- Yunguo Yu, PhD, MD, Vice President of AI Innovation & Prototyping
Imagine a patient discharged from the hospital after hip surgery. The procedure went smoothly. The care team feels confident. But within days, confusion over medications, missed therapy sessions, and worsening pain lead to a preventable readmission.
This isn’t an outlier. It’s the reality for nearly 1 in 5 Medicare patients and a growing financial and clinical burden for payers and managed care organizations.
Post-acute care (PAC) is where recovery truly begins. Yet too often, it’s also where care falls apart. But here’s the truth: Post-acute care isn’t broken—it’s disconnected. The systems, data, and people involved are working hard, but they’re not working together. The result? Gaps in care, rising costs, and burnout among clinicians. The good news? AI is emerging as the connective tissue that can close these gaps, not by replacing human care, but by empowering it.
At Zyter|TruCare, we believe the future of PAC isn’t about overhauling the system. It’s about reconnecting it with intelligence, automation, and seamless coordination.
Let’s explore how.
Why Post-Acute Care Feels Broken (But Isn’t)
The challenges in PAC aren’t due to poor intentions. They stem from systemic disconnections:
Fragmented Data, Fragmented Care
Referrals get lost. Discharge summaries arrive late or not at all. Without timely, complete clinical data, skilled nursing facilities (SNFs) and home health agencies (HHAs) are forced to operate with half the picture.
The result? Misaligned care plans, delayed interventions, and avoidable complications.
The Rising Cost of Avoidable Readmissions
According to the Medical University of South Carolina, 20% of Medicare patients are readmitted within 30 days, costing over $41 billion annually in preventable spending.
Many of these readmissions stem from poor transitions, lack of monitoring, or unclear discharge instructions—not clinical failure, but coordination failure.
Burnout Behind the Scenes
Clinicians spend 30–50% of their time on documentation, according to CMS-backed studies. That’s 1–2 hours per shift lost to charting instead of patient care.
In an industry already facing staffing shortages, this administrative burden fuels burnout and turnover, especially in home health and long-term care.
Siloed Systems, Limited Visibility
Despite investments in EHRs, many systems still don’t talk to each other. Payers lack real-time visibility into care quality. Care teams waste hours reconciling data manually.
Without interoperability, proactive management is nearly impossible.
How AI Is Reconnecting the Post-Acute Continuum
AI isn’t a futuristic concept—it’s a practical tool already transforming how payers and providers manage risk, reduce costs, and improve outcomes.
Here’s how it’s making a difference across three key areas:
1. Predict Risk, Prevent Crises
After discharge, the real work of recovery begins. Stability. Adherence. Support. Monitoring. But too often, early warning signs go unnoticed, until it’s too late.
AI changes that. Using machine learning models trained on clinical data, lab values, medication history, and social determinants of health, predictive analytics can:
- Stratify patients into high, medium, and low-risk categories
- Flag subtle signs of deterioration before symptoms appear
- Recommend targeted interventions based on individual risk profiles
And unlike static risk scores, AI learns and adapts in real time, so care teams can act before a crisis unfolds.
Real-World Impact:
Intermountain Healthcare deployed an AI model to identify patients at high risk of readmission to SNFs. With targeted interventions, they achieved a 15% reduction in 30-day readmissions, translating to millions in annual savings.
The Outcome?
- 15–20% drop in avoidable readmissions
- Shorter hospital stays due to faster, smarter discharges
- Fewer falls, infections, and medication errors
2. Free Clinicians from Paperwork with Smart Automation
Care planning shouldn’t be a paperwork marathon. Yet in PAC, clinicians often spend hours copying, pasting, and re-entering data. That is time that could be better spent with patients.
Generative AI is changing that. By automating documentation and care planning, it reduces administrative load while improving accuracy and compliance.
Key capabilities include:
- Personalized care plans generated from clinical notes, comorbidities, and patient goals
- Real-time clinical documentation via AI-powered scribing during patient visits
- Context-aware content that aligns with payer and regulatory guidelines
- Reduced errors and denials through consistent, audit-ready records
Real-World Impact:
A leading home health agency implemented AI-driven documentation. Nurses saved 30–40% of their charting time, gaining back 1–2 hours per shift for direct patient care.
They also saw:
- 41% fewer claim denials
- 34% more accurate coding
- 28% reduction in low-level E/M codes
The Outcome?
- Clinicians deliver more care, with less burnout
- Organizations improve audit readiness and revenue integrity
- Patients benefit from more attentive, personalized support
3. Coordinate Care Without the Chaos
Seamless transitions don’t happen by accident. Yet in PAC, handoffs between hospitals, SNFs, HHAs, and primary care are often fragmented, delayed, and error-prone.
That’s where orchestrated AI agents come in. These intelligent agents coordinate across care settings, automating and streamlining the entire transition process. Unlike typical UM/CM processes that are reactive and manual, orchestrated agents proactively manage the flow of care with speed and precision.
Before vs. After Orchestrated AI Agents
Before: A Manual, Fragmented Process
- UM nurse manually checks benefits, eligibility, and medical necessity
- Referrals depend on staff availability and manual paperwork
- Care plans are created manually, with delayed outreach to members
- Communication lags between discharge teams and care coordinators
After: Orchestrated AI Agents Driving Intelligent Coordination
- AI agents handle omnichannel intake and route cases to the right queue instantly
- Benefits, eligibility, and medical necessity are auto-verified using real-time clinical documentation
- AI generates a care plan and stratifies patients by risk to prioritize follow-up
- Virtual agents conduct voice outreach, schedule assessments, and stay connected
- Prior authorization requests are auto-initiated and tracked
- Real-time discharge alerts ensure smooth, proactive transitions
Real-World Impact:
One healthcare network implemented orchestrated AI agents. Results included:
- 35% reduction in transition delays (from discharge to admission)
- 25% fewer missed follow-up appointments
- 10-point increase in patient satisfaction
The Outcome?
- Faster throughput and better bed utilization
- Higher provider capacity and revenue
- Smoother patient experience and stronger engagement
How to Get Started: 5 Strategic Steps to Scale AI in PAC
AI isn’t a one-size-fits-all solution. Success comes from starting smart and scaling with purpose.
Here’s how to begin:
- Start with the Problem, Not the Technology
Focus on high-friction areas: preventable readmissions, delayed discharges, documentation bottlenecks. Set measurable goals.
- Build on Interoperable Foundations
AI can’t fix siloed data. Ensure your platform integrates with EHRs, care management systems, and payer infrastructure.
- Engage Clinicians Early
Frontline teams know where the pain points are. Involve them in selecting use cases and designing workflows.
- Prioritize Compliance and Trust
Protect patient privacy, audit for bias, and ensure transparency in how AI supports decisions.
- Measure, Learn, Scale
Treat AI as an evolving partner. Track outcomes, gather feedback, and refine over time.
Turn PAC from Cost Center to Care Catalyst
Post-acute care doesn’t have to be a blind spot or a budget buster. With the right tools, it can become a proving ground for value-based care where better outcomes, lower costs, and higher satisfaction aren’t trade-offs, but results.
At Zyter|TruCare, we help payers and care networks close the gaps in the post-acute journey. Not with flashy tech, but with purpose-built AI that integrates into real workflows, learns from real data, and delivers measurable results. From predictive risk modeling to automated care planning and intelligent coordination, our platform is designed to connect what’s broken and make it work.
Ready to Reconnect Your Post-Acute Network?
See how AI can transform your PAC strategy—from reducing readmissions to freeing up clinician time and improving member satisfaction.
👉 Schedule a consultation with our care transformation team today.
