Hospital leaders are navigating one of the most transformative periods in modern healthcare as organizations invest heavily in artificial intelligence, predictive analytics, and digital infrastructure. Yet one of the deadliest and most expensive forms of preventable harm inside hospitals receives far less strategic attention than it deserves: hospital-acquired pressure injuries.
Pressure injuries contribute to an estimated 60,000 deaths annually in the United States, according to the Agency
Read More
Compliance-First AI Engineering in Healthcare: Why Platforms Matter More Than Models
The healthcare industry spent an estimated $3.7 billion on artificial intelligence solutions in 2025, according to Statista. Executives cite clinical decision support, revenue cycle optimization, and administrative automation as their top priorities. Yet a striking pattern has emerged: roughly 75% of healthcare AI pilots never reach production, per Gartner's 2025 analysis of digital health deployments.
The conventional explanation blames model accuracy, data
Read More
How to Scale a Private Medical or Dental Practice from One to 100 Locations
For many private practitioners, getting one brick-and-mortar medical or dental office up and running is hard enough. The thought of going from zero to one location — let alone scaling your practice from one to 100 — is hard to fathom. Yet the path from one to 100 isn’t as arduous as it might seem.
Well-run practices that have the personnel and ability to scale might not do so simply because they lack important knowledge — and leave millions of dollars on the table as a result. The
Read More
From Governance to Enablement: How Healthcare CIOs Can Stop Killing AI Innovation
AI governance in healthcare has a branding problem. The word "governance" alone is enough to make half the room shut down. I've seen it happen. You put that word on a meeting invite, and suddenly everyone assumes this is the conversation where someone tells them what they can't do. That framing kills innovation before it starts.
I spent nearly a decade leading data and analytics teams at the largest healthcare system in Indiana, and we eventually stopped calling it governance altogether. We
Read More
The Casino Model: Why Medtech VCs Are Betting Billions on Unproven AI
Last week I ended up at a fancy venue hired by a hopeful medtech company trying to impress potential investors with delicious food and an emotional story about their life-saving device. Pitching has become performance art. Founders deliver sharp decks, polished demos, bold promises of “AI-powered transformation,” impressive market sizes, and superior outcomes. What all these startups usually have in common is a near-fanatical belief in the importance, capabilities, and value of their product -
Read More
The Womenʼs Health Blackout: How Defunding Gender Research Puts Patients at Risk Across Every Life Stage
Women experience mental health disorders at significantly higher rates than men. In primary care settings, 43% of women have at least one mental disorder compared to 33% of men, with particularly elevated rates of mood and anxiety disorders. Despite this higher prevalence, only 7% of healthcare research focuses on conditions that exclusively affect women.
This research gap leaves clinicians without clear guidance when treating women's mental health across different life stages. How does
Read More
Preparing Healthcare Data for AI: Why Health Systems Must Fix Legacy Systems
Artificial intelligence (AI) promises to transform healthcare operations and decision-making. Healthcare alone now captures nearly half of all vertical AI spend – approximately $1.5 billion in 2025, more than tripling from $450 million the year prior and exceeding the next four verticals combined. Yet many organizations discover that their AI initiatives stall before they deliver value. The problem often isn’t the AI models themselves, but rather the data behind them.
For
Read More
Why Hospital Dashboards Tell the Future But Operations Remain Stuck in the Past
Over the past decade, health systems have poured sustained capital and attention into data infrastructure. Enterprise warehouses consolidated fragmented reporting environments. Interoperability initiatives linked EHR instances that had operated in parallel for years.
Population health platforms brought predictive modeling into conversations about utilization and risk. Dashboards became ubiquitous, appearing in service line reviews, access meetings, finance updates, and clinical
Read More
The Clinical Resolution Gap: Why AI Can’t Fix Broken MSK Care Platforms
For years, clinicians have complained about the same thing: they became doctors to care for patients, not to stare at screens.
The electronic health record inserted a keyboard into the most important relationship in medicine. Now, for the first time in decades, artificial intelligence (AI) is beginning to remove it. Ambient listening technology is giving providers back the focused attention that documentation demands have quietly eroded. That is not a minor workflow improvement. It is a
Read More
Finding the Right Five Percent: How Machine Learning Is Reshaping Care Management
Population Health Has a Precision Problem
Population health programs continue to rely on blunt tools. Many risk stratification approaches emphasize historical utilization—basic risk scores or vendor-generated models that explain who was expensive—rather than identifying emerging clinical risk. These methods struggle to detect deterioration early enough to influence outcomes.
At the same time, care management teams face persistent resource constraints. Organizations cannot provide intensive
Read More
