scholarly journals Level of data quality from Health Management Information Systems in a resources limited setting and its associated factors, eastern Ethiopia

2016 ◽  
Vol 18 (1) ◽  
Author(s):  
Kidist Teklegiorgis ◽  
Kidane Tadesse ◽  
Gebremeskel Mirutse ◽  
Wondwossen Terefe
Keyword(s):  
Information System ◽  
Data Quality ◽  
Health Management ◽  
Health Facilities ◽  
Health Management Information System ◽  
Department Heads ◽  
Management Information ◽  
Cross Sectional ◽  
Eastern Ethiopia ◽  
Limited Setting

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.

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
Keyword(s):  
Information System ◽  
Data Quality ◽  
Management Information System ◽  
Health Professionals ◽  
Health Management ◽  
Health Centers ◽  
Southern Ethiopia ◽  
Health Management Information System ◽  
Management Information ◽  
Cross Sectional

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.

scholarly journals Data Quality of the Routine Health Management Information System at the Primary Healthcare Facility and District Levels in Tanzania

2020 ◽  
Author(s):  
SUSAN F. RUMISHA ◽  
EMANUEL P. LYIMO ◽  
IRENE R. MREMI ◽  
PATRICK K. TUNGU ◽  
VICTOR S. MWINGIRA ◽  
...  
Keyword(s):  
Information System ◽  
Data Quality ◽  
Management Information System ◽  
Health Management ◽  
Health Centre ◽  
Healthcare Facility ◽  
Health Management Information System ◽  
Management Information ◽  
Service Areas

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.

scholarly journals Perceptions and experiences with District Health Information System software to collect and utilize health data in Bangladesh: A qualitative exploratory study

2020 ◽  
Author(s):  
Tahmina Begum ◽  
Shaan Muberra Khan ◽  
Bridgit Adamou ◽  
Jannatul Ferdous ◽  
Muhammad Masud Parvez ◽  
...  
Keyword(s):  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Management Information System ◽  
Program Effectiveness ◽  
Health Management ◽  
Quality Data ◽  
Health Management Information System ◽  
Management Information ◽  
District Health

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.

scholarly journals Data Utilisation and Factors Influencing the Performance of the Health Management Information System in Tanzania

2021 ◽  
Author(s):  
Leonard Mboera ◽  
Susan Rumisha ◽  
Doris Mbata ◽  
Irene Mremi ◽  
Emanuel Lyimo ◽  
...  
Keyword(s):  
Health Care ◽  
Information System ◽  
Management Information System ◽  
Health Management ◽  
Health Care Facilities ◽  
Health Facilities ◽  
Health Management Information System ◽  
Management Information ◽  
Factors Influencing ◽  
Care Facilities

Abstract Background: Health Management Information System (HMIS) is a set of data regularly collected at health care facilities, aimed to meet the needs of statistics on health services. This study aimed to determine the utilisation of HMIS data and factors influencing the performance of health system at the district and primary health care facility levels in Tanzania. Methods: This cross-sectional study was carried out in 11 districts and involved 115 health care facilities in Tanzania. Data were collected using a standard questionnaire and an observational checklist. The collected data was cleaned, summarized into proportions and graphical presentation using STATA version 13 software. Results: This study involved 115 health facilities in 11 districts. A total of 93 health facility workers and 13 district officials were interviewed. About two-thirds (60%) of the facility respondents reported to use the HMIS data they collect. Data were mainly used for comparing performance in terms of services coverage (53%), monitoring of disease trends over time (50%), and providing evidence for community health education and promotion programme (55%). The majority (41.4%) of the facility’s personnel had not received any training on data management related to HMIS in the past 12 months. Only five out of 13 district respondents reported to routinely analyse HMIS data. Patient load was described to frequently affect staff performance on data collection and management. Less than half (42%) of the health facilities (HFs) had received supervisory visits from the district office. Nine district respondents reported to systematically receive feedback on the quality of their reports on monthly and quarterly bases from higher authorities. More than half (n=7) of district respondents reported that those responsible for HMIS activities are also responsible for other equally important activities. Conclusion: Poor data utilisation was common in most of the districts and health facilities in Tanzania. Inadequate human and financial resources, inadequate training, lack of supervision, and lack of standard operating procedures were the major challenges affecting the HMIS performance in Tanzania.

scholarly journals Perceptions and experiences with District Health Information System software to collect and utilize health data in Bangladesh: A qualitative exploratory study

2019 ◽  
Author(s):  
Tahmina Begum ◽  
Shaan Muberra Khan ◽  
Bridgit Adamou ◽  
Jannatul Ferdous ◽  
Muhammad Masud Parvez ◽  
...  
Keyword(s):  
Information System ◽  
Data Quality ◽  
Health Information ◽  
Management Information System ◽  
Program Effectiveness ◽  
Health Management ◽  
Quality Data ◽  
Health Management Information System ◽  
Management Information ◽  
District Health

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.

scholarly journals Utilization of Routine Health Management Information and Associated Factors among Health Professionals Workingat Public Health Facilities of Hadiya Zone Southern Ethiopia

2019 ◽  
Author(s):  
Animut Addis Feleke ◽  
Takele Tigro Olbamo ◽  
Binyam Taddesse ◽  
Yibeltal Siraneh
Keyword(s):  
Public Health ◽  
Information System ◽  
Health Professionals ◽  
Confidence Level ◽  
Health Management ◽  
Health Facilities ◽  
Southern Ethiopia ◽  
Health Management Information System ◽  
Management Information ◽  
Public Health Facilities

Abstract Background Health management information system is a system that used for routine data collection, analysis and utilization in health system. However, limited study done on routine health management information at individual health professionals level. Hence, the objective of this study was to assess utilization of routine health management information and associated factors among health professionals working at public health facilities of Hadiya Zone Southern Ethiopia. Methods A facility based cross-sectional survey was conducted among health professionals working at public health facilities of Hadia Zone from March 15-30, 2018. Using single population proportion formulae, 477participants were randomly selected. Data were collected by self-administered questioner. The data were entered in to Epi data version 3.1 and exported to SPSS version 23 for statistical analysis. Both bivariate (at P<0.25) and multi variable logistics regressions (at P<0.05) were used to identify predictors of utilization. Finally, the findings were presented using graphs, tables, narratives and descriptive numerical summary. Results The finding of this study revealed that utilization of health management information system among health workers was 54.9%. Knowledge [AOR=1.576, 95%CI (1.012, 2.454)], confidence level [AOR=1.873, 95%CI(1.264,2.776)], participation on data aggregation [AOR=2.289, 95% CI (1.293,4.05­)], register their daily data [AOR=2.529, 95% CI(1.023, 6.251)], and complexity of formats [AOR=1.971, 95%CI(1.29,3.011)] were found to be significantly associated with utilization of health information system at 95%confidence level. Conclusion and recommendations The overall health information utilization among health workers was low relative to other literature. Having good knowledge, high confidence level, participation on data aggregation, registering their daily data were independent predictors of information utilization. Therefore, stakeholders at each level should improve capacity of health care providers like providing training and regular mentorship related with information use.

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