discussions (n=2). The study participants were individuals involved with DHIS2 implementation from the community level to the national level. The data were analyzed thematically.Results: DHIS2 could improve the timeliness and completeness of data reporting over time. The reported facilitating factors were strong government commitment, extensive donor support, and positive attitudes toward the technology among staffs. Quality checks and feedback loops at multiple levels of data gathering points were helpful to minimize data errors. Introducing a dashboard makes DHIS2 compatible to use as monitoring tool. However, the barriers to effective DHIS2 implementation were lack of human resources, slow Internet connectivity, frequent changes to of DHIS2 versions, and maintaining both manual and electronic system side-by-side. Data in DHIS2 remains incomplete because it does not capture data from private health facilities. Having two parallel management information systems reporting the same RMNCAH indicators threatens data quality and increases the reporting workload. Conclusion: The overall insights from this study are expected to contribute to the development of effective strategies for successful DHIS2 implementation and building responsive health management information system. Focused strategic direction is needed to sustain the achievements of digital data culture. Periodic refresher trainings, incentives for increased performance, and an automated single reporting system for multiple stakeholders could make the system more user-friendly. A national electronic health strategy and implementation framework can facilitate creating a culture of DHIS2 use for planning, setting priorities, and decision making among stakeholder groups.


2019 ◽  
Author(s):  
Tahmina Begum ◽  
Shaan Muberra Khan ◽  
Bridgit Adamou ◽  
Jannatul Ferdous ◽  
Muhammad Masud Parvez ◽  
...  

Abstract Background: Accurate and high-quality data are important for improving program effectiveness and informing policy. Bangladesh’s health management information system adopted the District Health Information Software, Version 2 (DHIS2) in 2009 to capture real-time health service utilization data. However, routinely collected data are being underused because of poor data quality. We aimed to understand the facilitators and barriers of implementing DHIS2 as a way to retrieve meaningful and accurate data for reproductive, maternal and child health (RMCAH) services. Methods: This qualitative study was conducted in two districts of Bangladesh from September 2017 to 2018. Data collection included key informant interviews (n=11), in-depth interviews (n=23), and focus group discussions (n=2). The study participants were individuals involved with DHIS2 implementation from the community level to the national level. The data were analyzed thematically. Results: DHIS2 could improve the timeliness and completeness of data reporting over time. The reported facilitating factors were strong government commitment, extensive donor support, and positive attitudes toward the technology among staffs. Quality checks and feedback loops at multiple levels of data gathering points were helpful to minimize data errors. Introducing a dashboard makes DHIS2 compatible to use as monitoring tool. However, the barriers to effective DHIS2 implementation were lack of human resources, slow Internet connectivity, frequent changes to of DHIS2 versions, and maintaining both manual and electronic system side-by-side. Data in DHIS2 remains incomplete because it does not capture data from private health facilities. Having two parallel management information systems reporting the same RMNCAH indicators threatens data quality and increases the reporting workload. Conclusion: The overall insights from this study are expected to contribute to the development of effective strategies for successful DHIS2 implementation and building responsive health management information system. Focused strategic direction is needed to sustain the achievements of digital data culture. Periodic refresher trainings, incentives for increased performance, and an automated single reporting system for multiple stakeholders could make the system more user-friendly. A national electronic health strategy and implementation framework can facilitate creating a culture of DHIS2 use for planning, setting priorities, and decision making among stakeholder groups.


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