Wednesday, February 4, 2026

< + > AI Enhances Outreach to Blood Donors

While collecting blood, Versiti collects data. Versiti is a nonprofit founded in 1947 with the two goals of providing a sustainable blood supply to clinical settings and advancing research. Over the past 20 years, the company has tripled in size and provides blood to more than 400 hospitals. The company is now using AI and partnering with Lenovo to improve donor outreach and research.

On the blood donation side, Versiti tries to treat donors as well as a good clinician treats their patients. CIO Lynne Briggs says “we know who you are when you come in the door.” Versiti integrates the data from all its partners. CEO Chris Miskel says they get more than 300,000 blood donors every year, so they are using AI to improve engagement and “be more donor-centric.”

One simple application is AI-drive chat, but Justin T. Collier, MD, Healthcare CTO in North America at Lenovo mentions also the use of AI to automate documentation and mundane tasks such as engaging with insurers. He says that the value of AI makes it worthwhile to collect more data and keep it “forever.” AI can lead to meaningful insights and better research outcomes.

Briggs also cites the use of AI to analyze their donor base so they can adjust their messaging to reach key demographics and to personalize their outreach. She also mentioned that AI is useful in security.

On the research side, Miskel illustrates the use of AI through a bioinformatics project they led to seek more precise diagnoses and better treatments. Briggs says that NIH now expects the use of AI to find cures.

Briggs mentioned the logistical difficulties of collecting blood in corporate lounges, churches, college dining halls, etc. The technology needs to be rugged but easy to set up, so that it can’t get in staff’s way. Each setup is an “almost military operation.”

At the end, Collier mentions a few of the hot topics in health IT: digital twins, virtual reality, and gaming to entertain patients.  Check out our interview with Versiti and Lenovo at the CES conference to learn more.

Learn more about Lenovo: https://techtoday.lenovo.com/us/en/solutions/healthcare

Learn more about Versiti: https://versiti.org/

Listen and subscribe to the Healthcare IT Today Interviews Podcast to hear all the latest insights from experts in healthcare IT.

And for an exclusive look at our top stories, subscribe to our newsletter and YouTube.

Tell us what you think. Contact us here or on Twitter at @hcitoday. And if you’re interested in advertising with us, check out our various advertising packages and request our Media Kit.



< + > HTI-5: Less Red Tape, More AI Flexibility for HTI-4’s Complex Requirements – Regulatory Talk Series

The following is a guest article by Nick Barger, PharmD, Vice President, Product at DrFirst.  This article is the next in the Healthcare Regulatory Talk series.

On December 22, the Assistant Secretary for Technology Policy/Office of the National Coordinator for Health Information Technology (ASTP/ONC) dropped the Health Data, Technology, and Interoperability (HTI-5) proposed rule.

And while the timing lived up to the ONC’s nickname as the “Office of No Christmas” (for its history of announcing regulatory changes toward the end of the year), the rule isn’t the “bah humbug” that EHR and health IT vendors have come to expect. Instead of adding compliance requirements, it takes some away.

With HTI-5, the ASTP/ONC seeks to “reduce burden, offer flexibility to both developers and providers, and support innovation through the removal and revisions of certain certification criteria and regulatory provisions.” If finalized, it would eliminate 34 of 60 criteria in the Certified Health IT Program, relax requirements around AI systems, and make it easier for patients to access their own health data.

The public comment period runs until February 27, 2026, with the final rule expected to match up with existing compliance timelines.

HTI-4 Deadlines Still in Place

Mandates for real-time prescription benefit (RTPB) checks, electronic prior authorization (ePA), and National Council for Prescription Drug Programs (NCPDP) SCRIPT Standards remain in place.

A reduction in administrative overhead from HTI-5 means vendors can increase their focus on improving e-prescribing workflows, benefiting prescribers, pharmacies, payers, and, most importantly, patients.

The goals of HTI-4 are unchanged, so it’s full speed ahead for the timeline and deadlines:

  • Now through 2027. Complete RTPB and ePA development, certify all required features, and begin the testing phase.
  • From 2026-2027. E-prescribing systems can still use SCRIPT 2017071 or 2023011.
  • January 1, 2028. SCRIPT 2023011 required.
  • January 1, 2028. RTPB becomes mandatory for Base EHR certification.

Beyond Checking the Box

As a vendor, you have a great deal of work to do in the next two years but also some intriguing opportunities for innovation. Now is the time to make thoughtful decisions — will you meet minimum requirements or will you aim to improve real-world clinical workflows in a way that goes above and beyond?

Despite advances, physicians and pharmacists continue to grapple with interruptions and rework. Without key information readily available in the prescribing workflow, patients encounter delays that prevent timely access to therapy. This leads to the time-consuming ping pong of back-and-forth communications: phone calls to verify prescription information, faxes requesting prior authorization, and messages about formulary alternatives. Each exchange delays fulfillment and adds more friction for providers and patients.

