IT Adoption, Diffusion, and Evaluation in Healthcare
Permanent URI for this collection
Browse
Recent Submissions
1 - 10 of 10
-
ItemWhere to Start with AI?—Identifying and Prioritizing Use Cases for Health Insurance( 2022-01-04)Artificial Intelligence (AI) arguably represents a key technology for the digitalization of health care. Specifically, health insurers can benefit from AI as they typically have access to vast amounts of data. However, practitioners struggle to adopt AI in productive use, and extant research lacks an overview of use cases for AI in health insurance as well as prioritization criteria that can guide their implementation. To address this gap, we conduct explorative interviews in the context of the German statutory health insurance system. We identify AI use cases in the areas of predictive health, individualized service, anomaly detection, and operations enhancement. We find that health insurers are likely to prioritize these use cases according to implementation complexity and business orientation, whereas focusing on simple use cases that target cost savings is recommended by experts. Our study advances the understanding of AI adoption in health insurance and supports practitioners in guiding future AI initiatives.
-
ItemTrust Recipes for Enhancing the Intention to Adopt Conversational Agents for Disease Diagnosis: An fsQCA Approach( 2022-01-04)In this study, we examine the configurations of trust-enhancing factors that determine the intention to adopt conversational agents (CAs) for disease diagnosis. After identifying trust factors influencing the behavioral intent to adopt CAs based on the information systems acceptance research field, we assigned 201 participants to use the mobile Ada application and surveyed them about their experience. Ada is a medical diagnostic CA that combines patients’ symptoms with their medical history and provides diagnostic suggestions. The collected data was analyzed using a fuzzy set qualitative comparative analysis to capture the causal complexity of trust. We identified several configurations of trust-enhancing factors affecting the intention to adopt the CA. In particular, our results show that the adoption intentions are strongly determined by trust factors associated with the performance dimension. Furthermore, we derived two propositions for the development of CAs for healthcare purposes and elaborated implications for research and practice.
-
ItemPredicting Medical Students’ Intention to Integrate Digital Health into their Medical Practice: A Pre- and Post-COVID-19 Survey in Canada( 2022-01-04)In recent years, many stakeholders have advocated digital health (dHealth) as a promising avenue to reduce inefficiencies, increase the accessibility and quality of care, and manage infectious diseases. In this context, an emerging issue for researchers and practitioners lies in the dHealth education and training that must be provided to medical students to prepare them to make effective use of dHealth technologies, and of artificial intelligence (AI) in particular, in their future medical practice. In addressing this issue, this paper aims to validate a theoretical model that hypothesizes relationships between medical students’ individual background, experimentation with dHealth, perceived dHealth education needs, and openness to AI-related innovations. To do so, a two-phased survey study of Canadian medical students was realized. Results confirming all but one of the research hypotheses thus constitute a valid basis for prediction and prescription with regard to the students’ integration of dHealth into their medical practice.
-
ItemInvestigating the impact of social support embedded in online consultation on physicians’ online reputation: The moderating role of media capabilities( 2022-01-04)The importance of physicians’ online reputation (POR) has been recognized in the healthcare consultation process. However, few studies provide physicians with practical advice that help them improve their online reputation. Drawing on the taxonomy of social support and media synchronicity theory, this study proposes a theoretical model to study the relationship between physicians’ computer-mediated social support (CMSS) and POR, and the moderating effect of media capabilities on above relationships. This study collects online consultation records from a leading Chinese online consultation platform and employs the long short-term memory (LSTM) model to extract measurements of two types of CMSS. Our finding suggests that physicians’ action-facilitating support and nurturant support have significant positive impacts on POR. Furthermore, physicians’ communication frequency and communication depth strengthen the relationship between physicians’ action-facilitating support and POR. Readability strengthens the relationship between social support and POR. This study provides implications on how physicians can improve their online reputation.
