The rapid growth of artificial intelligence (AI) technology has created new chances to improve healthcare systems across the United States. One place where AI has made a clear difference is inside Electronic Health Records (EHRs), especially by adding Best Practice Advisory (BPA) alerts. These alerts, powered by AI, help doctors make decisions, improve how they work, and keep patients safer. For medical practice managers, owners, and IT staff in the U.S., it is important to understand how AI and BPA alerts work together in EHRs to help reduce medical mistakes, improve care coordination, and use resources better.
This article talks about how AI-driven BPAs are now part of EHR systems to deal with problems like delayed follow-up on test results and unsafe opioid prescriptions. It shows what leading healthcare centers have done and explains how these tools can be used in clinics to support safe and timely care.
Imaging tests are very important in finding diseases early. But a common problem in healthcare is missed or late follow-up on incidental findings. An incidental finding is a result found during an imaging test that is not related to the reason the test was done. Some of these findings can be serious, like lung lumps or adrenal gland problems, that need quick follow-up care.
Northwestern Medicine, a large U.S. health system, created an AI program to fix this problem by adding it to their EHR workflows. Their AI uses Natural Language Processing (NLP) to read radiology reports and find mentions of incidental findings that need follow-up, especially for lung and adrenal issues. When the AI finds such a result, it sends a BPA alert in the doctor’s EHR screen to guide them on the right follow-up steps.
From December 2020 through more than a year, this system checked over 460,000 imaging studies. About 23,000 reports, or 5% of these exams, had lung follow-up advice. This means on average 68 findings are flagged each day that need quick clinical action.
Before the AI was added, there was no special workflow to track these incidental findings. This led to delays and patient harm that could have been avoided. The AI-driven BPA alerts remind doctors in real time while they work. This helps them avoid missing important results. The system also contacts patients using online portals. If patients do not use portals or don’t have a primary care doctor, nurses call them to make sure they know what to do.
Mozziyar Etemadi, MD, PhD, Medical Director of Advanced Technologies at Northwestern Medicine, called delayed follow-up on incidental findings a type of “preventable harm.” His team showed how common these findings are and why solutions are needed to lower risks to patients and healthcare costs. Missed lung findings alone are linked to more than $43 million in yearly U.S. malpractice payments.
When building their AI system, Northwestern Medicine used a new method to label and train the AI. Nurses and frontline clinical staff who were on light-duty and could not do normal clinical tasks were trained to mark radiology report data in-house. This made sure the data used to train the AI was high-quality and clinically reviewed. It also avoided paying for outside services.
The success of this program has led to expanding it beyond lung and adrenal findings. Now it also covers incidental findings in the liver, thyroid, and ovaries. This broadens the chance to reduce preventable harm.
The opioid crisis in the U.S. is still a serious public health problem. Since the COVID-19 pandemic, fatal drug overdoses have gone up 29%. Some states like Ohio have their highest opioid overdose rates in ten years. Doctors face the hard job of managing pain well while lowering the risk of opioid misuse and overdoses.
Cleveland Clinic has made important changes to improve opioid prescribing safety by putting AI-driven clinical support tools inside its Epic EHR system. Their Enterprise Pain Management Committee, led by Dr. Brendan Patterson, adjusts clinical workflows and sets up Best Practice Advisory alerts to warn about opioid risks and suggest safer options.
Key parts of their method include:
These upgrades have helped doctors reduce unsafe prescribing as overdose risks rise. Dr. Eric Boose, Associate Chief Medical Information Officer at Cleveland Clinic, said that customizing workflows all the time helps keep a balance between patient safety and work speed. Putting these tools inside the EHR avoided adding extra work for providers, which can block change.
Healthcare groups like Northwestern Medicine and Cleveland Clinic show how AI joined with EHRs can change workflows for medical offices in the United States. AI-driven Best Practice Advisory alerts do many important jobs that help make work smoother and improve patient safety:
AI-driven BPAs inside EHRs are not meant to replace doctors’ judgment. They help by sorting huge amounts of data into useful alerts. This helps keep vital patient safety issues clear while cutting down on workflow problems.
For medical practice managers, owners, and IT staff, putting in these systems needs teamwork. Successful projects work with clinical leaders, IT experts, quality and safety teams, and frontline staff to make sure solutions are useful, practical, and affordable.
Medical practices across the United States face growing demands for efficiency, quality, following rules, and patient satisfaction. The experience of large centers offers lessons for smaller practices and health systems that want to use AI-driven best practice advisory alerts:
Medical practice managers, owners, and IT staff who want modern healthcare IT tools should think about AI-driven BPAs as important parts of safer, more effective clinical workflows. By working with technology providers who know healthcare challenges—like balancing clinical work, patient safety, and efficiency—practices can add AI tools in their EHRs that make a real difference.
Simbo AI focuses on front-office phone automation and answering services using artificial intelligence made for medical offices and healthcare groups. Their solutions help lower administrative work and improve patient communication. These tools support clinical AI systems like BPA alerts inside EHRs. By combining automation in patient communication and clinical workflows, Simbo AI offers a full way to use technology in healthcare front offices across the U.S.
In the changing healthcare system of the United States, AI-driven clinical support tools built into EHRs are an important step toward lowering preventable errors and improving patient results. Medical practices can benefit by using these tools and adding them to their workflows. This lets their providers give safer and more efficient care.
The article addresses the problem of delayed and missed follow-up on incidental diagnostic imaging findings, which can lead to patient harm and increased healthcare costs.
The AI system uses natural language processing (NLP) integrated with the electronic health record (EHR) to automatically identify radiology reports with incidental findings requiring follow-up and triggers alerts within the physician’s workflow.
The AI facilitates physician decision-making by identifying reports and triggering alerts but does not make clinical decisions, which remain the responsibility of radiologists and ordering physicians.
Physicians receive a Best Practice Advisory (BPA) alert directly within the EHR, which displays findings and provides workflows to order appropriate follow-up studies.
Patients receive notifications through their online portals with study results; if they do not use the portal or have no primary physician, follow-up nurses manage direct outreach to ensure care continuity.
In one year, over 460,000 imaging studies were screened with 23,000 lung findings flagged requiring follow-up, demonstrating the prevalence of incidental findings and effectiveness of the AI alert system in managing follow-ups.
Northwestern Medicine used trained nurses and front-line staff on light-duty to annotate and label relevant radiology report data in-house, ensuring high-quality, expert-reviewed data effectively and cost-efficiently.
A multidisciplinary team from Radiology, Quality, Patient Safety, Process Improvement, Primary Care, Nursing, Informatics, and others collaborated to design and implement the AI follow-up alert system.
Integration ensures alerts appear in the existing physician workflow without requiring additional software access, improving usability and response time to incidental findings.
Yes, the system is being expanded to cover hepatic, thyroid, and ovarian findings requiring follow-up to further reduce missed or delayed care across more conditions.
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