Business intelligence application for patient reported experience measures (PREMs) to support performance management analytics
| dc.contributor.author | Shaiket, MD Hosne Al Walid | |
| dc.contributor.examiningcommittee | Carson, Kai-Sang Leung (Computer Science) Noman, Mohammad (Computer Science) | en_US |
| dc.contributor.supervisor | Pourang, Irani (Computer Science) | en_US |
| dc.date.accessioned | 2022-01-24T22:29:17Z | |
| dc.date.available | 2022-01-24T22:29:17Z | |
| dc.date.copyright | 2022-01-24 | |
| dc.date.issued | 2022-01-07 | en_US |
| dc.date.submitted | 2022-01-24T22:14:12Z | en_US |
| dc.degree.discipline | Computer Science | en_US |
| dc.degree.level | Master of Science (M.Sc.) | en_US |
| dc.description.abstract | Business Intelligence (BI) is a widely known technology that is used to facilitate decision-making processes in many organizations. BI is a collection of decision support technologies that provides information and knowledge from a variety of sources, analyzes them, and presents them in a user-friendly fashion. Research into the adoption, utilization, and success of BI systems has grown substantially over the past two decades. However, despite the growing investments and significant market expansion, evidence suggests that several organizations fail to reap benefits from the implemented BI systems. Nearly 60% to 70% of BI projects fail to yield the expected returns or often result in little or no benefits for organizations. Previous studies report that although user under-utilization and resistance are vital challenges, little empirical research has focused on user-centred issues. From the literature’s findings, it is notable that organizational and Information Systems (IS) perspectives were more frequently considered, while a little light has been shed on users’ perspectives of BI application. In this thesis, we developed a BI application with interactive visualization based on the Emergency Departments (ED) patient survey data of British Columbia (B.C.), Canada to visualize the important insights for better healthcare decision-making. We also investigated if a BI application can equally benefit both novice and expert users within an organization. The purpose of this thesis is to develop and understand how BI facilitates the decision-making process for all types of users within an organization regardless of their previous experience with BI application use. We evaluated our developed application using a user study which includes an online semi-structured interview followed by survey questionnaires to investigate the effect of the user’s prior experience on their performance and perception of BI application. Our study found that BI applications are not equally beneficial to novice and experienced users in terms of performing analytical tasks. We found a significant experience effect in completing the difficult analytical tasks, and experienced users significantly overperformed the novices in performing difficult analytical tasks independently. But interestingly, we found no significant impact of the user’s prior experience on their usability perception of a BI application. Based on the interview findings, we also proposed a design recommendation both for novice and experienced users to develop a BI application that can potentially increase BI adoption and success within an organization. | en_US |
| dc.description.note | February 2022 | en_US |
| dc.identifier.uri | http://hdl.handle.net/1993/36213 | |
| dc.language.iso | eng | en_US |
| dc.rights | open access | en_US |
| dc.subject | Business intelligence | en_US |
| dc.subject | Data modeling | en_US |
| dc.subject | Extract-transform-load (ETL) | en_US |
| dc.subject | Healthcare analytics | en_US |
| dc.subject | Patient-reported experience measures (PREMs) | en_US |
| dc.subject | Patient-centered measurement (PCM) | en_US |
| dc.title | Business intelligence application for patient reported experience measures (PREMs) to support performance management analytics | en_US |
| dc.type | master thesis | en_US |