An Investigation into the impact of automation on efficiency of Kenyan Hospitals

By: Contributor(s): Publication details: Nairobi Strathmore University 2017Description: x, 50pSubject(s): LOC classification:
  • RA971.23.G43 2017
Online resources: Summary: As per the 2017 guidelines governing health facilities in Kenya, a health management information system (HMIS) has become mandatory in every level of health facility. However, the relationship between these HMIS and efficiency is not fully understood in Kenyan contexts. This study examined the determinants of successful automation of operations in Kenyan hospitals. It argued that automation ought to have positive impacts on efficiency in the operations of Kenyan hospitals and sought to corroborate this thinking. Factors determining the success of the required automation were studied and ranked and hence allowed the selection of the most important during implementation of the HMIS so as to get the biggest benefit. As a research method, the study used both descriptive and inferential approaches. Data was collected by way of a questionnaire distributed to the target population which included all the Level 4, 5, and 6 hospitals in Nairobi spanning both public and private sectors. Data analysis was done with descriptive and inferential statistics through linear regression and exploratory factor analysis. The data was represented through pie charts, graphs for descriptive statistics. For the inferential statistics, correlation matrix and regression analysis was used. The results showed that only 48.1% of hospitals have automated systems as required by law. It also showed that the main determinant of successful automation was training and user buy-in totaling to over 82% of the success of automated system. Automation was also shown to have a positive impact on efficiency in terms of cost reduction. The conclusions drawn from this study were that automation in Kenyan hospitals were subpar, and that successful automation depended on adequate training and user buy-in. This study also showed that the highest impact on efficiency by these automated systems was on cost reduction. The study recommends that an adequate budget allocation be made for training and buy-in of the end user. Further research should be done to elaborate on duration and types of methods used in training.
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Thesis Thesis Special Collection Processing Center RA971.23.G43 2017 Not for loan 78596
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As per the 2017 guidelines governing health facilities in Kenya, a health management information system (HMIS) has become mandatory in every level of health facility. However, the relationship between these HMIS and efficiency is not fully understood in Kenyan contexts. This study examined the determinants of successful automation of operations in Kenyan hospitals. It argued that automation ought to have positive impacts on efficiency in the operations of Kenyan hospitals and sought to corroborate this thinking. Factors determining the success of the required automation were studied and ranked and hence allowed the selection of the most important during implementation of the HMIS so as to get the biggest benefit. As a research method, the study used both descriptive and inferential approaches. Data was collected by way of a questionnaire distributed to the target population which included all the Level 4, 5, and 6 hospitals in Nairobi spanning both public and private sectors. Data analysis was done with descriptive and inferential statistics through linear regression and exploratory factor analysis. The data was represented through pie charts, graphs for descriptive statistics. For the inferential statistics, correlation matrix and regression analysis was used. The results showed that only 48.1% of hospitals have automated systems as required by law. It also showed that the main determinant of successful automation was training and user buy-in totaling to over 82% of the success of automated system. Automation was also shown to have a positive impact on efficiency in terms of cost reduction. The conclusions drawn from this study were that automation in Kenyan hospitals were subpar, and that successful automation depended on adequate training and user buy-in. This study also showed that the highest impact on efficiency by these automated systems was on cost reduction. The study recommends that an adequate budget allocation be made for training and buy-in of the end user. Further research should be done to elaborate on duration and types of methods used in training.

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