Computational Medicine Legal Accelerator
Health data contains rich patterns and information that, if made available to machine learning researchers, could lead to breakthroughs in diagnosis and patient care. However, this data is siloed and fragmented within different medical and research institutions. Efforts that aggregate clinical data of patients across institutions are urgently needed. However, every time an institution gains access to patient data at another institution, there is a legal process that must take place, typically involving a data sharing agreement and / or Institutional Review Board approval. The COVID-19 crisis has made obvious what many researchers already knew: necessary and important legal agreements can slow their access to data significantly.
Our fundamental goal is to safely get more health data into the hands of machine learning researchers faster, while maintaining the critical legal review process involved in sharing health data between institutions.
To improve the current data-sharing process and advance science, we are building a coalition of individuals across institutions committed to a shared understanding of the issues and to making improvements in their communities of practice or home institutions. This group currently consists of 15 individuals across 11 institutions working to improve the process of data sharing for computational medicine research. If you are interested or involved in the data sharing process at your institution, we would love to hear from you!
In the past six months we completed the first phase of our project, which was focused on user research. We interviewed 30+ people across 13 different institutions to better understand the current data sharing process within the university research ecosystem, and built a coalition of 15 advocates and advisors, diverse in title and institution, committed to helping us shape tools that address the legal process challenges we identified in our user research.
The output of this phase was to identify three core deliverables to be completed in the first half of 2021: a template DUA, a data sharing process flow chart template, and a guided set of worksheets for data sharing. These tools will help lawyers, principal investigators, researchers, reviewers, and other administrators at institutions address challenges we discovered across training, legal review, and process efficiency.
We are hopeful that these tools will help principal investigators, reviewers, and others at research institutions in addressing challenges we discovered pertaining to training, legal review, and process efficiency.
Amy Pitelka is the chief legal officer of Nightingale Open Science, and the founder of Barker Pitelka PLLC, a legal and policy strategic advisory firm focused on technology startups and social good organizations. Prior to starting her own firm, Amy was the Acting Deputy Administrator and lead Counsel for the United States Digital Service at the White House, where she focused on identifying, combating, and removing key legal and policy hurdles to the USDS’s ongoing efforts to revolutionize the federal government’s use of technology in delivering services to the American people. In her time at the USDS, Amy led the legal effort to unlock key datasets used for health benefits administration to additional human services programs administered by states and counties across the country. Amy has also worked at Dropbox, Google, and Kirkland & Ellis International LLP. She graduated from Harvard Law School.Amy Pitelka
Linda Pantale, '20
Linda Pantale has worked as a project manager and research assistant on several CAI initiatives, most recently the Economic Precision Epidemiology project and the Legal Accelerator. She has a background in higher education administration and strategy and recently finished her MBA at Chicago Booth, focusing on strategy, entrepreneurship, and behavioral science.Linda Pantale, '20
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