Public health surveillance means collecting, analyzing, and understanding health data all the time. This helps public health workers take quick action and track diseases in groups of people. In the past, this work was done by hand, which caused delays and made it hard to bring together different types of data.
AI brings new skills for analyzing data fast and improving how infections are watched. It can handle large amounts of data from many sources, which helps especially in tracking infectious diseases and outbreaks.
An important AI tool used in the United States is the Electronic Medical Record Support for Public Health (ESP) system. It was created with the Massachusetts Department of Public Health (MDPH) and the Centers for Disease Control and Prevention (CDC). ESP automatically collects and nearly instantly analyzes electronic health record (EHR) data.
ESP covers more than 60% of people in Massachusetts for watching infectious diseases and about 20% for chronic health issues. It takes important clinical data, changes it into common formats, and looks at it for public health reports. This system gives daily automatic reports about diseases that must be reported. These reports help health departments know what is happening quickly.
Tools like RiskScape show where and when diseases happen, helping health officials understand trends. The RAVIOLI platform tracks respiratory virus infections by combining lab results and diagnosis codes, which helps watch infections more closely. Also, ESP-VAERS improves vaccine safety by monitoring side effects from COVID-19 and Mpox vaccines and reporting them to federal bodies.
For medical practice managers and IT workers, systems like ESP show how AI can work well with existing EHRs. They help make public health reports faster and more accurate, lower the amount of work done by hand, and use resources better for infection control.
AI helps find outbreaks faster by looking at large amounts of data from many places. These include news articles, emergency room reports, satellite pictures, and lab tests. For example, the CDC’s National Syndromic Surveillance Program uses AI to watch symptoms in real time and find new health threats.
AI tools can read about 8,000 news articles each day to find signs of disease clusters or outbreaks. This fast watching helps public health workers respond quicker to contain diseases.
AI also finds sources of infection in the environment. For example, during Legionnaires’ disease outbreaks, AI helps find cooling towers by looking at satellite images. This saves over 280 hours of investigations every year and helps find the source faster.
These examples show clear benefits for healthcare leaders who need quick and accurate data for decisions, planning, and talking with public health officials.
Clinical trials are important for creating new treatments, vaccines, and tests. But clinical trials can be hard and need a lot of staff time. Tasks like finding patients, collecting data, watching disease changes, and following rules take effort.
AI helps by automating data analysis, sorting patients, and watching disease progress quickly. AI can look at medical histories, referrals, lab results, and care gaps to give trial coordinators summaries fast. This helps manage and follow up with patients better.
One example is Salesforce’s Agentforce for Health. This AI tool is used by places like Rush University System for Health. Agentforce automates tasks like checking if patients qualify, verifying insurance, approving trips, and scheduling. It works with EHRs and talks to patients to match them with the right specialists and arrange appointments smartly.
This AI help works all day and night. It makes it easier for patients and lets healthcare workers focus on harder cases and medical decisions instead of paperwork. Studies show staff think AI could save them up to 10 hours a week. It can cut admin work by 30% for doctors, 39% for nurses, and 28% for office staff. These gains help clinical trials run better, finish faster, and have better data.
AI automation helps solve workflow problems in medical offices. Many healthcare workers have too much paperwork. A survey by Salesforce found 87% work extra hours to handle paperwork. About 59% say this causes them to feel tired and stressed.
AI agents can automate talks with patients and insurance companies. For example, they check insurance eligibility and benefits quickly through systems like athenahealth and Availity. This speeds up prior authorization decisions so they happen in seconds. It also meets CMS rules for data sharing. Faster admin work means less waiting and less patient frustration.
Besides insurance, AI helps inside the clinic by getting key clinical information ready before patient visits. Care coordinators get detailed reports with past diagnoses, referrals, and missing care. This helps clinics prepare better and focus on important issues during visits.
With AI taking over routine office tasks, doctors, nurses, and staff can spend more time with patients. This improves job satisfaction. About 61% of healthcare workers think AI tools would make their jobs better by cutting down boring and tiring tasks.
For IT managers, adding AI tools means choosing systems that work well with current EHRs and billing software. Working with companies like Salesforce, athenahealth, and Availity helps build AI tools that fit the size and type of the practice and its patients.
