Panorama - cognitive mobile healthcare

michael nova michael@pathway.com

Abstract

The proper goal for any healthcare delivery system should be to improve the value of care delivered to patients. It is not the number of different services provided, or the volume of services delivered, that matters. It is the value of the care that is important. There are two factors that substantially contribute to decreased value in healthcare: unstructured health data and health care costs.

 

The Data Problem

Every two years, the world’s database doubles, and medical information, specifically, doubles every three years. By 2020, global healthcare data will double every three days, with 80% of the data being unstructured.[1] Healthcare costs in the United States currently exceed 17% of the GDP and continue to rise – patients bear little responsibility for the cost of healthcare services they demand.

 

In general, medicine – and precision medicine – is a big data and systems problem, with many different types of healthcare data, such as lab results, BMI, genetic tests, and insurance information, needing to be collected and intelligently codified on an individual user basis. But data is worthless unless it can be analyzed and acted on. Patients and physicians deserve accurate and actionable recommendations on this healthcare data to truly personalize medicine.

 

The Cost Problem

A powerful driver of value in health care is that better outcomes often go hand-in-hand with lower total care cycle costs. Spending more on prevention, early detection and better diagnosis of disease, for example, spares patients suffering and often leads to less complex and less expensive care later. As an example, the use of telemedicine in the UK has led to a 45% drop in mortality rates, and a 20% reduction in emergency hospital admissions.[2]

 

The Solution: Natural Language Processing Artificial Intelligence

With the above caveats in mind, the use of artificial intelligence (AI) that can read unstructured data automatically, collate and make recommendations on the myriad of healthcare data streams (cognitive medicine) will dramatically impact medical care. Natural language processing (NLP) AI, such as IBM Watson, has already shown utility in oncology programs at Memorial Sloan Kettering and other institutions.



[1] IBM, 2015

[2] Healthcare UK, 2014

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