Hospital CIOs today face enormous and seemingly contradictory pressures.
Hospital CIOs say they face ever-growing demands for IT services despite tight operating budgets, constrained staff resources, and aging technology infrastructure.
What’s a beleaguered hospital CIO to do?
A need for flexibility
There’s a lot on the CIO’s plate: finding ways to optimize the use of the EHR, improving systems interoperability to sharpen data analysis and reporting, strengthening
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Redesigning Pharma Adherence Around Patient Behavioral Signals and AI-Native MCP Rails
AI’s biggest contribution to adherence can be a new model: reading the signals patients leave before they stop, and responding with support built for that moment, but only if pharma decides who it wants to be to that patient.
In 2003, the World Health Organization reported that adherence to long-term therapy in developed countries averages about 50%. Since then, the industry has taken on that number in waves: first as a compliance problem, then as a cost problem, then as an infrastructure
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How Real-World Data (RWD) Is the Turning Point for Pharma Innovation
The pharma industry is accustomed to operating in a highly regulated and risk-conscious environment. While companies continue to invest in scientific innovation, they have been slower to adopt technology.
Long cycle times and uncertainty around new platforms have made organizations hesitant to disrupt entrenched workflows. That hesitation has led to many leaders falling into a “watch and wait mentality,” missed opportunities to lower costs, shorten timelines and deliver new treatments
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Do Patients Need to Understand AI Before They Can Trust It?
AI is being rapidly integrated into healthcare, and its role is expanding quickly. Yet, despite this rapid adoption, AI trust among patients remains critically low. That is a problem because trust is fundamental to healthcare. Patients who trust their healthcare providers are more likely to share information, follow recommendations, and actively engage with their care. In my current professional role, I spend a considerable amount of time thinking about the reasons why patients should trust
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Consumer AI Is Healthcare’s New Front Door. Who’s Deciding What Happens There?
One in four U.S. adults, more than 66 million people, have now used AI tools or chatbots for health information or advice according to a West Health–Gallup survey released in April. Most aren't using it in place of care. They're using it around care: 59% of recent users researched their medical question with AI before seeing a doctor, and 56% did so afterward.
I see this in practice. A patient arrives with a cough, fever and body aches, and a chatbot has already suggested pneumonia. It might
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Why the AMA’s AI Liability Policy Shifts Risk to Health System Data Access Logs
The AMA says physician oversight can’t substitute for adequate evidence and system design. That puts the burden on whoever holds the usage records.
In many hospitals, an AI tool is reading patient records through a shared service account that no one can tie to a person. That gap matters more now. The American Medical Association's new framework, released October 29, 2026, divides responsibility among developers, physicians, and the health systems that deploy AI tools. Of the three parties,
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Advancing Clinical Trials Through Digital Health Technology
Decentralized and hybrid trials continue to grow in popularity, making it essential for contract research organizations (CROs) to seamlessly integrate remote wearable technologies into trial operations. Traditional, site-based trials often miss meaningful changes between participant visits, so remote wearable devices are appealing because they improve study quality through continuous, real-world data collection. One study showed that a 14-day adhesive ECG patch detected arrhythmias in 59.5% of
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Why Regulatory Flexibility Demands Decision-Ready Clinical Evidence
Regulatory guidance plays a critical role in clinical trial development, but it cannot anticipate every question that may emerge during the development of a program. When guidance is absent, outdated or inconsistent across authorities, sponsors have legitimate room to exercise judgment. However, that flexibility should be approached as conditional rather than permissive. Flexibility in a program’s design does not change the level of scrutiny that regulators will apply to the evidence sponsors
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Mental Health Tech M&A Needs a Consent Continuity Standard
Mental health technology deals are increasingly sold on continuity. A larger platform can offer more providers, more forms of care, and fewer disruptions when a patient changes jobs, insurance, or treatment needs. That promise is compelling. It also creates a data governance problem that is easy to miss during integration.
When two platforms combine, the transaction may bring together therapy records, assessment responses, care navigation history, claims, wearable streams, voice data,
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Medicare Fraud Has an AI Problem. So Does Healthcare Compliance
For years, healthcare organizations have approached Medicare fraud and billing compliance as primarily a retrospective exercise. Claims are submitted, payments are made, audits follow, and organizations investigate problems after they surface.
That model is becoming increasingly unsustainable.
The federal government is moving toward a more aggressive approach to Medicare program integrity, using data analytics, artificial intelligence (AI), and machine learning to spot suspicious billing
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