Bill Siwicki
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Articles by Bill Siwicki
Value-based care technology ambitions outpace confidence in funding
Healthcare organizations are moving quickly to embrace technology-enabled care, but confidence in how to pay for it is lagging. A joint survey by the National Association of ACOs and healthcare technology company Innovaccer found that 73% of respondents say the Centers for Medicare & Medicaid Services' ACCESS Model has influenced their technology strategies. But only 30% consider the model's co-management payments a meaningful funding source, while 59% say it is too early to tell.
What it will take for AI to deliver better clinical decisions
Electronic health records have transformed how healthcare organizations capture and store patient information. But making sense of that mountain of data remains a challenge for clinicians. AI could help turn EHR data into something more valuable: better-informed decisions at the point of care.
HIMSSCast: Training nurses to speak care out loud
Using generative artificial intelligence in frontline care requires a hands-on, collaborative shift in training that is worth making, say Advocate Health's nursing informatics leaders. Artificial intelligence is uncovering the hidden work of nursing, according to Advocate Health's Katie Barr, senior vice president and chief nursing informatics officer, and Tracy Breece, vice president, nursing informatics AI and emerging technologies.
Effective clinical AI adoption starts before go-live
This is Part 2 of a two-part feature. Click here to read Part 1. CIOs and other health IT leaders at hospitals and health systems can make technology available. Voila. But earning voluntary use among staff is a whole other proposition. For physicians, in particular, skepticism of new technology is a rational response to years of systems that promised efficiency while adding clicks, alerts and more work. "Physician resistance is not primarily a technology problem," said Dr. R.
Physicians say AI works best when it disappears
This is Part 1 of a two-part feature. Part 2 will be published tomorrow. Many physicians have reached the conclusion that, in healthcare, artificial intelligence must do its best to become The Invisible Man. Yes, AI offers impressive capabilities that often shine in the spotlight. But for many clinicians, there is a less glamorous requirement that the tools vanish into existing clinical work. Value disappears when a physician must leave the EHR, move data manually or manage another interface.
Consumer AI is becoming a digital front door. What should health systems do?
Artificial intelligence has brought about a shift in patient behavior. Patients increasingly seek instant health information from consumer AI like ChatGPT and Google Gemini when worried about symptoms, appointments or test results. There is immediate value to consumer AI. Take ChatGPT Health as an example. It is a dedicated feature inside OpenAI's ChatGPT platform designed to securely combine a user's personal medical records and wellness data with artificial intelligence.
Behavioral health AI moves from screening to continuous risk
There remains a structural divide between behavioral health and primary and specialty care. Mental health affects outcomes across conditions – but prescribing and basic screening can become a dead end when there is no coordinated path to treatment.
Beyond reimbursement: The business case for permanent virtual care
This is Part 2 of a two-part feature. To read Part 1, click here. The so-called telehealth cliff – where reimbursement for Medicare telehealth runs out unless Congress acts – is seemingly always just ahead. Congress in recent years has been content to simply pass temporary fixes, rather than effecting permanent change in policy. So hospitals and health systems stay stuck baking uncertainty into their virtual care plans.
Health systems still must plan, even as telehealth goalposts keep moving
This is Part 1 of a two-part feature. Part 2 will be published tomorrow. Building a long-term strategy on temporary rules is no one's idea of fun. But that's just the assignment that's been given to the health system executives charged with designing and scaling telemedicine programs. Virtual care is no longer experimental, yet major telemedicine rules remain temporary, even after years of ongoing uncertainty.
Nurses must take lead on governing the AI that's changing their workflows
This is Part 2 of a two-part feature. Click here to read Part 1. There must be a nonnegotiable principle in nursing care that AI-generated documentation is a draft – the licensed nurse remains accountable for a patient's medical record. "The starting point has to be clear: AI-generated documentation is a draft, not a decision," said Tracy Breece, RN, CENP, vice president, nursing informatics AI and emerging technology, at Advocate Health, a 69-hospital health system that serves eight states.
Measuring AI's value for nurses, beyond faster charting
This is Part 1 of a two-part feature. Part 2 will be published tomorrow. Is artificial intelligence documentation for nurses returning meaningful bedside time? Or simply relocating administrative work? That may be the central question when assessing whether AI is worth the investment for nurses.
How AI can improve patient access – beyond simply filling the next open slot
There is a paradox when it comes to patients accessing hospitals and health systems digitally: While the organizations have made many aspects of access easier online, patients still can struggle to identify the right specialty, clinician or level of care. "Health systems have made it easier to complete certain tasks online," said Andy Parham, CEO of Brado AI, vendor of a generative AI patient engagement platform.
