Excited for this one. Congrats to Alex Cohen and Hello Patient on their seed round announcement.
Hello Patient stands to change the communication paradigm between patients and providers forever. Their generative AI call agent technology is tackling the tremendous admin burden of patient facing comms (scheduling, follow ups, referrals, prescription refills, etc).
Massive opportunity and we think Alex and his team are expertly positioned to become market leaders. Max Ventures is thrilled to co-lead the seed round with 8VC and Bling Capital
A great quote below from Alex highlighting the concept of "service as a software". Healthcare is a heavily service oriented industry - so the opportunity for step change is even more profound.
The startup's approach is part of a paradigm shift where AI companies are offering service as software.
"I'm a big believer that the right way to do this is through a managed services business. We're not building SaaS. I believe we can do this services as software where what was traditionally a services business now has software margins because I don't have to go employ a whole bunch of people to do the services under the hood," Cohen noted.
https://lnkd.in/ehNN2AmW
Seed Raise: Tokenizing premium spring water & helping 1.4 billion people in need of clean drinking water 💧 Quenching thirst, boosting profits 💧 30M+ Impressions/Year | RWA | DeFi | DAO
Medical practice staff handle a large volume of calls and texts to patients for things like appointment scheduling, referral follow-ups and prescription refills. It's a time-consuming process and results in a lot of administrative overhead. I chatted w/ Alex Cohen about how his new startup Hello Patient built AI agents to automate this patient-facing communication work
Building the future of patient experiences in healthcare
Excited to share that today we're launching Hello Patient out of stealth with our $6.3M seed round led by 8VC, Bling Capital, and Max Ventures!
For the last 7 months, we've been heads down building complex infrastructure and tooling to support real time AI agents that we deploy on behalf of healthcare practices. Our agents can call and text patients just like practice staff do, taking on full workflows like scheduling, reminders, and rescheduling.
Having run consumer and growth product teams at Carbon Health for 3.5 years, we're building what I wished we had back then. No matter how many self-service tools we built, patients still called and texted in. I looked at almost every contact platform on the market, and none actually resolved calls or required tons of work from us to do so.
We're live today with customers and already seeing the impact of automating all this patient-facing communication work. Our agents have incredibly low latency and sound remarkably human. They handle complex edge cases and actually get stuff done vs just routing calls around.
Full article here: https://lnkd.in/ddSAHc6z
2 big updates this week:
-Ability to automatically append OPTIONALLY the previous encounter for longitudinal context via "Record Follow Up Visit" button from the Patient Thread.
-We added the ability to collapse all notes with one click leading to an extremely economical patient thread when it comes to scrolling.
The Startup is producing from its total revenue 75% profit, it was 85% but I sacrificed that 10% to bring the new AI Fax, Telehealth and an improved AI Nurse Experience. Still bootstrapped. We closed a corporate contract yesterday for an organization with hundreds of users.
We haven't closed a single sale for thousands of users yet though, but taking into consideration that we don't have a sales team, I like the current growth trajectory.
Exciting news in the world of healthcare! Automated healthcare platform, Plenful, has emerged from stealth mode with $9M in funding.
Their AI-powered software streamlines medical administrative tasks, freeing up time for healthcare professionals to focus on patient care.
Learn more about this innovative solution and its potential to revolutionize the industry below. #RPA#AaroRnTech#AI#Chatbots#ChatAgility#Taskmining
🚀 Milestone Alert: Official Launch of MVP and First GP Onboarded to Test JarvisMD! 🎉
Exciting news from HealthBridge AI! This week, Cofounder & CTO Minh Nguyen and I welcomed our first of many GPs onboard to test JarvisMD, our AI-powered scribe and Clinical Copilot. Our esteemed GP tester brings decades of experience in digital health and clinical governance, already offering invaluable insights to enhance our platform and streamline healthcare workflows for clinicians.
With JarvisMD, clinicians can seamlessly integrate an AI Scribe and AI Clinical Copilot into their daily practice, reducing administrative tasks and freeing up more time for patient care. 🕒
While being first to market isn't our goal, our priority is to be the safest and most trusted solution. We are deeply committed to patient data privacy, security, clinical governance, and ethical AI. As a doctor myself, I understand the critical role trust plays in the clinical systems we rely on for patient care. That's why my team and I are dedicated to building a platform that both clinicians and patients can fully trust and depend on.
We're onboarding and expanding our tester base and inviting clinicians to join us on this journey! If you're a clinician in Australia interested in early access to JarvisMD for free and see how it can revolutionise your workflow, reach out to me to join our beta tester waitlist.
Hats off to our dedicated team and testers for reaching this milestone. The journey has only just begun!
#HealthTech#JarvisMD#MVP#AIScribe#AIClinicalCopilot#DigitalHealth#ClinicalGovernance#GPOnboarding#BetaTesters#EarlyAccess#Innovation#HealthcareTransformation#Australia#Startups
❗Intuitive operation is key❗
Emergency rooms often treat between 100 and 200 patients per day.
