Misha Palecek

Latest #PitchBook data for #HealthIT investment shows a preference for later stage investment across healthIT that pre-dates the VC downturn and current interest rate environment. Even though healthIT has been more resilient to current headwinds compared to health care services and PPM plays, perhaps it speaks to a need to scale solutions and points of saturation for new entrants. "...In the lower middle market, we are beginning to see more examples of a phenomenon we have anticipated for a while: PE firms and PE-backed companies acquiring VC-backed startups. Lower-middle-market PE firms perennially complain that VC- backed companies expect too-high multiples, and these firms would generally prefer to invest on a multiple of EBITDA rather than a multiple of revenue..." Speaks to a convergence that would allow PE-VC M&A on both ends of the startup spectrum. #HealthcareVC #healthcarePE

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Investing in companies that fill needs for health systems is a growth opportunity for both delivery organizations and start ups. Some systems are jumping in on their own, while others are partnering with like minded systems or with established VC firms. While this is a relatively new trend for systems, health plans have been making similar bets for many years. The benefits of becoming a health system portfolio company can be significant. Data, access to beta populations and real world coaching can be extremely beneficial. Start ups get mentoring and systems have to ability to leverage outside resources to solve relevant business problems. I predict a booming business!

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There’s a category we believe is getting too little attention when it comes to AI in healthcare: AI Clinical Documentation Integrity (CDI) While AI ambient scribes and autonomous medical coding solutions have gotten most of the headlines, we’d argue AI CDI is equally impactful when it comes to quality care and accurate billing. For those not familiar, CDI ensures that clinical documentation accurately reflects the patient’s medical condition and the provided care. Historically, CDI was a manual slog, with dedicated CDI specialists, nurses, and physicians painstakingly reviewing patient charts to ensure documentation supported the care delivered. Today, AI is reshaping this landscape. While it’s still early days, we’re seeing three primary approaches to applying AI when it comes to CDI: 1️⃣ CDI ambient scribing—an AI ambient scribe and AI CDI assistant operate simultaneously, generating comprehensive notes and surfacing codes for physicians to review at the point of care. (Example: Ambience Healthcare’s AutoCDI) 2️⃣ CDI via real-time diagnosis support—diagnoses are suggested at the point of care based on clinical data in the EHR, with auto-generated documentation and audit trails. (Example: Regard) 3️⃣ CDI via an AI-driven post-coding / pre-billing review—the entire patient record is ingested and analyzed against what is coded, surfacing suggestions for revenue and quality opportunities. (Example: SmarterDx) To date, AI in healthcare has focused primarily on administrative use cases. With the increasing adoption of AI CDI solutions, we’re now taking a step closer to clinical workflows. As clinicians get used to AI-suggested diagnoses in the CDI context, it will be interesting to see if this increases their comfort with AI playing a role in clinical care. Here's our working list of AI CDI vendors. Anyone else we should add? • Ambience Healthcare • Brellium • Iodine Software • Regard • Semantic Health • SmarterDx   

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