Reducing hospital readmissions with data and care coordination solutions

Avoidable hospital readmissions not only drive up healthcare costs; they also disrupt employees’ recovery, productivity, and confidence in the system meant to support them. Reducing these readmissions requires more than a discharge checklist; it takes connected data, coordinated care teams, and seamless communication across every setting. With better visibility into the care journey, employers and health partners can identify at-risk individuals sooner, close follow-up gaps, and help patients stay well after leaving the hospital, in turn improving outcomes, lowering costs, and strengthening overall workforce well-being.

 

Why care transitions matter in post-acute care management

 

Care transitions are some of the most decisive moments in recovery. Each move from hospital to home, rehabilitation, or a skilled nursing facility brings new care teams, new environments, and new risks. When discharge instructions, medication updates, or follow-up plans aren’t communicated clearly, patients can fall through the cracks. Nearly one in five Medicare patients is readmitted within 30 days of discharge , accounting for billions in avoidable costs. Research also shows that  as many as 76% of these readmissions may be preventable with stronger coordination and follow-up across settings. 

 

Evidence from national studies supports this pattern: patients with heart failure who receive early home-health visits, medication reconciliation, and symptom monitoring experience lower 30-day readmission rates  than those discharged without follow-up support. Strengthening these handoffs through shared data, proactive communication, and clear accountability can mean the difference between relapse and recovery.

 

Care transitions and their impact

 

Care transitions occur when patients move between settings, potentially leading to high-risk handoffs. Nearly 20% of Medicare patients  experience an adverse event within three weeks of discharge, often due to poor coordination. Improving data sharing and defining clear care team roles help ensure smoother transitions, fewer complications, and better recovery outcomes.

 

Risks associated with poor transitions

 

When patient care transitions are not managed well, When patient care transitions are not managed well, such as moves from the hospital to home, a skilled nursing facility, or outpatient care, patients may experience gaps in communication, incomplete discharge plans, or failures in information sharing. These breakdowns can lead to medication errors, missed follow-ups, and avoidable readmissions. A 2025 systematic review in BMC Nursing found that nurse-led transitional care interventions reduced hospital readmission risk by 33%  and lowered emergency department visits for adult patients discharged from acute care hospitals. Strengthening communication protocols, ensuring timely exchange of patient information, and defining clear care team responsibilities remain critical.

 

The essential role of patients and caregivers

 

Active engagement from patients and caregivers plays a key role in safe and effective care transitions. When individuals understand their discharge instructions, medications, and follow-up plans, they are better equipped to avoid complications and readmissions. Involving family caregivers and using structured communication during transitions from hospital to home can reduce adverse events and help smooth  the handoff process.

Education, clear communication, and inviting caregiver involvement in medication review or follow-up planning strengthen continuity of care and reduce the risk of missed warning signs or support breakdowns.

 

Strengthening care coordination across the continuum

 

Effective care coordination bridges the gaps that often appear as patients move between hospitals, post-acute settings, and home. Coordination models that combine clinical oversight with timely communication have shown strong impact on reducing readmissions and improving outcomes. Multidisciplinary care teams, nurse-led transition programs, and case management models help strengthen accountability and continuity of care. Care coordination involves deliberately organizing patient‐care activities  and sharing information among all participants concerned with a patient’s care to achieve safer and more effective care. Integrated models that link inpatient and community providers, supported by shared data systems and patient navigators, further ensure patients receive the right care at the right time, improving safety, satisfaction, and long-term recovery.

 

Overcoming common barriers with innovative solutions

 

Siloed information and fragmented care remain major obstacles to effective transitions. Health systems are addressing these challenges by adopting shared data platforms, standardized communication protocols, and cross-setting care teams that connect hospitals, post-acute providers, and home health services. These approaches help ensure that discharge details and follow-up plans reach every care partner in real time. As outlined in Carelon’s perspective on post-acute care, data-driven coordination and integrated provider networks are turning disconnected recovery pathways into connected, patient-centered care.

 

A data-driven care coordination model

 

Data-driven coordination helps health systems identify at-risk patients early and tailor interventions that prevent readmissions before they occur. Proven strategies include timely home health visits, medication reconciliation, and personalized discharge education that ensures patients understand their care plans. Analytics can flag patients with complex needs, such as multiple chronic conditions or recent hospitalizations, so care teams can prioritize proactive outreach. Evidence shows that structured follow-up and transitional care supported by data can significantly lower readmission rates. One study found that interventions combining home visits and medication reconciliation reduced 30-day readmissions by nearly 30% . Using integrated data platforms to guide follow-ups, track outcomes, and coordinate across providers helps improve recovery, and enhance patient experience.

