Health care C-suite’s guide to artificial intelligence

Health care C-suite’s guide to artificial intelligence

August 15, 2017
Health IT
From the August 2017 issue of HealthCare Business News magazine

By Bipin Thomas

In previous columns, I introduced the emerging relevance of artificial intelligence (AI) in the health care industry.

While the future of AI looks bright, there are several questions C-suite executives must ask.
They include:

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• How can we aggregate all the data input generated within our four walls to do right for our patients? How can we draw insights from the data to take actionable steps to improve quality of care? How can we serve up the data to make each and every member of the care team operate at the highest level? How can we do all this cost-effectively?
• Are we capable of both the descriptive analytics that tell us how good we are at taking care of patients and the predictive analytics that will let us take on more risk-based contracts?
• Is our EHR system open to the cloud? Can it incorporate third-party apps? Is it user-friendly?
• Are we paying license fees that are proportional to the benefits we get out of our databases? Do they update every day? Are our vendors really leveraging all the advances in AI technology?

High potential AI applications
Accenture predicts that health care AI will grow at an annual rate of 40 percent through 2021, reaching $6.6 billion by that year. Digging a little deeper, there are a few specific AI applications that will have the biggest near-term effect on health care. To gain a thorough understanding of their impact, Accenture comprehensively analyzed the applications. The organization estimates each item will have the following value (or potential annual benefits) by 2026:

• Robot-assisted surgery — $40 billion.
• Virtual nursing assistants — $20 billion.
• Administrative workflow assistance — $18 billion.
• Fraud detection — $17 billion.
• Dosage error reduction — $16 billion.
• Connected machines — $14 billion.
• Clinical trial participant identifier — $13 billion.
• Preliminary diagnosis — $5 billion.
• Automated image diagnosis — $3 billion.
• Cybersecurity — $2 billion.

This adds up to a total value of about $150 billion. The No. 1 application, robot-assisted surgery, specifically applies to orthopedic surgery. Cognitive robotics can integrate information from pre-op medical records with real-time operating metrics to physically guide and enhance the physician’s instrument precision. The AI technology incorporates data from actual surgical experiences to inform new, improved techniques and insights.

The No. 2 application, virtual nursing assistants, can save nurses from unnecessarily having to visit patients and can keep patients from unnecessarily visiting the hospital. And administrative workflow assistance applications can save valuable time for physicians and nurses by cutting down on non-patient care tasks such as writing prescriptions. Hospital leadership should focus on four areas — care reach, institutional readiness, security and workforce — so as to take advantage of all that AI has to offer.

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