Examining health information systems success factors in Uganda’s healthcare system
Abstract
Healthcare Health Information Systems offer several benefits towards healthcare service delivery in Uganda including
easy record keeping, enhancing communication, performing simple calculations, supporting decision making, gaining
competitive advantage, better management of chronic diseases, faster retrieval of records, improving process flow and
increasing productivity. However, the benefits mentioned have been hindered by failure of HIS in Uganda. The success
factors for Information Systems in Ugandan healthcare system are largely unknown. The effect of these failures is most
felt in Small and Medium Healthcare Enterprises who have limited resources and semi-skilled employees.
This study determines success factors for Information Systems in Small and Medium Healthcare Enterprises in a
developing country context like Uganda. The findings of the study therefore aid in understanding the key issues that
lead to the success of Information Systems in developing countries, Uganda in particular.
The study targeted staff of Small and Medium Healthcare Enterprises including doctors, nurses, administrators and
laboratory attendants. A sample of 274 was taken from 954 health units but only 202 questionnaires were considered
for analysis after data cleaning. Data were analyzed using Convergent and Discriminant Validity, Rotated Component
Matrix tables, Communality and Regression analysis.
The findings indicate that management support, user involvement, resource supply, and education and training are the
most important success factors for HIS success. Principal component analysis results obtained show that all items on
the listed variables had communalities above the significant level of 0.4, implying that all items exhibited sufficient
loadings. This therefore implies that each of the items correlates highly with all other items and can at least easily load
onto one of the factors. Further, multiple correlation coefficient R=0.717 obtained implies that there is a strong
relationship between the multiple independent factors and the dependent variable.