 

Monitoring and understanding readmission rates

 

Tracking and analyzing 30-day readmission metrics help organizations identify weak points in care transitions and drive process improvements. Key steps include:

• Establish a baseline: Measure unplanned readmissions within 30 days of discharge and track trends over time.
• Benchmark performance: Compare results to national standards from the Centers for Medicare & Medicaid Services (CMS) .
• Stratify data: Break down readmissions by discharge setting, diagnosis, or risk group to uncover common causes such as missed follow-up appointments or incomplete medication reconciliation.
• Track leading indicators: Monitor metrics like follow-up visits within seven days, medication reconciliation completion, and timely transfer of discharge summaries.
• Use results to improve: Apply findings to plan–do–study–act (PDSA) cycles and quality initiatives focused on reducing preventable readmissions.

 

Learn more about system-level challenges and coordinated care strategies in Carelon Perspectives: Post-Acute Care Challenges.

 

Harnessing predictive analytics for safer transitions

 

Predictive analytics in healthcare enables care teams to anticipate risks and intervene before readmissions occur. By analyzing data from electronic health records, claims, and social determinants of health, predictive models can identify patients most likely to experience complications post-discharge. Examples indicate how continuous monitoring tools that integrate predictive analytics reduce risk of deterioration  in hospitalized cardiac patients. Integrating these tools into workflows, such as flagging high-risk patients for follow-up, home-health visits, or medication reconciliation, helps health systems shift from reactive to proactive care, improving patient outcomes. 

 

Identifying at-risk patients early

 

Understanding who is at greatest risk for complications post-discharge starts with data that spans clinical history, social context, and care-transition signals. Key sources include:

• Clinical history & utilization — recent hospitalizations, multiple chronic conditions, lab trends, and medication changes.
• Post-acute transition indicators — discharge to home without home-health support, delayed follow-up appointment, or transition from skilled nursing to outpatient care.
• Social determinants of health (SDoH) — factors such as food insecurity, housing instability, limited transportation, or lack of caregiver support that increase risk of adverse outcomes. Innovative programs now blend clinical and social-need data to flag members earlier.
• Predictive modeling — by combining these data sources, risk-stratification models identify patients whose recovery paths are most fragile so care teams can intervene before a high-risk handoff leads to readmission.

The Carelon two-visit engagement model blends clinical data, home-visit findings, and social-barrier screens to drive targeted action: Visit 1 identifies barriers, Visit 2 implements supports, enabling early and proactive engagement.

By pulling together these varied signals into a unified risk-profile, care teams move from one-size-fits-all discharge plans to tailored, resource-focused support; improving patient outcomes and reducing avoidable readmissions.

 

Embedding analytics into care pathways

 

Embedding predictive analytics into care pathways works best when insights are simple, timely, and integrated into the tools clinicians already use. Effective systems surface only the most relevant risk indicators, such as a readmission score or social risk flag, within the electronic health record or case management dashboard. Automated alerts can prompt follow-up calls, home health referrals, or medication reviews without adding manual steps. Training care teams to interpret and apply these insights during daily rounding or discharge planning helps turn data into action. When analytics are embedded seamlessly into workflows, clinicians can make informed decisions that prevent readmissions and improve patient outcomes.

 

The impact of Carelon’s post-acute care coordination solutions

 

Carelon’s post-acute care coordination model shows how structured oversight and data-driven decision support can improve outcomes while optimizing resource use. In one large health plan case study, implementation led to:

• 51% increase in appropriate redirection to inpatient rehabilitation facilities (IRFs)
• 61% increase in appropriate redirection to long-term acute care hospitals (LTACHs)
• 24% decrease in average length of stay at skilled nursing facilities (SNFs)
• 14% decrease in SNF admissions per 1,000 members
  
  

By aligning clinical review with real-time data and coordinated transitions, the program improved placement accuracy, reduced avoidable utilization, and enhanced patient and provider satisfaction. 

 

Explore how the right care coordination solutions can have an impact

 

Coordinated, data-informed care can transform post-acute outcomes by improving communication, reducing readmissions, and ensuring patients receive the right level of support at every stage of recovery. As health systems and employers continue to navigate complex care transitions, solutions that combine predictive analytics, clinical insight, and seamless collaboration deliver measurable value across the continuum.

Explore Carelon’s post-acute solutions to learn how our approach helps organizations strengthen care coordination and achieve better results for patients, providers, and payers alike.