By Scott E. Rupp, editor, Electronic Health Reporter.
In 2025, AI in healthcare is no longer a distant ambition—it’s an operational force. But as we stare down the next five years, what matters isn’t what AI could do. It’s what it will do, based on current trajectory, real-world deployment, and policy infrastructure.
Let’s cut past the marketing fluff. Below is a grounded look at how AI is reshaping healthcare now—and how it will evolve by 2030—through the lens of diagnostics, documentation, monitoring, drug development, operations, and governance. This isn’t speculation. It’s what the tech, the economics, and the outcomes are already showing us.
AI in Diagnostics: From Hype to Clinical Utility
Recent developments in diagnostic AI underscore a leap beyond narrow models. Microsoft’s Multimodal AI Diagnostic Orchestrator (MAI-DxO), for example, has shown 85.5% accuracy in diagnosing complex conditions—significantly outperforming unaided physicians in a controlled study. It isn’t replacing clinicians, but rather augmenting them by synthesizing imaging, lab values, and clinical notes into actionable differentials.
What’s next? Between now and 2030, expect diagnostic support tools to become embedded into EHR workflows. AI won’t just suggest differential diagnoses—it will flag overlooked symptoms, propose appropriate next steps, and track care adherence. Clinicians who adopt this technology will find themselves practicing “assisted medicine,” with reduced cognitive load and more consistent care across patient populations.
Clinical Documentation: The Administrative Front Line
Physician burnout continues to correlate with time spent in EHRs—often charting late into the night. AI scribes and ambient listening tools like Suki, Abridge, and Nuance DAX are making measurable inroads. One recent study found documentation time dropped by over 60% after implementing voice AI, with corresponding improvements in patient satisfaction and physician experience.
This is one of the lowest-risk, highest-yield applications of AI in healthcare, and adoption is accelerating. By 2027, we should expect clinical documentation to be mostly machine-generated and human-edited in ambulatory care and some inpatient settings. Expect significant expansion into coding, utilization review, and real-time note summarization. In revenue cycle management, this will radically improve claims accuracy and reduce denials.
AI in Remote Monitoring: Early Intervention, Not Just Passive Data
The convergence of wearables, ambient sensors, and AI analytics is quietly becoming one of the most effective tools for managing chronic conditions. What’s changing now is contextualization: AI doesn’t just measure—it interprets and flags risk. Systems are already showing promise in detecting atrial fibrillation, early-onset heart failure, and even cognitive decline through pattern recognition in voice and movement.
Expect AI to play a growing role in longitudinal care between visits. More than 35% of U.S. health systems are expected to integrate AI-driven monitoring solutions by 2026. Hospital-at-home models will increasingly rely on these tools to support early discharge, flag adverse trends, and prevent readmissions—helping address the financial strain from value-based care models.
AI in Drug Discovery and Trial Design: Time-to-Therapy Will Shrink
AI is accelerating drug discovery by optimizing target identification, simulating molecular interactions, and streamlining trial recruitment. Insilico Medicine, Recursion, and Exscientia are examples of companies slashing preclinical timelines by up to 50% using AI.
By 2030, expect AI to redesign how clinical trials are run—from adaptive designs that learn during execution, to digital twins that simulate patient responses to reduce trial size. Large language models will also aid protocol writing, patient matching, and compliance documentation. The result? Fewer failed trials, faster paths to market, and dramatically lower costs.
Back-Office Automation: The Real Cost Frontier
Administrative complexity remains one of the largest sources of waste in the U.S. healthcare system. AI is already reducing this burden through automations in prior authorizations, denial management, supply chain logistics, and call center operations.
By 2030, back-office automation powered by AI will be table stakes. Health systems will deploy intelligent agents for high-volume tasks like eligibility checks, appointment reminders, claims scrubbing, and patient financial counseling. This will reshape the workforce, reallocating humans to oversight and exception handling, rather than repetitive processing.
Estimates from McKinsey and others suggest that automation could drive over $150 billion in annual savings across the U.S. healthcare system, without touching a single clinical procedure.
