Patient Engagement Platforms

▶️ Is patient engagement critical for effective digital adoption? Effective patient engagement is rapidly emerging as a cornerstone of technology-driven healthcare models. Patients who are actively engaged are more likely to adopt digital tools, adhere to treatment plans, and take an active role in their care, leading to improved outcomes and the successful integration of digital health solutions. While #patientengagement has been practised for years, #healthtechnology has transformed the landscape, making it easier for patients to stay connected with their care teams. Technology integration has diversified patient engagement, enabling interactions across multiple touchpoints and enhancing the patient experience. It is also important to understand that technology is not "one size fits all," and every patient has their own place on the spectrum of technology skills and #healthliteracy. Some steps to improve adoption can include: 🔷 Patient portals should focus on user-friendly interfaces with clear instructions to ensure patients are comfortable using the tools and do not get overwhelmed. 🔷 Privacy and security concerns are paramount for patients, healthcare organizations need to address these concerns by implementing transparent data protection measures. 🔷 Healthcare providers should ensure that patient engagement tools don't complicate the patient's healthcare routine. 🔷 Clear guidance and ongoing support are pivotal to ensuring patients can integrate these tools seamlessly into their lives. 🔷 Health hashtag #techtools should be affordable. Providing transparency about potential costs and highlighting the long-term benefits can facilitate patient engagement. 🔷 Build hashtag #inclusive platforms that transcend access, language, and culture barriers. 🔷 Engage patients and hashtag #hcps while designing new tech solutions, gathering continuous feedback to ensure innovations meet user needs. Fostering a patient-centered culture is crucial. We can empower and motivate patients by initiating educational programs, providing adequate support, and developing user-friendly, inclusive, and cost-effective platforms with transparent data privacy guidelines. By addressing the adoption challenges, we can move towards proactive and preventive care management, driving better #healthoutcomes for individuals and communities.

The Future of Patient Portals as 'Engines and Infrastructure supporting the NHS App' https://lnkd.in/esrqRE9v The digital architecture of the United Kingdom's National Health Service (NHS) is currently executing a fundamental pivot, a transformation that marks the end of the "destination portal" era and the rise of the "aggregation engine." For the past decade, the prevailing model for digital patient engagement was characterised by fragmentation and sovereign operational silos. Individual NHS Trusts, operating as semi-autonomous fiefdoms, procured standalone Patient Engagement Platforms (PEPs), proprietary "front doors" that required patients to register, retain credentials and navigate distinct user interfaces for every provider they encountered. A patient with complex needs might manage a login for myhospital.com for their oncology care, a separate account for their General Practitioner (GP) and yet another for mental health services. This fragmented landscape, while functionally operative, created profound friction, limiting adoption and stifling the potential for a unified longitudinal health record. The current strategic trajectory, crystallised by the NHS England "Wayfinder" program and the statutory weight of the Data Saves Lives strategy, mandates a reversal of this fragmentation. The NHS App is no longer merely a utility for ordering repeat prescriptions or displaying COVID-19 vaccination status; it has been designated as the "single front door" for the health service. This designation is not simply a branding exercise but a rigid architectural mandate that redefines the commercial and technical reality for third-party suppliers. In this new ecosystem, patient portals are ceasing to be standalone destinations. Instead, they are evolving into "engines", sophisticated backend infrastructure layers that handle complex business logic (scheduling, triage, clinical correspondence, rule-based routing) but surface their functionality through the national infrastructure of the NHS App.

It saddens me that when healthcare talks about Patient Engagement, we still mostly talk about: → Patient portals → Scheduling appointments → Payments → Generic patient education Now the discourse has shifted to AI agents… to mostly do more of the same: → An AI agent to schedule appointments more easily → An AI agent to collect payments from patients more easily → An AI agent to send generic patient education more easily While Access is critical, the biggest opportunity with Patient Engagement is to deliver personalized care that actually improves health outcomes. To do that we need Patient Engagement to be personalized, clinically-relevant, and continuous across the entire healthcare journey - not just the start (Scheduling) and the finish (Payment). What does that look like? → Step-by-step education specific to a patient’s condition or surgery → Daily guidance personalized a patient’s demographics, comorbidities and risk factors → Symptom and health status tracking that intelligently guides the patient to the right self-management or escalation to the right provider → Ability for care team to remotely monitor patients outside the clinic or hospital, to catch things earlier This is the “Patient Engagement” model we have been pioneering at SeamlessMD over the past 12 years. 40+ studies and evaluations have shown this approach to lower mortality, complications, length of stay, readmissions and cost of care. We - along with our health system partners - are living proof that Patient Engagement doesn’t only need to be about hitting revenue targets, patient acquisition goals and “check the box” education. We CAN make Patient Engagement actually about improving Human Health. It’s time to make Patient Engagement… more about the Patient and what they’re looking for from the healthcare system: Better Health.

