Digital Health Tools

💡 Publication alert on digital determinants of health! Health and well-being are shaped by countless factors—often referred to as social determinants. But in our increasingly digitalised world, what role do #digital determinants of health play?   Together with The London School of Economics and Political Science (LSE), our team at the WHO Regional Office for Europe and other WHO colleagues, along with experts on the subject, identified 127 key digital factors affecting health, especially:   🌐 access to the internet 🖥 availability of devices and software 🧑🏻💻 digital literacy 🗑 moderation of harmful content online 📲 algorithmic transparency   This shows how pervasive digital content can be enabled through the combined influence of digital, commercial, economic, and political factors across different levels of governance, reinforcing the importance of an equitable and sustainable digital transformation. While younger and healthier populations are better equipped to use digital tools, they are also more likely to be exposed to their adverse effects. In contrast, older people, those living with disabilities or chronic illness, migrants or other vulnerable groups, may gain the most from digital tools, but are at risk of being excluded. Ironically, this also means they are among the best protected from negative factors.   Improving digital access and literacy, placing individuals at the centre of the digital health design process, can help ensure safe and equitable solutions for everyone. Finally, we must consider how the digital divides evolve over time: basic digital technologies like phones and computers are still not accessible to everyone equally, while advanced tools such as artificial intelligence (AI), blockchain and spatial computing, may leave even more communities at risk of exclusion.   We are proud to announce this study during the #RC74CPH week, where the progress report on our Regional #DigitalHealth Action Plan is being presented (more on that later this week). This publication is already available in the @Bulletin of the World Health Organization (to be included in the issue of February 2025) and an extended version will be published in mid-November as a WHO report.   A huge thank you to Robin van Kessel, Elias Mossialos, and the many partners and experts who have contributed to this vital research, and to Natasha Azzopardi Muscat and WHO Regional Director for Europe Hans Kluge for always championing digital health🙏.   Discover the study here: https://lnkd.in/ernASh_y

Tech didn’t just support our healthcare goals, it reshaped them. When I started in healthcare marketing, technology was something we used around the patient experience. Today, it sits at the heart of it. At Lupin India, we’re living that shift in real time. Our AI-powered chatbots began as a small pilot. They’ve since evolved into essential tools, supporting patients with real-time answers, guidance, and reassurance at critical moments. Remote monitoring tools are helping us move closer to truly personalised care. Not just generic recommendations, but insights tailored to each patient are tracked and refined over time. And then there’s telehealth and patient apps, now core areas of investment for improving outcomes. In a country as diverse as India, technology is removing one of our biggest barriers: distance. Patients who once had to travel hours for care can now connect with experts from wherever they are. What strikes me most is how this isn’t just about technology, it’s about the people behind it. I’ve seen firsthand how these innovations give patients and families a sense of hope and control during uncertain times. But this isn’t about chasing digital trends. It’s about using technology with purpose to expand access, improve outcomes, and create a care experience that feels personal, even from afar. We’re still in the early chapters of this transformation. The future won’t be built on more tech, but on better, more meaningful use of it. Solutions that are timely, relevant, and rooted in real patient value. The future of healthcare will belong to those who innovate with empathy and scale with purpose. What role do you see tech playing in reshaping care where you are?

Proud to share new peer-reviewed evidence from a clinical trial conducted by Elevance Health and the UC Irvine, in collaboration with Apple, showing that a digital asthma self-management program significantly improved symptom control in adults. In a 12-month randomized clinical trial of 901 adults across 41 states, those using the digital health tool improved their Asthma Control Test scores by 4.6 points, more than twice the improvement seen with usual care. Participants also reported better medication adherence, higher confidence in self-management, and reduced impact on work productivity. The study underscores how thoughtfully designed digital tools can support broader access and drive whole health outcomes. Proud of this interdisciplinary collaboration and what it means for the 26 million Americans living with asthma. #WholeHealth #DigitalHealth 🔗 Read the full release + study: https://lnkd.in/gdkesA4e