Prescription orchestration capabilities from DrFirst address the needs of pharmacies, pharmacy benefit managers (PBMs), electronic health records (EHRs), providers, and patients.

Real-time workflow alignment ensures that all healthcare stakeholders automatically access necessary information—resolving issues pre-emptively so prescriptions reach the pharmacy ready to fill.  Simply passing data between doctor and pharmacy doesn’t cut it anymore, and recognizing that a new approach is needed is where the real opportunity lies.

The Bottom Line

HTI-4’s medication management requirements remain unchanged and urgent, and whether you decide to build or buy, the clock is ticking. RTPB and ePA will enable fundamental changes in how medications are prescribed, approved, and managed across healthcare systems.

Consider the significant resources it will take to build complex RTPB and ePA capabilities mandated by HTI-4 from scratch. You might decide to work with a trusted partner like DrFirst so you don’t have to sacrifice product differentiation in favor of compliance. Either way, look at this as an opportunity to level up your e-prescribing game.

If you’re looking to shift your strategy in the face of HTI-5 and learn about intelligent workflow innovations that go above and beyond the regulatory mandates of HTI-4, reach out to speak to one of our experts.

About Nick Barger, PharmD 

Nick is Vice President of Product at DrFirst, where he leads design and development of intelligent medication management solutions for the e-prescribing pioneer and the 270 EHRs and health information systems they partner with, providing clinical, regulatory, and digital workflow solutions that make healthcare more efficient and effective. Check out all the articles in the Healthcare Regulatory Talk series.

DrFirst is a proud sponsor of Healthcare Scene.



< + > This Week’s Health IT Jobs – February 4, 2026

It can be very overwhelming scrolling through job board after job board in search of a position that fits your wants and needs. Let us take that stress away by finding a mix of great health IT jobs for you! We hope you enjoy this look at some of the health IT jobs we saw healthcare organizations trying to fill this week.

Here’s a quick look at some of the health IT jobs we found:

If none of these jobs fit your needs, be sure to check out our previous health IT job listings.

Do you have an open health IT position that you are looking to fill? Contact us here with a link to the open position and we’ll be happy to feature it in next week’s article at no charge!

*Note: These jobs are listed by Healthcare IT Today as a free service to the community. Healthcare IT Today does not endorse or vouch for the company or the job posting. We encourage anyone applying to these jobs to do their own due diligence.



Tuesday, February 3, 2026

< + > How Health Catalyst Turns Analytics Into Action Clinicians Actually Use

Healthcare analytics has never been more sophisticated, yet many improvement efforts still stall. Reports arrive too late. Dashboards lack context. Frontline teams struggle to connect yesterday’s work to tomorrow’s outcomes. The gap is not insight. It is timing, trust, and follow-through. Health Catalyst has a solution.

How Near-Real-Time Data and AI Are Changing Clinical Improvement Work

In a sit down interview with Healthcare IT Today, Holly Rimmasch, Chief Clinical Officer and SVP of Improvement Services at Health Catalyst, and Kathleen Merkley, SVP of Clinical Improvement, unpacked why analytics alone rarely change behavior and how faster feedback, AI-guided prioritization, and clinician ownership are driving healthcare improvement today.

Key Takeaway

  1. Near-real-time data changes behavior in ways retrospective reporting never can. When clinicians see yesterday’s sepsis case instead of last quarter’s averages, feedback becomes persona and far more likely to drive sustained improvement.
  2. AI creates value when it removes guesswork, not when it adds complexity. Health Catalyst uses AI to identify which interventions are most likely to move outcomes like length of stay, readmissions, and mortality before teams invest time and effort.
  3. Sustainable improvement depends on clinician ownership, not top-down mandates. Some of the biggest gains come from frontline clinicians designing solutions they believe in and then seeing the data confirm their impact.

Why Near-Real-Time Analytics Drive Clinical Behavior Change

One of the clearest shifts Health Catalyst has observed is what happens when teams stop waiting weeks or months for reports and instead see performance within a day. Near-real-time data turns improvement from a retrospective exercise into something clinicians can recognize, remember, and act on while cases are still fresh.

As Merkley explained through the lens of sepsis care, speed changes everything.

“If I’m a sepsis coordinator and in a health system, I can look within 24 hours at someone who was in the ED yesterday with sepsis. I can see when their antibiotic was started, when their fluids were started, how much fluid they got, what was their lactate, what was their length of stay.”

She contrasted that with traditional reporting cycles.

“Someone two months later is not going to remember that case like they did the day before.”

Health Catalyst supports this shift by refreshing key clinical data on a 24-hour cadence and structuring dashboards around real clinical workflows. That timing allows multidisciplinary teams to meet regularly, review recent cases together, and keep improvement grounded in lived experience rather than faded memory.

Using AI To Prioritize the Improvements That Actually Move Outcomes

Rather than positioning AI as a replacement for clinical judgment, Health Catalyst uses it to narrow the field. The goal is to identify which actions are most likely to change outcomes before teams invest time and energy.

