Epilogue: Professional Cooperation and Rivalry in the Future of Data-Driven Healthcare

Abstract

To the extent that technologists in fields such as machine learning can develop their own distinct professional identity, steps toward the digitization of health monitoring and even diagnosis and treatment are likely to advance the triple aim (improving quality, cutting cost, and increasing access to care). However, as historians and sociologists of the professions have shown, such an identity is hard to achieve. It will require mandatory education and ethical rules (with enforceable penalties for violations) designed to apply legal and medical principles of confidentiality, informed consent, and other norms to processes of medical data collection, analysis, and use. Standards to balance privacy and trade secrecy against scientific demands for open data and replicability will be critical. As technologists develop such standards, they should work with — rather than try to replace — the physicians, attorneys, and other professionals whose long experience with fiduciary and other obligations can inform the development of socially responsible data practices.

Keywords: Health Law, Health Policy, Machine Learning, Patient Privacy, Automation, Future of the Professions, Master Algorithm, Black Box, HIPAA