Clinical AI forces a rethink of reimbursement
One of the biggest unanswered questions in healthcare AI is not whether the technology works, but how hospitals, physicians and health plans should pay for it. A new report from the Peterson Health Technology Institute argues that today's reimbursement models were designed for human-delivered care, not AI-enabled care, and that simply applying existing payment rules to clinical AI could unintentionally increase healthcare costs without improving outcomes.
An enterprise-wide approach to digital transformation may be the better way forward
Digital transformation is an increasingly urgent priority for hospitals and health systems as they seek to improve the patient and clinician experience, modernize operations, and make more effective use of evolving technologies But some are finding that a piecemeal approach to artificial intelligence or automation deployments isn't bringing the ROI they'd hoped for.
Build the AI audit trail now, before anyone asks for it
Editor's Note: This is Part 2 of a two-part feature. Click here to read Part 1. The uncertainty surrounding AI-generated healthcare data is not an argument for waiting to manage it. If anything, attorneys and governance experts say the lack of a settled regulatory framework makes it even more important for hospitals to establish their own defensible rules now. That task extends well beyond deciding whether an ambient note belongs in the chart.
What belongs in the medical record in the AI era?
[Editor's Note: This is Part 1 of a two-part feature. Part 2 will be published tomorrow.] Generative AI is rapidly changing how healthcare organizations create clinical documentation. Ambient scribes can turn conversations into draft notes. Decision-support tools can suggest diagnoses or treatments. Chatbots can generate patient messages. Behind those visible outputs, systems may also produce transcripts, prompts, confidence scores, alternate recommendations, coding suggestions and technical logs.
How KC Care built an IT-enabled workforce that could scale
Kansas City, Missouri-based KC Care Health Center has nearly tripled the number of patients it serves over five years, reaching 23,000 patients annually across primary care, behavioral health, dental and HIV services. But accommodating that growth required more than adding clinical capacity. The nonprofit needed its workforce operations to expand without allowing administrative work to rise at the same pace.
Ardent Health finds ambient AI's value goes beyond ROI
Ardent Health's enterprise deployment of ambient AI has passed a milestone that gives the multi-state health system a substantial body of experience to judge the technology: more than 1 million patient encounters supported since the rollout began last September. The results include an 87% utilization rate among clinicians using the technology, more than three hours a week saved on documentation and, for one Texas family medicine physician, a 53% reduction in documentation time.
Inside hospitals, virtual care takes on a new and bigger role
In Part 1 of this two part series, we explored how telemedicine is moving beyond the familiar model of connecting physicians and patients from afar and becoming part of care delivery inside hospitals. Health systems are using virtual nursing, tele-ICU, remote specialty care and other models to extend scarce clinical expertise and support clinicians at the bedside.
Telemedicine becomes more deeply embedded into hospital workflows
Editor's Note: This is Part 1 of a two-part feature. Part 2 will appear tomorrow. Telemedicine may still evoke the familiar image of a physician appearing on a patient's laptop or phone.
Rural hospitals face high stakes in allocating AI investments
Small and rural providers face a technology paradox: Artificial intelligence could help them stretch scarce staff, stabilize revenue and expand access to care. But many of the organizations that stand to benefit most from AI have the least money, infrastructure and technical expertise to invest in it adequately. That makes AI adoption an exercise in disciplined prioritization, says Julia Clark, managing director at research and consulting firm BRG.
How AI can give healthcare teams more time to care
Every hospital treating cancer patients faces a demanding data obligation: turning sprawling patient records into standardized registry information that can support reporting, benchmarking and research. But the specialized workforce that performs that work is small, while the volume and complexity of cancer data continue to grow. Brent Dover, CEO of Carta Healthcare, sees artificial intelligence as a way to close that capacity gap without removing credentialed cancer registrars from the process.
Telemedicine won't work without care coordination
Telemedicine has made it routine for clinicians and patients to connect by video. But for health systems, establishing that connection is no longer the hardest part of virtual care. The bigger challenge is making sure the right patient gets a virtual visit in the first place – and that everything that should happen afterward actually happens.
Why workflow accountability may define healthcare AI's next phase
Healthcare organizations spent the past two years experimenting with generative AI for summarizing notes, drafting messages and searching internal knowledge. The arrival of healthcare-specific platforms such as ChatGPT for Healthcare and Claude for Healthcare marks a different phase of adoption, according to Manu Agrawal, chief architect leading artificial intelligence and machine learning initiatives at Oracle Health.
