Health Management Information System (HMIS); Whose Data is it Anyway? Contextual Challenges

Muhindo, Richard; Joloba, Edith Nakku

doi:10.4172/2315-7844.1000190

Cited by 11 publications

(10 citation statements)

References 28 publications

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“…Finally, in both examples, it is clear that the key to driving up data quality is the utilisation of the data by the various stakeholders [ 65 ]. In Uganda, it has become clear that those districts with over 90% reporting rates are actively using the data to improve health outcomes, while in others low reporting rates are reflected in the limited role which the data play in operational activities.…”

Section: Discussionmentioning

confidence: 99%

Beyond pilotitis: taking digital health interventions to the national level in China and Uganda

Blaschke²,

2017

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BackgroundInnovation theory has focused on the adoption of new products or services by individuals and their market-driven diffusion to the population at large. However, major health sector innovations typically emerge from negotiations between diverse stakeholders who compete to impose or at least prioritise their preferred version of that innovation. Thus, while many digital health interventions have succeeded in terms of adoption by a substantial number of providers and patients, they have generally failed to gain the level of acceptance required for their integration into national health systems that would promote sustainability and population-wide application. The area of innovation considered here relates to a growing number of success stories that have created considerable enthusiasm among donors, international agencies, and governments for the potential role of ICTs in transforming weak national health information systems in middle and low income countries. This article uses a case study approach to consider the assumptions, institutional as well as technical, underlying this enthusiasm and explores possible ways in which outcomes might be improved.MethodsLiterature review and case study analysis.ResultsThe two systems considered have had considerable success in terms of gaining and maintaining government support and addressing the concerns of providers without compromising their core elements. In Uganda, the system has flourished in spite of severe resource constraints, using a participatory approach that has encouraged a high level of community engagement. In China, concern with past failures generated the political will to build a high quality surveillance system, using the latest technology and drawing on a highly skilled human resource base.ConclusionsBoth example stress the importance of recognising the political, social and historical context within which information systems have to function. Implementers need to focus as much on the perceptions, attitudes and needs of stakeholders as on the technology. Implementers should distinguish between factors which may influence engagement at an institutional level and those aimed at supporting and supervising individuals within those institutions. Finally, we would suggest that designing interoperability into systems at the outset, rather than assuming that this can be achieved at some point in the future, may prove far easier in the longer term.

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Section: Discussionmentioning

confidence: 99%

Beyond pilotitis: taking digital health interventions to the national level in China and Uganda

Blaschke²,

2017

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“…Generally, in many Sub-Saharan African countries, data utilisation at all healthcare systems is low [4,[7][8][9][10][11]. Available literature suggests that, despite some notable successes, the impact of HMIS on the decision-making process within Africa health systems remains limited [4,11,12]. Several barriers have been reported to prevent the HMIS from achieving full potential in Africa [13,14].…”

Section: Introductionmentioning

confidence: 99%

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

Mboera

Rumisha

Mbata

et al. 2021

BMC Health Serv Res

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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.

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“…Generally, in many Sub-Saharan African countries data utilization at all levels of the health care system is low [4,[7][8][9][10][11]. Available literature suggests that, despite some notable successes, the impact of HMIS on the decision-making process within Africa health systems remains limited [4,11,12]. Several barriers have been reported to prevent investments in HMIS from achieving full potential in Africa [13,14].…”

Section: Introductionmentioning

confidence: 99%

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

Mboera

Rumisha

Mbata

et al. 2021

Preprint

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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.

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Health Management Information System (HMIS); Whose Data is it Anyway? Contextual Challenges

Cited by 11 publications

References 28 publications

Beyond pilotitis: taking digital health interventions to the national level in China and Uganda

Beyond pilotitis: taking digital health interventions to the national level in China and Uganda

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

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

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