Determinants of Point-of-Care Technology Use among Health Care Workers in Comprehensive Care Centres, A Case of Central Kenya
Abstract
The Point of Care (POC) approach is the highest level of interaction between health care workers (HCW) and the information system, which generally requires interaction during clinical meetings. Although it is hard to do so, it offers the most significant benefits. The POC strategy offers the system’s benefits to healthcare workers, patients, and those who monitor and evaluate them. The study focused on identifying key determinants of point-of-care technology use among healthcare workers offering services in comprehensive care centres in Central Kenya. A Cross-sectional descriptive study was adopted, two-stage cluster sampling design method was used in determining the sample size. The study involved a sample size of 217 respondents and over a 100% was achieved. The study results revealed that social demographic factors of health care workers have no significant influence on POC technology use as a p-value of above 0.05 was observed on all the variables. Some organisational factors such as adequate workstations (p = 0.0) and EMR reducing patient time (p = 0.012) were found to have significant influence on POC technology use. Significant influence on POC use was noted on source of funding for software and hardware maintenance (p = 0.001). The utilisation of EMR to review client progress in real-time (p = 0.001) was found to have a significant influence on POC technology use as well as the use of EMR to report to the national reporting system (KHIS) (p = 0.014). 71% of respondents reported that availability of clinical decision support features in the EMR was contributing to improved use of POC. An overwhelming 72% reported that they were very motivated to use POC technology due to the ability of auto generating reports. In addition, three factors were highlighted as key contributors to the success of POC use, and these were reliable power supply (44%), adequate and trained healthcare workers (24%), standard and stable EMR Systems (17%). The study recommended for adequate training of health care workers, adequate workstations, and reliable power supply. For initial implementers of EMRs, they should consider having Standard EMRs that support both clinical decision support features and automated reporting.
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Copyright (c) 2023 Keziah Muiruri, Kevin King’utu, Mary Wangui Gitahi, PhD, George Ochieng Otieno, PhD
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