, Tessema Abera Osse2, Teshome Sosengo3UTILIZATION OF HEALTH MANAGEMENT INFORMATION SYSTEM AND ASSOCIATED FACTORS IN HEALTH INSTITUTIONS OF KEMBATA TEMBARO ZONE, SOUTHERN ETHIOPIA
Hailu Kebede Kondoro1, Eyassu Mathewos Oridanigo1, Tessema Abera Osse2, Teshome Sosengo3
1Kembata Tembaro Zone Health Department, P.O. box 20, Durame, Ethiopia.
1Department of public health, College of Medical and Health sciences, Wachemo University, Durame Campus, Durame, Ethiopia.
2Durame Town Health Office Kembata Tembaro Zone, Durame, Ethiopia.
3School of Pharmacy, Haramaya University, Harar, Ethiopia.
Background: Health Management Information System (HMIS) is one of the six building blocks of a health system designed to provide important data for continuous quality improvement at all levels of health care administration. It is a major source of information for monitoring and adjusting policy implementation and resources use. Some studies have been conducted in health data collection and ways to improve data quality, but little is known about utilization of HMIS in health services organization. Therefore, this study aimed to assess the utilization of HMIS and associated factors in the study area.
Methods: A facility-based cross-sectional study conducted in public health institutions of Kembata Tembaro zone from March 1 to 30 March 2018. The sample size was calculated using single population proportion formula,and a total of 317 heads of units/departments of district health offices and health facilities were included. Both quantitative and qualitative data were collected using structured questionnaires, observational check-lists and interview guide by trained data collectors. Multivariable logistic regressions were performed using Enter method to identify factors independently associated with dependent variable. Statistical significant variables were declared at P-value less than 0.05 and Odds ratio with 95% confidence interval were used for data interpretation.
Result: In this study, overall data utilization was 131(41.59%) with 95% CI of 38.9-46.1%.The data utilization was found to be 98(38.73%) and 33(53.23%) in the health facilities and health administrative units respectively. Training for HMIS [AOR (95% CI)=3.06(2.15-6.75)], availability of procedure manuals [AOR (95% CI)=3.67(1.78-9.01)], and Supportive supervision[AOR (95% CI)=5.30(3.05-11.53)] were found to be significant with HMIS utilization.
Conclusion: Utilization of HMIS in public health institution was lower compared to previous studies. HMIS training, supportive supervision and availability of procedure manuals were positively associated with utilization of HMIS. Health facilities and offices should avail HMIS manuals and capacity building of health workers through training and supportive supervision was recommended.
Keywords: Ethiopia, HMIS utilization, Kembata Tembaro, Public health institutions.
INTRODUCTION
Health management information system (HMIS) is defined as collective effort to collect, process, reportand use health information and knowledge to influence policy making, programme action and research1. The purpose of HMIS is to routinely generate quality health information that provides specific information support tothe decision-making process at each level of the health system for improving the health system performance, to respond to emergent threats, and to improve health2. Utilization of data from HMIS is the practice of maintenance and care of health records by traditional (paper-based) and electronic means in hospitals, health administrative office, health departments, health insurance companies, and other facilities to generate quality health information and use that information for management decisions to improve the performance of health services delivery3. Utilization of data from HMIS at all level of health services organizations is used to improve health services effectiveness and efficiency3.
Despite the credible use of data from HMIS for evidence based decision making, countries with the greatest burden of ill health andthe most urgent needs for good data have the weakest utilization of health data in the vast majority of world’s low income countries4. Although high effort to improve the efficiency of data utilization in the past few years, low and ineffective data utilization practicing from HMIS, poor utilization of data at the local leveland inadequate knowledge and interest of health service providers in HMIS was seen in health system5.
Poor/absence of data utilization will result in occurrence of inadequate transparency between health administrative units and health care providing centers, which encounter unfair allocation of resources according to their need and interrupt supplies within the organization. As a result, it can frustrate the health staffs in health facilities compromising the attention paid to successful application of the system6. Government of Ethiopia gives due recognition to HMIS as a management supportsystem for improving the health system in Ethiopia by providing continuousinformation support todecision-making processat each decision-making7. Federal Ministry of Health (FMOH) emphasized HMIS as a key to a successful implementation of the Health Sectors Transformation Plan (HSTP) and used information revolution for transformation agenda9. HSTP underlined that routine data generated at district health facilities should beconsidered as the entrance to utilizing health information and a primary source of information for continuous monitoring of health services in the country, and that data should be utilized at theplace where it was generated8.
