Success in Healthtech Innovation

I've watched 3 "revolutionary" healthcare technologies fail spectacularly. Each time, the technology was perfect. The implementation was disastrous. Google Health (shut down twice). Microsoft HealthVault (lasted 12 years, then folded). IBM Watson for Oncology (massively overpromised). Billions invested. Solid technology. Total failure. Not because the vision was wrong, but because healthcare adoption follows different rules than consumer tech. Here's what I learned building healthcare tech for 15 years: 1/ Healthcare moves at the speed of trust, not innovation ↳ Lives are at stake, so skepticism is protective ↳ Regulatory approval takes years usually for good reason ↳ Doctors need extensive validation before adoption ↳ Patients want proven solutions, not beta testing 2/ Integration trumps innovation every time ↳ The best tool that no one uses is worthless ↳ Workflow integration matters more than features ↳ EMR compatibility determines adoption rates ↳ Training time is always underestimated 3/ The "cool factor" doesn't predict success ↳ Flashy demos rarely translate to daily use ↳ Simple solutions often outperform complex ones ↳ User interface design beats artificial intelligence ↳ Reliability matters more than cutting-edge features 4/ Reimbursement determines everything ↳ No CPT code = no sustainable business model ↳ Insurance coverage drives provider adoption ↳ Value-based care is changing this slowly ↳ Free trials don't create lasting change 5/ Clinical champions make or break technology ↳ One enthusiastic doctor can drive adoption ↳ Early adopters must see immediate benefits ↳ Word-of-mouth beats marketing every time ↳ Resistance from key stakeholders kills innovations The pattern I've seen: companies build technology for the healthcare system they wish existed, not the one that actually exists. They optimize for TechCrunch headlines instead of clinic workflows. They design for Silicon Valley investors instead of 65-year-old physicians. A successful healthcare technology I've implemented? A simple visit summarization app that saved me time and let me focus on the patient. No fancy interface, very lightweight, integrated into my clinical workflow, effortless to use. Just solved an problem that users had. Healthcare doesn't need more revolutionary technology. It needs evolutionary technology that works within existing systems. ⁉️ What's the simplest technology that's made the biggest difference in your healthcare experience? Sometimes basic beats brilliant. ♻️ Repost if you believe implementation beats innovation in healthcare 👉 Follow me (Reza Hosseini Ghomi, MD, MSE) for realistic perspectives on healthcare technology

95% of healthtech startups don’t survive their first real market test. Not because of the product. Not because of funding. But because they misunderstood what the real test even is. Let me explain. Most founders think the test is: Will users try it? Can we grow fast? Does the product work? But in healthtech, the true test is this: Can the market trust you enough to use your product in a clinical workflow, at scale, without hand-holding? That’s where 95% of startups fail. Because healthcare doesn’t reward novelty. It rewards credibility, compatibility, and continuity. Here are 4 brutal truths I’ve learned after 25+ years in this space: 1. Healthcare doesn’t buy tech. It buys trust. Even if your ML model is 95% accurate, it won’t be adopted unless people trust how it works and why it works. If clinicians don’t understand it and decision-makers can’t defend it, they won’t risk patient care or reputations on it. 2. Pilots aren’t validation unless they prove real-world value. A controlled trial is only useful if it demonstrates measurable improvements - like saved clinician time, lower readmission rates, or better outcomes. Without that, it’s just a demo, not validation. 3. Integration beats innovation. If your product forces staff to log into a new system, learn new workflows, or switch between screens - it won’t scale. The best products blend into existing tools and workflows, not break them. 4. Good storytelling doesn’t secure funding. Proof does. You can impress with a flashy deck, but serious investors and clinical buyers want published studies, cost-benefit analyses, and evidence of adoption. Credibility beats charisma - every time. So if your startup fails at the first market test - it probably wasn’t bad tech. It was bad strategy. Too many teams build with optimism instead of realism. If you’re pre-launch or pre-scale, ask yourself: Who exactly will use this every day? Who will approve and pay for it? What will they stop doing once they adopt it? Healthtech isn’t about hacking growth. It’s about building trust - through data, design, and delivery. I’ve seen brilliant teams crash because they built for what should work - Not what actually gets used. You don’t need a better product. You need a better go-to-market reality check. Have you seen healthtech ideas die at the last mile? What caused the failure? #healthtech #founders #startups #innovation