In these highly process-oriented departments of our #emergency hospitals, every minute counts.
If a process in operating medical software takes one minute longer per patient, that's 100-200 minutes of pure work time per day that can be avoided.
To provide healthcare professionals with the best possible support, we have placed the highest value on an intuitive operation of #elea with streamlined processes and minimal "clicks".
You will understand elea in no time, be able to operate it, and be fully ready to use it.
No more endless clicks through deep menu navigation that waste your valuable time. With elea, you can now invest this valuable time in those who really matter: your patients!
We #simplifyhealthcare!
#ai#digitalhealth#solution#startup#hamburg
Neuromechanist | Applied Mathematician | Physiologist | Data Analyst | Biomechanist working at the intersection between data and life science to help make people’s lives healthier and happier. All opinions are my own.
I couldn’t agree more, as someone with expertise in both applied mathematics/data science and physiology, who is writing this while literally sitting next to their partner (with the same areas of expertise) who is post medical procedure in a hospital bed right now.
I’ve seen a lot of cases where people come into physiology or medicine and think what they’re doing is innovative, but what they’re doing that’s new generally isn’t right and what they’re doing that’s right generally isn’t new.
Or the math may be independently sound and the physiology independently sound, but they don’t understand that knowing how to combine the two is a field in and of itself. This is complicated by the addition of artifact-prone electronic signals.
Coming into this situation as someone who does work in this intersection can be a minefield because you have to work around people’s fictions of how much they know or did with real data. This is especially fraught when you have knowledge beyond their actual understanding but not their perception of or belief about their understanding. It makes real improvement difficult if not impossible.
Or the precision or accuracy of the product isn’t sufficient for the use case or is only sufficient for certain populations or circumstances in ways that widen current inequalities, which begs the question of whether the existence of the product is or ever will truly be a net benefit to the world or if it is exacerbating and expanding current exploitation patterns. If you’re working with people with “helper” identities, this is yet another minefield to navigate.
Even in cases where the product may work, it’s often not due to innovation, just obfuscation of the degree to which the people who “produced” said product are co-opting others’ ideas and previous work. Consider this part 3 of the minefield.
So, it is domain expertise. But it’s not just domain expertise; it’s having complex thinking ability and the capacity to see multiple possibilities combined with that domain expertise and being able to recognize what contributions were actually yours, who the product truly benefits, and not claiming value beyond that in ways that hold net innovation, not to mention equality or net gain, back.
Oh, and, all other things being equal, I’ll take a defensive player over a striker any day of the week. Physiology in general or medicine in particular is not a field where you do or should get celebrated for one victory among many failures. It’s one where you cannot risk even one mistake without severe consequences.
AI for healthcare | Dev&Doc Podcast | Neurology Registrar
🤖What I learnt meeting with >30 healthtech start-ups this year. A common theme is that ~ half of them pitched interesting ideas that unfortunately would not be a product I'd want to use as a clinician or would fit in meaningfully into a clinical work flow...
😐There was also a recurring theme of overly ambitious #LLM use cases - It was really painful hearing a number of companies (that raised a modest amount £££) tell me how they'd like to revolutionise healthcare by creating a model to diagnose any undifferentiated patient, spanning over all specialties. It quickly became painfully clear the person had no understanding of EHRs, no understanding of the scientific literature, and no medical knowledge. Can we just perfect #LLMs for administrative tasks before jumping into clinical decision making?
👨🏻⚕️It was also interesting to see majority had no clinicians in the founding team, and even when they did, there was a clear gap between clinical and technical expertise so the two sides were not communicating and sharing ideas effectively.
It's a message repeated over and over again by y-combinator and other VCs alike -
1. Build a product that users want
2. For healthcare I think tech needs to be developed use case by use case. Instead of jumping on an ambitious undifferentiated model for all patients. (similar to what Dr. Zhong Wei Khor recently alluded to)
3. The core team should consist of a subject matter specialist to direct the development in a meaningful way, but I'd go as far as saying that the clinician needs to have at least an intermediate level of understanding of data systems, AI models and limitations. (this is something both Keith Grimes and I have explored, and will be an incoming episode on the Dev and doc podcast 👀)
4. My personal opinion, but we can't just keep building healthcare products based on a closed source proprietary model, to me this is not future proofing our technology, and puts the power of people's health into the hands of one big for-profit conglomerate.
-----------
Hello 👋 we run a Substack and Podcast, Dev and Doc: AI for healthcare. This includes latest news, education, and deep dives in AI for healthcare! 👨🏻⚕️🤖
Substack- https://lnkd.in/e_XV4Pbz
YT - https://lnkd.in/ey3mxsuN
Spotify - https://lnkd.in/ecFRTN9R
🤖What I learnt meeting with >30 healthtech start-ups this year. A common theme is that ~ half of them pitched interesting ideas that unfortunately would not be a product I'd want to use as a clinician or would fit in meaningfully into a clinical work flow...
