The exponential growth of computational power and the widespread availability of computable datasets have created the potential for artificial intelligence to impact most aspects of life, including healthcare.
As early as 1927’s “Metropolis,” films have portrayed intelligent machines with nefarious intent. The reality is that AI transforms our potential to improve and extend lives—although plenty of apprehension still exists that machines could replace healthcare professionals, leading to catastrophic errors and the dehumanization of healthcare.
A new report from the Blue Ridge Academic Health Group, a study group of academic health center leaders, focuses on the most likely capacity of AI in healthcare—the ability to make automated predictions based on insights developed by machine learning algorithms. Healthcare has lagged behind most other industries in automating its processes for collecting and sharing data. The Blue Ridge Academic Health Group report encourages healthcare leaders to avoid that mistake with AI and invest early in its enormous potential for advancing health education, research and care delivery.
Health professionals are bombarded by data, much of it unstructured and therefore un- or under-utilized. With the explosion of technologies and medical devices, it’s estimated that every patient will generate enough health data to fill nearly 300 million books in his or her lifetime. Meanwhile, research is expanding so rapidly that it would take physicians 150 hours a week to read everything published in their field.
Want to publish your own articles on DistilINFO Publications?
Send us an email, we will get in touch with you.
Existing technologies, even sophisticated data analytics, cannot provide humans with the interpretive power to overcome these challenges. Machine learning has the potential to complement (not replace) healthcare providers and scientists. By doing such things as recognizing patterns and making inferences, machines can analyze massive, constantly changing datasets and perform tasks without explicit instructions.
As AI allows us to make sense of the data deluge, we have the potential to significantly improve health and reduce costs by enhancing the patient and clinician experience through augmenting, not replacing, the healthcare team. Examples include:
- Enhancing decision support for patients with life-threatening conditions, so that all factors determining outcome (genetics, drug therapies, and social and behavioral circumstances) can be considered.
- Helping patients and their caregivers assess the risk of future events, from drug side effects to chronic diseases, and make prudent lifestyle and screening choices based on a full array of contributory factors.
- Reducing the paperwork, improving back-office functions of healthcare delivery, and cutting the cost of care while improving patient and clinician satisfaction.
While these technologies are being developed, it behooves leaders to invest in building the infrastructure, competencies and collaborations needed to move a healthcare system that has traditionally made decisions based on what providers can see, touch and feel, to a new realm that relies partly on assistance from intelligent systems that help us assess possibilities, prioritize outcomes and automate decision implementation.
Nevertheless, many possible pitfalls remain to be navigated to fully realize AI’s potential for clinical decisionmaking, intervention and documentation. Among the inherent risks are biases within the algorithms driving the applications, complacency among clinicians who become dependent on the new tools, and compliance with legal and ethical frameworks. We must develop healthcare AI in a manner that ensures societal benefit, focuses on essential healthcare problems and delivers human-centered workflow.
AI requires that our healthcare and biomedical science workforces acquire new competencies, which can and will impact care delivery. It is up to hospitals and health systems and their leaders to embrace these technologies and shape them to ensure we augment the most important decision tasks, solve the most vexing problems, eliminate the most troublesome bottlenecks, and train the most compassionate and capable workforce. It is incumbent on us to boldly and thoughtfully shape this age of transformation in human health.
Date: May 02, 2019
Source: ModernHealthcare