An investigation of analytics and business intelligence applications in improving healthcare organization performance: a mixed methods research

UNCG Author/Contributor (non-UNCG co-authors, if there are any, appear on document)
Rudolph Tetteh Bedeley (Creator)
Institution
The University of North Carolina at Greensboro (UNCG )
Web Site: http://library.uncg.edu/
Advisor
Lakshmi Iyer

Abstract: The healthcare ecosystem in the US is currently undergoing series of refinement and reformation due to the need to (i) improve quality of care and (ii) reduce cost. To achieve their key objective, healthcare organizations (HCOs) currently face a fundamental challenge: how to best use or optimize limited resources while providing better care and services to patients? The answer to this question might lie within HCO’s massive data and the ability to identify and apply appropriate analytics and business intelligence (A&BI) techniques and technologies to discern and extract relevant information and knowledge from that data. However, despite the increasing interest in the implementation and utilization of A&BI techniques and technologies by various organizations to improve operational efficiencies and financial performance, HCOs still lag behind other sectors in the adoption and use of A&BI capabilities. Motivated by the “data rich but information poor” syndrome currently facing HCOs, this dissertation applies a mixed method research–case study (interpretivist) and survey (positivist) – to investigate how healthcare organizations can leverage A&BI techniques and technologies to improve their overall performance. In achieving this objective, I illustrate an exemplar of how A&BI techniques and technologies can effectively be applied by specifically answering this high-level research question (RQ): How can A&BI techniques, methods, and technologies be developed and leveraged to improve performance in healthcare organizations? This high-level RQ has been broken down into four sub-questions that will be answered in two different studies in this dissertation. In the first study, I investigate what combination of A&BI techniques and technologies HCOs are currently applying to create value. This study was conducted by using content/literature analysis and case study methods in a large healthcare organization. The second study builds on the first study to investigate, using both interview and survey data, how A&BI capabilities can be developed, cultivated and nurtured as a core competency or capability that significantly helps improve healthcare organizations’ overall performance (such as cost reduction, quick access to providers and treatment, effective diagnostics, etc.). I found very novel and interesting results in both studies that not only address the research questions, but also provide significant theoretical and practical contributions. Major contributions of study 1 include: revising and remodeling of an outdated healthcare value chain (HCVC) framework that is more realistic and applicable to current care delivery practices in the healthcare industry and mapping of A&BI capabilities to the different domains of the revised HCVC framework. Study 2 provides theoretical contribution to the existing literature by conceptualizing and empirically validating A&BI capability as a third-order multi-dimension construct and its significant influence on performance.

Additional Information

Publication
Dissertation
Language: English
Date: 2017
Keywords
Analytics, Analytics Capability, Business Intelligence, Healthcare Value Chain, Organization Performance, Predictive Analytics
Subjects
Health facilities $z United States $x Business management
Health services administration $x Information technology $z United States
Medical care $x Information technology $z United States
Medical informatics $z United States
Health care reform $z United States

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