Health Information Exchange: Growth and Patient Privacy

Health Information Exchanges (HIE) provide the electronic movement of health-related information among organizations according to nationally recognized standards. The goal of health information exchange is to facilitate access to and retrieval of clinical data to provide safer, timelier, efficient, effective, equitable, patient-centered care. HIEs are becoming integral parts of the national healthcare reform efforts, chiefly owing to their potential impact on cost reduction and quality enhancement in healthcare services. However, the potential of a HIE platform can only be realized when its multiple constituent users actively participate in using its variety of services. In this research, Yaraghi models HIE systems as multisided platforms that incorporate self-service technologies whose value to the users depends on both user-specific and network-specific factors. Yaraghi also will discuss patient privacy on HIE systems and show the effect of the emotional and environmental factors on the patients’ decision to disclose their medical information on HIE systems

(How) did attack advertisements increase affordable care act enrollments?

We examine the effects of exposure to negative information in attack advertisements in the context of Affordable Care Act (ACA) and Common Core (CC) education standards and show that they lead to an increase in the ACA enrollments and support of the CC standards. To explain this effect, we rely on the knowledge-gap theory and show that individuals who were exposed to more attack advertisements were also more likely to independently seek information, become more knowledgeable, and consequently support these subjects. In addition to an observational study, to test our hypotheses on the link between exposure to negative information, curiosity, and shifts in knowledge and support levels, we design and conduct a randomized experiment using a sample of 300 unique individuals. Our multi-methods research contributes to marketing literature by documenting a rare occasion in which exposure to attack advertisements leads to increased demand and unveiling the mechanisms through which this effect takes place

Doctors’ Orders or Patients’ Preferences? Examining the Role of Physicians in Patients’ Privacy Decisions on Health Information Exchange Platforms

Health information exchange (HIE) platforms could increase the efficiency of health care services by enabling providers to instantly access the medical records of their patients. However, these benefits cannot be realized unless patients disclose their information on HIE platforms. We examine actual privacy decisions made by patients on an HIE platform, study the influence of physicians’ recommendations on patients’ decisions, and explore the process through which this effect takes place. By analyzing a unique data set consisting of the privacy decisions of 12,444 patients, we show that contrary to common belief, patients do not simply follow physician recommendations, but rather carefully consider the risks and benefits of providing consent. We show that competition among medical providers does not hinder patient participation in HIEs, but that providers’ decisions to ask for consent are primarily driven by the potential benefits of HIE for themselves and their patients

From Facebook to the Streets: Russian Troll Ads and Black Lives Matter Protests

Online trolling is typically studied in the IS literature as an uncoordinated, anarchic activity. Coordinated, strategic online trolling is not well understood despite its prevalence on social media. To shed light on this prevailing activity, the present study examines the proposition that coordinated online trolling is timed to leverage macro societal unrest. In testing this proposition, we analyzes the dynamics of the Russian State’s coordinated trolling campaign against the United States beginning in 2015. Using the May 2018 release of all Russian Troll Facebook advertisements, this study constructs a topic model of the content of these ads. The relationship between ad topics and the frequency of Black Lives Matter protests is examined. We argue that the frequency of Black Lives Matter protests proxies for civil unrest and divisiveness in the United States. The study finds that Russian ads related to police brutality were issued to coincide with periods of higher unrest. This work also finds that during periods of relative calm (evidenced by lower frequency of protests) Russian ads were relatively innocuous

Impact of the COVID-19 pandemic on staff turnover at long-term care facilities : a qualitative study

Objective The objective of this research was to explore the lived experiences of long-term care facilities’ staff during the COVID-19 pandemic and examine if and how the pandemic played a role in their decision to leave their jobs. Design Qualitative study using thematic analysis of semistructured interviews. Interview transcripts were analysed using coding techniques based in grounded theory. Participants A total of 29 staff with various roles across 21 long-term care facilities in 12 states were interviewed. Results The pandemic influenced the staff’s decision to leave their jobs in five different ways, namely: (1) It significantly increased the workload; (2) Created more physical and emotional hazards for staff; (3) Constrained the facilities and their staff financially; (4) Deteriorated morale and job satisfaction among the staff and (5) Increased concerns with upper management’s commitment to both general and COVID-19-specific procedures. Conclusions Staff at long-term care facilities discussed a wide variety of reasons for their decision to quit their jobs during the pandemic. Our findings may inform efforts to reduce the rate of turnover in these facilities

Compress the curve : a cross sectional study of variations in COVID-19 infections across California nursing homes

