IT Adoption, Diffusion, and Evaluation in Healthcare

Permanent URI for this collectionhttps://hdl.handle.net/10125/107485

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Competing Institutional Logics in the Health Information Exchange Field of US Healthcare Industry
(2024-01-03) Sun, Zuan
Inter-organizational collaboration on health information exchange (HIE) has been identified as one of the major challenges for further advancing the development of inter-organizational HIE networks in the US. Heterogeneous collaboration initiatives on HIE need to be overhauled from a holistic view to better understand future evolving directions. Key concepts in institutional theory, such as organizational field and institutional logic, provide an appropriate lens for digging deeper into this phenomenon. The structuration of the HIE organizational field informs that HIE stakeholders are not only social actors who conform to macro institutional environments - policies and regulations in healthcare, but also social agents who generate micro institutional environments in inter-organizational HIE networks - social networks of health provider (HP) organizations. Furthermore, the social networks weaved by different kinds of inter-organizational relationships become collaboration anchors for inter-organizational HIE networks.
Investigation of Current Translation Challenges and Barriers to the Use of Artificial Intelligence in the German Healthcare System
(2024-01-03) Erler, Christina; Perret, Sophie-Charlotte; Biri, Gergely; Stork, Wilhelm
It has been suggested that Artificial Intelligence (AI) could be the key to solving some of the biggest challenges (cost saving, care quality improvement, and personal load reduction) facing healthcare today. Although there is a growing trend in research, only a few of these research projects have reached the stage of medical approval. This raises the question of what hurdles and challenges impede the effective translation of AI technologies into routine healthcare practice. Our paper aims to investigate the current translation challenges and barriers to using AI in healthcare, specifically focusing on the European Union, particularly Germany. During our research process, with the help of a workshop and interviews with domain experts, we identified challenges and barriers and will provide a comprehensive overview of the hurdles hindering AI adoption in multifaceted healthcare.
Implementation of Electronic Health Records (EHR) and its impact on readmissions and Total Performance Score (TPS): an analysis of American Hospital Association’s (AHA) data
(2024-01-03) Dadgar, Kourosh; Lo, Claudia
This study investigates the impact of EHR (Electronic Health Records) implementation on hospitals' readmissions and total performance score (TPS). Hospitals adopt and implement EHR to improve quality of care and improve patients' care process and experience. Data from American Hospital Association (AHA) and Centers for Medicare & Medicaid Services (CMS) are used to measure the impact of EHR implementation. Our results show that EHR implementation increases readmissions in large hospitals and increases TPS scores in hospitals located in non-metro areas. The practical implications of the results are discussed in the paper.
Influence of Audio Speech Rate and Source Text Difficulty on Health Information Comprehension and Retention
(2024-01-03) Ahmed, Arif; Leroy, Gondy; Lee, Sumi; Harber, Philip; Kauchak, David; Rains, Stephen A.; Barai, Prosanta
Health literacy is crucial for patients to make informed healthcare decisions. Although text has historically been the main form of health information dissemination, people rely increasingly on audio-delivered information, e.g., through smart speakers. In this study, we evaluate the effects of audio speech rate and text difficulty on audio information comprehension and retention. We created audio snippets from easy and difficult text and conducted a study on Amazon Mechanical Turk (AMT). Audio speech rate and source text difficulty are the independent variables and perceived difficulty (measured with a Likert scale) and comprehension and retention (measured with AI-generated multiple-choice questions and free recall of information) are the dependent variables. Audio created from difficult source text was perceived as more difficult and comprehension was also lower than for audio from easy text. Speech rate also influenced information comprehension and retention of information: a higher speech rate (+60% faster audio speech rate) lowered the comprehension of health information by 38% compared to a moderate speech rate.
Understanding the Information Privacy Concerns of Digital Contact Tracing Application Users
(2024-01-03) Rostami, Ashkan; Farhadloo, Mohsen; Bishnoi, Rakesh
Given the anticipated instrumentality of digital Contact Tracing Applications (CTAs) in tracing the sources of infectious diseases, such applications have not been widely adopted by the general public. One major barrier to the diffusion of CTAs is public concerns about the privacy of their information. In this study, we first measured the attitudes of Canadians toward the nature of information privacy. We then distinguished and measured general and specific information privacy concerns of Canadians to better understand such concerns in the context of CTAs. Finally, we explored the potential associations between participants’ attitudes toward information privacy and their major information privacy concerns. Our results shed light on the relative importance of various types of information privacy concerns in general and in relation to CTAs, and how such concerns might be affected by one’s attitudes toward information privacy.
DELEGA(I)TING HEALTHCARE TASKS – A Qualitative Analysis of AI Delegation Factors for Healthcare Professionals
(2024-01-03) Nserat, Joseph; Braun, Marvin; Kegel, Felix; Kolbe, Lutz
Artificial Intelligence (AI) has the potential to tackle the challenges of the healthcare industry by relieving the workforce and reducing costs. As the capabilities of AI advance, it becomes more capable of conducting sophisticated tasks autonomously, such as detecting symptoms and suggesting treatments. To realize these benefits, AI needs to be embedded into daily medical practice. In this context, understanding how and under which circumstances healthcare professionals delegate tasks to AI is crucial for a successful integration. Hence, we investigate drivers of task delegation to AI in healthcare by conducting interviews with 30 physicians from a wide range of disciplines. We find that task delegation in healthcare differs from general AI task delegation frameworks and even within activities of healthcare. Moreover, we confirm our findings through a qualitative comparative analysis. Thereby, our work contributes to understanding why and based on which factors physicians are willing to delegate tasks to AI.