The Chief Information Officer at Rush University System for Health, Jeff Gautney, said using Agentforce AI helps patients 24/7. The AI guides them through the hospital and helps pick providers based on each patient’s needs. This automation made the patient experience better and lets human staff handle tougher questions. It improves the overall work done by the practice.
AI also plays an important role in finding infectious diseases and managing medicine resistance. Using machine learning, AI improves how well labs detect germs, organizes lab and clinic work, and helps track treatment faster.
One important use is in antimicrobial stewardship. AI looks at data from molecular tests, blood tests, and clinical info to find infections quickly and suggest the right medicines. This helps use antibiotics wisely and fight antibiotic resistance.
Despite these benefits, using AI widely faces problems. These include separated data systems, rules and regulations, privacy concerns, and a lack of trained staff who know AI tools. Differences in digital tools between rich and less rich areas also affect how well AI works.
Still, AI-powered point-of-care diagnostic tools bring testing to places with few resources or far away clinics. By combining biosensors, images, and molecular tests with AI, health workers can make faster, evidence-based decisions about infections.
For healthcare leaders in the US, investing in AI systems that link many data sources is important to improve infection control and keep patients safe.
The Centers for Disease Control and Prevention (CDC) supports AI to improve public health work. The CDC uses AI chatbots agency-wide, which saved about $3.7 million in labor and gave a 527% return on investment.
The CDC also uses AI to study thousands of grant reports, saving 5,500 staff hours and $500,000. AI tools helped in faster outbreak response, public health messages, and data analysis by combining data from health records to satellite images.
The CDC’s AI Accelerator (AIX) program and AI Community of Practice helped prepare operations and educate workers. Over 2,200 members joined monthly sessions in 2024. These programs focus on safe AI use, data security, and following federal AI rules, which are important for public trust and meeting laws.
Medical practice leaders and IT managers should know that working with public agencies, tech companies, and universities helps build systems for AI use. These partnerships help share data and encourage new ideas in disease tracking and medical research.
By understanding AI’s growing role in public health surveillance, infection monitoring, and clinical trial support, medical practice leaders in the US can make their organizations work better and improve patient care. Combining AI automation with current work can cut workloads, improve data accuracy, and help timely decisions in clinical care and public health. These improvements help create a more responsive healthcare system that benefits both providers and patients.
Agentforce for Health is a new library of pre-built AI agent skills and actions created by Salesforce in 2025 to address time-consuming administrative healthcare tasks like eligibility checks, scheduling, insurance verification, and prior authorization.
The AI agents handle patient inquiries, eligibility checks, insurance benefit verifications, prior authorizations, scheduling appointments, monitoring infection spread, and supporting clinical trial site analysis and innovation.
AI agents reduce administrative burdens, saving healthcare teams up to 10 hours weekly, with estimated workload reductions of 30% for doctors, 39% for nurses, and 28% for administrative staff, thereby improving job satisfaction.
The agents chat directly with patients to match them with in-network providers and specialists and intelligently schedule appointments via integration with electronic health record systems like athenahealth.
Salesforce partners with athenahealth for scheduling, Availity for direct payer communication and eligibility checks, and Infinitus.ai for electronic benefits verification to streamline prior authorization and insurance validation processes.
Agentforce supports compliance with Centers for Medicare & Medicaid Services interoperability mandates by enabling real-time submissions and receipt of prior authorization decisions within seconds, reducing administrative delays.
AI monitors the spread of infections by auto-classifying cases and accelerates drug and medical device innovation via real-time integrated study data and intelligent clinical trial support.
Agentforce provides care coordinators with patient summaries including medical history, referrals, care gaps, and benefits, enhancing patient access and personalized care management prior to appointments.
Organizations like Rush University System for Health use AI to automate administrative tasks and provide 24/7 patient support, freeing human staff to focus on complex issues and improving the patient experience.
Salesforce executives anticipate a modest revenue contribution from Agentforce in fiscal year 2026, with a more meaningful financial impact expected in the following year, reflecting gradual market adoption.
Simbo is using AI agents to automate all phone related workflows. Connect now to know more.
Schedule AI Agents Demo Now© Since 2019, Simbo AI.
