Video education about genetic privacy and patient perspectives about sharing prenatal genetic data: a randomized trial

BACKGROUND

Laboratories offering cell-free DNA often reserve the right to share prenatal genetic data for research or even commercial purposes, and obtain this permission on the patient consent form. Although it is known that nonpregnant patients are often reluctant to share their genetic data for research, pregnant patients' knowledge of, and opinions about, genetic data privacy are unknown.

OBJECTIVE

We investigated whether pregnant patients who had already undergone cell-free DNA screening were aware that genetic data derived from cell-free DNA may be shared for research. Furthermore, we examined whether pregnant patients exposed to video education about the Genetic Information Nondiscrimination Act-a federal law that mandates workplace and health insurance protections against genetic discrimination-were more willing to share cell-free DNA-related genetic data for research than pregnant patients who were unexposed.

STUDY DESIGN

In this randomized controlled trial (ClinicalTrials.gov Identifier: NCT04420858), English-speaking patients with singleton pregnancies who underwent cell-free DNA and subsequently presented at 17 0/7 to 23 6/7 weeks of gestation for a detailed anatomy scan were randomized 1:1 to a control or intervention group. Both groups viewed an infographic about cell-free DNA. In addition, the intervention group viewed an educational video about the Genetic Information Nondiscrimination Act. The primary outcomes were knowledge about, and willingness to share, prenatal genetic data from cell-free DNA by commercial laboratories for nonclinical purposes, such as research. The secondary outcomes included knowledge about existing genetic privacy laws, knowledge about the potential for reidentification of anonymized genetic data, and acceptability of various use and sharing scenarios for prenatal genetic data. Eighty-one participants per group were required for 80% power to detect an increase in willingness to share data from 60% to 80% (α=0.05).

RESULTS

A total of 747 pregnant patients were screened, and 213 patients were deemed eligible and approached for potential study participation. Of these patients, 163 (76.5%) consented and were randomized; one participant discontinued the intervention, and two participants were excluded from analysis after the intervention when it was discovered that they did not fulfill all eligibility criteria. Overall, 160 (75.1%) of those approached were included in the final analysis. Most patients in the control group (72 [90.0%]) and intervention (76 [97.4%]) group were either unsure about or incorrectly thought that cell-free DNA companies could not share prenatal genetic data for research. Participants in the intervention group were more likely to incorrectly believe that their prenatal genetic data would not be shared for nonclinical purposes than participants in the control group (28.8% in the control group vs 46.2% in the intervention; P=.03). However, video education did not increase participant willingness to share genetic data in multiple scenarios. Non-White participants were less willing than White participants to allow sharing of genetic data specifically for academic research (P<.001).

CONCLUSION

Most participants were unaware that their prenatal genetic data may be used for nonclinical purposes. Pregnant patients who were educated about the Genetic Information Nondiscrimination Act were not more willing to share genetic data than those who did not receive this education. Surprisingly, video education about the Genetic Information Nondiscrimination Act led patients to falsely believe that their data would not be shared for research, and participants who identified as racial minorities were less willing to share genetic data. New strategies are needed to improve pregnant patients' understanding of genetic privacy.

The National COVID Cohort Collaborative: Analyses of Original and Computationally Derived Electronic Health Record Data

BACKGROUND

Computationally derived ("synthetic") data can enable the creation and analysis of clinical, laboratory, and diagnostic data as if they were the original electronic health record data. Synthetic data can support data sharing to answer critical research questions to address the COVID-19 pandemic.

OBJECTIVE

We aim to compare the results from analyses of synthetic data to those from original data and assess the strengths and limitations of leveraging computationally derived data for research purposes.

METHODS

We used the National COVID Cohort Collaborative's instance of MDClone, a big data platform with data-synthesizing capabilities (MDClone Ltd). We downloaded electronic health record data from 34 National COVID Cohort Collaborative institutional partners and tested three use cases, including (1) exploring the distributions of key features of the COVID-19-positive cohort; (2) training and testing predictive models for assessing the risk of admission among these patients; and (3) determining geospatial and temporal COVID-19-related measures and outcomes, and constructing their epidemic curves. We compared the results from synthetic data to those from original data using traditional statistics, machine learning approaches, and temporal and spatial representations of the data.

RESULTS

For each use case, the results of the synthetic data analyses successfully mimicked those of the original data such that the distributions of the data were similar and the predictive models demonstrated comparable performance. Although the synthetic and original data yielded overall nearly the same results, there were exceptions that included an odds ratio on either side of the null in multivariable analyses (0.97 vs 1.01) and differences in the magnitude of epidemic curves constructed for zip codes with low population counts.

