Determinants Of Effective Utilization Of Health Management Information For Decision Making Among Health Program Managers: A Case Of Malindi Sub County, Kilifi County, Kenya.
The Kenya’s Ministry of Health established the District Health Management Information Systems (DHMISs) in 1978 to strengthen the routine health information so that information can be available for the purpose of being utilised to make decisions in all the levels that health care is provided. These systems are available and in use in Malindi sub County of Kilifi County however, there was need to find out what determines the utilization of information in decision making so as to improve on them and enhance information use. These factors studied were categorized into behavioural, technical and organizational factors and classified as independent variables. The study was delimited to the health program managers and to the study variables in the conceptual frame work. Empirical literature of the works of widely published scholars was reviewed in the study and the gaps in literature documented. The study was grounded on performance of routine health information system management framework by Aqil, Lippeveld & Hozumi and used an evidence based health information system theory and HIS design theory as the key theoretical models. The study adopted a cross sectional research design and employed a mixed method paradigm. Stratified and purposive sampling methods were used to select the sample of the respondents from the target population of 280 health workers. Using the statistical formula by Fisher et al, a sample size of 162 individuals was determined to constitute the sample size for the study. A four level data collection questionnaire of semi structured questions was used in data collection. Reliability, content and validity of the questionnaire were tested through pilot tests and pre-tests by the researcher. Qualitative data was cleaned, coded and analyzed using inferential statistics. SPSS software version 20 and Microsoft excel were used to clean and analyze the quantitative data. Appropriate descriptive statistics were done using absolute numbers, percentages and tables. It was found out that all the three factors studied had a positive correlation and thus had an influence in the utilization of data for decision making among health program managers. It was also established that there was a substantial relationship between all the three variables termed as independent with information utilization as dependent variable. On behavioural factors roles and responsibilities (nature of work) affected data collection and use with a p value of 0.0007<0.05 and Pearson coefficient correlation of 0.694, also staff competence/skills and positive attitude had a relationship to the use of information at a Pearson value of 0.305 and lack of incentives to use information and nature of work related to information use at Pearson value of 0.239. On technical factors, availability of information for use was seen to be affected negatively by knowledge on IT (rho -0.726), system complexity (rho -0.711) and lack of documentation tools (rho -0.719). Organizational factors especially support for data review and sharing forums were seen to affect information use at p value of 0.017 <0.05 and rho 0.376. All the three hypotheses tested in the study were therefore not rejected. The study established that utilization of health management information for decision making among health program managers in Malindi Sub County is ongoing (97.4%) however it is determined by behavioral, technical and organizational factors and that organizational factors played a key role in enhancing the behavioral and technical factors. It is therefore recommended that these three factors should be enhanced and strengthened so as to maximize the use of information to make decisions in Malindi Sub County. It is also recommended that the same research be conducted in other sub counties of the county to correlate this information. Also, it is recommended that another research to assess the knowledge, attitude and perception of the health workers on data collection tools should be conducted.
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