Simply Curious

I was catching up on healthcare news from the past week when I stumbled upon this: https://www.fiercehealthcare.com/finance/healthleap-banks-38m-funding-backed-sequoia-capital-first-round-capital-and-hummingbird - it brings attention to a practical application of healthcare AI: identifying patients whose clinical needs might otherwise be missed. It got me thinking about a broader question around healthcare AI implementations: once an AI model identifies a patient who needs attention, what does the organization do differently, and how will it know whether that change helped? When we evaluate a model, we usually examine how well it predicts. During implementation, we may also track adoption, usage, and the number of alerts generated. These measures tell us whether the technology performs and whether people use it. Establishing patient benefit requires following the prediction further. Following a prediction through care Let’s consider a hypothetical hospital implementing a model to iden...

Healthcare leaders should agree on the population and measurement rules before tying digital health payments to outcomes. A result among patients who complete a program is not the same as the result across everyone the program was intended to serve. PHTI’s purchasing survey reports that 68% of employers and 55% of health plans surveyed use performance-based contracts. It also finds that 47% of purchasers say fewer than a quarter of their eligible members enroll in digital health solutions. It is important to make the population definition part of the evidence discussion from the beginning. For a payer, that definition affects whether an intervention can improve results across its membership. For a provider, it helps clarify which patients receive actionable support and which remain outside the workflow. Start with the population A buyer should be able to follow patients from eligibility through enrollment, continued participation, and outcome measurement. At each stage, the report sho...

For a long time now, healthcare has been trying to meet patients where they are, instead of forcing them to avail of the care they need at a facility such as a hospital or a clinic. Retail giants and pharmacies have repeatedly tried in-store clinics, only to retreat. Walmart opened its first Walmart Health centers in 2019 and planned 4,000 clinics by 2029, but by 2024 closed all 51 clinics and shuttered its virtual health unit, blaming rising costs and low reimbursements. Walgreens poured billions into its VillageMD primary care chain, but after patient volumes lagged it announced it would close 160 VillageMD locations in 2024. CVS, which operates over 1,100 MinuteClinics, quietly cut dozens of its retail clinics (in California and New England) around the same time. Best Buy Health launched remote-monitoring services (acquiring Current Health in 2021) but then sold Current Health in 2025 and took a $109 million charge on its health division amid restructuring. These instances make it c...

The healthcare industry has long grappled with a paradoxical reality: while pioneering medical advancements on one front, it often lags significantly in administrative efficiency. Mountains of paperwork, complex billing procedures, convoluted prior authorizations, and endless phone calls contribute to a staggering administrative burden that siphons time, resources, and morale from healthcare professionals. However, a silent revolution is now well underway, with artificial intelligence (AI) emerging as the vanguard in transforming healthcare's notoriously inefficient back office. Recent funding rounds and innovative product launches underscore a powerful shift: AI is moving beyond its traditional roles in diagnostics and drug discovery to become a critical tool for operational streamlining and administrative automation. For years, the promise of AI in healthcare often conjured images of intelligent systems assisting surgeons, predicting disease outbreaks, or accelerating pharmaceuti...

When Walmart announced the shuttering of all 51 of its ambitious Walmart Health centers in April 2024, citing a broken business model of high operating costs and poor reimbursements, the narrative was one of defeat. The retail behemoth, it seemed, had been humbled by the brutal economics of American healthcare. But a year later, it's becoming clear that this "failure" wasn't an ending, but a critical data point that fueled a much smarter, more formidable strategy. Walmart announced their recent partnership with the tech startup Soda Health to launch the "Everyday Health Signals™" program. The initiative, which uses AI to analyze grocery shopping data and provide personalized nutrition insights to Medicare Advantage and Medicaid members, is a stark departure from the capital-intensive, low-margin business of running physical clinics. It represents a shift from competing in the crowded, bloody "red ocean" of direct healthcare delivery to creating a...

For the better part of a century, the hospital has been the undisputed center of the American healthcare universe. It is the fortress of high-acuity care, the primary engine of revenue for health systems, and the physical manifestation of a community's health infrastructure. That era is rapidly coming to a close. A fundamental, tectonic shift is underway, and large health systems are leading the charge. They are systematically selling off their traditional inpatient hospitals, not in a fire sale of distress, but as a calculated, strategic pivot towards a new, more lucrative frontier: the outpatient market. This trend is not merely about cost-cutting; it's a fundamental re-architecting of the modern health system's business model. We are witnessing a great migration of capital, talent, and strategic focus away from the resource-intensive, low-margin business of inpatient care and into the dynamic, data-rich, and financially attractive world of ambulatory services. The driver...