CONCLUSIONS

This paper presents the results of each use case and outlines key considerations for the use of synthetic data, examining their role in collaborative research for faster insights.

Spot the difference: comparing results of analyses from real patient data and synthetic derivatives

BACKGROUND

Synthetic data may provide a solution to researchers who wish to generate and share data in support of precision healthcare. Recent advances in data synthesis enable the creation and analysis of synthetic derivatives as if they were the original data; this process has significant advantages over data deidentification.

OBJECTIVES

To assess a big-data platform with data-synthesizing capabilities (MDClone Ltd., Beer Sheva, Israel) for its ability to produce data that can be used for research purposes while obviating privacy and confidentiality concerns.

METHODS

We explored three use cases and tested the robustness of synthetic data by comparing the results of analyses using synthetic derivatives to analyses using the original data using traditional statistics, machine learning approaches, and spatial representations of the data. We designed these use cases with the purpose of conducting analyses at the observation level (Use Case 1), patient cohorts (Use Case 2), and population-level data (Use Case 3).

RESULTS

For each use case, the results of the analyses were sufficiently statistically similar (P > 0.05) between the synthetic derivative and the real data to draw the same conclusions.

DISCUSSION AND CONCLUSION

This article presents the results of each use case and outlines key considerations for the use of synthetic data, examining their role in clinical research for faster insights and improved data sharing in support of precision healthcare.

Doctors Routinely Share Health Data Electronically Under HIPAA, and Sharing With Patients and Patients' Third-Party Health Apps is Consistent: Interoperability and Privacy Analysis

Since 2000, federal regulations have affirmed that patients have a right to a complete copy of their health records from their physicians and hospitals. Today, providers across the nation use electronic health records and electronic information exchange for health care, and patients are choosing digital health apps to help them manage their own health and health information. Some doctors and health systems have voiced concern about whether they may transmit a patient's data upon the patient's request to the patient or the patient's health app. This hesitation impedes shared information and care coordination with patients. It impairs patients' ability to use the state-of-the-art digital health tools they choose to track and manage their health. It undermines the ability of patients' family caregivers to monitor health and to work remotely to provide care by using the nearly unique capabilities of health apps on people's smartphones. This paper explains that sharing data electronically with patients and patients' third-party apps is legally consistent under the Health Insurance Portability and Accountability Act (HIPAA) with routine electronic data sharing with other doctors for treatment or with insurers for reimbursement. The paper explains and illustrates basic principles and scenarios around sharing with patients, including patients' third-party apps. Doctors routinely and legally share health data electronically under HIPAA whether or not their organizations retain HIPAA responsibility. Sharing with patients and patients' third-party apps is no different and should be just as routine.

Cyber-Analytics: Identifying Discriminants of Data Breaches

In this study, the relationship between data breach characteristics and the number of individuals affected by these violations was considered. Data were acquired from the Department of Health and Human Services breach reporting database and analyzed using SPSS. Regression analyses revealed that the hacking/IT incident breach type and network server breach location were the most significant predictors of the number of individuals affected; however, they were not predictive when combined. Moreover, network server location and unauthorized access/disclosure breach type were predictive when combined. Additional analyses of variance revealed that covered entity type and business associate presence were significant predictors, while the geographic region of a breach occurrence was insignificant. The results of this study revealed several associations between healthcare breach characteristics and the number of individuals affected, suggesting that more individuals are affected in hacking/IT incidents and network server breaches independently and that network server breach location and unauthorized access/disclosure breach type were predictive in combination.

Private collection: high correlation of sample collection and patient admission date in clinical microbiological testing complicates sharing of phylodynamic metadata

Infectious pathogens are known for their rapid evolutionary rates with new mutations arising over days to weeks. The ability to rapidly recover whole genome sequences and analyze the spread and evolution of pathogens using genetic information and pathogen collection dates has lead to interest in real-time tracking of infectious transmission and outbreaks. However, the level of temporal resolution afforded by these analyses may conflict with definitions of what constitutes protected health information (PHI) and privacy requirements for de-identification for publication and public sharing of research data and metadata. In the United States, dates and locations associated with patient care that provide greater resolution than year or the first three digits of the zip code are generally considered patient identifiers. Admission and discharge dates are specifically named as identifiers in Department of Health and Human Services guidance. To understand the degree to which one can impute admission dates from specimen collection dates, we examined sample collection dates and patient admission dates associated with more than 270,000 unique microbiological results from the University of Washington Laboratory Medicine Department between 2010 and 2017. Across all positive microbiological tests, the sample collection date exactly matched the patient admission date in 68.8% of tests. Collection dates and admission dates were identical from emergency department and outpatient testing 86.7% and 96.5% of the time, respectively, with >99% of tests collected within 1 day from the patient admission date. Samples from female patients were significantly more likely to be collected closer to admission date that those from male patients. We show that PHI-associated dates such as admission date can confidently be imputed from deposited collection date. We suggest that publicly depositing microbiological collection dates at greater resolution than the year may not meet routine Safe Harbor-based requirements for patient de-identification. We recommend the use of Expert Determination to determine PHI for a given study and/or direct patient consent if clinical laboratories or phylodynamic practitioners desire to make these data available.

