The Role of HIPAA Omnibus Rules in Reducing the Frequency of Medical Data Breaches: Insights From an Empirical Study.

Policy Points: Frequent data breaches in the US health care system undermine the privacy of millions of patients every year-a large number of which happen among business associates of the health care providers that continue to gain unprecedented access to patients' data as the US health care system becomes digitally integrated. Implementation of the HIPAA Omnibus Rules in 2013 has led to a significant decrease in the number of privacy breach incidents among business associates. CONTEXT: Frequent data breaches in the US health care system undermine the privacy of millions of patients every year. A large number of such breaches happens among business associates of the health care providers that continue to gain unprecedented access to patients' data as the US health care system becomes digitally integrated. The Omnibus Rules of the Health Insurance Portability and Accountability Act (HIPAA), which were enacted in 2013, significantly increased the regulatory oversight and privacy protection requirements of business associates. The objective of this study is to empirically examine the effects of this shift in policy on the frequency of medical privacy breaches among business associates in the US health care system. The findings of this research shed light on how regulatory efforts can protect patients' privacy. METHODS: Using publicly available data on breach incidents between October 2009 and August 2017 as reported by the Office for Civil Rights (OCR), we conducted an interrupted time-series analysis and a difference-in-differences analysis to examine the immediate and long-term effects of implementation of HIPAA omnibus rules on the frequency of medical privacy breaches. FINDINGS: We show that implementation of the omnibus rules led to a significant reduction in the number of breaches among business associates and prevented 180 privacy breaches from happening, which could have affected nearly 18 million Americans. CONCLUSIONS: Implementation of HIPAA omnibus rules may have been a successful federal policy in enhancing privacy protection efforts and reducing the number of breach incidents in the US health care system.

How Online Quality Ratings Influence Patients' Choice of Medical Providers: Controlled Experimental Survey Study.

BACKGROUND: In recent years, the information environment for patients to learn about physician quality is being rapidly changed by Web-based ratings from both commercial and government efforts. However, little is known about how various types of Web-based ratings affect individuals' choice of physicians. OBJECTIVE: The objective of this research was to measure the relative importance of Web-based quality ratings from governmental and commercial agencies on individuals' choice of primary care physicians. METHODS: In a choice-based conjoint experiment conducted on a sample of 1000 Amazon Mechanical Turk users in October 2016, individuals were asked to choose their preferred primary care physician from pairs of physicians with different ratings in clinical and nonclinical aspects of care provided by governmental and commercial agencies. RESULTS: The relative log odds of choosing a physician increases by 1.31 (95% CI 1.26-1.37; P<.001) and 1.32 (95% CI 1.27-1.39; P<.001) units when the government clinical ratings and commercial nonclinical ratings move from 2 to 4 stars, respectively. The relative log odds of choosing a physician increases by 1.12 (95% CI 1.07-1.18; P<.001) units when the commercial clinical ratings move from 2 to 4 stars. The relative log odds of selecting a physician with 4 stars in nonclinical ratings provided by the government is 1.03 (95% CI 0.98-1.09; P<.001) units higher than a physician with 2 stars in this rating. The log odds of selecting a physician with 4 stars in nonclinical government ratings relative to a physician with 2 stars is 0.23 (95% CI 0.13-0.33; P<.001) units higher for females compared with males. Similar star increase in nonclinical commercial ratings increases the relative log odds of selecting the physician by female respondents by 0.15 (95% CI 0.04-0.26; P=.006) units. CONCLUSIONS: Individuals perceive nonclinical ratings provided by commercial websites as important as clinical ratings provided by government websites when choosing a primary care physician. There are significant gender differences in how the ratings are used. More research is needed on whether patients are making the best use of different types of ratings, as well as the optimal allocation of resources in improving physician ratings from the government's perspective.

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 outbreaks.