Even though the FMOH has made tremendous efforts on initiative of HMIS and reform changes, data/information utilization remains weak, particularly at district health offices and primary health care facilities, which have primary responsibility for operational management and decision making10. According to study conducted in public HCs of Addis Ababa, Ethiopia, level of HMIS utilization was 41.7%4. According to HMIS performance base line survey conducted in Southern Nations Nationalities and People Republic (SNNPR) of Ethiopia, the utilization of information was found to be limited in the assessed zones/special woreda. Absence of guidelines and limited information feedback to health facilities were the contributing factors for the observed minimum use of HMIS11. Therefore, this study was designed to greatly signal the current status of HMIS utilization in the study area, which can strengthen the communication channel for timely delivery of services.
MATERIALS AND METHODS
Study area and period
A facility based cross-sectional study design using both quantitative and qualitative study was used in public health institutions of Kembata Tembaro zone from March 1 to 30, 2018. The Zone is located in Southern Nations, Nationalities and People Republic (S/N/N/P/R) of Ethiopia and its capital town, Durame, which is located 293 kilometers (KM) from Addis Ababa and 118 KM from Hawassa, capital town of S/N/N/P/R government of Ethiopia. In this zone, there are 8 woreda health offices and 4 health administrative health units, 1 general and 4 primary hospitals,33 governmental and 3 non-governmental health centers, 136 health posts and 1170 different types of health professionals.
Source and study population
The source population were all health units/departments of Zonal health department, district health offices and Health facilities (HF) while study population were randomly selected units/departments of Zonal health department, district health offices and HF in the zone.
Sample size determination and sampling technique
The sample size was calculated using single population proportion formula, assuming 5% precision, 95% confidence interval and 32.9% proportion of overall utilization of HMIS in Jimma zone at district level12. The population correction formula was used since the source population was less than 10,000(13) and by assuming 10% non-response rate, the final sample size was 317. Since all health facilities in the Zone currently were implementing HMIS, all units/departments heads from all health facilities and offices were included in the study. In the study area, there were 633 units/departments from all health facilities and health offices. Simple Random Sampling (SRS) was used to select 64 and 253 study participants from health administrative units/health offices and health facilities respectively. For qualitative study, heads of health offices, hospital and health centres, HMIS focal persons and case team leaders were selected purposively for in-depth interview.
Data collection tools and techniques
Data were obtained from heads of units/departments of health facilities and health offices of the zone. A face-to-face interview was conducted using self-administered structured questionnaires that were developed after reviewing different relevant literatures4,12,14,15 and observational checklists in the study units/departments to identify how data and information is generated like observation of registration books, monthly and annual reports, and graph, charts and Maps. Six Bsc nurses and one health officer were recruited to collect the data and supervise data collection process respectively.
Data Quality control
The quality of data was assured by proper designing of the questionnaires and by training the data collectors and supervisors for two days before the data collection. Every day after data collection, questionnaires were reviewed and checked to maintain its accuracy and completeness by supervisors. The English version questionnaires were translated into Kambatissa and Amharic languages (local languages) and again translated back to English version and comparisons were made on the consistency of these versions. Data collection tools were pretested at 5% of samplesize in shone primary hospital and East Badawacho health office, outside of the study areaprior to its actual use in data collection.
Data management and statistical analysis
Quantitative data were checked for completeness, inconsistency then coded and entered into epidata version 3.1 and exported to SPSS version 21 for analysis. Descriptive statistics were computed and tables, graphs and numerical summary presented the results. Bivariate analysis was carried out to see the association of each independent variable with utilization of HMIS. Variables with P-value less than 0.25 in bivariate analysis were considered as candidates for multivariable logistic regression analysis. Multivariable logistic regression analysis was performed using Enter method to identify factors independently associated with dependent variable. Statistical significance was declared at P-value less than 0.05 and the strength of statistical association was measured by adjusted odds ratios and 95% confidence intervals. The qualitative data were transcribed and coded then merged in their thematic areas and a thematic framework analysis was employed manually. Based on participants’ explanation, the descriptive summaries were made, which were used as supplementation for quantitative data to verify events.