HealthTech AI is no longer exciting. It’s expensive. And the market has re-priced itself for performance. The first half of 2025 solidified a new reality in digital health. US-based digital health startups secured $6.4 billion across 245 deals (Rock Health). While total funding is up from H1 2024, the trend of fewer, larger checks persists. Rock Health pegs the average deal size at a robust $26.1 million, a significant increase from $20.4 million in 2024, signaling a concentrated investment in more mature, impactful companies. Investors are no longer buying potential. They're buying precision and demonstrable value. They care if your AI: Saves hours, not just clicks: The focus is on quantifiable time savings for clinicians and administrative staff, directly addressing burnout and efficiency gaps. Cuts costs, not just code: Real-world cost reduction is paramount, whether through optimized operations, reduced errors, or improved resource allocation. Embeds in real workflows, not pitch decks: Solutions need to be seamlessly integrated into existing healthcare systems, proving their utility in daily practice. McKinsey calls this the "productivity premium," and it has become the new funding filter. A significant portion of VC dollars continues to flow into AI-enabled startups, not because they're novel, but because they perform and deliver tangible returns. Abridge: This AI note-taking startup for doctors raised a staggering $316 million in June 2025 (Series E), bringing its total funding to over $770 million. Its value proposition is clear: giving clinicians hours back by automating documentation. Innovaccer: Secured $275 million in Series F funding in January 2025 to expand its AI and cloud capabilities, aiming to be a "one-stop shop" for healthcare AI solutions. They focus on data aggregation and intelligence to optimize value-based care programs and reduce administrative burden. Truveta: Raised $320 million in Series C funding in January 2025, solidifying its position in health data and analytics. Their mission revolves around leveraging data to drive insights and improve care. Hippocratic AI: Completed a $141 million Series B financing round in February 2025, valuing the company at $1.64 billion. Their focus is on developing safe, patient-facing AI for non-diagnostic tasks, addressing healthcare staffing shortages. These companies optimize operations, not optics. The delta? Execution. This is not a hype cycle. It’s a competency correction. The end of vision-only founders. The rise of operator-founders who understand: Unit economics: The true cost and value generated by each patient interaction or service delivered. Integration latency: The speed and ease with which new technologies can be embedded into complex, often legacy, healthcare IT infrastructure. Reimbursement drag: Navigating the intricate and often slow process of getting innovative solutions covered by payers. What part of this feels uncomfortably true?

Germany’s Digital Therapeutics DiGA Fast-Track Under Scrutiny: 📑A new npj Digital Medicine systematic review analyzed 23 approval studies behind Germany’s reimbursable digital health apps (DiGAs). While all reported medium‑to‑large positive effects (mostly in mental health), every study carried a high risk of bias, largely due to reliance on self‑reported outcomes, missing data, and inconsistent designs. Key takeaways: 🔘 21 of 23 studies measured their primary outcomes via patient reported measures raising concerns over objectivity (but authors also acknowledged objective reporting is difficult in mental health) 🔘Dropout rates averaged 22% in intervention groups, higher than controls 🔘Only one study assessed process‑level improvements (eg access, patient literacy, safety, adherence, guideline alignment) despite DiGAs aiming to improve both outcomes and care pathways 🔘 Despite the reported flaws, over 1 million DiGA prescriptions have been issued, costing insurers €234M by end 2024 🔘Authors call for stricter standards, mandatory study protocols, and real‑world evidence as Germany’s model influences other countries 💬Germany pioneered reimbursed digital therapeutics, but this study suggests the evidence base is shakier than it looks. Tightening approval standards may be key before others adopt this model at scale 📍Note: The review itself isn’t flawless. It excluded failed or withdrawn DiGAs, faced patchy reporting and missing protocols, and required judgment calls due to vague guidelines. Effect sizes varied, and without author input, some bias risks may have been overstated 👇Link to study in comments #DTx #DigitalHealth 

