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Master of Science in Health Systems Management

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    Factors Influencing Utilization of Health Information Data in Nairobi County Public Health Facilities, Kenya
    (KeMU, 2022-10) Njuguna, Duncan Chege
    Effective management of today's health systems depends on the critical use of data and information for policy formulation, planning, service monitoring, and decision-making. However, data use has been restricted and inadequate; resulting in vital health decisions frequently being based on political opportunism, donor demand, and infrequently repeated national studies that are insensitive to changes occurring over a shorter timescale. This study's objective was to investigate the factors that influence the utilization of Health information data. Specifically, assess the influence of data quality, establish the extent to which individual factors determines utilization of health information data, establish the level of staff involvement influences the utilization of health information data and identify organizational factors that influences the utilization of health information data in Nairobi County Public Health Facilities. A descriptive cross-sectional study employing quantitative methodology was conducted with at least 216 participants. Using a multistage sampling technique, the sample size of respondents was determined. Three public health facilities were sampled with proportional representation of respondents in each facility. Using SPSS version 25, quantitative data from structured questionnaires was entered, verified, cleaned, and analyzed. In the event of a relationship between categorical variables, the Chi-square test was applied. The majority of respondents were between the ages of 30 and 39, they were female, and were nurses. Majority also held a diploma as their highest level of education. Less than two- thirds of respondents (65.3%) used routine data for decision making on occasion. Additionally, (19.9%) and (14.8%) use routine data/health information for decision making infrequently and frequently, respectively. Level of education (p=0.025), gender of the health worker (p=0.010), cadre (p=0.001), participation in data discussion forums (p=0.013), training on data utilization (p=0.036), data collection (p=0.041), data analysis (p=0.032), data management (p=0.007), overall levels of competency (p=0.0001), access to routine data (p=0.001), access to a functional computer (p=0.023), and internet access (p=0.030). The researcher hopes that the study's findings will serve as a wake-up call for the management of public health facilities regarding the value of health information data in informing every decision made in the health facilities. The study recommends that County health management, in conjunction with the national level, provide training to improve health workers' skills, with a focus on routine data use, through on-the-job trainings and mentoring. It also recommended that the organizational context be improved by providing resources that support the use of information.
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    Factors Influencing Utilization of Health Information System in the Management of Missed Appointments among HIV Positive Patients in Mombasa County, Kenya
    (KeMU, 2022-10) Mbiya, Odilia Amalemba
    A health system requires a well-functioning health information system to enhance measurement of health outcomes, and ensure effective health care decisions. This process of utilizing health information, increases retention rate, improves patients‘ health outcome and reduces cost of care. With low retention rates among HIV positive patients, this study aimed at determining the factors associated with the utilization of health information in curbing missed appointments. The research study was guided by the following specific objectives: to establish infrastructural factors influencing health information utilization; to assess the influence of staff capacity on health information utilization; to determine the influence of staff supervision on utilization of health information; and to establish the existing behavioral factors that influence health information use among CCC health care providers. This study utilized descriptive cross- sectional study design using quantitative method of data collection to assess utilization of health information among healthcare workers. The study population for this research was approximately 215 CCC, a sample size of 69 health care workers in the three high volume hospitals offering HIV care in Mombasa County that contributed to high defaulter rate. Primary data was obtained via questionnaires while secondary data was obtained from hospital records available, via checklist. The data was coded and analyzed using the statistical package for social sciences (SPSS). A p-value of less than 0.05 was considered as statistically significant, Asymptotic Significance (2-sided) results indicated a p-value of .000 across all the four factors in relation to the Independent variable on Chi-square test (Infrastructure X1=138.182, p value .001, Staff capacity X1=168.368, p value .000, support supervision X1=145.811, p value .000 and behavioral factors X1=202.570, p value .000). For Spearman Rank Correlation, a strong positive correlation between supervisory factors and utilization of health information (r=.811, 9=.000), an indication that staff supervision improved data utilization hence reducing gaps that could lead to missed appointments, weak positive correlation between Infrastructural factors and utilization of health information, (rs=.114, p=.384), an indication that infrastructure was important mode in support of data capture and generation of reports thus improving in utilization of data reducing missed appointments. Moderate negative correlation between behavioral factors and utilization of HMIS, (rs= -.505, p=.000) an indication that staff attitude did not interfere with utilization of information therefore did not affect management of missed appointments. The study concludes that effective support supervision for the CCC health care workers in management of missed appointments would greatly improve data use and thus able to identify where gaps are, hence reducing number of missed appointments among HIV positive patients. Also the study concludes that effective quality targeted training of the staff would improve in data collection and use therefore reducing number of missed appointments among HIV positive patients. The study recommends establishment of SOPs to guide support supervision and also emphasis on continual training among the staff in the CCC. The institutions to also invest on reliable internet network for effective health information systems. There is need for further research to be done to determine other influencing factors in the service delivery of the 47 county governments.