As the gap between the data and the doctor gets deeper and wider, we are faced with the issue of who and/or what will fill the gap.
As the gap between the data and the doctor gets deeper and wider, we are faced with the issue of who and/or what will fill the gap. Some think IBM’s Watson can do the job. Others are doubtful and think biomedical data scientists or systems engineers are the answer. It will probably be a combination of both. However, many, like me, think that the players who will fill the gap have yet to be defined and trained and that the jobs of the future in clinical data practice have yet to be created.
I propose we consider three levels of biomedical data science education and research: basic, applied, and biomedical data science entrepreneurship.
We should design offerings at different levels for each depending on their needs.
In that vein, I'm thinking we need “clinical data navigators.” Rather than computer scientists, engineers, and others with PhDs, these would be people trained at a master’s level in how to use clinical and business data to assist doctors and patients when it comes to making decisions and recommending treatment. They would make rounds with doctors, participate in care planning, help with recruiting patients into clinical trials, advise patients and their families, and serve as translators and interpreters, helping patients understand the complex world of translating complex genomic, population health, and outcomes data into actionable information at the point of care in the face of ethical, administrative, and business pressures.
The Commonwealth Fund seems to like this idea. They’ve listed four barriers :
• Technical challenges
• Lack of clear business models
• Absence of policies to guide development of DHA services and ensure their quality
• Cultural gaps between healthcare providers, the consumer digital industry, and the public
There are others as well, including liability, manpower development, scope of practice, licensure and credentialing, certification issues, security and confidentiality, and many more.
Clinical data navigators might be an answer to closing the gaps. However, as with any new idea, we need to determine whether there is a good product-market fit and how we would deploy and sustain the business model.