A new study in Nature tackles a challenge we hear often in kidney care: low patient engagement. The "My Kidneys & Me" (MK&M) digital health tool offers fresh hope for addressing this, particularly for those with early-stage chronic kidney disease (CKD) who may feel disconnected from their care. In the SMILE-K trial, MK&M helped boost patient activation, especially among those with the lowest engagement levels at baseline. Among these participants, Patient Activation Measure (PAM-13) scores improved by +9.2, with nearly half moving from lower activation levels into higher ones, a change considered both clinically and personally meaningful. These results show us that digital tools like MK&M are not just for the "already engaged" but can make the biggest difference for those starting with the least knowledge and confidence in managing their CKD. This study reminds us of something important: when we identify early-stage CKD, we often focus on those who are already proactive. But tools like MK&M prove the real opportunity lies in empowering less engaged patients, providing them with clear education, practical FAQs, and goal-setting support to take charge of their health. For many, these "simple" digital interventions could mean the difference between preventing disease progression or not. It’s inspiring to see these findings and their implications for future CKD care strategies. If we want to make the biggest impact, let’s meet patients where they are — especially those with the most room to grow. Great study, thanks team! Read the full paper here: https://lnkd.in/eh2X6f7Q

Here's the problem with AI health platforms: trust. You can build the smartest algorithms and most personalized care pathways, but if employees don't trust the platform, none of it matters. Utilization stays at 30%. Your AI sits idle. ROI never materializes. At MiSalud Health, we solved the trust problem by inverting the implementation: instead of asking employees to download an app and trust an algorithm first, we bring our AI-powered platform to life through health coaches they meet face-to-face. Our hybrid model: 🔹 Onsite Health Clinic: Biometric screenings, results explanation, and in-person registration. The AI already knows their baseline health data. 🔹 AI-Powered Care Activation: Our health & patient engagement teams use our AI-enhanced platform to: - Risk-stratify employees (diabetes, hypertension, mental health) - Send personalized nudges in Spanish/English at optimal times - Route urgent cases to U.S.-licensed providers - Track medication adherence and lifestyle changes 🔹 Ongoing: Human + AI Delivery: Employees choose text guidance for quick questions, or video/phone with their Health Coach for complex needs. The results: ✅ 80% enrollment (vs. 30% industry average) ✅ 45% ongoing utilization ✅ 1 risk level drop in chronic conditions over 16 weeks What makes this defensible? Traditional telehealth is stuck in a binary: human-only (doesn't scale) or AI-only (doesn't engage). We built a hybrid intelligence model where: - AI handles scale, personalization, prediction, and monitoring - Humans handle trust-building, cultural competency, and complex decisions - Onsite clinics make the digital platform feel safe The companies that win in AI healthcare won't be the ones with the smartest algorithms - they'll be the ones who solved the adoption problem. #HealthcareAI #AIinHealthcare #HybridIntelligence #DigitalHealth #PopulationHealthManagement #EmployeeBenefits #HealthTech