Ethical consideration
The study was conducted after getting permission from the institutional review board (IRB) of Jimma university institute of Health (letter No: IRB/205/10 and date: 18/01/2018). Letter of cooperation was obtained from kembeta Tembero zone health department and woreda health offices. After clear discussion about the actual study or explaining of purpose of the study, verbal informed consent was obtained from each study subjects.
Operational definition
Utilization of HMIS: Utilization of data from HMIS was assessed by using matrixes such as information for decision making to take immediate action, feedback from respective supervisors, calculation of area coverage and preparation of maps, presentation of key indicators with charts or tables and presentation of achievements of targets. Based on these criteria, the respondents were considered as utilized data when they practiced a minimum of three out of five criteria4,12.
Completeness: completeness is measured as filling in all data elements in the facility report
form, and also as the proportion of facilities reporting in an administrative area. Completed if > 85 % of them were filled
Consistency: Is correspondence between data reported and data recorded in registers and
patient/client records, as measured by a Lot Quality Assurance Sample (LQAS) checked by allunits /department Consistency >90%.
RESULTS
General characteristics of the respondents
In this study, 315 study participants responded to the questionnaires with a response rate of 99%. Out of total respondents who responded to the questionnaires, sixty two were selected from health administrative units (health offices) while 253 wereselected from hospitals and health centers. Out of total respondents, majority of them, 138(43.8) were within the age range of 25-30 with a mean and standard deviation age of 27.24 and 5.4 respectively. The sex distribution of individuals working in the study units showed that about two third of them, 197(62.5%) were males.
About two fifth, 131(41.6%) respondents’service year was 2-4 years. Regarding educational status of respondents,198(62.9%) were diploma holders (Table 1).
Organizational characteristics
Among 315 observed units/departments, 99(31.4%) of them had computers. Based on organizational classification, 50(15.9%) and 49(15.6%) units/ depart-ents in health facilities and health offices had computers respectively. Regarding supervision, 127 (40.3%) units/departments were supervised at least once by higher bodies to provide and support directions of health services in the last six months. Among them, about one quarter, 33(26%) were supervised irregularly while 42(33%), 32(25%) of them were supervised once, twice and 3 times respectively.
One of HMIS focal persons from health centre said that“... supervision was conducted poorly and it was irregular, and not planned, supported by check list and well organized. Although, it was conducted as supportive, was simply traditional type and conducted during seasonal programs like campaigns.”
About two third of the observed units/departments, 204(64.8%) had HMIS multi-disciplinary committee for over all design and direction users of data. Among them, 60(19%) of units/departments didn’t have schedule for meeting any more.
One of key informant from head of health offices said that“...there were meetings in the departments/units for reviewing performance. They were conducted not according to plan and schedule setted but they were conducted as needed and not problem solving and some times corrections were not given on the points that were mentioned and discussed during the meetings”
Regarding HMIS training and technical support, 168(53.3%) staffs working in the units/departments received training (Table 2).
Quality dimension of study subjects
In this study, almost all the units/departments prepared reports to submit next higher officials on weekly, monthly, quarterly and annual basis. Out of total units/departments, 301(95.6%) had data transmission, processing, and reporting rules. Among the total units/departments, 248(78.7%) keep their reports and registrations in well-organized hard copy form while 56(17.8%) keep their reports in both hard and soft copy form. Regarding submission of reports, 117(37.1%) submit reports within 20-24 days (Table 3). From the total interviewed respondents in the units/departments, 186(59.1%), 58.7%, and 46.7% revealed ambiguity and absence of WHO codes, redundancy and incompleteness of reporting formats respectively.
One of the HMIS focal person from the health centers said that “…routine data was collected from both individual and working unit level but the tally process was laid to the HMIS focal person. Therefore, the data were not tallied in daily basis due to negligence, shortage of tally sheets and problem of awareness on reporting formats ….”
Data utilization
More than half of the units/departments, 182(57.8%) calculated area coverage. Regarding receiving of feedback to recommend future action, more than half, 162(51.4%) of the units/departments received feedback. Most of the units/departments, 287(91.1%) had key indicators and about half of the units/departments presented their achievement of the targets. Based on measurement criteria, the overall data utilization was 131(41.59%) with 95% CI: (38.9-46.1%). The data utilization was found to be 98(38.73%) and 33(53.23%) in the health facilities and health administrative units/health offices respectively (Figure 1).
