Two days after a knee replacement, the patient’s phone rings. An AI agent is calling for the surgeon’s office, working through the check-in the care team wrote: pain level, fever, the incision, whether physical therapy is booked. The patient says the incision looks red and feels warm, so the agent routes the call to a nurse and books a wound check for that afternoon. In most health systems, that call depends on a nurse finding a free hour, and a red incision can go unreported until the patient shows up in the emergency room.
What is care coordination in health care?
Care coordination is the deliberate organization of patient care activities and information sharing among everyone involved in a patient’s care, so the patient’s needs and preferences reach the right people at the right time. Care coordination in healthcare covers post-surgical check-ins, referrals to specialists, follow-up testing and treatment, and handoffs between primary care physicians and everyone downstream.
For decades, coordinators and nurses have tracked every open loop by hand, and there are always more patients than hours. Artificial intelligence is changing that math. AI agents can now start the conversation, follow the care team’s protocol, complete the task, and bring in a person when an answer calls for one.
A 2019 JAMA study estimated that failed care coordination wastes $27.2 billion to $78.2 billion in U.S. health care spending each year, and chronically ill patients with the most fragmented care cost $4,542 more per year than those with the least (AJMC, 2015). An estimated 68% of patients experience fragmented care, and poor coordination leads to medication errors and worse health outcomes. Effective care coordination reduces hospital and ER visits by 30% to 40%.
Care management and coordinated care break at care transitions
Care management builds personalized care plans for high risk patients and connects them to community programs and other resources. Care coordination turns any plan into effective care.
Coordinated care fails most often at care transitions, where responsibility changes hands: the discharge back to primary care, the referral to a specialist. Chronic conditions affect 51.8% of U.S. adults (CDC, 2018), and social determinants like transportation and language shape who can act on a plan.
Find the patients who need care before they call
Registries, care gap reports, and the patient data in electronic health records already name the patients overdue for a colonoscopy or a mammogram, and a recall agent works that list. A reactivation agent reaches patients who lapsed years ago and books them back in. A referral agent picks up every referral that was sent and never booked, a loop where only about a third of specialty referral attempts end in a documented appointment.
Prep the patient so the visit can happen
Before the patient arrives, an insurance agent clears eligibility and a payment agent shares the estimate and copay. An intake agent collects demographics, consent, and chief complaint by text or voice, so the provider reads a summary before walking into the room. For example, a readiness agent sends colonoscopy prep instructions and runs the day-before check.
Book the right visit inside the conversation
Healthcare research puts phone first: it remains the primary scheduling channel for 56% of patients (Dialog Health, 2025). A scheduling agent answers that line around the clock for a diverse set of patients in 23 languages, including the 6 p.m. caller who used to wait for morning, and books, moves, or confirms in the conversation. When a patient cancels, a waitlist agent offers the slot to the next patient in line. For an affiliate practice with no electronic link, an affiliate agent calls the office, books the time, and texts the patient.
Follow up so clinical decision making reaches better outcomes
Follow-up reaches well past surgery. A reminder agent confirms the visit and catches a likely no-show while the slot can still be filled. A care-plan agent checks on patient health between cardiology visits and flags a weight change to the care team. A home care agent coordinates outreach where the patient lives. When an abnormal result gets a follow-up call and a booked specialist visit, life saving treatments start on time. Completed care is what moves health outcomes, and accountable care organizations are measured on exactly that.
Care coordination software is becoming an AI care coordination platform
Most care coordination software centers on the care team, with key features like shared worklists, a unified patient profile, real time collaboration among clinicians and specialists, HIPAA compliant communication, and dashboards that provide insights on open tasks. These tools streamline workflows, cut administrative burden, and improve information sharing among healthcare providers and hospital departments.
The shift underway is from software that tracks the task to AI that completes it. A task marked “referral sent” is closed in a worklist and still open in the patient’s life. Many AI solutions still serve the care team as AI powered tools for note summarization, risk scoring, and real time insights. An AI care coordination platform works the patient’s side through real time communications by phone, text, and chat. Closing those loops is how it will improve patient outcomes, and it is improving quality in a form a CFO and a CMO can both read.
Mila, DexCare’s AI care coordination engine, is built around the find, prep, book, and follow up journey, with custom workflows configured to each health system’s operation. Task-specific agents run pathways that passed medical review, so an agent can provide safe answers at scale, and a request that needs a person goes to staff with full context. On outbound outreach, Mila’s agents see a 54% response rate, 80% higher than manual calls. Referral conversion doubles. No-shows fell 50% at Gilroy Gastroenterology. The work returned roughly four workdays a month to schedulers, nurses, and coordinators, who can focus on complex cases. Patient engagement gets measured by the visit it produced.
Better care shows up as a visit on the schedule
Care coordination is heading toward a model where every open loop has an owner, and for routine tasks that owner is an AI agent. The health systems getting the most from AI start with one workflow and keep adding agents. If a coordinator does something the same way twenty times a day, an agent can do it for every patient who needs it. Agents that finish the task lead to better patient outcomes, improve outcomes first for high risk patients, and give the patient experience a simple benefit: one fewer call to chase.
The knee replacement patient never had to decide whether a red incision was worth a phone call. Better care is the health system calling first, and AI is what lets it make that call for every patient who needs one.
