Optimal Pricing Strategy for Multichannel Healthcare Services

As a combination of online and offline channel services, multichannel healthcare services currently play important roles in helping consumers solve their health problems. In this study, we establish a stylized model to investigate how healthcare service providers should price in multi-channels and when consumers should choose online service, taking misdiagnosis rate and the severity of disease problems into account. Our results show that the prices of the online channel and offline channel can increase when the misdiagnosis rate is low and minor problem inspection rate online is high. Moreover, when the diagnosis rate is high, the profit of online channel would increase, and then improve the profit of multichannel services. These findings provide insights for the theoretical research of online healthcare services and practice management on pricing strategies in multichannel healthcare services

The Spillover Effects of Prescription Drug Monitoring Programs (PDMPs) Integration and Data Sharing on Opioids Prescribing Rate

To reduce the supply of opioids to non-medical users in the U.S., many states have implemented Prescription Drug Monitoring Programs (PDMPs) to collect patients’ opioids purchase history and provide physicians this information. We study the impact of two PDMP-enhancement policies: 1) within-state IS integration, which aims to integrate a state’s PDMP into local hospitals’ health information technologies (HITs), and 2) interstates IS data sharing, which facilitates the interoperability of PDMP data across states line. We construct a county-level panel dataset from 2006 to 2017. First, we do not find evidence that PDMP integration could reduce the focal state’s regional opioids prescribing rate; instead, we find that a focal state\u27s PDMP integration triggers doctor shopping phenomenon by increasing the opioids prescribing rate of counties located in neighboring states, suggesting the negative IT spillover effect. Second, we find nuanced evidence that PDMP interstate data sharing can mitigate this negative spillover effect, showing the positive information externality

Medical Specialists' Perspectives on the Influence of Electronic Medical Record Use on the Quality of Hospital Care:Semistructured Interview Study

Objective: The aim of this study was to examine how, and by which aspects, the relationship between EMR use and the quality of care in hospitals is influenced according to medical specialists. Methods: To answer this question, a qualitative study was conducted in the period of August-October 2018. Semistructured interviews of around 90 min were conducted with 11 medical specialists from 11 different Dutch hospitals. For analysis of the answers, we used a previously published taxonomy of factors that can influence the use of EMRs. Results: The professional experience of the participating medical specialists varied between 5 and 27 years. Using the previously published taxonomy, these medical specialists considered technical barriers the most significant for EMR use. The suboptimal change processes surrounding implementation were also perceived as a major barrier. A final major problem is related to the categories “social” (their relationships with the patients and fellow care providers), “psychological” (based on their personal issues, knowledge, and perceptions), and “time” (the time required to select, implement, and learn how to use EMR systems and subsequently enter data into the system). However, the medical specialists also identified potential technical facilitators, particularly in the assured availability of information to all health care professionals involved in the care of a patient. They see promise in using EMRs for medical decision support to improve the quality of care but consider these possibilities currently lacking. Conclusions: The 11 medical specialists shared positive experiences with EMR use when comparing it to formerly used paper records. The fact that involved health care professionals can access patient data at any time they need is considered important. However, in practice, potential quality improvement lags as long as decision support cannot be applied because of the lack of a fully coded patient record

Testing the Links from Fit to Effective Use to Impact: A Digital Hospital Case

The global health sector is undergoing rapid digital transformation. Because such transformations often fail to meet expectations, researchers have begun studying the full chain from implementation to outcomes to learn what improvements are needed. Recent studies suggest that it is especially important to learn what ‘effective use’ of new systems involve, because effective use is the lynchpin between a system and its benefits. A key challenge, however, is operationalizing effective use. In this paper, we compare two approaches: theory-driven, operationalizing effective use using the ‘theory of effective use’, and context-driven, operationalizing it in terms of the workarounds users devise to achieve their goals. We compare these approaches using survey data from a multi-hospital digital transformation. The results support the theory-driven approach, while offering useful insights on workarounds

Does Information Technology Mitigate the Healthcare Geospatial Disparity? An Examination of Healthcare Information Exchange