Medication adherence continues to be a significant challenge – nearly 50% of patients don’t take their medications as prescribed [1]. Why is this happening? One contributing factor is digital friction points. We know this because when digital engagement is done right, patients are 2x more likely to seek prompt care and 3x less likely to face unmet medical needs [2]. Pharma’s response? More websites and apps to “help” patients” start and stay on treatment. For a single medication, we counted 𝟭𝟮 (!) 𝗱𝗶𝗴𝗶𝘁𝗮𝗹 𝘁𝗼𝘂𝗰𝗵𝗽𝗼𝗶𝗻𝘁𝘀. Overwhelming? Absolutely. Especially when studies show: • The 30-day retention rate for health apps is only 4% [3]. • Online patient support programs fare no better, with only 3% of patients enrolling in these programs [4]. • Most patients either do not know about the programs or find them mediocre at best when it comes to patient experience [5]. Patients don’t need more apps. They need simpler, centralized solutions that naturally integrate into systems they already use. Here’s what that can look like in practice: → Integrate with systems and devices that patients already use: Voice assistants like Siri and Alexa, native iOS and Android calendar and task list integrations, text messaging, and wearables like smartwatches to offer discreet reminders. → Utilize AI-powered personalization and symptom trackers to recognize patterns, predict trends, and provide proactive, individualized care → Consolidate all patient programs into one: access and affordability, companion/guide support, administration training, treatment center locators, advocacy group connectors, transportation, recycling, etc. Have one place to go to get all these services. → Don’t collect repetitive information, require extra app downloads, or repetitive logins. Provide value and service without requiring registration when possible. When asking for a registration, clarify how the information will be used and the value the patient will receive in return. → Ensure great UX that makes interactions seamless, intuitive, embedded into patients’ lives, and doesn’t require extra time or effort. The future of medication adherence lies in a combination of AI and great UX: • AI unlocks the incredible potential for personalized, proactive care. • Great UX promotes access and adherence to such care. Pharma companies that invest in AI and UX will shape the future of medication adherence. They’ll also make an even more important investment: Improving health outcomes.