How Oxford PT combined AI documentation and RCM to recover revenue
Oxford Physical Therapy knew its homegrown EHR and billing platform had served the organization well, but leaders concluded it would be difficult to keep pace as artificial intelligence became increasingly important for clinical documentation and revenue cycle management. That realization led the provider to adopt the Athelas platform across its 11 locations in February 2026.
Sentara's Epic EHR model targets MRSA infections early
Healthcare organizations have spent years refining infection prevention programs, but many interventions begin only after patients show signs of colonization or infection. Sentara Health believed technology could help clinicians intervene much earlier^. Working across clinical, operational and IT teams, the Virginia-based health system developed a predictive MRSA risk score embedded directly within its Epic EHR.
New healthcare AI council prioritizes governance beyond go-live
Healthcare organizations have been building governance processes to decide whether artificial intelligence tools are ready to be deployed. Waleed Mohsen argues that the more dangerous question begins after that decision: What happens when the AI starts interacting with real patients at scale? Mohsen, cofounder and CEO of Verbal AI Technologies, helped convene the new Council for Healthcare AI Responsibility and Safety, or CHAIRS.
From first 72 hours to first 90 days, tech extends hospital care beyond discharge
For decades, hospitals have largely treated discharge as the end of the acute care journey. Once patients left the building with a folder of instructions and follow-up recommendations, responsibility shifted largely to them and their families. But that approach is becoming increasingly difficult to sustain as hospitals assume greater accountability for patient outcomes long after patients leave inpatient care.
NCQA's first CMO aims to modernize quality measurement for the AI era
Quality measurement has influenced American healthcare for decades and has been essential to improving the care delivery process and boosting patient outcomes. But many clinicians still often experience it as an expanding list of reporting requirements, rather than a tool that improves care. "Quality measures land, ultimately, on clinicians," said Dr. Ari Robicsek.
Hospitals must prove they can make AI operational at scale
Artificial intelligence has produced no shortage of successful healthcare pilot projects. Yet many provider organizations still struggle to expand those early wins into enterprise-wide capabilities. A new survey suggests the question is no longer whether AI can deliver value.
How proactive tele-ICU models are reshaping critical care
Critically ill patients often need immediate access to specialized expertise, yet many hospitals – especially rural and community facilities – struggle to staff intensive care units with board-certified intensivists around the clock. As workforce shortages deepen and patient acuity rises, tele-critical care is evolving from a technology centered on remote monitoring into a collaborative clinical model designed to extend expert critical care wherever it is needed.
Bill Siwicki | Healthcare Finance News
October 22-23, 2026 | San Diego AI in Healthcare Forum San Diego The AI in Healthcare Forum brings clinicians, executives, technologists, researchers, and innovators for an immersive day focused on the real-world application of AI in health and care, with a deliberate emphasis on governance, policy, and responsible implementation.
Setting the stage for effective and efficient physical AI in healthcare
Part 1 of this feature story explored what physical AI is and why healthcare leaders increasingly believe it could become the next major evolution in artificial intelligence.
Is physical AI healthcare's next transformational technology?
For the past several years, hospitals and health systems have raced to deploy artificial intelligence in the forms of ambient documentation, clinical summarization, patient messaging, coding assistance and administrative automation. AI has helped, reducing paperwork and streamlining workflows. But its role has largely remained confined to the digital world.
AI alone cannot solve Rx translation
Health systems have embraced generative AI across clinical documentation, revenue cycle and patient communications. But one area demands far greater caution than many leaders appreciate: the prescription label patients rely on after they leave the pharmacy. According to Sharon Blank, CEO of RxTran and Language Scientific, the industry's biggest problem is no longer the translation technology itself.
AI ambitions outpace healthcare's infrastructure
Healthcare organizations are racing to adopt artificial intelligence, but many may be trying to accelerate before their technology foundations are ready. That is the central message from new research examining how provider organizations are approaching AI infrastructure, governance and deployment. Healthcare leaders see enormous potential in AI but continue to face significant technical and operational barriers, according to a new survey from enterprise cloud software company Nutanix.
Children's Nebraska IT leader says innovation must become a core competency
Healthcare organizations face no shortage of emerging technologies, from AI to virtual care and advanced analytics. The bigger challenge, says Jose Mathew, vice president of technology and innovation at Children's Nebraska, is creating organizations that can adopt these technologies quickly while maintaining reliability, security and trust.
How one kidney care company built a solid AI foundation
By the time many health systems begin experimenting with artificial intelligence, they quickly discover the technology itself is rarely the biggest obstacle. Disconnected data, limited interoperability and clinician workflows that are already overloaded often prevent promising AI projects from moving beyond pilots. Those were the problems Strive Health set out to solve as it expanded AI across its value-based kidney care organization.