Healthcare Information Exchange (HIE) enables healthcare providers to access and share patients’ medical information. While HIE is touted as a potential solution to address healthcare geospatial disparities, its impact on reducing inequality between urban and rural hospitals remains unclear. Using data envelopment analysis (DEA) to construct health professionals’ productivity measure and applying the difference-in-differences (DID) approach, we reveal that hospitals with HIE adoption experience a significant increase in health professionals’ productivity. However, this effect is only pronounced in urban hospitals but not rural hospitals, suggesting that HIE adoption does not mitigate healthcare geospatial inequalities. Additionally, our study reveals that HIE adoption leads to improved communication quality and clinical decision-making quality among urban health professionals, but not among health professionals in rural hospitals. The implications of these findings and the future work of the study are discussed

Exploring How Healthcare Information Technology Use Impacts the Quality of Care: A Process Perspective

Although the impacts of healthcare information technology (HIT) on care quality are widely studied, existing research presents mixed findings and little is known about its underlying mechanism. In this ongoing study, an insight is given from a process perspective. Based on the theory of swift and even flow (TSEF), we investigate how HIT use impacts the quality of care by affecting continuity of care and how such impacts depend on patient demand level. By using digital trace data from cerebrovascular disease inpatients from a hospital in China, we measure continuity of care and conduct an empirical test through econometric models. Our findings show that HIT will improve continuity of care, and then improve quality of care. And this effect is more pronounced at a high patient demand level. This study integrates and extends the literature, and provides guidance for managers to improve care and deliver the value of HIT efficiently

Does the Electronic Medical Record (EMR) Adoption Matter? Exploring Patterns of EMR Implementation and its Impact on Hospital Performance

We aimed to explore the patterns of electronic medical records (EMR) adoption and its effects on hospital performance. We analyzed hospital-level panel data from 2008 to 2013 using Bayesian regression and the Naïve Bayes model. Our research analysis revealed 38 different adoption patterns for 1,919 hospitals that completed EMR implementation (having all of the four components) and 42 different investment patterns for 1,341 hospitals that could not complete the EMR implementation. We examined the hospitals’ EMR adoption patterns that were not completed; but predicted as completed using the Naïve Bayes model. Our results revealed that the hospitals that completed EMR adoption showed higher performance in terms of patient recommendation and net patient revenue than those that did not complete EMR adoption. More importantly, most of hospitals that observed as “not completed” but predicted as “completed” showed lower performance in terms of patient recommendation as well as net patient revenue

Framing Research Questions Intersecting Information Systems and Health: A New Research Perspective at Micro- and Macro-Level

Digital health is an established research area in information systems (IS) research. The domain involves individual human behavior, the broader social, healthcare providers, and other organizations. The rapid spread and use of health technologies have opened up considerable opportunities for research to evaluate and test existing theories. To generate an overview of the status quo, we apply the believe-action-outcome (BAO) framework as a lens to understand how current research has addressed the various aspects of digital health. Overall, we analyzed 46 studies from well-regarded IS outlets. Therefore, we aim at providing a comprehensive review and synthesis of the literature. Our results indicate a focus on behavioral research and action formation, but also a void regarding design-oriented studies, as well as multi-level studies. In summary, this study develops a research agenda for digital health, which includes six research questions that address research focus, health phenomena, at the macro- and micro-level

Unraveling the Link between Simulation EHR Training and Task Performance: The Mediation Role of Stress

Past research has explored the link between computer-mediated communication (CMC) and task performance, but it remains unclear how (i.e., under what mechanisms) CMC impacts task performance. Drawing on media naturalness theory and the stimulus-organism-response model as our theoretical framework, we develop a research model and describe how simulation-based EHR training (a type of CMC) can improve EHR-based task performance by mitigating stress. We empirically test the model with a unique experimental dataset from EHR lab assessment and questionnaires that 225 participants completed. The structural equation modeling analysis results show that simulation EHR training helped improve EHR-based task performance (both effectiveness and efficiency) by reducing perceived stress. We discuss theoretical and practical implications, limitations, and future research