Tech Solutions for Reducing Hospital Readmissions

Thrilled to finally share the results of our trial. 🗞️ Here's a rundown: 📱 To date, evidence has been mixed regarding the impact of #virtualcare programs in reducing hospital readmission, particularly in high risk populations such as those with heart failure and coronary disease. ❤️ We conducted an open-label prospective randomized study on discharged patients with cardiovascular disease, comparing intervention patients who received care with Heartbeat Health vs usual care alone. 💊 Our intervention: virtual visits to adjust guideline directed medical therapy, remote patient monitoring, and care coordination.  🏥 Findings demonstrate that intervention patients had a 53% lower rate of cardiac readmissions and 44% lower rate of all-cause readmissions over three months. 👟 Additionally, intervention patients experienced weight loss (4.5 pounds), reduced systolic pressure (-11.0 mmHg) and improved quality of life (QOL) including improved symptoms during exercise and daily activities. 🩺 Using innovative care pathways to improve access, applying medical interventions that are proven to play a significant role in reducing hospitalization and improving mortality, can make a difference. Grateful to have the chance to make a significant impact in people’s lives and look forward to continuing to do so. 🚀 #digitalhealth #cardiology #clinicaltrials #healthcareinnovation Jeffrey Wessler Aniket Zinzuwadia Stacey Pratt, PA-C Lindsey Mandrayar, PA-C Sarah Littleton Sophia Kim https://lnkd.in/eGkdmXE5

The future of healthcare isn’t hospitals—It’s at Homes. AI in healthcare has been framed all wrong. ❌ It’s not about replacing doctors and nurses. ❌ It’s not about futuristic robots diagnosing diseases. The real transformation? AI is quietly fixing healthcare’s biggest crisis: Maximizing capacity, expanding access, and reducing workforce shortages. And this shift isn’t coming—it’s already here. The aging population surge is REAL: 📈 By 2030, 1 in 4 Americans will be 65+. 📈 By 2050, the 65+ population will jump 47% (from 58M to 82M). 📈 11,200 Americans turn 65 every single day. Meanwhile, healthcare is buckling under pressure. 🚨 Not enough caregivers – 59% of home care agencies cite workforce shortages as their #1 issue 🚨 Rising costs – Compliance, staffing, and care costs are outpacing budgets 🚨 Regulatory complexity – The 2025 Home Health Final Rule is reshaping reimbursement models 🚨 Compromised quality – 72% of providers say staffing shortages are hurting care standards But here’s the massive shift no one is talking about: 🏡 87% of seniors want to age at home. Fewer caregivers. Rising costs. An aging population. How do we make home healthcare sustainable? AI is already started fixing the right problems 1. AI-powered remote monitoring detects health deterioration 2-3 days before symptoms escalate. 📉 31% fewer hospital readmissions in one home care agency. 2. AI-agent for caregivers minimizing documentation-cutting charting time from 50+ minutes to 15min. ⚡ More time with patients, less time buried in paperwork. 3. AI predictive analytics is identifying at-risk patients before a crisis hits. 🏥 26% reduction in ER visits for one elderly care program. 4. Intelligent patient-caregiver matching is improving care quality, reducing burnout, and increasing patient satisfaction. The real AI revolution in healthcare isn’t about replacing humans—it’s about empowering them. At Inferenz, we’re building human-first AI that solves real problems: 🔹 AI that reduces admin friction, not creates it. 🔹 AI that enhances human decision-making, not replaces it. 🔹 AI that works in the background—so care teams can focus on people, not systems. Because AI at scale sounds great—until it starts making the wrong decisions. It’s how we ensure AI serves the people who make healthcare work. Let’s build human-first AI, not machine-first AI. Gayatri Akhani Yash Thakkar James Gardner Jalindar Karande Prachi Shah Marek Bako Michael Johnson Chris Mate Joe Warbington 📊 Patrick Kovalik Julie Dugum Perulli Brendon Buthello Trupti Thakar Carole Hodsdon Liza Berger Ananth Mohan Puneet Kaushik Ray Lowe Darrell Bodnar Michael Ashy Eric vanGoethem Sabrina vangoethem Jeff Horing Bobby Le Blanc Greg Feldman Arthur Lauren Michael Weinberg Matthew Frankel Tony Tamer The Vistria Group Apollo Global Management, Inc. Bruce Evans Eric Zinterhofer Coltala Holdings Adam Blumenthal #AI #Healthcare #AgingPopulation #HealthTech #HumanizingAI #PatientCare

