ASSESS: Human vs. Machine

During the delivery of healthcare, information is required at the point of service. Making good judgments and decisions about health, whether directed by a clinician or self-directed by individuals, requires access to any information that may be needed. Recent clinical experience with machine support for this human cognitive function has ranged from disappointment to frustration, especially with electronic health records (EHR) and patient portals.

There’s been a great deal of dialog around new analytic methods, and the ability to assess larger data sets can help us with this task. Can machine learning and other forms of artificial intelligence help us with this fundamental and complex cognitive task?

To find this answer we have to start with another question: what is the role of machines and what is the role of the humans in this enterprise?

Decisioning is the active process of maneuvering information, probabilities, likelihoods, and individual values and desires to allow a valid and reproducible decision to be made among alternatives. (Dacso, C., et.al. Project on Decisioning, 2003.)

Time and effort have been spent in trying to displace the professional part of this process, which can be the most difficult, and to degrade the value of professional input to the lowest value-add function, data entry.

The cognitive tasks associated with diagnosis, decisioning and prescription are complex, requiring a step of inference, and thus far cannot be replaced by dropdown boxes and clicks. The time a clinician spends on these tasks should be protected as if by a bubble. It should be our goal to automate all of the data and processes that are needed to inform this bubble and all actions and communications that come from this bubble.

Our focus is to automate processes and the output of advanced analytics and machine learning in new ways that support the goal of delivering health.

Keeping the roles straight helps both machine-human interface and human acceptance of that interface. The role of the machines is to deliver useful information in either pre-styled ways or in response to ad hoc requests, new tools for expanded approaches. The role of humans is to continue the complex cognitive tasks associated with diagnosis, decisioning and prescription. If the loops close and the learning is automatic, the combination of population health improvement with personal precision care may occur.


Bob Teague, MD, Chief Medical Officer of SocialCare

Bob brings a wealth of experience to his articles based on a career spanning clinical practice in major healthcare institutions as well as leadership roles in multiple entrepreneurial enterprises and Fortune 50 technology enterprises. These financially successful enterprises were transformative in their markets for respiratory home care services, diabetes chronic care management, and Medicare Advantage risk management through transitional care. Bob’s first blog series focuses on a central SocialCare paradigm, “Acquire + Assess + Act”.

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