One of the head of health centers said that“...the utilization of data was gearing back ward to traditional type since there was inappropriate data management due to inadequate investment and attention given in the data utilization and management from concerned bodies. Most of the health workers considered the data utilization as responsibilities of heads and HMIS focal persons...”
One of HMIS focal person of woreda health office said that…. “Most reports were aggregated but not analyzed and interpreted in work units at health center level. But this was relatively better worked in Woreda health offices and zonal health department; the problem is due to the complexity of reporting formats, miss matching of calculation indicators and understanding level of health workers.”
Factors associated with data utilization
Among sixteen variables in bivariate logistic regression analysis, seven of them had a P-value less than 0.25; hence, they were candidates for multivariable logistic regressions. The candidate variables were again entered in to multivariable logistic regression model to obtain variables which were independently associated with outcome variable, utilization of data. The variables with P-value less than 0.05 in multivariable logistic regression analysis were taken as significant predictors of outcome variable. Supportive supervision, availability of procedure manuals, and receiving of HMIS training was found to be significantly associated with data utilization. Health units/departments, which had trained staffs were 3.06 times more likely utilizing routine data as compared to the units/departments without trained staffs [OR (95% CI)=3.06(2.15, 6.75)]. Health units/departments, which had HMIS procedure manuals were 3.67 times more likely utilizing data as compared to units/departments without HMIS procedure manuals [OR (95% CI)=3.67(1.78, 9.01)] (Table 4).
DISCUSSION
Sound and reliable information has remarkable importance on decision-making across all health system building blocks, and it is essential for health system policy development and implementation16. The finding of this study revealed that utilization of HMIS was 41.6% in all study units/departments. This finding was comparable with study conducted at public health centers in Addis Ababacity that reported the data utilization of 41.7%4. However, it was lower than what was documented in studies conductedin East Ethiopia, 53.1%17 and East Gojam Zone of Northwest Ethiopia, 45.8%9.This variation might be due to inadequate provision of training and supervision for healthcare providers in this study than previous studies.
In this assessment, health units/departments, which used HMIS manuals as reference and guidelines were more likely utilizing routine data as compared to units/departments, which didn’t use HMIS procedure manuals for data utilization. This finding was comparable to study conducted in Addis Ababa city and S/N/N/P/R4,11. This might be due to utilizing HMIS procedure manual may guide the operation and used as reference for routine health data generated from daily health care service in health facility level18. Receiving of training on HMIS was an important predictor that was significant with utilization of HMIS. Health units/departments, which had trained staffs, were more likely utilizing routine data as compared to units/departments without trained staffs. This finding was supported by studies conducted in different regions of Ethiopia9,17,19. Staff training is the most important motivator and could improve the potential of health workers to analyze and make evidence-based decision20. It is known that continuous training as a part of capacity development is important to create awareness on data utilization and decrease data misinterpretation due to the lack of the right capacity, which is experienced in all developing countries21. In this study, supportive supervision was another important factor that was significant with utilization of routine data. This finding was supported with study conducted in Northwest Ethiopia9. This might be due to the fact that supervision has a significant role in identifying the gaps of routine health data use and provides feedback on identified problems and improving health workers’ performance. Availing of manuals for HMIS and capacity building of health workers through training and supportive supervision was recommended.
Limitation
Limitation of the study was relatively small sample size which might reduce the power of the study and increase margin of error.
CONCLUSION
Utilization of HMIS in public health institution was lower compared to previous studies for decision making in health institutions of Kembata Tembaro Zone. There was poor capacity building of health workers in HMIS training and inadequate and irregular provision of supportive supervision to service units/departments from higher officials. Among many factors affecting the utilization of HMIS, only receiving of training for HMIS, availability of procedure manuals and supportive supervision were found to be significantly associated.Woreda health offices should avail the procedure manuals for the units/departments of both health facilities and heath offices. SNNPR health bureau should arrange HMIS training for health workers in the study area. The data sets used and/analyzed during this study are available from the corresponding author up on reasonable request.
ACKNOWLEDGEMENTS
We are grateful to Jimma University for the financial support of data collection of this work. Our thanks go to managers of study health facilities for their permission to conduct the study in their facilities. We also acknowledge our study participants for providing the necessary information and the data collectors for collecting the data carefully.
CONFLICT OF INTEREST
There is no conflict of interest associated with this study.
REFERENCES