On the Edge of the Future: Imperatives to Succeed in Health care’s Grand Transformation


By Paul Grundy, MD, MPH, FACOEM, FACPM

Making health care smarter

The current health system transformation has been referred to as health care’s “moon shot” – that defining moment when a grand vision is fulfilled and the world changes.  Cognitive computing systems play a major role in achieving this moon shot.

Cognitive computing systems learn and interact naturally with people to extend what neither humans nor machines could do on their own. They enhance humans’ ability to make decisions by penetrating the complexity of Big Data.

Traditional computers, while powerful, are limited by their programming. They are programmed to review every possible answer or action needed to perform a function or set of tasks. They can only do what they have previously been told to do.

Cognitive computing systems, by contrast, are “trained” using artificial intelligence and machine learning algorithms. They mine the world’s data, make correlations, identify patterns and present actionable, patient-specific information and recommendations to physicians at the point of care. This enables physicians to focus on the diagnosis and the patient relationship when the patient is in front of them rather than spending that time on research. In this sense, cognitive computing is the X-ray of diagnosis: It reveals hidden details of the patient’s condition to enable more informed and accurate decisions.

Consider this example of how cognitive computing will contribute to a patient’s long-term health as well as the healing relationship of trust between the doctor and patient.

A patient with chronic heart failure (CHF) visits his primary care physician seeking a plan of treatment. After the patient meets with his physician he is handed off to the office’s care manager, who calls up the patient’s record and is provided with a personalized plan of care based on a multitude of factors, including the patient’s current health status, family history, genetic predisposition, socio-economic factors and other information. The patient is encouraged by the care manager to download an app for his smartphone that will let his provider track his progress against the plan.

Each day, the app collects information such as the patient’s weight and the answers to his questions about common symptoms. If he has questions about some aspect of his health, his plan of care or his medications, the app either answers the question, or escalates the question to an e-visit with a care manager. In addition, persistent health reminders encourage patients to adopt the right behaviors and develop healthy habits that lead to better health and lower costs.

Based on that patient’s history and current remote data, as well as population health data for thousands of other CHF patients and information from the clinical literature, the app may spontaneously send an alert recommending that the patient consult his doctor.  In that case, it offers to set up an appointment via integration with the office’s scheduling system.

As you can see from this scenario, population health management supported by cognitive computing lets health care organizations identify the right type and scope of care to treat patients in a minimally-invasive fashion and in the most cost-effective setting.



Outlook for the future

It is not difficult to imagine what health care will look like in the future, because we have already made great strides toward achieving a transformed health care system. The fabric of the care team will continue to advance. New technologies and new structures will drive more efficiency and accountability across healthcare, and give us the confidence that we are making a meaningful difference in patients’ lives.


Paul Grundy, MD, MPH, FACOEM, FACPM, is the Chief Medical Officer and Global Director of Healthcare Transformation for IBM Healthcare and Life Sciences. He is also a founder of the Patient-Centered Primary Care Collaborative (https://pcpcc.org/), and is an Adjunct Professor in the Department of Family and Preventive Medicine at the University of Utah School of Medicine.


Leave a Reply

Fill in your details below or click an icon to log in:

WordPress.com Logo

You are commenting using your WordPress.com account. Log Out /  Change )

Facebook photo

You are commenting using your Facebook account. Log Out /  Change )

Connecting to %s