The term “artificial intelligence” (AI) was coined in 1956 by a computer scientist who was part of the first academic conference on the subject. Still, while it has been around for decades, the phrase—along with “machine learning” (ML), an approach used to achieve AI—has permeated many aspects of everyday life in recent years. Voice-enabled devices such as Amazon’s Echo, email spam filters, and mobile check deposits are just a few examples of the way this technology has changed our world.
Of course, AI’s reach goes beyond home life; the healthcare sector has seen its influence, too. The implementation of AI technology is growing and will continue to increase as it solves and promises further solutions to challenges encountered by patients, facilities, and the healthcare industry at large.
A recent VentureBeat post by TechTalks founder Ben Dickson covers AI’s potential role in decreasing administrative costs in healthcare. Read on to learn about three important areas where efficiencies could be improved through this technology.
- Population health management
HIPAA, the HITECH Act, and other regulations have been key in driving the use of digital technology in healthcare, including the development and adoption of electronic health records (EHRs). Yet, as Dickson relates, the actual value of the medical data captured is more difficult to quantify.
Population health management tools currently in place require analysts to probe healthcare datasets. But AI could narrow the gap between collected information and that which is unknown because clinicians had not made the appropriate inquiries. “Unsupervised learning,” a subgroup of ML, could assess the data, and uncover similarities and differences with little human interaction. The findings could help hospitals and other healthcare organizations provide preventive and predictive care, which could lead to substantial savings in disease management and treatment.
- Evidence-based medicine
“[AI] may be used in the identification or development of evidence-based medicine and treatment protocols that can be used, generally, for the treatment of specific diseases,” says Pamela Hepp, an expert in data security, healthcare regulation, and digital health records and a shareholder at Buchanan, Ingersoll & Rooney PC, whose insights are included in the VentureBeat article.
AI algorithms are working to increase those endeavors at present. They could prove vital in terms of both patient health and cost in the diagnosis and treatment of diseases. A computer can study numerous, established treatment alternatives and propose the best option(s) for a patient. In addition to its capacity to save lives, the method could aid in reducing the expenses associated with recurring hospitalizations and premature discharge of at-risk patients.
- Medication research and discovery
The advancement of new medications and vaccines is a lengthy and costly process. However, Dickson notes AI could facilitate in decreasing expenditures and hasten the process by furthering analysis and research efforts. He illustrates the point by citing an example of a partnership between Pfizer and IBM Watson to utilize AI in the drug research process.
“IBM will use the massive computational power and cognitive abilities of its AI platforms to quickly analyze and test hypotheses from ‘massive volumes of disparate data sources’ that include more than 30 million sources of laboratory and data reports as well as medical literature,” he says. “For instance, researchers can use Watson’s natural language processing (NLP) capabilities to analyze the content of thousands of medical papers and reports at very fast speeds to find facts that are relevant to their work.”
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