Privacy protections to encourage use of health-relevant digital data in a learning health system

Abstract

The National Academy of Medicine has long advocated for a “learning healthcare system” that produces constantly updated reference data during the care process. Moving toward a rapid learning system to solve intractable problems in health demands a balance between protecting patients and making data available to improve health and health care. Public concerns in the U.S. about privacy and the potential for unethical or harmful uses of this data, if not proactively addressed, could upset this balance. New federal laws prioritize sharing health data, including with patient digital tools. U.S. health privacy laws do not cover data collected by many consumer digital technologies and have not been updated to address concerns about the entry of large technology companies into health care. Further, there is increasing recognition that many classes of data not traditionally considered to be healthcare-related, for example consumer credit histories, are indeed predictive of health status and outcomes. We propose a multi-pronged approach to protecting health-relevant data while promoting and supporting beneficial uses and disclosures to improve health and health care for individuals and populations. Such protections should apply to entities collecting health-relevant data regardless of whether they are covered by federal health privacy laws. We focus largely on privacy but also address protections against harms as a critical component of a comprehensive approach to governing health-relevant data. U.S. policymakers and regulators should consider these recommendations in crafting privacy bills and rules. However, our recommendations also can inform best practices even in the absence of new federal requirements.

Privacy Protection and Secondary Use of Health Data: Strategies and Methods

“…The heavy concerns about privacy disclosure much hinder secondary use of health big data. Much efforts tried to balance between privacy management and health data secondary use from both the legislation side [ 5 ] and the technology side [ 6 , 7 ]. But for much more circumstances, a perfect balance is difficult to achieve; instead, a certain tradeoff or compromise must always be made.…”

Towards Privacy Paradigm Shift Due to the Pandemic: A Brief Perspective

“…The most famous and practical solutions in the collected data analytics/mining for insights finding is multi-pronged approach [82]. By using this method, health-relevant data is protected from privacy violations and can only be used in a privacy preserving manner.…”

Big data and predictive analytics in healthcare in Bangladesh: regulatory challenges

“…Specific sectoral based legislation can be effective in protecting the privacy of medical data. HIPAA, 1996 in the US ensures health data privacy, though the effectiveness of the Act comes into question in the wake of current technological development ( McGraw and Mandl, 2021 ). The efficacy of HIPPA will not be discussed here as it requires a whole study of its own.…”

“…Hence, protecting the privacy and security of health data cast doubt over the future of artificial intelligence in medicine. The requirement of providing continuous high-quality datasets demands a balance between protecting health data privacy and making data available to improve health and healthcare ( McGraw and Mandl, 2021 ). Such balance is generally guaranteed by the data protection legislation such as Health Insurance Portability and Accountability Act 1996 (HIPAA) of the USA and General Data Protection Regulation 2016 (GDPR) of the European Union (EU).…”

“…Such balance is generally guaranteed by the data protection legislation such as Health Insurance Portability and Accountability Act 1996 (HIPAA) of the USA and General Data Protection Regulation 2016 (GDPR) of the European Union (EU). The effectiveness of these legislation in the environment of big data analytics is still debatable ( Casey et al., 2019 ; Gil González and de Hert, 2019 ; Hoeren and Niehoff, 2018 ; Kesa and Kerikmae, 2020 ; McGraw and Mandl, 2021 ; Turpin et al., 2020 ). Despite these concerns, artificial intelligence technologies have already shown outstanding results in medicine and have expected to bring further innovations into medical technologies and future healthcare ( Park et al., 2020 ).…”