Why is it so hard for healthcare innovators to gain traction in the traditional system? Because workflows are extremely fragile and deeply entrenched. Fax machines are routinely derided, but, as backward and inefficient as they may seem in today's tech forward world, they're a comfortable, familiar, and "dependable" tool for many medical offices. Nothing causes chaos in a doctor's office like a technical glitch or minor change in protocol. Introducing a slightly altered workflow -- an extra step or couple of extra clicks -- has ripple effects that can bring efficiency to its knees. In an overworked and under-resourced setting, the default will always be to take the path of least resistance and fall back on familiar processes. This is the challenge all healthcare disruptors face -- how to make your product or service so seamless or so "must-have" that you overcome fragility and entrenchment. Finding a champion works if that champion has enough sway or influence. Otherwise, you need organizational leadership that is forward-thinking, excellent at change management, and deeply trusted. (Not always easy to find in healthcare). Of course, there is another, harder way -- re-build processes from the ground up. Create systems that aren't so fragile or entrenched. Disruption in healthcare isn’t just about better technology -- it’s about overcoming inertia. #medicine #healthcare #healthcareinnovation #healthcaredisruption

A lesson from self-driving cars… Healthcare's AI conversation remains dangerously incomplete. While organizations obsess over provider adoption, we're neglecting the foundational element that will determine success or failure: trust. Joel Gordon, CMIO at UW Health, crystallized this at a Reuters conference, warning that a single high-profile AI error could devastate public confidence sector-wide. His point echoes decades of healthcare innovation: trust isn't given—it's earned through deliberate action. History and other industries can be instructive here. I was hoping by now we’d have fully autonomous self-driving vehicles (so my kids wouldn’t need a real driver’s license!), but early high-profile accidents and driver fatalities damaged consumer confidence. And while it’s picking up steam again, but we lost some good years as public trust needed to be regained. We cannot repeat this mistake with healthcare AI—it’s just too valuable and can do so much good for our patients, workforce, and our deeply inefficient health systems. As I've argued in my prior work, trust and humanity must anchor care delivery. AI that undermines these foundations will fail regardless of technical brilliance. Healthcare already battles trust deficits—vaccine hesitancy, treatment non-adherence—that cost lives and resources. AI without governance risks exponentially amplifying these challenges. We need systematic approaches addressing three areas:   Transparency in AI decision-making, with clear explanations of algorithmic conclusions. WHO principles emphasize AI must serve public benefit, requiring accountability mechanisms that patients and providers understand.   Equity-centered deployment that addresses rather than exacerbates disparities. There is no quality in healthcare without equity—a principle critical to AI deployment at scale.   Proactive error management treating mistakes as learning opportunities, not failures to hide. Improvement science teaches that error transparency builds trust when handled appropriately. As developers and entrepreneurs, we need to treat trust-building as seriously as technical validation. The question isn't whether healthcare AI will face its first major error—it's whether we'll have sufficient trust infrastructure to survive and learn from that inevitable moment. Organizations investing now in transparent governance will capture AI's potential. Those that don't risk the fate of other promising innovations that failed to earn public confidence. #Trust #HealthcareAI #AIAdoption #HealthTech #GenerativeAI #AIMedicine https://lnkd.in/eEnVguju

A big question nowadays at national meetings is how do we use Ai and drive its adoption.  We need to reframe the question Let’s shift the focus from “how can we use AI?” to “how can AI support better care?” The key is understanding clinical  workflow. I always enjoy listening to FDA Dr. Robert Califf’s approach to big problems (and that includes when I was a resident at a Duke and also when I was at FDA with him during his first stint!) During a recent advisory committee around AI, Dr. Califf emphasized a crucial point: AI adoption in healthcare must be driven by clinical care, not technology for technology’s sake. His message is a reminder that AI isn’t the solution—it’s a tool. For AI to truly transform healthcare, it needs to align with the needs of patients and providers, enhancing decision-making, improving outcomes, and addressing inequities in care. But achieving this requires more than innovative algorithms. It demands: • Clinician input during AI development to ensure real-world relevance. • Robust evidence showing AI’s impact on patient outcomes, safety, and quality of care. • Trust and transparency, so patients and providers feel confident using these tools. He also pointed out the need to re-evaluate Ai tools. That seems to be an issue that’s an afterthought right now. We need to change that approach. Yes, AI has the potential to streamline workflows, reduce burnout, and personalize care. However, as Dr. Califf noted, its adoption must be guided by what works in the clinical setting—where care happens. That might might be the hospital, physician office, or even the home! How do you think AI can be integrated into clinical workflows to meet the needs of patients and health care professionals ? Share your thoughts below! #ai #clinicalcare #aihealth #FDA #aitransparency #artificialintelligence

