⚕️Roadmap For A Successful Healthcare MVP

Good Morning and welcome to another edition of HealthTech Zen: your weekly dose of HealthTech innovation.

Today we’re covering a myriad of topics from brain data privacy to AI in healthcare.
Let’s dive in!

DEEP DIVE
Roadmap For Building A Successful Healthcare MVP

42% of the startups fail because there’s no market need for the product.

A healthcare MVP (minimum viable product) helps validate the business idea early on and iterate it before deploying it in the market.

Top Benefits Of Healthcare MVP

1. Enhances time to market

2. Allows for incorporation of user feedback

3. Facilitates pitches for funding

4. Results in cost effective development

Unlike other industries, developing healthcare software comes with its unique set of challenges owing to compliance and interoperability challenges.

Read about the steps involved in charting a successful roadmap for developing a healthcare MVP that sells here.

PULSE POINTS
Latest Breakthroughs This Week

Here’s the most important breakthroughs and advancements we spotted in the healthcare technology space this week.

• Project Health: UC Davis Health and Amazon are using generative artificial intelligence to counter health misinformation. Project Health, which employs AI and machine learning to detect emerging public health misinformation and score its threat to human health, can then generate responses tailored to different demographics and communities.

• Neural Data Protection: With the increasing number of technologies that track brain activity, a new Colorado law aims to protect people's neural data from falling into the wrong hands. The first-of-its-kind legislation gives data collected from people's brains the same protections as other biometric information, such as fingerprints and facial images.

• Generative AI: Providence and Microsoft are using artificial intelligence to scan massive amounts of patient data to improve cancer care. Generative AI summarizes unstructured data from test results, imaging and EHRs into a readable, text-based format for busy oncologists.

• Patient portal messages make up only a small percentage of the healthcare services providers bill for. Only 0.8% of fee-for-service Medicare beneficiaries were charged for at least one patient portal message from 2020 to 2022.

• Artificial Intelligence at Stanford Health Care is facilitating enhanced collaboration between physicians and nurses by utilizing predictive models to identify patient deterioration risks. The AI system continuously analyzes vital signs, laboratory results, and EHRs, providing real-time alerts to the clinical team. This proactive approach fosters communication among clinicians throughout shifts, improving patient care beyond traditional handoffs.

• Stats: 40% of U.S. physicians said they are prepared to use Gen AI (generative artificial intelligence) during patient interactions at the point-of-care

• Partnership: Northwestern Medicine sealed an artificial intelligence partnership with Dell Technologies to develop a generative multimodal large language model for analyzing chest X-rays.

• FDA has approved an artificial intelligence algorithm for Eko Health's digital stethoscope that can detect low ejection fraction, a key indicator of heart failure. The AI stethoscope will allow clinicians to detect low EF — when the heart does not efficiently pump blood — in about 15 seconds during routine exams.

DECODER
What Is Technical Debt In Healthcare?

Technical debt refers to the choices made to delay necessary maintenance or replacement of IT systems that will eventually impact an organization’s operations. As healthcare organizations continue with their digital transformation, they must balance debt remediation with new platform investments.

Read the comprehensive guide to upgrading legacy systems and reducing technical debt in healthcare here.