-
ItemInfluence of Personality Traits on the Continued Use of Fitness Apps( 2022-01-04)While fitness apps show promise to improve people’s health and well-being, studies have indicated a high dropout rate among their users. This study uses the expectation confirmation model (ECM) to examine post-adoption factors affecting continued use or dropout among users of fitness apps, with a specific focus on the impact of users’ personality traits (the “big five” traits) on the ECM model variables. We present our theoretical model and the results of our survey with 129 participants. We confirm that satisfaction, perceived usefulness, and confirmation of expectations resulting from use of fitness apps influence the continued use of the apps. Moreover, we show that conscientiousness and neuroticism, as traits, positively influence perceived usefulness. This study increases our understanding of the factors impacting continued use of fitness apps
-
ItemHow to turn the Fast-Track into a Fast-Track: Process integration for evaluation of the quality of Digital Health Applications (DiGAs) on the example of the German Fast-Track Process( 2022-01-04)In this paper, we address the research question of which integration points in the \textit{German Fast-Track process} are particularly well suited for the integration of evaluation platforms for digital health applications. For this purpose, possible integration points are first identified and then analyzed with the help of a utility analysis with regard to the posed research question. Finally, a recommendation for action is made based on the results of the conducted utility analysis.
-
ItemA Thematic Analysis of Provider Comparisons of Telemedicine Satisfaction Measures( 2022-01-04)Satisfaction remains one of the most frequently used and inconsistent measures in Information Systems research. These inconsistencies can create challenges for interpreting the results of satisfaction measures. These challenges are noticeable in the telemedicine literature where researchers often rely on single item measures of overall satisfaction. While researchers have attempted to address these issues by studying satisfaction’s measurements and methodologies there remain gaps in the knowledge on how variations in measures may be interpreted regarding decision making. This research seeks to contribute to the knowledge in this area by investigating medical provider perspectives on single versus multi-dimensional measures of telemedicine satisfaction. Through a thematic analysis this research shows variations and similarities in decision making between measures across eleven themes. The results show not only variations in views but indicate subjective experiential interpretations of results. Findings along with implications for researchers and medical providers are discussed.
-
ItemAn Institutional Theory Perspective on EHR Engagement: Mandates, Penalties, and Enforcement( 2022-01-04)Electronic Health Record (EHR) systems are the predominant information system (IS) used by healthcare clinicians and have been the source of both great success and pain. User engagement with EHR systems is unique from traditional IS contexts in significant ways. Prior research explains EHR usage and success primarily on traditional technology acceptance research (i.e., TAM, UTAUT). However, these models assume that EHR engagement is no different from IS systems in general business domains. Yet, the healthcare context is far more regulated than most. Based on qualitative focus group sessions with a leading healthcare analytics firm (KLAS Research), we identify the role of mandates, penalties, and enforcements from government, organizations, associations, and insurance companies in explaining EHR engagement. We validate a measurement instrument for these factors and demonstrate that their inclusion can improve model fit five times over a traditional UTAUT-based model (R2 = 54.8% versus 10.2%).
-
ItemAddressing unwarranted clinical variation in healthcare as a quality improvement process( 2022-01-04)The reduction of unwarranted clinical variation is a common goal of healthcare systems worldwide. However, the process of developing and implementing variation reducing interventions as a quality improvement process is often overlooked and performed sub-optimally within healthcare organizations. This gap in practice is mirrored by a gap in existing research. The development of a clinical variation specific prescriptive model will assist with the identification, development and application of healthcare specific variation reducing initiatives. Such a model should complement the existing plan, do, study, act quality (PDSA) improvement methodology and respect the learning health systems (LHS) learning cycle. Development through the lens of the quadruple aim of healthcare will ensure that the focus remains true to the core values of clinical organizations. Addressing unwarranted clinical variation is a complex task, however. With organizational support, the utilization of collaborative methodologies and the leveraging of available digital health technologies, healthcare organizations are provided the greatest opportunity for the reduction of unwarranted clinical variation and the optimization of healthcare outcomes.
-
Item