How Technology Streamlines Healthcare Delivery

As a surgeon, I've seen the potential of AI to diagnose diseases and streamline the entire patient journey, from the moment patients walk through the door to the day they're discharged. Imagine a patient arriving at the hospital with a suspected heart condition. Traditionally, this could involve multiple appointments, tests, and specialist consultations, causing delays and potential anxiety for the patient. With AI, this process can be expedited and personalized. Algorithms can quickly analyze medical records, lab results, and imaging scans to identify potential issues, flagging them for immediate attention. AI-powered chatbots can guide patients through the process, answering questions, scheduling appointments, and providing educational resources. For example, AI can help identify patients at high risk of readmission, allowing for proactive interventions and follow-up care that reduces hospital stays and improves outcomes. But AI's potential goes beyond efficiency. It can also enhance the patient experience by: ◾️Personalizing care plans: Tailoring treatment based on individual patient data. ◾️Providing 24/7 support: Offering virtual consultations and access to information anytime. ◾️Empowering patients: Giving them the tools and information they need to actively participate in their own care. I'm excited about AI's possibilities for improving healthcare delivery. By seamlessly integrating AI into the patient journey, we can create a more efficient, effective, and, ultimately, human-centered healthcare system. #AI #healthcare #innovation #patientjourney #efficiency #heart

𝐑𝐞𝐯𝐨𝐥𝐮𝐭𝐢𝐨𝐧𝐢𝐳𝐢𝐧𝐠 𝐏𝐫𝐢𝐦𝐚𝐫𝐲 𝐂𝐚𝐫𝐞: 𝐓𝐡𝐞 𝐓𝐞𝐥𝐞𝐡𝐞𝐚𝐥𝐭𝐡 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐁𝐫𝐞𝐚𝐤𝐭𝐡𝐫𝐨𝐮𝐠𝐡🏥 Did you know? 76% of hospitals in the US now use telehealth services. But are we maximizing its potential in primary care? Let's dive in! Telehealth isn't just about video calls with your doctor. It's reshaping how we approach healthcare delivery, especially in primary care settings. Here's the scoop: 𝟏. 𝐑𝐞𝐝𝐮𝐜𝐢𝐧𝐠 𝐑𝐞𝐝𝐮𝐧𝐝𝐚𝐧𝐜𝐢𝐞𝐬:   • Cuts down on unnecessary in-person visits by up to 40%   • Minimizes duplicate lab tests and imaging studies   • Streamlines referral processes, saving time and resources 𝟐. 𝐄𝐧𝐡𝐚𝐧𝐜𝐢𝐧𝐠 𝐂𝐨𝐧𝐭𝐢𝐧𝐮𝐢𝐭𝐲 𝐨𝐟 𝐂𝐚𝐫𝐞:   • Enables frequent check-ins for chronic disease management   • Facilitates medication adjustments without office visits   • Allows for real-time monitoring of vital signs and symptoms 𝟑. 𝐈𝐦𝐩𝐫𝐨𝐯𝐢𝐧𝐠 𝐀𝐜𝐜𝐞𝐬𝐬:   • Bridges the gap for 57 million Americans living in rural areas   • Reduces wait times - average telehealth wait: 20 mins vs. 2 hours in-person   • Increases appointment adherence by 19% 𝟒. 𝐂𝐨𝐬𝐭-𝐄𝐟𝐟𝐞𝐜𝐭𝐢𝐯𝐞𝐧𝐞𝐬𝐬:   • Saves an average of $19-$121 per visit compared to in-person care   • Reduces hospital readmissions by up to 25%   • Lowers overhead costs for healthcare providers 𝐊𝐞𝐲 𝐈𝐧𝐭𝐞𝐠𝐫𝐚𝐭𝐢𝐨𝐧 𝐒𝐭𝐫𝐚𝐭𝐞𝐠𝐢𝐞𝐬: ✅ Implement hybrid care models (e.g., initial telehealth triage followed by in-person if needed) ✅ Utilize AI-powered symptom checkers for pre-appointment screening ✅ Integrate wearable devices for continuous patient monitoring ✅ Employ secure messaging systems for non-urgent communication ✅ Develop telehealth-specific clinical protocols and best practices 𝐂𝐡𝐚𝐥𝐥𝐞𝐧𝐠𝐞𝐬 𝐭𝐨 𝐀𝐝𝐝𝐫𝐞𝐬𝐬: • Ensuring equitable access to technology • Navigating complex reimbursement policies • Maintaining data privacy and security • Overcoming resistance to change among some providers and patients 𝐓𝐡𝐞 𝐅𝐮𝐭𝐮𝐫𝐞 𝐢𝐬 𝐍𝐨𝐰: By 2026, the global telehealth market is projected to reach $185.6 billion. Primary care is at the forefront of this revolution. What's your vision for the future of telehealth in primary care? Have you experienced its benefits firsthand? Share your thoughts below! 👇 Let's co-create a healthcare system that's accessible, efficient, and patient-centered. Because your health deserves the best of both worlds - high-tech and high-touch. #TelehealthRevolution #PrimaryCareInnovation #DigitalHealthcare #HealthTech #PatientCenteredCare #HealthcareEfficiency #RuralHealth #ChronicCareManagement #FutureOfMedicine #HealthcareAccess American Medical Association World Health Organization HIMSS