Social Media Tips to Enhance Medical Education

In this article, we describe how social media can supplement traditional education, articulate the advantages and disadvantages of various social media platforms for both teachers and learners, discuss best practices to maintain confidentiality of protected health information, and provide tips for implementing social media-based teaching into the training curriculum.

Electronic Communication of Protected Health Information: Privacy, Security, and HIPAA Compliance

PURPOSE

Technology has enhanced modern health care delivery, particularly through accessibility to health information and ease of communication with tools like mobile device messaging (texting). However, text messaging has created new risks for breach of protected health information (PHI). In the current study, we sought to evaluate hand surgeons' knowledge and compliance with privacy and security standards for electronic communication by text message.

METHODS

A cross-sectional survey of the American Society for Surgery of the Hand membership was conducted in March and April 2016. Descriptive and inferential statistical analyses were performed of composite results as well as relevant subgroup analyses.

RESULTS

A total of 409 responses were obtained (11% response rate). Although 63% of surgeons reported that they believe that text messaging does not meet Health Insurance Portability and Accountability Act of 1996 security standards, only 37% reported they do not use text messages to communicate PHI. Younger surgeons and respondents who believed that their texting was compliant were statistically significantly more like to report messaging of PHI (odds ratio, 1.59 and 1.22, respectively).

DISCUSSION

A majority of hand surgeons in this study reported the use of text messaging to communicate PHI. Of note, neither the Health Insurance Portability and Accountability Act of 1996 statute nor US Department of Health and Human Services specifically prohibits this form of electronic communication. To be compliant, surgeons, practices, and institutions need to take reasonable security precautions to prevent breach of privacy with electronic communication.

CLINICAL RELEVANCE

Communication of clinical information by text message is not prohibited under Health Insurance Portability and Accountability Act of 1996, but surgeons should use appropriate safeguards to prevent breach when using this form of communication.

The Need for a Privacy Standard for Medical Devices That Transmit Protected Health Information Used in the Precision Medicine Initiative for Diabetes and Other Diseases

Privacy is an important concern for the Precision Medicine Initiative (PMI) because success of this initiative will require the public to be willing to participate by contributing large amounts of genetic/genomic information and sensor data. This sensitive personal information is intended to be used only for specified research purposes. Public willingness to participate will depend on the public's level of trust that their information will be protected and kept private. Medical devices may constantly provide information. Therefore, assuring privacy for device-generated information may be essential for broad participation in the PMI. Privacy standards for devices should be an important early step in the development of the PMI.

Privacy and Security Issues Surrounding the Protection of Data Generated by Continuous Glucose Monitors

Being able to track, analyze, and use data from continuous glucose monitors (CGMs) and through platforms and apps that communicate with CGMs helps achieve better outcomes and can advance the understanding of diabetes. The risks to patients' expectation of privacy are great, and their ability to control how their information is collected, stored, and used is virtually nonexistent. Patients' physical security is also at risk if adequate cybersecurity measures are not taken. Currently, data privacy and security protections are not robust enough to address the privacy and security risks and stymies the current and future benefits of CGM and the platforms and apps that communicate with them.

Prevalence Estimation of Protected Health Information in Swedish Clinical Text

Obscuring protected health information (PHI) in the clinical text of health records facilitates the secondary use of healthcare data in a privacy-preserving manner. Although automatic de-identification of clinical text using machine learning holds much promise, little is known about the relative prevalence of PHI in different types of clinical text and whether there is a need for domain adaptation when learning predictive models from one particular domain and applying it to another. In this study, we address these questions by training a predictive model and using it to estimate the prevalence of PHI in clinical text written (1) in different clinical specialties, (2) in different types of notes (i.e., under different headings), and (3) by persons in different professional roles. It is demonstrated that the overall PHI density is 1.57%; however, substantial differences exist across domains.

