Factors influencing utilization of routine health data in evidence based decision making in Hiv/Aids services by public health facilities in Nakuru county

Abstract

Most Ministries of Health across Africa invest substantial resources in some form of health management information system (HMIS) to coordinate the routine acquisition and compilation of monthly treatment and attendance records from health facilities nationwide. The relationship of improved information, demand for data, and continued data use creates a cycle that leads to improved health programs and policies. However, despite the expense of the HMIS, poor data coverage means they are rarely, if ever, used to generate reliable evidence for decision makers. The purpose of this study was to examine the factors influencing the utilization of routine health data in evidence based decision making by public health facilities offering HIV treatment services in Nakuru County. According to the Kenya HIV Estimates Technical Report of 2013, Nakuru County is one of the 10 counties with the highest number of people (61,598) living with HIV/AIDs in the county and therefore chosen as a study point. The study adopted a descriptive survey research design. The study was guided by the following objectives; to assess the influence of data quality on evidence based decision making; to establish the influence of data availability on evidence based decision making; to examine the influence of capacity on data use competencies in evidence based decision making and to investigate the influence of institutional support in evidence based decision making by public health facilities in Nakuru county. A structured questionnaire was used to collect data from 58 respondents from 33 health facilities providing HIV/AIDs treatment services. A stratified random sampling technique was used to achieve the desired representation of the various subgroups within the population and simple random sampling was applied to identify respondents from the facilities. Data was analyzed using frequencies, percentages, mean, standard deviation, coefficient of variation and correlation coefficient with the aid of Statistical Packages for Social Sciences (SPSS) computer software version 20.0. The results were presented in tables. From the coefficient correlation analysis, only data quality and capacity on data use had significant positive relationship on evidence based decision making. I.e. data quality at r =.368** with p =.004 (<0.05) and capacity on data use competencies r =.323* with p =.013 (<0.05). There was no significant relationship between data availability r =.059 with p = 662 (>0.05) and institutional support r =.087and p = .514 (>0.05) with evidence based decision making. The study therefore recommends that there is need to develop and implement data quality protocols at the health facilities, train health care providers on synthesis and communication of routine health data using appropriate channels, need for training in leadership and advocacy skills for health managers to leverage on funding and sustaining data use and demand interventions and lastly, need to develop standard operating procedures that clearly state the role and value of data in organizational functioning. There is need for further research on the cost and effectiveness of using routine health data in planning and management.