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Published on
Monday, June 22, 2026 at 12:08 AM

By Sarah Chen — Center-Left Desk

AI System Helps Doctors Catch At-Risk Patients

Clalit Health Services has implemented an artificial intelligence system designed to help family doctors identify patients who may be slipping through the cracks of routine care, flagging those at risk for preventable complications before their conditions worsen.

The system, called AI–PRO and based on the C–Pi platform, scans medical information from computerized records every night, cross-references it with clinical guidelines and knowledge bases, and surfaces recommendations and patients at risk to the doctor the next day.

How the System Works

Examples of the system's interventions include flagging a patient with diabetes who has not performed required tests, identifying a female patient with unbalanced hypertension, highlighting patients at risk for osteoporosis, and calling attention to medication combinations that require clinical review.

The technology is designed to assist, not replace, physician judgment. The decision remains with the doctor: the system raises a flag, and the doctor decides whether to contact the patient, change treatment, send for a test, or ignore the recommendation.

Proactive and Personalized Care

The AI–PRO system represents an effort to move primary care from reactive treatment—addressing problems when patients present with symptoms—to proactive management that identifies risks before they become emergencies. By automating the surveillance of thousands of patient records against established clinical guidelines, the system aims to catch gaps in care that might otherwise go unnoticed in busy family practices.

The platform's nightly scans allow it to process medical information continuously, potentially identifying patients who have missed follow-up appointments, stopped taking medications, or developed new risk factors based on recent lab results or diagnoses.

Clinical Guidelines and Knowledge Bases

The system's recommendations are grounded in clinical guidelines and knowledge bases, meaning its alerts are tied to established standards of care rather than experimental protocols. This approach is intended to support evidence-based medicine while adapting to individual patient circumstances that the physician can evaluate.

By surfacing patients who may need intervention—such as those with chronic conditions who have not had recent monitoring, or those on medication regimens that pose interaction risks—the AI system functions as a clinical safety net, helping doctors manage large patient panels more effectively.

Why This Matters:

The implementation of AI-assisted decision support in primary care addresses a persistent challenge in modern healthcare: ensuring that patients with chronic conditions receive consistent, guideline-concordant care even as physician workloads increase and patient panels grow. Systems like AI–PRO have the potential to reduce preventable complications, catch early warning signs of deterioration, and ensure that vulnerable patients—particularly those with multiple conditions or complex medication regimens—do not fall through gaps in the healthcare system. The success of such platforms depends on their ability to augment rather than override clinical judgment, keeping the physician in control while providing data-driven alerts that might otherwise be missed. As healthcare systems worldwide grapple with aging populations and rising rates of chronic disease, technology that helps doctors deliver proactive, personalized care at scale may become essential infrastructure for equitable access to quality primary care.

Reviewed by the editorial desk — June 22, 2026
Last updated June 22, 2026

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