By: Richard L. Smith
Artificial intelligence is increasingly being used to help make real healthcare decisions – from predicting what treatments patients might need to deciding what services insurers will cover.
This change is coming to New Jersey, and public health experts say it brings both potential benefits and serious concerns.
According to the report of New Jersey Monthlyacademic researchers and healthcare leaders across the state are exploring how AI can improve care, speed diagnosis, and help doctors focus more on patients rather than administrative tasks.
AI tools are already used in hospitals and research centers to analyze medical records, support personalized treatment plans, and help clinicians identify critical scan and test results faster than a simple manual review.
These applications can improve workflow efficiency and, in some cases, improve early detection and responsive care for people facing serious illness.
At the same time, a major change underway nationwide could directly affect New Jersey residents enrolled in Medicare. Federal health agencies are planning a pilot program that will use AI to support decisions about whether Medicare will cover certain procedures and services.
Critics of the program warn that using algorithms for prior authorizations or coverage decisions — even if aimed at reducing unnecessary care — risks introducing delays or denials that can be difficult for patients and doctors to challenge.
This “AI in coverage decisions” model is rooted in broader trends where insurers and government payers rely on automated systems to review claims and authorize services, a practice that is already drawing scrutiny for its potential to slow down care and create barriers for patients.
Potential concerns cited by health policy analysts include:
• Delays in care — Algorithms filtering out “low value” services could slow approval of necessary procedures, particularly when patients or providers need to appeal automated decisions.
• Lack of transparency — Proprietary models may not clearly explain why a decision was made, leaving patients and doctors uncertain about how to respond.
• Risk of bias —Emerging research suggests that AI models sometimes recommend different care based on socioeconomic or demographic factors in their training data, which could worsen disparities.
At the same time, supporters support Smarter use of AI can reduce clinician burnout by handling data-intensive tasks, speeding up diagnosis, and helping personalize treatments more precisely than conventional methods, benefits that could improve outcomes for many patients when the tools are used under strict human supervision.
Whether the growing role of AI in medical decision-making will help or harm New Jersey patients depends on how these systems are governed, how transparent they are, and whether strong human oversight remains at the center of care decisions.
Patients, advocates, and clinicians are demanding safeguards that preserve access, equity, and accountability as this technology becomes ever more deeply integrated into the healthcare system.