💥 𝗟𝗲𝘁 𝗺𝗲 𝗶𝗻𝘁𝗿𝗼𝗱𝘂𝗰𝗲 𝘆𝗼𝘂 𝘁𝗼 Listen Phirst™, 𝗮𝗻𝗱 Sheila Phicil, MPH, MS, PMP, FACHE 𝘁𝗵𝗲 𝗳𝗼𝘂𝗻𝗱𝗲𝗿 𝗯𝗲𝗵𝗶𝗻𝗱 𝗶𝘁. It's one of the most exciting and innovative approaches I’ve seen for involving and compensating people for contributing to research, by 𝙩𝙧𝙚𝙖𝙩𝙞𝙣𝙜 𝙥𝙖𝙧𝙩𝙞𝙘𝙞𝙥𝙖𝙣𝙩𝙨 𝙡𝙞𝙠𝙚 𝙚𝙭𝙥𝙚𝙧𝙩𝙨, 𝙣𝙤𝙩 𝙨𝙪𝙗𝙟𝙚𝙘𝙩𝙨. 📊 𝗟𝗶𝘀𝘁𝗲𝗻 𝗣𝗵𝗶𝗿𝘀𝘁 𝗶𝘀 𝗮 𝗱𝗮𝘁𝗮‐𝘁𝗼‐𝗶𝗻𝘀𝗶𝗴𝗵𝘁 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 that collects lived‑experience stories from patients using #AIVoiceCompanions. 𝗧𝗵𝗲𝗶𝗿 𝗰𝘂𝘀𝘁𝗼𝗺𝗲𝗿𝘀 (𝗵𝗲𝗮𝗹𝘁𝗵 𝘀𝘆𝘀𝘁𝗲𝗺𝘀, 𝗵𝗲𝗮𝗹𝘁𝗵𝗰𝗮𝗿𝗲 𝗶𝗻𝗻𝗼𝘃𝗮𝘁𝗼𝗿𝘀, 𝗽𝗵𝗮𝗿𝗺𝗮) don’t buy raw data—they ask questions, and pay for insights based on patient stories. 🎇 𝗪𝗵𝗮𝘁 𝗺𝗮𝗸𝗲𝘀 𝗶𝘁 𝗺𝗮𝗴𝗶𝗰𝗮𝗹 is that It creates an inclusive way to engage and compensate research participants by lowering the barriers to participation, and applying AI in ways that aim to reduce bias and invite participation rather than reinforce historical patterns. And it’s being built to fit into how health systems and builders already work, not as an afterthought. 𝗔𝗯𝗼𝘂𝘁 𝘁𝗵𝗲 𝗟𝗶𝘀𝘁𝗲𝗻 𝗣𝗵𝗶𝗿𝘀𝘁 𝗽𝗹𝗮𝘁𝗳𝗼𝗿𝗺 🗣️ 𝗩𝗼𝗶𝗰𝗲‐𝗳𝗶𝗿𝘀𝘁 𝗮𝗰𝗰𝗲𝘀𝘀 via a toll‑free number, with a fully phone‑based approach and no app or website needed, to minimize friction and expand access. 🔀 𝗠𝘂𝗹𝘁𝗶-𝗹𝗶𝗻𝗴𝘂𝗮𝗹: Starting with English, Spanish, Mandarin, and Portuguese, will eventually support 50+ languages 💼 𝗗𝗮𝘁𝗮 𝘀𝗼𝘃𝗲𝗿𝗲𝗶𝗴𝗻𝘁𝘆 𝗺𝗼𝗱𝗲𝗹 - Patients keep control over how their information is used, and can change or withdraw consent any time 💵 𝗖𝗼𝗺𝗽𝗲𝗻𝘀𝗮𝘁𝗶𝗼𝗻: $50-150 per session, plus ongoing payments from insights generated 👩🏽💻 𝗣𝗮𝘁𝗶𝗲𝗻𝘁 𝗱𝗮𝘀𝗵𝗯𝗼𝗮𝗿𝗱 provides transparency into data usage, earnings over time, and opt-in opportunities for research projects 💳 𝗩𝗶𝗿𝘁𝘂𝗮𝗹 𝗴𝗶𝗳𝘁 𝗰𝗮𝗿𝗱 𝗽𝗮𝘆𝗺𝗲𝗻𝘁𝘀 are provided via text 🪢 𝗖𝗼𝗻𝘁𝗲𝘅𝘁𝘂𝗮𝗹𝗶𝘇𝗲𝗱 𝗶𝗻𝘀𝗶𝗴𝗵𝘁𝘀 𝘃𝘀 𝗱𝗲-𝗶𝗱𝗲𝗻𝘁𝗶𝗳𝗶𝗲𝗱 𝗱𝗮𝘁𝗮 - “De-identified data is like talking to headless person” according to the founder. 🛫 𝗘𝗮𝗿𝗹𝘆 𝗽𝗶𝗹𝗼𝘁𝘀 will inform future opportunities and provide critical proof points including: 𝗖𝗼𝗺𝗽𝗮𝗿𝗮𝘁𝗶𝘃𝗲 𝘀𝘁𝘂𝗱𝘆: platform vs traditional surveys/focus groups 𝗜𝗥𝗕 𝘀𝘁𝘂𝗱𝘆 to enable peer-reviewed publication Sheila’s approach from the get go is to strive for “𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝘀𝘆𝘀𝘁𝗲𝗺 𝗳𝗶𝘁” 𝘃𝘀 “𝗣𝗿𝗼𝗱𝘂𝗰𝘁 𝗺𝗮𝗿𝗸𝗲𝘁 𝗳𝗶𝘁”. “𝘠𝘰𝘶 𝘩𝘢𝘷𝘦 𝘵𝘩𝘦 𝘱𝘢𝘵𝘪𝘦𝘯𝘵 𝘢𝘯𝘥 𝘵𝘩𝘦 𝘤𝘢𝘳𝘦𝘨𝘪𝘷𝘦𝘳𝘴 𝘢𝘵 𝘵𝘩𝘦 𝘤𝘦𝘯𝘵𝘦𝘳, 𝘢𝘭𝘸𝘢𝘺𝘴. 𝘈𝘯𝘥 𝘵𝘩𝘦𝘯 𝘺𝘰𝘶 𝘵𝘩𝘪𝘯𝘬 𝘢𝘣𝘰𝘶𝘵 𝘵𝘩𝘦 𝘱𝘳𝘰𝘷𝘪𝘥𝘦𝘳𝘴, 𝘵𝘩𝘦 𝘴𝘶𝘱𝘱𝘰𝘳𝘵 𝘵𝘦𝘢𝘮, 𝘵𝘩𝘦 𝘢𝘥𝘮𝘪𝘯𝘪𝘴𝘵𝘳𝘢𝘵𝘰𝘳𝘴, 𝘳𝘦𝘨𝘶𝘭𝘢𝘵𝘰𝘳𝘴, 𝘱𝘢𝘺𝘦𝘳𝘴, 𝘪𝘯 𝘵𝘩𝘢𝘵 𝘰𝘳𝘥𝘦𝘳.” 😎 𝗬𝗼𝘂 𝗱𝗼𝗻’𝘁 𝘄𝗮𝗻𝘁 𝘁𝗼 𝗺𝗶𝘀𝘀 𝘁𝗵𝗶𝘀! https://listenphirst.com/ #AgeTech #DesignWithUs #InclusiveResearch #ExpertsNotSubjects