On #MothersDay, everyone wants to celebrate Mom - nobody wants to fund her health. This is a really excellent, MUST-READ insightful analysis by Halle Tecco, MPH, MBA and Carolyn Witte of the funding cliff women's health startups hit at growth stage, the negative implications of that across so many fronts, and what the solutions are 💥 'The data confirmed our hunch: women's health companies aren’t just underrepresented—they’re under-capitalized at the growth stage, exactly the moment when capital matters most. This results in fewer scaled women’s health companies, fewer comps, and fewer exits. It’s a vicious cycle that holds the whole category back. Let’s break it down. ... While momentum is real, the majority of deals in women’s health are still happening in the early stages of a company’s journey. A striking 81% of women’s health deals in 2023–2024 (excluding bridge, debt, and unlabeled rounds) were Seed or Series A. That’s a significantly higher concentration than the broader digital health sector, where just 68% of deals fall into those early stages. ... Negotiating power is often limited in women’s health and is compounded by the female founder factor. Many of the funds investing in this space—especially the newer, women’s health-focused ones—are smaller and more valuation-sensitive. Some don’t have the ability to lead rounds or write larger follow-on checks, which makes it harder for founders to run competitive processes or set favorable terms. That lack of leverage can translate into lower valuations, “party rounds” made up of lots of little checks, more investor-favorable governance provisions, and higher traction bars in order to get a deal done at all. The result? A compounding dilution effect: smaller rounds, more equity given up, and less flexibility to raise future capital on founder-friendly terms. It’s a quiet penalty that builds over time—and holds back the very people trying to scale solutions in this space. ... 🔄 Break the “one-and-done” mindset. Too often, we hear investors say they’ve “already made their women’s health bet.” Imagine if someone said, “I already made my SaaS bet!” We need to normalize—and celebrate—investors who back multiple, adjacent players in women’s health (say, a maternity care startup and a menopause platform). Women benefit from having more choices in the market. So do the founders who get to scale, and the investors who back them. Treating women’s health like a box to be checked undercuts the plethora of women’s needs and the scale of the market opportunity.' https://lnkd.in/eVk2jCEs #FundFemaleFounders #FundFemaleFoundedFunds

I will never forget the mom in the ER whose child was just diagnosed with Type 1 Diabetes. Tears rolled down her face as she processed this- ‘Will he be okay?’ she asked. ‘Yes. Trust us- we will make sure of it.’ She nodded. There are many skills that a health care professional must have to deliver the best care for their patient. The one that has helped me most as a physician, is establishing trust, often with kind communication. From talking to the parents of the very sick 5-month-old who needed a spinal tap to rule out meningitis, to the teen who was in denial of her pregnancy and didn’t want to tell her mother, to diagnosing a 10-year-old with Type 1 diabetes and giving parents this news, the key ingredient is establishing trust. As AI and innovation explode in healthcare, what role does TRUST play for patient and clinician adoption? The best and most proven AI tools to improve health will not succeed, if they do not have TRUST and relationship building from the clinicians or patients who are using them. Do doctors and patients see AI in health similarly? There have been a number of surveys gauging attitudes towards AI. Recently, Future of Health Index (FHI) Philips questioned over 16,000 patients and 1,926 healthcare professionals in an online survey. The findings included that although 63% of HCPs felt that AI could improve healthcare, only 48% of patients do. Age of patients mattered- only 1/3 of those over 45 felt AI could optimize health. But the issue of TRUST for patients was key: - Over 70% of patients would feel more comfortable about AI use in healthcare, if their doctor or nurse gave them information about it. - 44% of patients would feel more comfortable with AI if reassured an HCP had oversight  - Validated testing for safety and effectiveness of the tool helped 35% of patients more comfortable Clinicians seem to be engaged in AI use in health; the AMA and Healio have shown physicians to be engaged and interested in AI use. In their respective surveys 50% to 68% of doctors are using AI enhanced tools, includeing transcription, search, and patient education. But one theme constantly resonates across all 3 surveys – the desire for SAFETY. 85% of HCPs were concerned about safety and legal risk of AI usage in the FHI survey with over half desiring clear guidelines for usage and limitations. In a time when patients are still waiting almost 2 months to see specialists and clinicians are still feeling overwhelmed with admin tasks, AI can certainly make a difference. But it seems that, at the end of the day, the simple task of TRUST is what will make a difference in the ADOPTION of these tools. And that means having clinicians and patients understand, and be comfortable with the technologies, and ensuring safe and tested innovations as well. Do you think TRUST is important in AI tool integration? #innovation #trust https://lnkd.in/es3tjwib