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]

𝗪𝗵𝗮𝘁 𝗛𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗟𝗲𝗮𝗱𝗲𝗿𝘀 𝗡𝗲𝗲𝗱 𝘁𝗼 𝗞𝗻𝗼𝘄 𝗮𝗯𝗼𝘂𝘁 𝗔𝗜......𝗡𝗼𝘄, 𝗡𝗼𝘁 𝗟𝗮𝘁𝗲𝗿. Forget the hype AI is already transforming care delivery and driving down costs. But adoption isn't just about plugging in a tool. Here’s what actually matters for decision-makers: 𝗖𝗹𝗶𝗻𝗶𝗰𝗮𝗹 𝗜𝗺𝗽𝗮𝗰𝘁 → Radiologists using AI detect kidney disease 48 hours earlier than humans → Early detection = fewer complications + lower costs → VA + DeepMind model saved lives and reduced dialysis risk 𝗔𝗱𝗺𝗶𝗻 𝗧𝗮𝘀𝗸𝘀 = 𝗕𝗼𝘁𝘁𝗹𝗲𝗻𝗲𝗰𝗸 → AI can cut charting time by up to 72% → Prior auth, EHR integration, and data cleanup fully automated → That’s not just time saved it’s burnout prevented 𝗘𝗰𝗼𝗻𝗼𝗺𝗶𝗰 𝗨𝗽𝘀𝗶𝗱𝗲 → Admin eats 15–25% of healthcare spend → AI could save $265B by reducing overhead and claims friction → Employers save up to $480 PMPM with early intervention AI tools 𝗕𝗮𝗿𝗿𝗶𝗲𝗿𝘀 𝗮𝗿𝗲 𝗿𝗲𝗮𝗹: → Initial cost, training, data quality, legal risks → HIPAA compliance and informed consent aren’t optional → Stakeholder buy-in must start early to scale effectively 🔄 𝗧𝗵𝗲 𝗕𝗼𝘁𝘁𝗼𝗺 𝗟𝗶𝗻𝗲 → AI in healthcare is already happening. → Outcomes are improving. Admin is shrinking. Burnout is falling. → The time to lead AI strategy is now not when it’s mandated. 𝗬𝗼𝘂𝗿 𝗠𝗼𝘃𝗲: → What’s holding back AI at your org trust, training, or ROI clarity? → What task would you most want to automate right now? 👇 Let’s discuss what’s working and what’s still missing. #AIinHealthcare #HealthcareLeadership #HealthTech #DigitalHealth #AdminAutomation #ClinicalAI #ValueBasedCare #TechlingHealthcare