The hardest part of being data driven is knowing what you should measure, not how to measure it. Take personal goals, for instance. Imagine you're on a quest to lose weight. It's tempting to obsess over the daily numbers on the scale, but those are merely outcomes, often slow to change and potentially misleading. Instead, a more insightful approach is to track caloric intake and expenditure. This shift in focus provides a clearer path to your goal, as consistently maintaining a calorie deficit will eventually result in weight loss. This concept extends to the business realm as well. Consider the objective of boosting sales. While increased sales are the ultimate goal, they're the result of multiple underlying factors: product or service quality, customer engagement, effective messaging, and so forth. It's easy to get caught up in the end goal without recognizing the steps needed to get there. The solution? Reverse analysis. Begin with your target outcome and work backward, identifying and monitoring all the elements that influence it. This method offers a more dynamic view, enabling quicker adjustments and more strategic decisions. In essence, it's about measuring the journey, not just the destination.

Venture Capital (VC) firms are shifting their focus from broad digital health platforms to specialised healthcare startups, Rwit Ghosh and Jessica Jani report for Mint. After years of large bets on digital pharmacies like PharmEasy, investors are now backing firms in diagnostics, stem cell therapies, and medical devices. Reason? Potential for high value creation via strong intellectual property and lucrative acquisition opportunities for investors. the report says. Recent deals include Innovaccer, which raised $275 million for AI-powered healthcare data solutions, Neuberg Diagnostics which got $109 million for its international diagnostic network, and Qure.ai, which secured $65 million to automate radiology exams for lung cancer and tuberculosis detection. “The sweet spot is single-specialty healthcare and healthcare AI startups addressing the global market,” Nithin Kaimal, Partner and COO at Bessemer Venture Partners India, told Mint. Others like Arise Ventures, and 3one4 Capital are scouting for companies combining AI with strong IP, from dental diagnostics to obesity and diabetes solutions. Endiya Partners, for instance, has invested in Eyestem, developing stem cell therapy for incurable diseases, and Nkure Therapeutics, focused on cancer treatments, the report says further. While the potential is high, a few hurdles remain. These range from slow regulatory approvals and limited insurance penetration to scarce patient capital. “For pure healthtech, it would require a payer mechanism in place,” says Mayur Sirdesai, co-founder of Somerset Indus Capital Partners, who sees hybrid digital-physical models as the most scalable. Despite challenges, investors believe that AI-driven innovation, coupled with acquisition potential from big pharma could make niche healthtech one of India’s most attractive sectors for long-term value creation, the report adds. What factors will drive the rise of niche healthtech in India? Share your thoughts in the comments section. Source: Mint: https://lnkd.in/dRYbpqBr ✍ : Nakul Ghai 📷 : Getty Images #Artificialintelligence #Healthtech #Venturecapital

Digital health isn’t just a trend—it’s becoming the default channel for care delivery across generations. The latest 2024 Consumer Adoption of Digital Health Survey offers a compelling snapshot of how different generations are embracing virtual care, health tracking, wearables, and data-sharing. 🔍 Key insights: - Millennials lead in virtual care use (68%) and wearable ownership (66%), showing strong engagement as Digital Devotees. - Gen Z is proactive in tracking health metrics digitally (64%) and owning connected devices (60%). - Surprisingly, older generations—especially the Silent Generation—are the most willing to share data (90%) and trust provider-shared health info (76%). This generational shift reinforces what many of us in healthcare already see: digital health is not about age, it’s about mindset and trust. As we design the future of care, the challenge isn’t just technology—it’s creating connected, trustworthy, and inclusive digital experiences for everyone. #DigitalHealth #ConnectedCare #PatientEngagement #VirtualCare #HealthTech #FutureOfHealthcare #HealthcareLeadership #WearableTech #GenerationalInsights #RockHealth #CareRedesign #HealthEquity #DataDrivenCare #VirtualFirst #TrustInHealthcare

