Personally Identifiable Information in State Laws: Use, Release, and Collaboration at Health Departments

Begley, Elin; Ware, Jamie M.; Hexem, Sarah; Rapposelli, Karina; Thompson, Kelly; Penn, Matthew; Aquino, Gustavo A.

doi:10.2105/ajph.2017.303862

Cited by 5 publications

(3 citation statements)

References 8 publications

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“…24 In addition, public health authorities collect and communicate individual information for communicable disease reporting 25 including in the setting of the pandemic emergency. While access to personally identifiable information is critically important for pandemic response, 26 mandatory collection of this information poses a threat to immigrants who have a dual increased risk of workplace virus exposure common in unskilled labor settings 27 and deportation as a result of federal immigration policies in place during the COVID-19 pandemic. Individuals who lack lawful immigration status were, therefore, substantially less likely to engage in COVID-19 testing.…”

Section: Unauthorized Immigrantsmentioning

confidence: 99%

US Immigration Policies Pose Threat to Health Security During COVID-19 Pandemic

et al. 2021

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Section: Unauthorized Immigrantsmentioning

confidence: 99%

US Immigration Policies Pose Threat to Health Security During COVID-19 Pandemic

et al. 2021

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“…Evidence suggests that most scientists endorse these positive values and norms, but fewer scientists believe that their colleagues behave in accordance with these positive norms ( Anderson et al ., 2007 ). Better incentives ( Begley et al ., 2017 ; Fanelli, 2010 ; Nosek et al ., 2012 ) and better methods for detecting scientific errors, might improve scientific practice and communication; yet fundamentally, we will always have to place some trust in the veracity of our fellow scientists ( Jamieson et al ., 2017 ).…”

Section: Resultsmentioning

confidence: 99%

Improving open and rigorous science: ten key future research opportunities related to rigor, reproducibility, and transparency in scientific research

et al. 2020

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Background: As part of a coordinated effort to expand research activity around rigor, reproducibility, and transparency (RRT) across scientific disciplines, a team of investigators at the Indiana University School of Public Health-Bloomington hosted a workshop in October 2019 with international leaders to discuss key opportunities for RRT research. Objective: The workshop aimed to identify research priorities and opportunities related to RRT. Design: Over two-days, workshop attendees gave presentations and participated in three working groups: (1) Improving Education & Training in RRT, (2) Reducing Statistical Errors and Increasing Analytic Transparency, and (3) Looking Outward: Increasing Truthfulness and Accuracy of Research Communications. Following small-group discussions, the working groups presented their findings, and participants discussed the research opportunities identified. The investigators compiled a list of research priorities, which were circulated to all participants for feedback. Results: Participants identified the following priority research questions: (1) Can RRT-focused statistics and mathematical modeling courses improve statistics practice?; (2) Can specialized training in scientific writing improve transparency?; (3) Does modality (e.g. face to face, online) affect the efficacy RRT-related education?; (4) How can automated programs help identify errors more efficiently?; (5) What is the prevalence and impact of errors in scientific publications (e.g., analytic inconsistencies, statistical errors, and other objective errors)?; (6) Do error prevention workflows reduce errors?; (7) How do we encourage post-publication error correction?; (8) How does ‘spin’ in research communication affect stakeholder understanding and use of research evidence?; (9) Do tools to aid writing research reports increase comprehensiveness and clarity of research reports?; and (10) Is it possible to inculcate scientific values and norms related to truthful, rigorous, accurate, and comprehensive scientific reporting? Conclusion: Participants identified important and relatively unexplored questions related to improving RRT. This list may be useful to the scientific community and investigators seeking to advance meta-science (i.e. research on research).

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“…Data protection laws have 5 fundamental elements: (1) a definition of protected data, (2) definition of a regulated person or entity, (3) data use or disclosure restrictions, (4) data use or disclosure exceptions, and (5) penalties for violating the law. It is common for data protection laws to vary wildly in these 5 elements [2][3][4][5][6]. Consequently, it can be exceptionally difficult to understand which law (or laws) apply to a data project and whether a proposed data use is permitted.…”

Section: Introductionmentioning

confidence: 99%

US Privacy Laws Go Against Public Preferences and Impede Public Health and Research: Survey Study

Schmit¹,

Giannouchos²,

Ramezani³

et al. 2021

J Med Internet Res

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Background Reaping the benefits from massive volumes of data collected in all sectors to improve population health, inform personalized medicine, and transform biomedical research requires the delicate balance between the benefits and risks of using individual-level data. There is a patchwork of US data protection laws that vary depending on the type of data, who is using it, and their intended purpose. Differences in these laws challenge big data projects using data from different sources. The decisions to permit or restrict data uses are determined by elected officials; therefore, constituent input is critical to finding the right balance between individual privacy and public benefits. Objective This study explores the US public’s preferences for using identifiable data for different purposes without their consent. Methods We measured data use preferences of a nationally representative sample of 504 US adults by conducting a web-based survey in February 2020. The survey used a choice-based conjoint analysis. We selected choice-based conjoint attributes and levels based on 5 US data protection laws (Health Insurance Portability and Accountability Act, Family Educational Rights and Privacy Act, Privacy Act of 1974, Federal Trade Commission Act, and the Common Rule). There were 72 different combinations of attribute levels, representing different data use scenarios. Participants were given 12 pairs of data use scenarios and were asked to choose the scenario they were the most comfortable with. We then simulated the population preferences by using the hierarchical Bayes regression model using the ChoiceModelR package in R. Results Participants strongly preferred data reuse for public health and research than for profit-driven, marketing, or crime-detection activities. Participants also strongly preferred data use by universities or nonprofit organizations over data use by businesses and governments. Participants were fairly indifferent about the different types of data used (health, education, government, or economic data). Conclusions Our results show a notable incongruence between public preferences and current US data protection laws. Our findings appear to show that the US public favors data uses promoting social benefits over those promoting individual or organizational interests. This study provides strong support for continued efforts to provide safe access to useful data sets for research and public health. Policy makers should consider more robust public health and research data use exceptions to align laws with public preferences. In addition, policy makers who revise laws to enable data use for research and public health should consider more comprehensive protection mechanisms, including transparent use of data and accountability.

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Personally Identifiable Information in State Laws: Use, Release, and Collaboration at Health Departments

Cited by 5 publications

References 8 publications

US Immigration Policies Pose Threat to Health Security During COVID-19 Pandemic

US Immigration Policies Pose Threat to Health Security During COVID-19 Pandemic

Improving open and rigorous science: ten key future research opportunities related to rigor, reproducibility, and transparency in scientific research

US Privacy Laws Go Against Public Preferences and Impede Public Health and Research: Survey Study

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