Deep Medicine by Eric Topol

Author:Eric Topol
Language: eng
Format: epub
Publisher: Basic Books
Published: 2019-02-18T16:00:00+00:00

TABLE 9.1: A sample of fifteen studies using AI to predict clinical outcomes.

THE HEALTHCARE WORKFORCE AND WORKFLOW

There are many uses of AI for hospitals and health systems that extend well beyond predicting death and major outcomes. By 2017, healthcare became the number one US industry by total jobs for the first time, rising above retail.21 More than 16 million people are employed by health services, with well over 300,000 new jobs created during calendar year 2017 and again in 2018. Almost one of every eight Americans is employed by the healthcare industry.22 Projections from the US Bureau of Labor Statistics for the next ten years indicate that most of the jobs with the highest anticipated growth are related to health, including personal care aides (754,000), home health aides (425,000), physician assistants (40,000), nurse practitioners (56,000), and physical therapy assistants (27,000). Because human resources are by far the most important driver of healthcare costs, now exceeding $3.5 trillion in the United States per year, you can imagine that people are thinking about how AI can automate operations and alleviate this unbridled growth and related costs. As Katherine Baicker of Harvard put it, “The goal of increasing jobs in health care is incompatible with the goal of keeping health care affordable.”23

Some economists have suggested that the growth of new job types in healthcare will match or exceed the rate at which AI can replace them. But Kai-Fu Lee, a leading authority in AI, thinks otherwise: “It will soon be obvious that half our tasks can be done better at almost no cost by AI. This will be the fastest transition humankind has experienced, and we’re not ready for it.”24

Hospitals, clinics, and health systems employ people to abstract their medical records to come up with the right billing codes for insurers, and they employ significant numbers of dedicated personnel for payment collection and claims management. The American Academy of Professional Coders has more than 175,000 members with an average salary of $50,000 to do medical bill coding. It is remarkable that the cost of doing the billing for a visit with a doctor in the United States is over $20, or 15 percent of the total cost. It’s even worse for an emergency room visit, as the cost of billing accounts for more than 25 percent of the revenue.25 Overall, in the United States, more than 20 percent of healthcare spending is related to administration.26 Manual, human scheduling for operating rooms or staffing all the inpatient and outpatient units in a hospital leads to remarkable inefficiencies. Much of the work that attends to patients calling in to schedule appointments could be accomplished with natural-language processing, using human interface as a backup. Algorithms are already being used at some health systems to predict no-shows for clinic appointments, a significant source of inefficiency because missed appointments create so many idle personnel. Even the use of voice assistants to replace or complement nurse call buttons in hospitals by Inovia’s AIVA may help improve productivity.27

All these operational positions await AI engagement and efficiency upgrades.

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