Sometimes research confirms the zeitgeist and sometimes it’s way ahead of the zeitgeist. An example of the latter is this amazingly prescient 2018 paper published in the journal JAMA Cardiology by Kevin Volpp, Harlan Krumholz, and David Asch. Kevin Volpp, the director of the Penn Center for Health Incentives and Behavioral Economics at the University of Pennsylvania, and David Asch, both Professors of Medicine and Health Care Management at the School of Medicine and Wharton School at the University of Pennsylvania, are members of Thrive Global’s scientific advisory board.    The paper, entitled “Mass Customization for Population Health,” notes that the U.S., which lags in life expectancy compared to other industrialized countries, spends huge amounts of money developing new medical technologies and yet doesn’t deploy existing ones very well. In cases in which effective treatment options exist, adherence is only about 40% to 45%.   And here was the prescient part: to increase adherence, and thus better health outcomes, “risk reduction strategies might be matched to individual preferences, observed behavioral phenotypes, and estimated risk.”   That’s exactly what AI, through hyper-personalization, will allow us to do — and it’s also what we’re currently integrating into our behavior change model at Thrive. Imagine a customized, hyper-personalized AI health coach trained not only on the best peer-reviewed science, but also on our biometric, lab and other medical data, and, as the paper states, our individual preferences — what conditions allow us to get quality sleep, which foods we love and don’t love, how and when we’re most likely to walk, move and stretch, and the most effective ways we can reduce stress.    The combination of behavioral science engagement tools combined with synchronized and automated medication refills could be thought of, the authors write, as a “behavioral polypill.” As they conclude, “behaviors ultimately determine much of the effectiveness we derive from the treatment strategies we already have.”   With AI, the behavioral polypill can become a powerful reality and significantly move the needle on health outcomes. https://lnkd.in/djvmuTxh #Health #AI #Personalization #ArtificialIntelligence #Behavior #Outcomes

You didn’t pursue a career in healthcare informatics just to chase outdated job titles. The world is changing. So are the roles. If you're still searching with 2015 job titles, you’ll miss the 2030 opportunities. Here’s the truth: The next decade will belong to those who understand not just healthcare, but data, automation, and digital systems together. And Healthcare Informatics is at that intersection. Top Hiring Trends for Healthcare Informatics (2024–2025): According to [HIMSS & BLS 2024 projections]: Healthcare Data Analyst roles grew by 18% last year. Clinical Decision Support & AI roles are emerging in major health systems. EHR System Support & Optimization remains the most in-demand skill. Population Health & Value-Based Care roles up by 11% due to Medicaid reforms. Clinical Research Informatics is growing in pharma/biotech. 2025–2035: What Roles Will Dominate? If you’re planning for long-term success, focus on roles that blend: Data + Outcomes AI + Patient Safety Compliance + Digital Health Here are the future-proof titles to track (and skill up for): Next-Gen Healthcare Informatics Roles: Healthcare Data Scientist (Python, SQL, predictive analytics) Clinical AI Analyst (ML models for outcomes + risk prediction) Digital Health Program Manager (mHealth, RPM, app-based care) Value-Based Care Analyst (Population health metrics, QI dashboards) Health Data Governance Specialist (HIPAA, HITECH, compliance) Clinical Informatics Consultant (Epic/Cerner + workflow redesign) Health Equity Data Analyst (DEI metrics, SDoH data) Telehealth Informatics Coordinator (virtual care workflows + UX design) Top Skills to Focus on (2025 and beyond): SQL, Python/R for health data Power BI / Tableau for dashboarding Epic or Cerner EHR optimization Clinical workflow mapping & UI/UX HL7, FHIR, interoperability knowledge Privacy regulations (HIPAA, GDPR) AI/ML foundations for clinical contexts Job Hunting Tip: Don’t search by degree. Search by outcome. Try: “Remote Patient Monitoring + Analyst” | “Epic + Optimization” | “Public Health + Data” These combos will open new doors. Tag a classmate, I’ll help you decode job titles, keywords, and roles that actually work in 2025. We rise faster when we learn together 💙 #HealthInformatics #HealthcareAnalytics #PublicHealthCareers #EntryLevelJobs #InternationalStudent #HealthTech