The average churn rate exceeds the average growth rate in U.S. hospitals by 3%. Patients may leave for a variety of reasons – some beyond control of the health system, such as changing residency or insurance coverage. What IS in the health system’s control is the patient experience. But that's difficult to improve when the delivery of care is fragmented and inefficient. Here are some primary examples of missed opportunities: • Diagnosis: 1 in 18 ED patients receive an incorrect diagnosis [1] • Referral: 22% of patients were referred out-of-network by physicians [2] • Follow-up: Less than 40% of recommendations for additional imaging are completed [3] Despite health systems throwing more people at many of its core challenges, the struggles persist. The answer to really becoming more efficient is AI technology, which can assist with helping reduce churn at three different points of the patient’s journey: Patient capture: Flagging and triaging cases for clinicians to review to ensure patients don’t fall through the cracks and suffer preventable medical harm. Care coordination: Driving digital collaboration between clinical stakeholders on each patient identified as being in need of care, simplifying communication and access to clinically relevant data. Follow-up: Identifying follow-up recommendations in records and alerting clinicians to them to ensure patients are reached out for critical follow-up imaging in an orderly fashion. However, there is the potential for AI to miss the mark in these areas if it’s deployed in a fragmented, disconnected and disparate fashion. If anything, improper deployment can exacerbate the fragmentation problem and uphold the clinical service line silos that already exist. What’s needed is a holistic approach, across the patient journey, where the patient is managed from entry through to the operating table and post. This is where a platform has become the only real viable technical option for AI to drive better patient care with maximum efficiency. By deploying AI holistically, in an inter-woven fashion, clinical care teams can improve the patient experience with the following examples: Improved disease awareness: A PE response team at Yale New Haven Health found that AI could help clinicians identify 72% more patients in need of vascular care consultations that were initially overlooked. [4] Reduced time to treatment: A radiology team at UT Southwestern found using AI could help reduce prescription retrieval time for patients with incidentally-found pulmonary emboli from 38.6 hours to 2.2 hours. [5] Reduced patient hospital length of stay: Clinicians at Cedars-Sinai Medical Center found AI in radiology workflows could reduce length of stay for patients with intracranial hemorrhages (ICH) and pulmonary emboli (PE) by 31 hours and 50 hours, respectively. [6] Reduced readmissions: An average 33% reduction in readmissions observed across 13 hospitals who were using AI for ICH and PE patients. [7]

