Automated Clinical Decision Support in HIV management: a comparative study of Point-of-Care and Retrospective Data Entry outcomes

Simple item page
dc.contributor.authorMasibo, Wundundi Sammy
dc.date.accessioned2022-08-02T07:25:16Z
dc.date.available2022-08-02T07:25:16Z
dc.date.issued2021
dc.descriptionA Dissertation submitted in partial fulfillment of the requirements for the award of the Degree of Master of Business Administration in Healthcare Management at Strathmore Universityen_US
dc.description.abstractKenyan healthcare facilities are increasingly adopting electronic medical records (EMRs) and electronic health management information systems (HMIS). Many public hospitals have automated HIV/AIDS care services in pursuit of efficiency and better patient outcomes. This has triggered interest in clinical decision support (CDS) systems. The CDS systems are designed to provide patient-specific information that is intelligently filtered to healthcare providers at appropriate times to enhance clinical decision-making. Studies have shown that automating CDS has certain advantages over manual systems. What remains unclear is whether the way the automated CDS is deployed has an impact. Point-of-care deployment refers to the use of CDS systems at the actual time of service delivery (data collection and system delivery are concurrent). Data is entered in real-time. Retrospective data entry (RDE) refers to deployment of systems to be used after the actual service delivery. Data is captured in primary manual tools and later transferred to the electronic database after the fact. This study sought to establish whether deploying a CDS system at point-of-care (POC) is more beneficial than deploying it retrospectively given the incidental capital outlays for POC systems. The study entailed a cross-sectional analysis of data collected through the KenyaEMR system; an electronic medical records system developed to manage HIV/AIDS services in Kenya. The study found that deploying CDS systems at point-of-care results in a lower patient missed appointment rate (21.34%, SD 8.24) compared to CDS applied retrospectively (31.58%, SD 15.47). CDS systems deployed at POC also result in better viral load testing rates (42.06%, SD 10.49) compared to retrospective CDS (37.56%, SD 10.03). There was no significant variation in the viral load suppression rates between POC and RDE modes (81.88%, SD 7.47 and 79.67%, SD 7.63 respectively). The study also enumerated challenges faced by system end-users when KenyaEMR is deployed retrospectively. These included duplication of work (84%) and lack of quality and timely data (74%). The potential barriers that constrain facility transition from retrospective data entry to point-of-care deployment were also established and included inconsistent power supply (95%) and negative staff attitude (74%).en_US
dc.identifier.urihttp://hdl.handle.net/11071/12918
dc.language.isoenen_US
dc.publisherStrathmore Universityen_US
dc.subjectKenya EMRen_US
dc.subjectHIV/AIDSen_US
dc.subjectPoint-of-Care (POC)en_US
dc.subjectRetrospective Data Entry (RDE)en_US
dc.subjectClinical Decision Support (CDS)en_US
dc.titleAutomated Clinical Decision Support in HIV management: a comparative study of Point-of-Care and Retrospective Data Entry outcomesen_US
dc.typeThesisen_US
Files
Original bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
Automated Clinical Decision Support in HIV management - a comparative study of Point-of-Care and Retrospective Data Entry outcomes.pdf
Size:
2.36 MB
Format:
Adobe Portable Document Format
Description:
Full - text thesis
Download
License bundle
Now showing 1 - 1 of 1
Thumbnail Image
Name:
license.txt
Size:
1.71 KB
Format:
Item-specific license agreed upon to submission
Description:
Download
Collections
MBA-HCM Theses and Dissertations (2021)