Past, Present, and Future of Informed Consent in Pain and Genomics Research: Challenges Facing Global Medical Community

In recent decades, there has been a revision of the role of institutional review boards with the intention of protecting human subjects from harm and exploitation in research. Informed consent aims to protect the subject by explaining all of the benefits and risks associated with a specific research project. To date, there has not been a review published analyzing issues of informed consent in research in the field of genetic/Omics in subjects with chronic pain, and the current review aims to fill that gap in the ethical aspects of such investigation. Despite the extensive discussion on ethical challenges unique to the field of genetic/Omics, this is the first attempt at addressing ethical challenges regarding Informed Consent Forms for pain research as the primary focus. We see this contribution as an important one, for while ethical issues are too often ignored in pain research in general, the numerous arising ethical issues that are unique to pain genetic/Omics suggest that researchers in the field need to pay even greater attention to the rights of subjects/patients. This article presents the work of the Ethic Committee of the Pain-Omics Group (www.painomics.eu), a consortium of 11 centers that is running the Pain-Omics project funded by the European Community in the 7th Framework Program theme (HEALTH.2013.2.2.1-5-Understanding and controlling pain). The Ethic Committee is composed of 1 member of each group of the consortium as well as key opinion leaders in the field of ethics and pain more generally.

Evaluation of PHI Hunter in Natural Language Processing Research

OBJECTIVES

We introduce and evaluate a new, easily accessible tool using a common statistical analysis and business analytics software suite, SAS, which can be programmed to remove specific protected health information (PHI) from a text document. Removal of PHI is important because the quantity of text documents used for research with natural language processing (NLP) is increasing. When using existing data for research, an investigator must remove all PHI not needed for the research to comply with human subjects' right to privacy. This process is similar, but not identical, to de-identification of a given set of documents.

MATERIALS AND METHODS

PHI Hunter removes PHI from free-form text. It is a set of rules to identify and remove patterns in text. PHI Hunter was applied to 473 Department of Veterans Affairs (VA) text documents randomly drawn from a research corpus stored as unstructured text in VA files.

RESULTS

PHI Hunter performed well with PHI in the form of identification numbers such as Social Security numbers, phone numbers, and medical record numbers. The most commonly missed PHI items were names and locations. Incorrect removal of information occurred with text that looked like identification numbers.

DISCUSSION

PHI Hunter fills a niche role that is related to but not equal to the role of de-identification tools. It gives research staff a tool to reasonably increase patient privacy. It performs well for highly sensitive PHI categories that are rarely used in research, but still shows possible areas for improvement. More development for patterns of text and linked demographic tables from electronic health records (EHRs) would improve the program so that more precise identifiable information can be removed.

CONCLUSIONS

PHI Hunter is an accessible tool that can flexibly remove PHI not needed for research. If it can be tailored to the specific data set via linked demographic tables, its performance will improve in each new document set.

Electronic medical records in colorectal surgery

Electronic medical records (EMRs) are being widely implemented today, either as stand-alone applications in smaller practices or as systems-based integrated network solutions in larger health care organizations. Advantages include rapid accessibility, worldwide availability, ease of storage, and secure transfer of protected health information (PHI). Computerized physician order entry (CPOE) and decision-support capabilities such as the triggering of an alarm when multiple medications with known interactions are ordered, as well as the seemingly endless possibilities for electronic integration and extraction of PHI for clinical and research purposes, have created opportunities and pitfalls alike. Risks include breaches of confidentiality with a need to implement tighter measures for electronic security. These measures contrast efforts required for the realization of common data formats that have national and even international compatibility. EMRs provide a common platform that could potentially allow for the integration and administration of clinical care, research, and quality metrics, thus promoting optimal outcomes for patients. Technical and medicolegal difficulties need to be overcome in the years to come so that the safe use of PHI can be ensured while still maintaining the benefits and convenience of modern EMR systems.

Implementation and use of a web-based interface for confidential communication of data between the clinical and research environments

Policies and regulations in the current health care environment have impacted the manner in which patient data - especially protected health information (PHI) - are handled in the clinical and research settings. Specifically, it is now more challenging to obtain de-identified PHI from the clinic for use in research while still adhering to the requirements dictated by the new policies and regulations. To meet this challenge, we have designed and implemented a novel web-based interface that uses a workflow model to manage the communication of data (for example, biopsy results) between the clinic and research environments without revealing PHI to the research team or associated research identifiers to the clinical collaborators. At the heart of the scheme is a web application that coordinates message passing between researchers and clinical collaborators by use of a protocol that protects confidentiality. We describe the design requirements of the messaging/communication protocol, as well as implementation details of the web application and its associated database. We conclude that this scheme provides a useful communication mechanism that facilitates clinical research while maintaining confidentiality of patient data.