Data about specific humans must primarily serve the interests of those same humans, and typically prevented from being used against those humans. This sounds obvious and trite but is very difficult to do in practice, since exceptions to this rule should take a “innocent until proven guilty” approach to the humans involved and a “first do no harm” approach to data usage involved. Most of my career has been in healthcare technology trying to apply sound ethics, data science and cybersecurity principles towards this end.
Fred Trotter is a leading authority on the intersection of Health IT and CyberSecurity. He was a founding member of the first Healthcare Industry CyberSecurity Task Force and co-authored the report on improving the cybersecurity of the healthcare industry which was presented to the US Congress in June 2017.
Fred is currently the CTO at CareSet Systems which commercializes Medicare Data. In that role, Fred works everyday to ensure that the privacy and security of Medicare/Medicaid beneficiaries is protected, while leveraging aggregated Medicare/Medicaid datasets to improve the delivery of healthcare in the United States.
Fred Trotter originally trained in cybersecurity as a contractor at the US Air Force Information Warfare Center. He went on to become Rackspace’s first Director of Internet Security, and work as Information Security consultant for VeriSign. He passed the CISSP certification and secretly wishes that he had the time to keep the certification current (sadly that certification and the need for it, have both long expired).
After a career focused on cybersecurity Trotter broadened his focus to healthcare technology and data journalism. He is a recognized leader in this field, and went to NCVHS to testify on the definition of ‘meaningful use’ under ARRA. This was the standards for EHR software funded under Obamacare. He is the co-author of the first Health IT O’Reilly book Hacking Healthcare. Fred Trotter won the 2016 healthcare data liberator award for his work opening significant healthcare data sets.