Accelerating the Adoption of Artificial Intelligence Technologies in Radiology: A Comprehensive Overview on Current Obstacles
(2024-01-03) Hennrich, Jasmin; Fuhrmann, Hannah; Eymann, Torsten
Radiology has always been considered a highly technological field in medicine. Recently, a new area of radiology has emerged with the adoption of Artificial Intelligence (AI)-based health information systems due to advancements in big data, deep learning, and increased computing power. While AI elevates prevention, diagnostics, and therapy to a new level, various obstacles hinder the adoption of AI technologies in radiology. To provide an overview on these obstacles as basis for corresponding solution approaches, we identify and comprehensively outline these obstacles by conducting a structured literature review. We find 17 obstacles, which we group into six categories. Furthermore, our research discusses relevant interrelations of the obstacles, most of which we have found to be related to user attitude. Besides, these complex interrelations we expose the necessity of approaching the obstacles simultaneously.
Examining Continuance Intention to Exercise in a Virtual Reality Environment
(2024-01-03) Ekpezu, Akon; Nutrokpor, Charles; Wiafe, Isaac; Oinas-Kukkonen, Harri
The use of virtual reality (VR) as a persuasive technology has gained research attention. However, few empirical research has been conducted to explain how persuasive systems design (PSD) features and user experience features affect users’ continuance intention to use VR to exercise. This study aimed to examine the factors that influence continuance intention to use VR to exercise. A VR exercise environment was developed, and quantitative data was collected from 118 users post-exercise. Results of the partial least squares structural equation modeling analysis showed that perceived enjoyment, effectiveness, and persuasiveness significantly influenced continuance intention. However, perceived effectiveness had the strongest impact. The exogenous driver constructs (primary task support, dialogue support, credibility support, and perceived immersion) also significantly influenced continuance intention. These findings highlight how the association between user experience and PSD features may be considered in the development of VR exercise systems to improve adoption and compliance.
Impact of Telemedicine Technology Tools and Perceived Barriers on Satisfaction and Continued Usage Intention of Office-based Physicians
(2024-01-03) Liu, Xiang; Sengupta, Avijit; Xu, Dongming
Government-imposed lockdowns and shelter-in-place orders during COVID-19 have accelerated the adoption of telemedicine for remote patient monitoring, consultation, diagnosis, and care. However, healthcare providers’ utilization of and satisfaction with telemedicine technologies could have a significant impact on the quality of care provided to patients during COVID-19. The objective of our study is to investigate the impacts of telemedicine technology tools and perceived barriers on physicians’ overall satisfaction and continued usage intention of telemedicine in office-based ambulatory care settings. With the help of task-technology fit model we develop a set of hypotheses and then test those hypotheses empirically with the help of National Electronic Health Records Survey (NEHRS) response data. While we find significant impacts of telemedicine technology tools on physicians’ satisfaction and continued usage intention, perceived barriers only significantly impact physicians’ satisfaction but not the continued usage intention. Our research has significant implications for both theory and practice.
Activity Theory Analysis of the Drivers of Telemedicine: A Mixed Methods Study
(2024-01-03) Parameswaran, Vijaya; Lyytinen, Kalle; Aron, David; Stange, Kurt
Telemedicine has a rich history, and recent advancements in communication technology have expanded its potential. Despite COVID-19 pandemic-related surges, telemedicine has returned to pre-pandemic levels in some settings, highlighting the need to understand the drivers and contextual factors. Previous studies using linear prediction models and single-method approaches fail to capture the complexities and nonlinear relationships among clinicians, patients, technology, and clinical tasks. We employ a concurrent mixed-method approach, combining quantitative analysis of electronic medical record (EMR) data and Activity Theory analysis of clinician interviews to investigate telemedicine drivers in primary care clinics. Findings confirm the significant role of clinicians and challenge assumptions of resistance to technology. Clinicians exhibit Plasticity and Elasticity by balancing roles, adjusting routines, and prioritizing patients' clinical and social needs to accommodate telemedicine. It informs technological design interventions to enhance telemedicine and clinical care, including data transfer, virtual touch, and sociodemographic integration into EMR.
Technology-Enabled Type-1 Diabetes Self-Management – Protection Motivation Theory Perspective
(2024-01-03) Bozan, Karoly; Bozan, Gabriella
There is a growing emphasis on technology-enabled self-management among patients with chronic conditions such as Type-1 (T1D) diabetes. Regular self-monitoring empowers individuals with Type-1 diabetes to actively participate in their care, make informed decisions, and adjust their treatment plans as needed. Mobile applications are available to support patients' efforts, yet many users do not utilize them to help manage their care. In this study, we integrated the Unified Theory of Acceptance and Use of Technology (UTAUT) with the Protection-Motivation Theory (PMT). By integrating PMT into UTAUT, we can incorporate the motivational factors associated with health threat perception and protective behaviors specific to adolescent diabetes patients. PMT adds a layer of understanding by considering the perceptions of severity, vulnerability, response efficacy, and self-efficacy, along with reward and response cost. The collected responses to our survey among related m-health app users and non-users were analyzed using an independent 2-tailed t-test. The PMT constructs highlighted that T1D self-monitoring app users perceived their disease as more severe with higher self- and response efficacy but lower response cost. Non-users perceive T1D-related health threats differently and may have different coping mechanisms. Results, implications, and future research directions are discussed.
Introduction to the Minitrack on IT Adoption, Diffusion, and Evaluation in Healthcare
(2024-01-03) Kamis, Arnold; Bozan, Karoly; Spil, Ton

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