𝐑𝐞𝐦𝐨𝐭𝐞 𝐏𝐚𝐭𝐢𝐞𝐧𝐭 𝐌𝐨𝐧𝐢𝐭𝐨𝐫𝐢𝐧𝐠: 𝐃𝐞𝐬𝐢𝐠𝐧𝐢𝐧𝐠 𝐚 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰 𝐓𝐡𝐚𝐭 𝐖𝐨𝐫𝐤𝐬 The future of healthcare is remote. RPM isn’t just about tracking vitals; it’s about 𝐭𝐫𝐚𝐧𝐬𝐟𝐨𝐫𝐦𝐢𝐧𝐠 𝐩𝐚𝐭𝐢𝐞𝐧𝐭 𝐜𝐚𝐫𝐞. But to succeed, RPM workflows must be thoughtfully designed and well-executed. 𝐇𝐞𝐫𝐞’𝐬 𝐡𝐨𝐰 𝐭𝐨 𝐛𝐮𝐢𝐥𝐝 𝐚𝐧 𝐑𝐏𝐌 𝐰𝐨𝐫𝐤𝐟𝐥𝐨𝐰 𝐭𝐡𝐚𝐭 𝐢𝐦𝐩𝐫𝐨𝐯𝐞𝐬 𝐜𝐚𝐫𝐞 𝐚𝐧𝐝 𝐝𝐫𝐢𝐯𝐞𝐬 𝐨𝐮𝐭𝐜𝐨𝐦𝐞𝐬: 𝟏. 𝐏𝐥𝐚𝐧 𝐰𝐢𝐭𝐡 𝐏𝐮𝐫𝐩𝐨𝐬𝐞 Ask critical questions: - What patient needs are we addressing? - How will this data drive clinical decisions? Define clear goals and use cases before diving in. A strong foundation ensures measurable impact. 𝟐. 𝐁𝐮𝐢𝐥𝐝 𝐒𝐦𝐚𝐫𝐭 𝐖𝐨𝐫𝐤𝐟𝐥𝐨𝐰𝐬 Design workflows that streamline operations, integrate seamlessly with clinical systems, and reduce friction for staff and patients alike. Document every step to maintain consistency. 𝟑. 𝐄𝐦𝐩𝐨𝐰𝐞𝐫 𝐘𝐨𝐮𝐫 𝐒𝐭𝐚𝐟𝐟 RPM demands more than tech; it requires people. - Train teams on roles and responsibilities. - Consider outsourcing certain tasks to manage workloads effectively. When staff are equipped and confident, the program thrives. 𝟒. 𝐏𝐚𝐫𝐭𝐧𝐞𝐫 𝐰𝐢𝐭𝐡 𝐏𝐚𝐭𝐢𝐞𝐧𝐭𝐬 Patients aren’t just participants; they’re partners. - Engage them with education on using RPM devices. - Keep them motivated with clear expectations, like using devices for 16 days a month for meaningful data. Collaboration between patients and providers drives better outcomes. 𝟓. 𝐒𝐭𝐚𝐧𝐝𝐚𝐫𝐝𝐢𝐳𝐞 𝐏𝐫𝐨𝐜𝐞𝐬𝐬𝐞𝐬 Develop SOPs for: - Patient enrollment - Device setup - Data collection and analysis Clear protocols eliminate confusion and improve efficiency. 𝟔. 𝐏𝐫𝐨𝐭𝐞𝐜𝐭 𝐃𝐚𝐭𝐚, 𝐀𝐥𝐰𝐚𝐲𝐬 RPM programs handle sensitive health data. - Implement HIPAA-compliant security measures to ensure privacy. - Build trust by prioritizing data safety. 𝟕. 𝐓𝐮𝐫𝐧 𝐃𝐚𝐭𝐚 𝐢𝐧𝐭𝐨 𝐃𝐞𝐜𝐢𝐬𝐢𝐨𝐧𝐬 - 𝐂𝐨𝐥𝐥𝐞𝐜𝐭 vital health metrics remotely. - 𝐓𝐫𝐚𝐧𝐬𝐦𝐢𝐭 them securely to providers. - 𝐀𝐧𝐚𝐥𝐲𝐳𝐞 the data for actionable insights. Then, act. RPM isn’t just about monitoring; it’s about enabling timely clinical interventions. 𝟖. 𝐄𝐯𝐚𝐥𝐮𝐚𝐭𝐞 𝐚𝐧𝐝 𝐄𝐯𝐨𝐥𝐯𝐞 Revisit your goals. - Did RPM reduce readmissions? - Improve patient engagement? Use success metrics to expand your program and find new opportunities for impact. RPM isn’t just a tool; it’s a 𝐠𝐚𝐦𝐞-𝐜𝐡𝐚𝐧𝐠𝐞𝐫. When done right, it reduces hospital visits, improves outcomes, and puts 𝐩𝐚𝐭𝐢𝐞𝐧𝐭𝐬 𝐚𝐭 𝐭𝐡𝐞 𝐜𝐞𝐧𝐭𝐞𝐫 𝐨𝐟 𝐜𝐚𝐫𝐞. Are you ready to build an RPM program that drives real change? Let’s connect and make it happen.

🏠 The Future of Heart Failure Care: Bringing Treatment to the Patient’s Home 🚀 At #THT2025, I had the privilege of speaking about a critical shift in heart failure (HF) management—moving beyond episodic, hospital-based care to a patient-centered, home-based model. The reality is that our current system is unsustainable, with: 📊 1.1M HF hospital discharges & 1.3M ER visits annually 📈 $31B in HF-related costs, projected to hit $70B by 2030 👥 A 46% expected increase in HF patients by 2030 Why Home-Based Management? ✅ Reduce hospitalizations & readmissions, increase health days at home ✅ Ease the burden on care teams with streamlined workflows ✅ Leverage emerging digital & AI-driven tools for early intervention ✅ Addresses disparities in HF care access & outcomes, overcome inertia! Innovations Driving This Shift 🔹 Remote Monitoring & AI Algorithms Bioimpedance, ballistocardiograph, seismocardiography, phonocardiography, ECG, and other variables to identify congestion before it leads to hospitalization. 🔹Smartphone-based HF detection—improving accessibility & early intervention. 🔹 The “Hospital-at-Home” Model High-acuity care is delivered in the home through a 24/7 command center. Virtual visits + on-demand clinician dispatch to preserve continuity of care. FDA-collaborated remote tech enabling proactive, rather than reactive, HF care. By combining virtual management, predictive analytics, and AI-assisted triage, we can envision a future in which we drastically reduce hospital burden and improve patient outcomes. 🔹 What are your thoughts on the shift toward home-based HF care? 🔹 How can we scale these technologies while preserving health equity? #HeartFailure #DigitalHealth #AIinHealthcare #RemotePatientMonitoring #THT2025