Key takeaways from the Digital Health Most Wired National Trends Report

At a glance

The 2026 Digital Health Most Wired survey scored 235 organizations on ten segments of digital maturity and named 14 of them Level 10. Full adoption of generative AI rose from 31 percent to 54.8 percent in a year, while 16.4 percent of AI users have a plan for monitoring a model after deployment. Organizations scoring 9 or 10 stand apart in how they manage technology, with 96 percent using a standard framework to define what an investment must deliver before they buy it.

The 2026 Digital Health Most Wired benchmark scored health systems on ten dimensions of digital maturity and named 14 of them Level 10, its highest designation.

The National Trends Report summarizes the annual survey run by the College of Healthcare Information Management Executives (CHIME) and Digital Health Analytics. Organizations answer for up to three care settings, acute, ambulatory and long-term and post-acute, and each setting is scored against its own peer group. Every submission receives scores on ten segments and an overall Level of Achievement from 1 to 10.

The 2026 survey covered 235 organizations in 46 states and five countries, together representing more than 45,000 facilities. Health systems running hospitals, clinics and nursing facilities were able to count each one separately, so those 235 organizations produced 476 total scored submissions.

The report organizes its findings around ten trends:

AI adoption outruns AI oversight

Generative AI went from 31 percent to 54.8 percent full adoption in a single year, while fewer than half of AI users have a fully documented way of evaluating a model before deployment. Only 16.4 percent have a plan for monitoring a model afterward. Organizations that score 9 or 10 sit at the top of the report’s scale, and half of them regularly test whether their AI models perform worse for some patient groups than others. Among organizations scoring below an 8, only one in ten run that same testing.

Top scorers set expectations before they buy

The top-tier organizations define what a technology investment must deliver before they buy it, and 96 percent use a standard framework to do so, against 41 percent of those scoring below 8. Across all participants, half of analytics programs measure their own return, and 38.7 percent evaluate innovation with a formal framework.

Most organizations drill for phishing, few for failover

Fewer than 40 percent of organizations report that clinical, administrative, network and employee communication systems can all be restored within four hours of losing the primary data center, and those with tested failover are about twice as likely to meet that bar. Phishing simulations run at least semi-annually at more than 95 percent of organizations, full-scale failover exercises at just 23.6 percent.

Two in five data elements are not ready for AI

Two-thirds of organizations maintain a data catalog and 60 percent run automated checks on data quality, but only 38.7 percent keep a single authoritative record for patient, provider and location. By respondents’ own estimate, roughly two in five of their data elements are not yet labeled, standardized and ready for AI to use.

Few organizations train their workforce to question what AI tells them

Only 15.7 percent have a comprehensive, role-based data literacy program, and 76.2 percent name end-user data literacy as a barrier to adopting analytics. Ambient listening is fully adopted for physicians at 60.8 percent of organizations and for nurses at below 10 percent.

Hospitals know who is at risk but act on it late

Most organizations can spot their high-risk patients, with 77.4 percent maintaining registries and 68.1 percent stratifying by risk. Predictive analytics that flag a patient before an admission are another matter, fully adopted by 69.5 percent of organizations scoring 9 or 10 and 24.3 percent of the rest.

National exchange is mainstream, but usable exchange is not

Four in five US organizations have joined a TEFCA Qualified Health Information Network, yet 56.8 percent have full two-way, real-time exchange with community providers, and 81.5 percent say those partners cannot connect. Prior authorization is automated at 49.4 percent, dropping to 28.9 percent among the smallest organizations, ahead of a January 2027 CMS deadline for payer APIs.

Hospitals can see capacity in real time but rarely forecast it

Integrated patient logistics systems are fully adopted at 64.1 percent of organizations and intelligent bed management at 54.3 percent, but predictive bed demand forecasting reaches 33 percent and AI-driven patient flow 14.8 percent. About 62 percent of hospitals run or pilot a command center, which the report sees as the natural place to connect forecasting with capacity and alarms.

Patient portals are open everywhere, but patient input rarely reaches care teams

Appointment reminders reach 97 percent of organizations and secure messaging and video visits 92.3 percent each, whereas two-way tools lag. Shared care planning is fully adopted at 56.2 percent, patient-reported outcomes at 50.6 percent and shared decision-making tools at 22.4 percent, and fewer than half monitor digital literacy by population segment.

Medication safety software is connected, devices are not

Closed-loop medication administration is in place at 65 percent of organizations, but only 41.1 percent have IV smart pumps that exchange data with the EHR in both directions, and just 26.3 percent have cardiac monitors that do the same. Where device data is still typed in, nurses carry the transcription burden and early-warning models lose data.

Pete Pappas is a journalist and writer with 15 years of experience, currently covering the intersection of healthcare IT and artificial intelligence. He has written on topics including AI adoption in health systems, ambient clinical documentation, and the practical realities of bringing emerging technology into care delivery. He can be reached at [email protected]