👩⚕️ Dr. Michal Tzuchman Katz's Kahun Elevates the Standard of Medical Care
FemWealth Springboard
Meet Dr. Michal Tzuchman Katz, a Pediatrician and Software Engineer Turned HealthTech Founder
Dr. Michal Tzuchman Katz is the co-founder of Kahun, a Tel Aviv-based HealthTech company on a mission to improve patient care and clinical outcomes by providing evidence-based and physician-trusted solutions.
Prior to becoming a founder, Dr. Tzuchman Katz worked as a Pediatrician and Software Engineer. These experiences provided her with a unique vantage point on the patients’ and clinicians’ unmet needs and the technical skills necessary to develop an innovative, technology-driven solution.
Kahun has developed a clinical reasoning engine, providing an AI component of medical intelligence for any patient-provider interaction, including virtual first, telemedicine, and traditional practice.
Learn more about Dr. Tzuchman Katz and Kahun’s mission in our deep dive Q&A:
What determined you to start Kahun? Was there a unique insight that has shown you a tool like Kahun is needed?
At the heart of any health provider’s work is the task of clinical reasoning, which represents the process of connecting the dots between a patient’s clinical presentation (including symptoms and tests) and reaching a diagnosis. When physicians conduct clinical reasoning, they essentially apply their own ‘mental map’ of medical knowledge and experience to the specific patient, a process that today has no benchmark or gold standards.
Coming from a tech background, it occurred to me early on as a medical student, and even more pronounced as a practicing pediatrician, that the clinical reasoning process limited to my accumulated knowledge and experience is a strong limiting factor to providing my patients the best medical care. Medical knowledge is continuously updated and researched, the knowledge is specific to population groups such as age, gender, ethnic groups, diseases in the background, immunocompetence level, etc. Scientific knowledge is statistical, which means that probabilistic reasoning needs to be applied in order to use it in relation to a specific patient. All this results in what the healthcare community refers to as using the ‘clinical hunch’ or intuition by clinicians.
With this realization, together with my partners from strong technical and business backgrounds, set out to build Kahun. We started with mapping the scientific medical knowledge into a structured format and then developed the algorithmic layer capable of utilizing this structured knowledge to perform evidence-based clinical reasoning.
How does Kahun support patients, respectively medical practitioners, and the health system?
Kahun gathers health information from patients based on medical literature from the company’s knowledge graph, which currently includes over 30 million clinical relations, making it the largest in the world. Information is collected in a way that is easy and convenient (from the comfort of their phone or computer) to help their healthcare providers make more informed clinical decisions and receive a higher standard level of care.
Kahun helps medical practitioners optimize their time with patients. They can spend less time on documentation, receive more information prior to the visit, and receive clinical insights that are specific to the patient and reference the original source in medical literature, making clinicians trust and rely on it.
Kahun helps health systems by reducing variability in care and improving patient experience as well as care outcomes.
What differentiates Kahun from other MedTech companies using AI?
Current AI tools for healthcare providers have failed to address current challenges and gain trust within the medical community. They use a combination of static decision trees or big-data engines built on patient records and experts’ knowledge. They are not dynamic and aren’t based on evidence-based medical literature. These tools face challenges and biases as they aren’t trained to perform actual clinical reasoning.
Kahun has essentially developed a clinical reasoning solution that can be understood and trusted by physicians. Its engine performs clinical reasoning at scale by basing its decisions on the company’s proprietary map of evidence-based medical insights. Kahun’s algorithmic engine utilizes this map in real-time to generate clinical insights tailored to each specific patient. Insights are referenced and backed by links to originating knowledge.
How does Kahun compare to other medical data-gathering platforms such as K-Health or Babylon?
Kahun was built for healthcare providers, and as such, it uses clinical reasoning. Many of the existing medical data-gathering platforms were built primarily for patients and are based on a technology that has limitations when it comes to helping providers in clinical environments. Kahun recently published the first-of-its-kind study assessing the data-gathering function of currently available chatbot symptom-checkers. Out of eight symptom-checkers—K Health, Babylon, ADA, Buoy, Kahun, Mediktor, Symptomae, and Your.MD—Kahun demonstrated the best overall performance in finding the most pertinent insights in a simulated patient conversation.
What advice do you have for Health Tech startups that are currently fundraising?
The healthcare market varies heavily between regions, and there are unique opportunities in each area but also a lot of companies trying to disrupt the industry. My advice would be to focus on one region and learn about its health system, financial motivation, and regulatory constraints so that the value proposition can be sharp enough and relatable enough for investors.
Follow Dr. Tzuchman Katz on Linkedin.
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