Here’s a truth about healthcare innovation we don’t talk about enough: (Great ideas often fail—not because they lack potential, but because they face resistance.) We often hear things like: “Technology will revolutionize medicine.” “Innovation is the key to better patient outcomes.” “New tools make healthcare more efficient.” But here’s the reality: Innovation in healthcare isn’t just about having great ideas; it’s about overcoming the barriers to adoption. Here’s why promising innovations often struggle: → Risk Aversion: Healthcare professionals prioritize safety and stick to proven methods unless there's undeniable evidence. → Disrupted Workflows: New tools can feel like complications, threatening established routines and patient interactions. → Time Pressures: Clinicians, already stretched thin, often lack time to learn and adapt to new systems. → Organizational Culture: Traditional mindsets can stifle innovation, favoring profit-driven solutions over simpler, impactful ideas. The takeaway? For innovation to thrive, healthcare must address these barriers with change management, engagement, and clear demonstrations of value. What’s your take? How can we foster innovation in such a risk-averse industry? Let’s discuss below! 👇

The most dangerous words in healthcare startups: "Our advisory board says the market needs this." Four things I see advisory boards typically miss, and how to solve for them: 1. The operational path to implementation Is your target market Medicare? Ask your advisors about 855R reassignments, TIN/NPI management, and delegated credentialing agreements. Watch for deer-in-headlights responses. Commercial plans? Question them about leased network requirements, admin service fees, and value-based contracting amendment structures. Employer deals? See if they understand network adequacy requirements, stop-loss implications, and benefits integration workflows. 2. The true economic buyer vs. clinical champion Clinical champions validate the problem but rarely control the budget. Quality leaders may love your solution but can't allocate resources. Even C-suite enthusiasm means nothing without operational ownership. 3. The regulatory constraints on adoption Does your solution trigger Stark Law considerations? Where does your offering sit in relation to ERISA? Have your advisors mapped your value proposition to compliance requirements? Can they articulate how your solution navigates HIPAA beyond signing a BAA? 4. The procurement reality Healthcare decision-making isn't linear—it's networked. Implementation teams can veto solutions champions approve (this happens a LOT in payor/employer GTM) Legal/compliance has different priorities than innovation or total reward teams. Procurement cycles follow their own logic independent of need. Most healthcare advisors deeply, DEEPLY understand their specific corner of the ecosystem—but rarely the commercial pathways between them. The safety-net system CEO knows their operation but not commercial payor contracting. The payor executive understands MLR but not provider workflow adoption. The clinical leader knows care gaps but not procurement processes. If your strategy relies heavily on advisor validation, let's pressure-test it against market reality. And, as an added bonus, I'm tagging some of the best advisors I know in the comments. #healthcarevalidation #strategyalignment #marketarchitecture

#womenshealth faces a slew of systemic barriers. We need a full list. What would you add below? A systemic barrier is an entrenched obstacle or structural challenge embedded within policies, practices, institutions, or cultural norms that restricts equitable access, participation, or opportunities for certain groups in women's health. It's something that reaches beyond specific care, such as fertility, menopause, cancer etc. 💵 Low Reimbursement Rates: Services and procedures in women’s health are undervalued, driving provider attrition and limiting access to care. 🟰 Budget Neutrality Rules: Federal policies cap reimbursement increases, stalling systemic reforms. ⚖️ Systemic Gender Discrimination: Gynecological and obstetric procedures are reimbursed at lower rates than comparable procedures in other specialties. 🥼 Provider Shortages: Unsustainable margins force providers out of practice, exacerbating access issues, especially in underserved communities.  Leading industry organizations predict we will not have enough women’s health providers after 2030.   🔴 Regulatory Red Tape:  Current regulatory structures make it difficult for women’s health innovations to come to market.  💰 Lack of Investment: Women's health receives only 4% of U.S. healthcare funding funding and 0.15% of venture capital investment, highlighting a significant underfunding of critical research and innovation in this space. 💡 Innovation: Women-specific healthcare solutions remain underdeveloped due to a lack of prioritization and funding, leaving major unmet needs in diagnostics, treatments, and care delivery. 💻 Research Gaps: Women were excluded from clinical trials until 1993, resulting in limited understanding of sex-specific health issues and treatments, with gaps that persist in research today. What else? I'd love to hear your thoughts below.