😐There was also a recurring theme of overly ambitious #LLM use cases - It was really painful hearing a number of companies (that raised a modest amount £££) tell me how they'd like to revolutionise healthcare by creating a model to diagnose any undifferentiated patient, spanning over all specialties. It quickly became painfully clear the person had no understanding of EHRs, no understanding of the scientific literature, and no medical knowledge. Can we just perfect #LLMs for administrative tasks before jumping into clinical decision making?
👨🏻⚕️It was also interesting to see majority had no clinicians in the founding team, and even when they did, there was a clear gap between clinical and technical expertise so the two sides were not communicating and sharing ideas effectively.
It's a message repeated over and over again by y-combinator and other VCs alike -
1. Build a product that users want
2. For healthcare I think tech needs to be developed use case by use case. Instead of jumping on an ambitious undifferentiated model for all patients. (similar to what Dr. Zhong Wei Khor recently alluded to)
3. The core team should consist of a subject matter specialist to direct the development in a meaningful way, but I'd go as far as saying that the clinician needs to have at least an intermediate level of understanding of data systems, AI models and limitations. (this is something both Keith Grimes and I have explored, and will be an incoming episode on the Dev and doc podcast 👀)
4. My personal opinion, but we can't just keep building healthcare products based on a closed source proprietary model, to me this is not future proofing our technology, and puts the power of people's health into the hands of one big for-profit conglomerate.
-----------
Hello 👋 we run a Substack and Podcast, Dev and Doc: AI for healthcare. This includes latest news, education, and deep dives in AI for healthcare! 👨🏻⚕️🤖
Substack- https://lnkd.in/e_XV4Pbz
YT - https://lnkd.in/ey3mxsuN
Spotify - https://lnkd.in/ecFRTN9R
I want to see basic privacy-by-design AI solutions for continuity of care that put patients in charge of their data. Put them into robotic appliances for hospital rooms where there’s a running cast of characters each day.
Then we can port them over to the education sector where we have a pittance of resources compared to medicine.
AI for healthcare | Dev&Doc Podcast | Neurology Registrar
🤖What I learnt meeting with >30 healthtech start-ups this year. A common theme is that ~ half of them pitched interesting ideas that unfortunately would not be a product I'd want to use as a clinician or would fit in meaningfully into a clinical work flow...
😐There was also a recurring theme of overly ambitious #LLM use cases - It was really painful hearing a number of companies (that raised a modest amount £££) tell me how they'd like to revolutionise healthcare by creating a model to diagnose any undifferentiated patient, spanning over all specialties. It quickly became painfully clear the person had no understanding of EHRs, no understanding of the scientific literature, and no medical knowledge. Can we just perfect #LLMs for administrative tasks before jumping into clinical decision making?
👨🏻⚕️It was also interesting to see majority had no clinicians in the founding team, and even when they did, there was a clear gap between clinical and technical expertise so the two sides were not communicating and sharing ideas effectively.
It's a message repeated over and over again by y-combinator and other VCs alike -
1. Build a product that users want
2. For healthcare I think tech needs to be developed use case by use case. Instead of jumping on an ambitious undifferentiated model for all patients. (similar to what Dr. Zhong Wei Khor recently alluded to)
3. The core team should consist of a subject matter specialist to direct the development in a meaningful way, but I'd go as far as saying that the clinician needs to have at least an intermediate level of understanding of data systems, AI models and limitations. (this is something both Keith Grimes and I have explored, and will be an incoming episode on the Dev and doc podcast 👀)
4. My personal opinion, but we can't just keep building healthcare products based on a closed source proprietary model, to me this is not future proofing our technology, and puts the power of people's health into the hands of one big for-profit conglomerate.
-----------
Hello 👋 we run a Substack and Podcast, Dev and Doc: AI for healthcare. This includes latest news, education, and deep dives in AI for healthcare! 👨🏻⚕️🤖
Substack- https://lnkd.in/e_XV4Pbz
YT - https://lnkd.in/ey3mxsuN
Spotify - https://lnkd.in/ecFRTN9R
Today's BuzzBelow post talks about Ambience Healthcare.
Ambience Healthcare, a leader in healthcare software, is pioneering the future of medical documentation with advanced AI technology. Their flagship product, Ambience AutoScribe, streamlines documentation across medical specialties, including behavioral health and geriatric care. AutoScribe's automation saves clinicians time, reduces burnout, and improves patient care quality. With a suite of tailored applications, Ambience caters to diverse medical specialties' unique needs. Founded in 2020 by Nikhil Buduma, the company has raised $70 million to date.
Read the post here: https://lnkd.in/gRNtu5ky#AIinHealthcare#AmbienceHealthcare#StartupSuccess
Founder & CEO at Stfalcon | Custom Mobile & Web App Development Services | Stfalcon Named Among Clutch’s Top 1000 Global Service Providers
3wThat's fantastic news, Matthew! How will Hello Patient further enhance patient-provider communications? 😊