Objective Nursing homes’ residents and staff constitute the largest proportion of the fatalities associated with COVID-19 epidemic. Although there is a significant variation in COVID-19 outbreaks among the US nursing homes, we still do not know why such outbreaks are larger and more likely in some nursing homes than others. This research aims to understand why some nursing homes are more susceptible to larger COVID-19 outbreaks. Design Observational study of all nursing homes in the state of California until 1 May 2020. Setting The state of California. Participants 713 long-term care facilities in the state of California that participate in public reporting of COVID-19 infections as of 1 May 2020 and their infections data could be matched with data on ratings and governance features of nursing homes provided by Centers for Medicare & Medicaid Services (CMS). Main outcome measure The number of reported COVID-19 infections among staff and residents. Results Study sample included 713 nursing homes. The size of outbreaks among residents in for-profit nursing homes is 12.7 times larger than their non-profit counterparts (log count=2.54; 95% CI, 1.97 to 3.11; p<0.001). Higher ratings in CMS-reported health inspections are associated with lower number of infections among both staff (log count=−0.19; 95% CI, −0.37 to −0.01; p=0.05) and residents (log count=−0.20; 95% CI, −0.27 to −0.14; p<0.001). Nursing homes with higher discrepancy between their CMS-reported and self-reported ratings have higher number of infections among their staff (log count=0.41; 95% CI, 0.31 to 0.51; p<0.001) and residents (log count=0.13; 95% CI, 0.08 to 0.18; p<0.001). Conclusions The size of COVID-19 outbreaks in nursing homes is associated with their ratings and governance features. To prepare for the possible next waves of COVID-19 epidemic, policy makers should use these insights to identify the nursing homes who are more likely to experience large outbreak

Impact of health information exchange adoption on referral patterns

Efforts to promote Health Information Exchanges (HIE) on a nationwide scale are beset with major challenges and one of them is its meaningful use for both physicians and patients. Referrals potentially provide a context for the meaningful use of HIE and we are yet to understand how HIEs affect referrals. This research studies the impact of HIE on referral patterns. We establish that participation in an HIE network increases the referrals sent to and received from other HIE participants. We investigate this relationship using both econometric and network-analytic methods. While the econometric analysis focuses on the underlying associations between HIE adoption and referral patterns, the network analysis addresses the transformation process by which HIE adoption and referrals co-evolve over time. This study has significant implications for healthcare policy-making, development of innovative HIE business models, and management of healthcare organizations

Dark clouds and silver linings : impact of COVID-19 on internet users’ privacy

Objectives: To examine the impact of COVID-19 pandemic on the extent of potential violations of Internet users’ privacy. Materials and Methos: We conducted a longitudinal study of the data sharing practices of the top 1,000 websites in the US between April 9th and August 27th, 2020. We fitted a conditional latent growth curve model on the data to examine the longitudinal trajectory of the third-party data sharing over the 21 weeks period of the study and examine how website characteristics affect this trajectory. Results: As the weekly number of COVID-19 deaths increased by 1,000, the average number of third parties increased by 0.26 [95%CI, 0.15 to 0.37] P<.001 units in the next week. This effect was more pronounced for websites with higher traffic as they increased their third parties by an additional 0.41 [95% CI, 0.18 to 0.64]; P<.001 units per week. However, privacy respecting websites that experienced a surge in traffic reduced their third parties by 1.01 [95% CI, -2.01 to 0]; P = 0.05 units per week in response to every 1,000 COVID-19 deaths in the preceding week. Discussion: While in general websites shared their users’ data with more third parties as COVID-19 progressed in the US, websites’ expected traffic and respect for users’ privacy significantly affect such trajectory. Conclusions: Attention should also be paid to the impact of the pandemic on elevating online privacy threats, and the variation in third-party tracking among different types of websites

Critical Success Factors for Risk Management Systems

Despite the existence of extensive literature regarding risk management, there still seems to be lack of knowledge in identification of Critical Success Factors (CSFs) in this area. In this research Grounded Theory is implemented to identify CSFs in Risk Management Systems (RMS). Factor analysis and one-sample t-test are then used to refine and rank the CSFs based on the results of a survey which has been performed among Risk Management practitioners in various types of Swedish corporations. CSFs are defined from three different perspectives: (a) the factors that have influence on the inclination and readiness of corporation for implementing RMS. (b) the factors that are important during the design and implementation of RMS in corporation and can significantly affect the success of RMS design and implementation and (c) the factors that are crucially important to successfully run, maintain and administrate RMS after the closure of the project of RMS design and Implementation. This systematic approach towards understanding the taxonomy of the success dimension in RMS is important for re-enforcing effective risk management practices