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Dissertation
Patient matching in health information exchange (HIE): a study of strategies, perspectives, & innovative solutions, in the data intensive era of healthcare
Doctor of Business Administration (D.B.A.), Drexel University
21 May 2025
DOI:
https://doi.org/10.17918/00010941
Abstract
In today's data intensive era of healthcare, Health Information Exchange (HIE) is thought of as a strategic tool that can be leveraged to help improve patient outcomes (Wu & LaRue, 2017). Yet, electronically sharing data between organizations can be challenging (Just et al., 2016) and a critical prerequisite step in that process is patient matching (Godlove & Ball, 2015), defined as the identification and linking of one patient's electronic health record within and across health system boundaries. The goal, to obtain a comprehensive view of that patient. This study utilizes a qualitative, grounded theory methodology, drawing on insights from 27 HIE expert interviews, and explores the complex landscape of patient matching. The research delves deeply into the value and problematic areas of HIE patient matching and reveals a novel theoretical framework, termed "Triadoxical Matching Dynamics", which highlights the interplay of three key factors: the "Value Striving Cycle", representing HIE's proactive efforts to enhance patient care through robust infrastructure and innovative use cases; "Funneling Matching Pressures", encompassing data quality issues, programmatic deficiencies, and technical limitations that contribute to matching errors, including false positives and false negatives; and "Macro Misaligning Contributors," highlighting systemic challenges such as conflicting government policies, fragmented ecosystem partnerships, and a lack of standardized reporting practices. This study reveals the critical importance of addressing these multifaceted challenges to improve patient safety, optimize HIE effectiveness, and ensure the integrity of healthcare data exchange, as data becomes more fragmented (Vest & Gamm, 2010). By unearthing the intricate dynamics influencing patient matching, this research provides valuable insights for stakeholders seeking to enhance HIE programs and ultimately improve patient care. Especially as there are numerous efforts around the country with HIE as part of their healthcare agenda (Holmgren & Adler‐Milstein, 2017). The study confirms HIEs put immense thought and care into patient matching activities, through effective program oversight, robust infrastructure, and innovative use cases. However, that value is tempered as part of an HIE ecosystem, as it is also disclosed that HIEs face challenges like false positives, false negatives, data inconsistencies, and technical limitations that impede HIE effectiveness. Contributing factors such as varying state-level consent models, the absence of a Universal Patient Identifier (UPI), fragmented collaboration, and inadequate transparency further pressurize matching programs. Industry expert sentiment calls for action, they envision enhanced accountability, technological advancement, and patient empowerment, advocating for stronger government enforcement, standardized definitions, modernized data intake, and the responsible use of Artificial Intelligence (AI). This updated view on the state of HIE patient matching has tremendous implications for the industry, and highlights the urgent need for a collaborative, multi-stakeholder approach to address the "Triadoxical Matching Dynamics" concept and findings. Implementing standardized practices, fostering technological innovation, and aligning policy frameworks are essential steps towards achieving seamless and accurate patient matching. Ultimately, this will ensure the full potential of HIE is realized, leading to improved patient safety, enhanced healthcare delivery, and a more efficient and equitable healthcare ecosystem.
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Details
- Title
- Patient matching in health information exchange (HIE)
- Creators
- Thomas R. Licciardello
- Contributors
- David Gefen (Advisor)
- Awarding Institution
- Drexel University
- Degree Awarded
- Doctor of Business Administration (D.B.A.)
- Publisher
- Drexel University; Philadelphia, Pennsylvania
- Number of pages
- xvi, 202 pages
- Resource Type
- Dissertation
- Language
- English
- Academic Unit
- Bennett S. LeBow College of Business; Drexel University
- Other Identifier
- 991022052935104721