scholarly journals Comparing data Reported Using the National Health Management Information System and data Declared Validated on the PBF Declaration Forms in Funding Health Districts in Nasarawa State

2021 ◽  
Vol 9 (2) ◽  
pp. 210-219
Author(s):  
Prince Olueseh Ezekiel
Keyword(s):  
Information System ◽  
Health Service ◽  
Service Delivery ◽  
Management Information System ◽  
Health Management ◽  
Health Service Delivery ◽  
Health Centers ◽  
Health Management Information System ◽  
Management Information

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.

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 Quality assurance of health management information system in Kayunga district, Uganda

2018 ◽  
Vol 6 (2) ◽  
Author(s):  
Harriet R. Kagoya ◽  
Dan Kibuule
Keyword(s):  
Health Care ◽  
Information System ◽  
Quality Assurance ◽  
Management Information System ◽  
Health Management ◽  
Care Delivery ◽  
Public Health Care ◽  
Health Management Information System ◽  
Management Information

Background: An efficient health management information system (HMIS) improves health care delivery and outcomes. However, in most rural settings in Uganda, paper-based HMIS are widely used to monitor public health care services. Moreover, there are limited capabilities and capacity for quality HMIS in remote settings such as Kayunga district.Objectives: The quality assurance practices of HMIS in health centres (HCs) in Kayunga district were evaluated.Method: A cross-sectional descriptive study design was used to assess the quality of HMIS at 21 HCs in Kayunga district. Data were collected through in-depth interviews of HMIS focal persons as well as document analysis of HMIS records and guidelines between 15 June 2010 and 15 July 2010. The main outcomes were quality assurance practices, the HMIS programmatic challenges and opportunities. The practice of HMIS was assessed against a scale for good quality assurance practices. Qualitative data were coded and thematically analysed, whereas quantitative data were analysed by descriptive statistics using SPSS v22 software.Results: All the 21 HCs had manual paper-based HMIS. Less than 25% of HCs practised quality assurance measures during collection, compilation, analysis and dissemination of HMIS data. More than 50% of HCs were not practising any type of quality assurance during analysis and dissemination of data. The main challenges of the HMIS were the laborious and tedious manual system, the difficulty to archive and retrieve records, insufficient HMIS forms and difficulty in delivering hard copies of reports to relevant stakeholders influenced quality of data. Human resource challenges included understaffing where 43% of participating HCs did not have a designated HMIS staff.Conclusion: The HMIS quality assurance practices in Kayunga were suboptimal. Training and support supervision of HMIS focal persons is required to strengthen quality assurance of HMIS. Implementation of electronic HMIS dashboards with data quality checks should be integrated alongside the manual system.

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 Utilization of Health Management Information System and Associated Factors in Hadiya Zone Health Centers, Southern Ethiopia

2016 ◽  
Vol 1 (2) ◽  
pp. 98 ◽  
Author(s):  
Ermias Abera ◽  
Kidist Daniel ◽  
Taye Letta ◽  
Desalegn Tsegaw
Keyword(s):  
Information System ◽  
Health Information ◽  
Management Information System ◽  
Health Management ◽  
Health Information System ◽  
Health Centers ◽  
Southern Ethiopia ◽  
Health Management Information System ◽  
Management Information ◽  
Key Indicators

<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>

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