Regulatory Momentum and Ethical Infrastructure
As of mid-2025, over 340 AI-enabled tools are FDA-cleared, mostly in radiology and cardiology. The regulatory environment is slowly catching up to the pace of innovation, with a push toward lifecycle oversight, real-world performance data, and post-market surveillance.
The next challenge is equity and transparency. Recent studies highlight significant performance discrepancies across demographic groups. To avoid algorithmic bias becoming clinical harm, AI developers and health systems must prioritize diverse training data, model interpretability, and explainable outputs.
We’re also likely to see a move toward mandatory algorithm audits and AI “nutrition labels”—initiatives that clarify how models were trained, tested, and validated for real-world use.
What Health IT Professionals Should Do Now
As stewards of digital infrastructure, health IT leaders are at the center of this transformation. But the task isn’t just implementation; it’s orchestration. Here’s where to focus:
Pilot with a purpose: Start small, measure well. Focus on low-risk, high-reward areas like documentation or revenue cycle automation.
Govern with clarity: Stand up AI review boards and build governance frameworks now—before use cases scale.
Invest in interoperability: AI is only as good as the data it receives. Ensuring clean, accessible, and standardized data remains the most strategic move any IT team can make.
Push for explainability: If a vendor can’t explain how their AI reaches conclusions, don’t implement it. Full stop.
Final Thought: Beyond the Buzzwords
AI in healthcare is real, impactful, and increasingly essential. But this isn’t about science fiction. It’s about systems — designed, tested, and governed by people — serving other people.
By 2030, the systems that win will be those that operationalize AI in ways that are trusted, useful, and invisible to the patient. We don’t need to marvel at AI. We need to make it mundane, baked into the background, improving care every day, without fanfare.
By Scott E. Rupp, publisher, Electronic Health Reporter.
Prior authorizations are hurting practices, the American Medical Association contends. According to the organization, prior authorization requirements have increased in the past five years, and 85 percent of physicians say the practice interferes with continuity of care. This is according to a new survey from the organization.
Prior authorization (PA) is a process requiring healthcare providers (physicians, pharmacists, medical groups and hospitals) to obtain advance approval from health plans before a prescription medication or medical service is delivered to the patient. While health plans and benefit managers say that PA programs are important to controlling costs, providers often find these programs to be burdensome and barriers to the delivery of necessary patient care.
The AMA’s report was conducted in partnership with the American Hospital Association, America’s Health Insurance Plans, American Pharmacists Association, Blue Cross Blue Shield Association and Medical Group Management Association, releasing the “Consensus Statement on Improving the Prior Authorization Process.” The statement “reflects agreement between healthcare providers and health plans on key reforms needed to reduce PA hassles and enhance patient-centered care.”
According to the 1,000 physicians interviewed, more than two-thirds of these fine folks said it’s difficult for them to determine whether a prescription or service needs prior authorization.
Alternatively, fewer than 10 percent of the physicians said they contract with a health plan that allows programs that can exempt providers from the requirement. Additionally, prior authorizations are primarily obtained by phone or fax, with just a bit more than 20 percent of physicians saying they are able to complete the requests through their electronic health records — which can be most efficient when that capability is allowed.
In a statement released with the survey findings, AMA charged insurance companies with a “year of foot-dragging and opposition” to prior authorization reforms.
According to the study, the AMA is encouraging the use of programs that selectively implement PA requirements based on stratification of healthcare providers’ performance and adherence to evidence-based medicine, but the results from the study show that only 8 percent of physicians report contracting with health plans that offer programs that exempt providers from PA. Likewise, the AMA wants an overall revision of PA requirements, including the list of services subject to PA, based on data analytics and up-to-date clinical criteria. A majority (88 percent) of physicians report that the number of PAs required for prescription medications and medical services has actually increased over the last five years.
From the payer’s point of view, prior authorizations serve as a cost control that limits unnecessary care, and the practice has supporters in high places. For example, a Government Accountability Office report released in 2017 found that prior authorization in Medicare saved as much as $1.9 billion through March 2017. The Trump administration’s proposed budget also includes expanded prior authorization measures for Medicare. The fight over them doesn’t appear head for anything but an ugly stalemate.
