Providers will need to boost cyber defenses amid AI adoption: Moody’s

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AI could ease labor shortages, but health systems will need to increase cybersecurity spending to manage increased risks, according to the credit ratings agency.

Published Nov. 21, 2024

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AI adoption could bring more vulnerabilities for hackers to exploit, according a report by Moody's Ratings. Olemedia via Getty Images

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Dive Brief:

  • Artificial intelligence could ease pernicious labor challenges facing the healthcare sector, but health systems will need to boost their cybersecurity spending to manage increased risks, according to a report by Moody’s Ratings. 
  • The emerging technology could help recruit and retain staff through tools that help nurses pick more flexible schedules or assist clinicians documenting clinical care, according to the credit ratings agency. 
  • But new technology also brings more vulnerabilities for hackers to exploit — already a challenge for the healthcare industry, which is dependent on IT systems that house sensitive and valuable patient data.

Dive Insight:

AI has become one of the most alluring technologies for healthcare executives, kindling hopes that new tools could lessen health systems’ heavy administrative workloads and help manage workforce shortages and clinician burnout.

Using AI to summarize clinical information could free up providers to see more patients or focus on higher level tasks, according to Moody’s. One product in use at St. Louis-based Mercy could attract nursing talent in a tight labor market, allowing nurses to choose shifts of varying lengths and utilizing AI to match their experience and qualifications with open shifts.

AI-assisted clinical documentation, typically where a tool records conversations between patients and providers and generates a draft note, is another large use case. Texas Health Resources is saving an average of 5.5 hours of documentation time per physician per week thanks to the technology, according to the Moody’s report. 

AI could eventually play a larger role in diagnosis and treatment too. The technology can analyze healthcare data to find patterns human clinicians might miss, potentially leading to earlier diagnoses, Moody’s said.

Better data analysis could help health systems manage operations. Los Angeles-based Cedars-Sinai uses AI to monitor local health data to better predict bed capacity and supply needs when infectious disease cases spike, according to the report. The health system said the AI was 85% to 95% accurate in modeling bed needs for illnesses like flu and COVID-19.

However, the healthcare sector will need to manage new challenges as it implements AI, including increased vulnerability to cyberattacks and data breaches. 

Cyberattacks are already a serious risk to hospital operations, sometimes cutting off access to critical technology systems and forcing hospitals to delay care or divert emergency cases. Healthcare organizations are already bulking up their cybersecurity budgets and personnel as threats rise, according to a report published this spring by Moody’s.

Increased risks from AI should push health systems to boost their cyber defense spending too, and they may need to navigate new regulatory challenges as they implement AI as well. 

“[...] The deployment of AI in clinical settings requires careful human oversight to address issues like incorrect responses and the risk of perpetuating biases present in the data, leading to potential legal and equity concerns,” the report’s authors wrote.

Health systems will also need to respond to AI use by insurers. Payers are already using AI to adjudicate claims, automatically denying late claims or those that don’t follow strict coding standards, according to Moody’s.

Lawmakers have previously criticized Medicare Advantage plans for using algorithms to delay or deny care that would have been covered under traditional Medicare, and some insurers have faced lawsuits over the practice. Providers will likely have to invest more time and funds in revenue cycle management to make up for increased claims denials. 

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