ABSTRACT: 

Objective: The project aimed to call to mind the exploration of health management and information systems among healthcare workers at Kenyatta National Hospital, Kenya.
Design setting: The investigation deployed a cross-sectional study.
Subjects or participants: A sample total of 263 respondents was calculated using the Krecie and Morgan formula for the quantitative study. A strict inclusion criterion was followed to select the respondents from all trained health personnel in Kenyatta National Hospital. The study utilized an interview schedule. Data were analyzed using SPSS version 21 while qualitative data was analyzed on themes developed. Data presentation was in the form of quantitative statistics such as frequency distribution, percentages and tables. Qualitative results were presented in verbatim form.
Results: A total of 263 respondents were engaged in the quantitative study. The study utilized a questionnaire and a key informant interview guide. Before processing quantitative data, data was cleaned, coded and keyed into MS Excel database computer and analyzed using SPSS version 21. Descriptive statistics were used to describe measures of central tendency and dispersion. Findings were presented using frequency distributions and summary tables. Associations between predictor and outcome variables were run through Correlational statistics. Of the 263 respondents, 193 (72.6%) were optimistic that HMIS had brought about better up-dating and expertise in healthcare service delivery and 40(15%) were neutral while, 33(12.4%) were pessimistic about the concept. A weak positive correlation (r = 0.3345, p =0.03) between self-confidence in productivity and HMIS implementation was observed.
Conclusion: The KNH management needs to ensure that there is system thinking, where each staff is not only motivated but also feels part and parcel of a robust and cohesive HIMS process

KEYWORDS :

Health Information, Health System, Health Management Information System, Interoperability, Universal Health Coverage, Implementation, Digital Transformation, Augmentation, Standardized

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