By Scott E. Rupp, publisher, Electronic Health Reporter.
The healthcare technology world is ablaze, on FHIR. New proposed standards for interoperability are being established to allow health systems the ability to share information and facilitate patient access to data. Specifically, in large part through a structure known as FHIR.
This “FHIR” the market is speaking of is Fast Healthcare Interoperability Resources, an interoperability standard for electronic exchange of healthcare information. FHIR was developed by Health Level Seven International (HL7), a not-for-profit that develops and provides frameworks and standards for the sharing, integration and retrieval of clinical health data and other electronic health information.
FHIR emerged in 2014 as a draft standard for trial use to enable health IT developers to more quickly and easily build applications for EHRs and to exchange and retrieve data faster from applications. FHIR soon received support from EHR vendors like Epic, Cerner and AthenaHealth. Shortly thereafter, the Argonaut Project emerged to move FHIR forward, and in February 2017, FHIR became a full data exchange standard.
FHIR is interoperability
FHIR is built on the concept of interoperability and modular components that can be assembled into working systems to try to resolve clinical, administrative and infrastructural problems in healthcare.
FHIR provides software development resources and tools for administrative concepts, such as patients, providers, organizations and devices, as well as a variety of clinical concepts including problems, medications, diagnostics, care plans and financial issues, among others. FHIR is designed specifically for the web and provides resources and foundations based on XML, JSON, HTTP, Atom and OAuth structures.
FHIR can be used in mobile phone applications, cloud communications, EHR-based data sharing and among institutional healthcare providers.
According to HL7, FHIR aims to simplify implementation without sacrificing information integrity. FHIR “leverages existing logical and theoretical models to provide a consistent, easy to implement and rigorous mechanism for exchanging data between healthcare applications. FHIR has built-in mechanisms for traceability to the HL7 RIM and other important content models. This ensures alignment to HL7’s previously defined patterns and best practices without requiring the implementer to have intimate knowledge of the RIM or any HL7 v3 derivations.”
Health sector buy-in
The healthcare sector has clearly bought into FHIR, primarily because of interoperability challenges.
“Sharing data between different health systems has required significant investment of IT resources on one-off projects,” said Nilesh Chandra, healthcare expert at PA Consulting. “As the needs for data sharing have increased, hospital IT departments have been swamped with demand for all of this custom integration.
“FHIR and similar standards are an attempt at standardizing data integration, to make it easier to connect EHR systems and easily extract or upload data into them, based on reusable IT components,” added Chandra. “That said, FHIR is an important step in the right direction, but is not the panacea for all health IT integration issues.”
FHIR uses a set of commonly used medical ideas termed as “resources.” The resources are used across many different types of companies and organizations, but can all mean the same thing. An example would be blood pressure readings, or an MRI scan. Those resources are held in EHRs, smartphones, health information exchange databases and so on. FHIR also allows for the mining of those elements since they are tagged in a similar way in the FHIR standard.
“The complex part is done by individual systems that don’t have the same operating system,” said Jason Reed, PharmD blog founder. “Because they can pull that tag then they pull it and exchange it with other entities. They only show the tag and not the other code or structures they had to use to get to that tag.”
While consolidated clinical document architecture allows a group of healthcare items to be sent together, this is essentially like sending an electronic PDF, Reed said. Other systems that have different operating systems can’t break that down unless they use the same operating system.
FHIR’s culmination
All of this is a culmination of the fact that digital health data can improve outcomes and lower costs, but the reality has been something less than ideal. For example, during the economic stimulus in 2009, systems were designed before modern web standards for storing and exchanging data were ubiquitous. The industry was caught in the middle of a technical revolution and spent its cash before the best new practices were available, said Nick Hatt, senior developer at Redox.
By Scott E. Rupp, publisher, Electronic Health Reporter.
