Healthcare organizations in the U.S. often have problems delivering good customer support. One big problem is high staff turnover, especially in home health care, where turnover can be as high as 65%. This makes training harder and leads to more patient support requests that need detailed coaching instead of simple help.
Before using AI, many healthcare platforms work with many separate systems—sometimes almost 20 different apps for care like home health, hospice, and long-term care. This causes mixed experiences for users and slow response times, sometimes up to 20 hours for customer support requests.
Because of these issues, support centers get a large number of routine questions. Around 60% of calls are about user coaching, not technical problems. This puts extra pressure on human agents and causes delays in helping patients and care providers quickly and accurately.
Traditional healthcare support usually responds only after a patient or staff member has a problem. Reactive support waits for the user to report issues and then fixes them. However, new trends show benefits when customer support tries to handle problems before users notice them.
Proactive service watches patient and user behavior, looks at data patterns, and uses AI to act. It works to stop problems like missed appointments or medicine mistakes by sending reminders and alerts on time. Research shows that this approach lowers frustration, improves loyalty, and cuts down how often users need costly support.
For example, Broad River Retail saw an 80% cut in resolution times after starting proactive support methods. These results are important for healthcare providers who deal with complex patient needs and have limited resources to handle many calls.
Healthcare groups using this model stop focusing only on quick reactive responses—like how long calls take or cost per contact—and instead watch how many patients finish their healthcare without needing help. This “silent success rate” shows how good their proactive care is.
AI technology, especially agentic AI, plays a key role in making proactive healthcare support work. Unlike older AI that follows set scripts or rules, agentic AI acts on its own to do complex tasks across many healthcare systems and departments.
Agentic AI systems watch patient data, medical devices, appointment schedules, and communication history closely. They analyze this information to find possible problems fast. For example, AI can spot insurance delays or gaps in medicine refills and alert patients with tailored solutions right away.
Studies say agentic AI will handle up to 68% of customer service questions by 2028. In healthcare, this means AI can offer support in many languages, all day and night, on phone, email, chat, or social media with consistent, helpful replies.
Large language models inside agentic AI understand natural language well. They help AI process complicated healthcare questions and give personal answers based on the patient’s history, current health, and preferences. AI can even handle multi-step tasks like rescheduling appointments, approving claims, and updating health records without human help.
MatrixCare is a large U.S. cloud EHR provider that serves about 13,000 healthcare groups. They faced problems like high staff turnover and many separate platforms. MatrixCare worked with DRUID AI to use agentic AI agents on many channels.
They set up three different AI agents:
External Support Agent through the Salesforce Community Portal to answer patient and client questions.
Internal Support Agent through Microsoft Teams to help healthcare staff with quick answers.
MatrixCare 360 Mobile App Agent giving caregivers real-time help during their work.
This AI approach led to clear improvements: support calls dropped a lot, accuracy reached 96%, and answers came faster. AI handled routine questions while giving personalized, proactive support that made operations smoother and helped patients more.
Tim Smokoff, General Manager at ResMed (MatrixCare’s parent company), said, “By changing how we serve our clients, we have improved not just response times but also the operational efficiency of customer support, setting a new standard for the industry in healthcare technology.”
MatrixCare plans to use more AI in case management and financial operations to improve compliance, openness, and easier access to data.
Using AI for workflow automation is a practical way for U.S. healthcare groups to make customer support better and faster.
AI automation helps with many repetitive and slow tasks, including:
Ticket categorization and intelligent routing: AI looks at incoming questions and sends them to the right department or agent, cutting wait times and backups.
Automated reminders and notifications: AI sends personal alerts for appointments, medicine refills, or preventive care to avoid missed visits and treatment problems.
Self-service portals powered by AI: These let patients and caregivers find answers, guides, and videos on their own, easing the call center’s work.
Multi-channel interaction management: AI tracks voice, chat, email, and social media talks to keep support smooth even when patients switch ways of talking.
Backend integration: AI connects with systems like CRM, ERP, and supply chain to automate tasks like billing questions, insurance approvals, and inventory control.
AI workflow automation also helps collect and analyze data about patient actions and support trends. This ongoing process lets healthcare leaders spot gaps, improve staffing, and raise patient satisfaction.
By automating common tasks, U.S. healthcare groups cut costs, lower agent workload, and improve how often patient problems are solved on first contact—leading to faster, better care.
Personalized help is important for making AI useful in real patient experiences. AI systems can customize messages using full patient profiles that include medical history, treatment preferences, past contacts, and engagement levels.
Personalized alerts—like reminders for medicine doses or follow-up visits—help patients stick to their care plans and avoid bad events. Also, AI can sense patient feelings in messages, spotting when someone is upset or unsure and getting human help when needed.
Continuous user engagement with proactive AI support improves patient loyalty and keeps patients in care. Patients who feel their provider knows their needs are more likely to follow treatments and stay with their provider.
Even though AI has many benefits, healthcare groups must handle issues related to data privacy and keeping a human feel. Rules like HIPAA and GDPR need careful control of patient data, and AI must follow these rules to avoid data problems or misuse.
Also, even with automation, human help is still needed. AI can handle routine questions and early steps, but hard or sensitive problems need quick access to human experts. Balancing automation with human support builds trust and satisfaction for patients and staff.
The growing use of agentic AI and data analytics will keep changing healthcare customer support. Future AI will likely get better at understanding language, emotions, and working across platforms, giving patients smooth and personal experiences anytime.
Healthcare leaders, practice owners, and IT managers in the U.S. should watch these tools closely and plan gradual AI use that fits their goals, resources, and patient needs.
Using AI to change healthcare support from reactive to proactive has many benefits: it cuts support delays, solves patient problems early, automates key tasks, and improves user engagement. Groups that invest in AI can offer more efficient and patient-focused care in today’s healthcare environment.
MatrixCare struggled with a fragmented platform consisting of nearly 20 separate applications across various care settings, resulting in inconsistent user experience and delayed support response times averaging up to 20 hours, exacerbated by high staff turnover and heavy reliance on call center agents.
DRUID AI automates routine inquiries, triages client queries 24/7, and routes users to relevant information instantly, thereby reducing human agent dependency, streamlining workflows, and enhancing response time and service consistency.
MatrixCare deployed three DRUID AI agents: an External Support Agent via Salesforce Community Portal for client queries, an Internal Support Agent via Microsoft Teams to aid staff, and a MatrixCare 360 Agent inside the mobile app for caregivers’ workflow support.
Support call volumes decreased significantly, response accuracy reached 96%, customer satisfaction improved, and the average response time was greatly reduced, resulting in lowered pressure on staff and faster resolution of coaching-related inquiries.
Due to high healthcare staff turnover (up to 65%) and a complex, fragmented software environment, users frequently required detailed step-by-step guidance and coaching rather than just technical support, causing increased support call volume and delays.
Adoption of DRUID AI eliminated variability in support quality by consistently delivering accurate, up-to-date information to users, ensuring standardized service across diverse healthcare settings.
DRUID AI offers intelligent self-service tools that personalize interactions and automate complex workflows, enabling proactive problem-solving by anticipating and addressing user needs continuously rather than reactively.
Upcoming deployments include a case management AI agent for Home Health & Hospice and an Enterprise Financials division agent to improve access to financial data, compliance, and operational transparency.
The AI-driven support system reinforces ResMed’s culture of customer delight by improving response times and operational efficiency, setting a new industry standard for healthcare technology customer support.
AI agents enhance patient engagement and clinical efficiency through personalized real-time interactions and integration with telemedicine and wearable devices, shifting care from reactive incidents to continuous, data-driven support.
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