How one kidney care company built a solid AI foundation
By the time many health systems begin experimenting with artificial intelligence, they quickly discover the technology itself is rarely the biggest obstacle. Disconnected data, limited interoperability and clinician workflows that are already overloaded often prevent promising AI projects from moving beyond pilots. Those were the problems Strive Health set out to solve as it expanded AI across its value-based kidney care organization.
Two visions for ambient AI and the future of the EHR
Ambient artificial intelligence entered healthcare as a way to listen to clinical encounters and draft notes. Its next act could be far more consequential: changing the electronic health record from the screen clinicians constantly navigate into the trusted infrastructure working beneath an AI-driven interface. That possibility is beginning to divide healthcare leaders. Seema Verma, general manager of Oracle Health, expects AI to become a primary way clinicians interact with healthcare technology.
Ascension's telehealth strategy: Building an enterprise, not a program
When many health systems rapidly deployed telemedicine during the COVID-19 pandemic, speed often took priority over long-term strategy. Virtual visits proliferated, but many organizations were left managing disconnected platforms, fragmented workflows and uncertain financial models once the public health emergency subsided. Ascension chose a different path.
AI misdiagnoses raise new liability questions for health systems
A Florida lawsuit alleging that artificial intelligence contributed to a patient's delayed cancer diagnosis is drawing fresh attention to a question many healthcare leaders have been asking as AI moves deeper into clinical practice: When technology becomes part of the diagnostic process, who ultimately bears responsibility when something goes wrong?
Why Johns Hopkins is benchmarking AI agents before deployment
Johns Hopkins Medicine is taking a deliberately cautious approach to agentic AI, focusing first on proving reliability and governance before expecting measurable financial returns. For Dr. T. Y. Alvin Liu, inaugural director of the Gills AI Innovation Center and a member of the Johns Hopkins Medicine AI Oversight Team, the first question was not which workflow to automate.
AORN maps a safer path for AI in the OR
As artificial intelligence moves deeper into operating rooms, hospitals cannot treat it as just another technology implementation. AI-enabled tools may help predict surgical risk, issue intraoperative alerts and analyze postoperative outcomes, but they also can introduce bias, drift over time and influence clinicians in ways that are difficult to detect. That is the challenge behind the Association of periOperative Registered Nurses' new Guideline for Integration of Artificial Intelligence.
Telemedicine's next phase demands an EHR ecosystem
For years, healthcare organizations treated telemedicine as an add-on to the electronic health record, connecting video platforms to core clinical systems just well enough to make virtual visits possible. That approach helped providers rapidly expand access during the COVID-19 pandemic, but it also created fragmented workflows, duplicate data paths and the perception that virtual care represented a separate mode of medicine.
DaVita puts connected data to work for kidney care
Healthcare organizations continue searching for ways to improve care while facing workforce shortages, rising patient complexity and relentless financial pressure. For kidney care providers, those challenges are particularly acute because patients often live with multiple chronic illnesses, take numerous medications and receive treatment from several specialists.
Quality leader's warning: 'Bad data at AI speed is still bad data'
Artificial intelligence promises to transform healthcare, but the technology's success will depend less on the sophistication of algorithms than on the quality of the information they consume. That's according to Troy Heninger, director of data governance and data quality at St. Luke's Boise Medical Center, who believes executives should spend just as much time strengthening data governance as evaluating AI vendors.
AI with human support reduces no-shows at Graybill
For healthcare organizations struggling with staffing shortages and rising administrative demands, the front office increasingly has become one of the biggest obstacles to timely patient access. Calls go unanswered. Patients abandon long hold queues. Appointment scheduling slows. Staff spend much of their day answering routine questions or processing repetitive requests instead of helping patients whose situations require judgment and empathy.
'Headless AI' aims to eliminate healthcare bottlenecks
Artificial intelligence already is appearing throughout healthcare, from documentation assistants to clinical decision support and patient messaging tools. But despite the growing number of AI applications, much of the industry's day-to-day work still depends on people manually moving information between electronic health records, payer portals, scheduling platforms and countless other systems.
New AI risks: 'Cognitive spoofing' and fake expertise
Artificial intelligence has quickly become one of healthcare's biggest strategic priorities, with hospitals and health systems investing heavily in clinical decision support, ambient documentation, revenue cycle automation and other AI-powered technologies. As organizations focus on accuracy, productivity and return on investment, Dr. David Kirk argues they also need to prepare for a subtler risk: clinicians and patients placing too much confidence in AI simply because it sounds authoritative.
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