Why does patient engagement drop after appointments? 🤔 Patients feel disconnected once they leave the clinic. Here’s how AI can help bridge that gap: 👉 Continuous, personalized follow-ups = better outcomes. Just like behavior change, patient engagement is in small, consistent touchpoints. When patients don’t receive regular support, they lose track of their treatment plan. How can AI drive engagement? ✅ Timely reminders. Subtle nudges to take medications, follow exercise routines, or schedule check-ups to keep patients on track. ✅ Personalized content. AI tailors follow-ups to each patient’s needs, making sure they receive relevant health information. ✅ Ongoing communication. Chatbots and virtual assistants can check in with patients between appointments, answering questions and providing guidance. ✅ Data-driven insights. AI monitors progress and provides feedback to both patients and healthcare providers, improving the care plan over time. ✅ Improved patient satisfaction. Continuous support leads to better experiences and long-term engagement. Consistency is key. Small, timely interactions can make a big difference in patient outcomes. Reference: CareSignal® – Lightbeam's Deviceless Remote Patient Monitoring

Patient engagement in healthcare is fundamentally broken: - ~50% of patients don’t adhere to treatment plans - Up to half drop out of care over time - Poor adherence is estimated to contribute to ~10% of hospitalizations and $100–300B in avoidable costs annually Most outcomes are driven between visits, but that’s where the system does almost nothing. A new layer is emerging: continuous, AI-driven patient engagement reinforcing care plans in real time: - Daily check-ins (symptoms, adherence) - Medication and measurement reminders - Context-aware behavioral nudges - Escalation to care teams when needed For example, with the Nozomi AI companion, instead of hoping patients follow instructions, you continuously support and guide patient behavior. Result: - Up to ~20–30% improvement in adherence (program-dependent) - Higher engagement and program completion - Fewer missed visits More in the scheme ↓ P.S. If you're working on chronic care or care programs, let’s discuss a pilot. 👉 𝗝𝘂𝘀𝘁 𝗰𝗼𝗻𝗻𝗲𝗰𝘁 𝘄𝗶𝘁𝗵 𝗺𝗲 𝗮𝗻𝗱 𝗰𝗼𝗺𝗺𝗲𝗻𝘁 “𝗣𝗶𝗹𝗼𝘁”. #engagement #adherence #patientengagement

Epic Systems and AI at point of care. Epic is poised to drive the adoption of AI in the industry with their significant technology presence in healthcare settings. During their recent Users Group Meeting, Epic introduced a range of AI solutions aimed at supporting clinicians, empowering patients, enhancing operations, and fostering research. Key innovations include: - Clinical Documentation (Art): An ambient AI assistant that captures real-time clinical encounters, reducing documentation workload, and simplifying order entry. - Patient Engagement (Emmie): An intelligent assistant aiding patients in preparing for visits, understanding lab results, managing preventive care, and navigating their healthcare journey. - Revenue Cycle & Operations (Penny + AI Suite): Tools for automating coding, supporting denial management, and optimizing workflows like discharge planning, surgical risk assessment, and patient flow. - Cosmos AI: Utilizing predictive models trained on Epic’s extensive de-identified Cosmos dataset, covering over 300 million patients and 16 billion encounters. These models facilitate research, predictive analytics, and scalable decision support, offering early insights into outcomes such as diagnoses and readmissions. The impact of these advancements includes: - Boosted clinician efficiency through automation and reduced administrative tasks. - Enhanced patient experience with personalized, easy-to-understand insights and proactive guidance. - Financial stability via AI-driven revenue cycle enhancements. - Accelerated research and innovation fueled by a vast real-world healthcare dataset. https://lnkd.in/eV4D3uvP