On March 21 HIMSS representatives vice president of government affairs, Tom Leary, and senior director of federal and state affairs, Jeff Coughlin, hosted a roundtable with members of the media to peel back a few layers of the onion of the newly proposed ONC and HHS rules to explain some of the potential ramifications of the regulations should they be approved.
The CMS proposed regulation is attempting to advance interoperability from the patient perspective, by putting patients at the center of their health care and confirming that they can access their health information electronically without special effort.
ONC’s proposed regulation calls on the healthcare community to adopt standardized application programming interfaces (APIs) and presents seven reasonable and necessary conditions that do not constitute information blocking.
According to HIMSS’s assessment of both proposals there’s room for interpretation of each, but the organization has not yet fully formed a complete response to each as of this writing.
Tom Leary
However, Leary said: “It’s important to emphasize that all sectors of the healthcare ecosystem are included here. The CMS rule focuses on payer world. The ONC rule touches on vendors and providers. All sectors really are touched on by these rules.”
With both, ONC and CMS is trying to use every lever available to it to push interoperability forward and is placing patients at center, Coughlin said. The healthcare sector got a taste of how CMS plans to empower patients through its recent MyHealthEData initiative, but the current proposal places more specifics around the intention of agency. Likewise, the ONC rule is attempting to define the value of the taxpayer’s investment in regard to the EHR incentives invested in the recent meaningful use program.
Key points of the rules
Some key points to consider from the rules: APIs have a role to play in future development of the sector and are seen as a real leveler of the playing field while providing patients more control of their information, Coughlin said.
HHS is focusing on transparency and pricing transparency. For example, there’s movement toward a possibly collecting charge master data from hospitals and, perhaps, publishing negotiated rates between hospitals and payers, which HHS is looking into.
Jeff Coughlin
What happens now that rules are out? According to HIMSS, education members is the first step to understanding it and responding to the federal bodies. “What we’ve done is focus on educating HIMSS members in briefings,” Coughlin said. “Trying to get early feedback and early impressions from members, convening weekly conference calls to address parts of the rule. Once we have critical mass then we work with executive leadership to make sure what we are hearing from membership to is reflected across the membership.”
Looking into the future?
For health systems, the broad exchange of data likely remains a concern. Data exchange within the ONC rule impacts providers and health systems in a number of ways, especially in regard to the costs of compliance to meet all of the proposed requirements.
HIMSS representatives are not currently casting a look into a crystal ball or if they are (they are), they’re not yet ready to tip their hand regarding what the organization intends to pursue through its messaging on behalf of its members.
“We’re not in a place to see where we are going to land,” Coughlin said. “We are hearing from our members about the complexities of rules and what’s included. It’s hard to overestimate how complex this is. ONC and CMS in designing broader exchange of information is something that speaks very well of them, but (this is) complex in interpretation and implementation.”
Information blocking exceptions, the default is broader sharing of information across the spectrum. More information has to be shared and expectations need to be defined, they said. From HIMSS’ perspective, compliance is the primary issue of its members. The question that needs answering is what kind of burden is being placed on health systems and providers. Leary is confident HIMSS will spend a good bit of ink in its response on citing potential concerns over information blocking and what that might mean.
“It will be helpful for the community to have examples and use cases for what’s included especially for exceptions for information blocking,” Coughlin said. “We need examples to clearly define the difference between health information exchange and health information network.”
Prior authorizations are hurting practices, the American Medical Association contends. According to the organization, prior authorization requirements have increased in the past five years, and 85 percent of physicians say the practice interferes with continuity of care. This is according to 
The healthcare technology world is ablaze, on FHIR. New proposed standards for interoperability are being established to allow health systems the ability to share information and facilitate patient access to data. Specifically, in large part through a structure known as FHIR.
On March 21 HIMSS representatives vice president of government affairs, Tom Leary, and senior director of federal and state affairs, Jeff Coughlin, hosted a roundtable with members of the media to peel back a few layers of the onion of the newly proposed ONC and HHS rules to explain some of the potential ramifications of the regulations should they be approved.