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

OBJECTIVES: To examine the impact of coronavirus disease 2019 (COVID-19) pandemic on the extent of potential violations of Internet users' privacy. MATERIALS AND METHODS: We conducted a longitudinal study of the data sharing practices of the top 1000 websites in the United States between April 9 and August 27, 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. We denote websites that asked for permission before placing cookies on users' browsers as "privacy-respecting." RESULTS: As the weekly number of COVID-19 deaths increased by 1000, the average number of third parties increased by 0.26 (95% confidence interval [CI] 0.15-0.37) P < 0.001 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 0.18-0.64); P < 0.001 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 1000 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 United States, 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.

(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.

An empirical analysis of the financial benefits of health information exchange in emergency departments.

OBJECTIVE: To examine the impact of health information exchange (HIE) on reducing laboratory tests and radiology examinations performed in an emergency department (ED). MATERIALS AND METHODS: The study was conducted in an ED setting in Western New York over a period of 2 months. The care of the patients in the treatment group included an HIE query for every encounter, while the care of other patients in the control group did not include such queries. A group of medical liaisons were hired to query the medical history of patients from an HIE and provide it to the ED clinicians. Negative binomial regression was used to analyze the effects of HIE queries on the number of performed laboratory tests and radiology examinations. The log files of the HIE system since 1 year before the ED admission were used to analyze the differences in outcome measures between the 2 groups of patients. RESULTS: Ceteris paribus, HIE usage is associated with, respectively, 52% and 36% reduction in the expected total number of laboratory tests and radiology examinations ordered per patient at the ED. CONCLUSIONS: The results indicate that access to additional clinical data through the HIE will significantly reduce the number of laboratory tests and radiology examinations performed in the ED settings and thus support the ongoing HIE efforts.

Drivers of information disclosure on health information exchange platforms: insights from an exploratory empirical study.

OBJECTIVE: The objective of this research is to empirically explore the drivers of patients' consent to sharing of their medical records on health information exchange (HIE) platforms. MATERIALS AND METHODS: The authors analyze a dataset consisting of consent choices of 20,076 patients in Western New York. A logistic regression is applied to empirically investigate the effects of patients' age, gender, complexity of medical conditions, and the role of primary care physicians on patients' willingness to disclose medical information on HIE platforms. RESULTS: The likelihood of providing consent increases by age (odds ratio (OR) = 1.055; P < .0001). Female patients are more likely to provide consent (OR = 1.460; P = .0003). As the number of different physicians involved in the care of the patient increases, the odds of providing consent slightly increases (OR = 1.024; P = .0031). The odds of providing consent is significantly higher for the patients whom a primary care physician has been involved in their medical care (OR = 1.323; P < .0001). CONCLUSION: Individual-level characteristics are important predictors of patients' willingness to disclose their medical information on HIE platforms.

Professional and geographical network effects on healthcare information exchange growth: does proximity really matter?

BACKGROUND AND OBJECTIVE: We postulate that professional proximity due to common patients and geographical proximity among practice locations are significant factors influencing the adoption of health information exchange (HIE) services by healthcare providers. The objective of this study is to investigate the direct and indirect network effects of these drivers on HIE diffusion. DESIGN: Multi-dimensional scaling and clustering are first used to create different clusters of physicians based on their professional and geographical proximities. Extending the Bass diffusion model to capture direct and indirect network effects among groups, the growth of HIE among these clusters is modeled and studied. The network effects among the clusters are investigated using adoption data over a 3-year period for an HIE based in Western New York. MEASUREMENT: HIE adoption parameters-external sources of influence as well as direct and indirect network coefficients-are estimated by the extended version of the Bass diffusion model. RESULTS: Direct network effects caused by common patients among physicians are much more influential on HIE adoption as compared with previously investigated social contagion and external factors. Professional proximity due to common patients does influence adoption decisions; geographical proximity is also influential, but its effect is more on rural than urban physicians. CONCLUSIONS: Flow of patients among different groups of physicians is a powerful factor in HIE adoption. Rather than merely following the market trend, physicians appear to be influenced by other physicians with whom they interact with and have common patients.