scholarly journals Factors influencing quality of health management information system (HMIS) data: The case of Kinondoni district in Dar es Salaam region, Tanzania

2007 ◽  
Vol 3 (1) ◽  
Author(s):  
DO Simba ◽  
MA Mwangu
Keyword(s):  
Information System ◽  
Management Information System ◽  
Health Management ◽  
Dar Es Salaam ◽  
Health Management Information System ◽  
Management Information ◽  
Factors Influencing

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.

Predictors of electronic health management information system for improving the quality of care for women and people with disabilities

2020 ◽  
pp. 026666692094714
Author(s):  
Edda Tandi Lwoga ◽  
Raphael Zozimus Sangeda ◽  
Restituta Mushi
Keyword(s):  
Information System ◽  
Quality Of Care ◽  
Management Information System ◽  
User Satisfaction ◽  
Health Workers ◽  
People With Disabilities ◽  
Health Management Information System ◽  
Management Information ◽  
Factors Influencing

The electronic Hospital management Information System (eHMIS) can improve care for vulnerable patients, help collect important disability and maternal health data, and improve the hospital’s overall data management. This study assessed the use of HMIS and factors influencing the usage and behavioral intentions to use the eHMIS at the Comprehensive Community Based Rehabilitation in Tanzania (CCBRT). We investigated both clinical and non-clinical staff (n=69) using tablets and online surveys, with a rate of return of 71.9%. The ICT staff were also interviewed to supplement data from the survey. The survey questionnaire was guided by the updated Information System Success (ISS) model. Most health workers (81.2%) used the eHMIS several times a day to support different decision-making activities. The better educated personnel were more likely to enter data more effectively into eHMIS as compared to their counterparts. Among six predictors, self-efficacy positively influenced self-reported use and user satisfaction of HMIS, while service quality negatively affected self-reported use of eHMIS. The system quality positively influenced health workers to be satisfied with the eHMIS, and user satisfaction positively influenced continued usage intention of the eHMIS. Both user satisfaction and continued usage intention were positively related to individual impact of eHMIS. Individual impact had positive effects on organizational impact of eHMIS. This is a comprehensive study conducted in Tanzania regarding the implementation of eHMIS, and factors influencing post-adoptive use of HMIS to improve quality of care of women and people with disabilities.

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 utilisation and factors influencing the performance of the health management information system in Tanzania

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
Leonard E. G. Mboera ◽  
Susan F. Rumisha ◽  
Doris Mbata ◽  
Irene R. Mremi ◽  
Emanuel P. Lyimo ◽  
...  
Keyword(s):  
Health Care ◽  
Information System ◽  
Data Management ◽  
Management Information System ◽  
Health Management ◽  
Health Care 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 to meet the needs of statistics on health services. This study aimed to determine the utilisation of HMIS data and factors influencing the health system’s performance 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 semi-structured questionnaire administered to health workers at facility and district levels and documented using an observational checklist. Thematic content analysis approach was used to synthesise and triangulate the responses and observations to extract essential information. Results A total of 93 healthcare facility workers and 13 district officials were interviewed. About two-thirds (60%) of the facility respondents reported using the HMIS data, while only five out of 13 district respondents (38.5%) reported analysing HMIS data routinely. The HMIS 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 programmes (55%). The majority (41.4%) of the facility’s personnel had not received any training on data management related to HMIS during the past 12 months prior to the survey. Less than half (42%) of the health facilities had received supervisory visits from the district office 3 months before this assessment. Nine district respondents (69.2%) reported systematically receiving feedback on the quality of their reports monthly and quarterly from higher authorities. Patient load was described to affect staff performance on data collection and management frequently. Conclusion Inadequate analysis and poor data utilisation practices were common in most districts and health facilities in Tanzania. Inadequate human and financial resources, lack of incentives and supervision, and lack of standard operating procedures on data management were the significant challenges affecting the HMIS performance in Tanzania.

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 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 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 requires accurate, 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 report forms (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 at the 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.

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