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Assessment of Health Management Information System (HMIS) Performance at Health Facilities
of Afar Region, 2013
Presenter: Mesfin Ayeta
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Presentation Outline
1. Background
2. Methods
3. Result and Discussion
4. Conclusion
5. Recommendation
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In developing countries, the collection, compilation, analysis and utilization of health data remains to be practically major problem.
In Ethiopia, the HMIS is characterized by burdensome data collection and inadequate staff skill and also the information flow is fragmented (WHO, 2007).
This resulted in redundant and conflicting reports and poor quality of data in terms of accuracy and timelines.
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Background
In Afar region, despite some improvements were observed; the problems on HMIS performance is still there.
However, there are not scientific evidences showing the possible determinants of HMIS performance in the region.
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General Objective To assess the status of HMIS performance at health
facilities level and identify its determinant factors.
Specific Objectives To assess the status of HMIS performance at health
facilities
To find out challenges and best lessons of HMIS performance in health facilities
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Objectives
Methods
Study Design A cross-sectional study design was carried out.
Data Source
Study Unit Health facilities
Service providers
Patients/Clients records
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Sample Size Determination
The Sample size is calculated based on the study unit:
Health facility: Rule of thumb sampling method was used. The rule
states, if the number of units are less than 50, take a 30-50% sample.
Record Review: Single Population Proportion formula was used. 384
Individual records were reviewed.
Health Professionals: All the selected health facilities health workers. 04/19/23 8
Data collection instrument/Tools Interview using questionnaire
Observation using checklist Record review
Self-administrative Questionnaires
In-depth Interview
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Data analysis SPSS version 20 was used to analyze quantitative data.
Tables, figures and frequencies
Logistic regression Thematic analysis for qualitative data
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Results and Discussion
Description of Respondents
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Variables Frequency
Respondent’s qualificationMD/HOclinical nurse/midwifePara medicals
4 (3.2%)80 (63.5%)42 (33.3%)
Responsibilities of RespondentsHead of facility and unitsClinical health service providersPara medicals
15 (11.9%)79 (62.7%)32(25.4%)
HIMIS Training Received Not received
40 (31.7%)86 (68.3%)
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Existence of Performance Monitoring Team (PMT) and HMIS guideline
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Present0%
20%
40%
60%
80%
PMTHMIS guideline
31%31%
69% 69%
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Presence of HMIS focal person and Supervision at health facilities
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Exist
Not exist
0%
20%
40%
60%
80%
HMIS focal person Supervision
71%65%
29% 35%
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HMIS process and practice at Health facilities
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Variables Frequency
Yes No I do not Know
Checking reports before sending to the next level?
Use standardized set of indicator
Send HMIS Report based on scheduled
Health facilities received written feedback on HMIS performance
41.7%
29.2%
12.5%
20.8%
35.4%
41.7%
87.5%
39.6%
22.9%
29.2%
37.5%
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Knowledge, attitude, practice and motivation of the health personnel on HMIS performance
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14.3%
85.7%
Knowledge
Adequate knowledge
Inadequate knowledge
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Knowledge, attitude, practice and motivation of the health personnel in HMIS performance
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11.1%
88.9%
Motivation
Better Motivated
Not motivated
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Health professionals culture of information use was found to be 37.3%.
Study in Jimma (2011) shows that utilization of health information was 32.9%.
In Tanzania (2011), 42% did not use the collected data for decision making process.
Study in Malawi (2005) revealed that that data is incomplete as there are gaps in the data collection tools.
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Factors associated with information use for decision making process
Health professionals who work in Health facilities which established PMT were 2.83 times more likely to use information.
Health care providers who had positive attitude were 2.79 times more likely to use information.
Motivated Health professionals were 3.5 times more likely to use information than not motivated.
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Study conducted in Nigeria (2012) shows motivated health professionals were more likely to use information for decision making process.
Similarly, India in 2007 shows establishment of PMT had showed significant association with health professional information use.
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Conclusion
Data quality of HMIS tools were found to be very poor.
Information use habit of health workers for decision making were found to be very low.
Establishment of performance monitoring team, motivation and attitude health care providers were found to be significantly associated with information use.
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Recommendation
The regional health bureau needs to design in-service trainings on information use culture and data quality.
The regional and district health offices should regularly give supportive supervision and technical assistants to health facilities
Regional and district health offices shall encourage, train and follow up health care providers to establish performance monitoring team.
Motivating health care providers and providing training on moral and ethical issues is recommended to improve information use for decision making.
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