Merkley shared a concrete example from heart failure care.

“We’re taking all of those identified opportunities and they’re running algorithms on them and saying, if you do this, you will see this rate reduction in length of stay and this improvement in mortality.”

That approach replaces intuition and pet projects with evidence.

“We can go in and say with authority that yes, if you do daily weights every day on your heart failure patients, you’re going to improve their length of stay and their readmission rate. So simple. But AI was able to tell us how important that was.”

Rimmasch added that this kind of prioritization used to require extensive human analysis.

“In past, we’ve always done this improvement work… that was a human intervention that happened. We can now integrate that into AI to say, here’s your opportunity, here are some projections, and here are some things you might want to consider doing.”

The result is less debate over what to tackle first and more confidence that effort is being spent where it matters.

Why Frontline-Led Improvement Outlasts Top-Down Programs

The most consistent theme across the conversation was where durable improvement actually comes from. Not predefined playbooks. Not executive directives. But clinicians who see the data, trust it, and help shape the solution.

Merkley described how her own approach evolved: “I always come in with a list of interventions. Well, you could do this, this, or this. And I used to be hurt because the interventions were never what I suggested.” She quickly put aside that frustration when she realized something important about the frontline teams she was working with: “These clinicians are so thoughtful and so passionate about caring, and they come up with really great ways to improve care. And we institute those and we see big results.”

Rimmasch noted that this ownership appears, even after there is early resistance: “Sometimes we start with people who aren’t really excited to do this. But they see the opportunities.” The key, according to Rimmasch is to show improvement over time: “We understand the importance of sustainability. We can follow a process, an improvement, for years if we need to.”

Health Catalyst’s role is to create the conditions where that ownership can take hold. Standardized metrics, trusted data definitions, and sustained visibility allow teams to track progress and maintain momentum beyond an initial push.

From Analytics to Improvement That Lasts

Throughout this conversation, Rimmasch and Merkley repeated the same themes:

  • Timely data that reflects real work
  • AI that clarifies priorities instead of complicating them
  • Improvement efforts shaped by the people closest to patient care

When those elements come together, analytics stop being a reporting function and start reinforcing a cycle clinicians want to sustain.

As Rimmasch put it, improvement builds on itself.

“You start doing it, you learn about it, and it just starts to swirl and it gets better for patients, for clinicians, for administrators. It gets better for everybody.”

Learn more about Health Catalyst at https://www.healthcatalyst.com/

Listen and subscribe to the Healthcare IT Today Interviews Podcast to hear all the latest insights from experts in healthcare IT.

And for an exclusive look at our top stories, subscribe to our newsletter and YouTube.

Tell us what you think. Contact us here or on Twitter at @hcitoday. And if you’re interested in advertising with us, check out our various advertising packages and request our Media Kit.

Health Catalyst is a proud sponsor of Healthcare Scene.



< + > No Hospital is an Island (Anymore): Removing Friction in Healthcare IT Systems Starts with Identity and Access

The following is a guest article by Paul Dant, Senior Solution Consultant at Radiant Logic

Hospitals and healthcare systems are reaching a breaking point. The Covid-19 pandemic didn’t create the industry’s challenges, but it exposed and accelerated them. Years of mergers and acquisitions, siloed data, and persistent staff turnover have left healthcare IT teams managing environments that are more complex, fragmented, and mission-critical than ever. Because of healthcare’s unique challenges and compliance requirements, this can create friction and, in the worst cases, impact patient care. Planning ahead and implementing a strong identity and access foundation improves security and compliance while reducing bottlenecks, creating a better patient and employee experience.

Complications in Healthcare IT

How do IT teams balance security and compliance requirements while giving healthcare providers the access they need to do their jobs? To effectively manage healthcare identity and access, we have to start by understanding the unique needs and challenges of the healthcare system and its workers.

Hospitals largely remain brick and mortar facilities, with physical systems that need to be connected across kiosks, medical devices, and other access points that must all be secure but accessible. Meanwhile, each healthcare facility, from Level 1 trauma centers to university hospitals to regional clinics, tends to be an “island” with its own IT system and tech platform. This creates friction after major events like mergers and acquisitions, when disparate systems have to be integrated, and staff may have to be onboarded or offboarded (or both).

It also creates friction in day-to-day operations, since healthcare providers often operate across multiple facilities with different roles and levels of access required. A surgeon affiliated with a teaching hospital might go from working in the hospital OR to evaluating pre-op patients at the clinic to teaching a course. In the course of a week, that doctor might have three different levels of access, and as they move from setting to setting, they need their identity and access to adjust to the corresponding role.

Patients also move between healthcare systems, with electronic healthcare records (EHRs) that their care teams need to be able to access. In a life-threatening situation, doctors need to be able to retrieve and review patient information quickly, regardless of where the information lives.

On top of the existing complexities of securing human access, non-human identities pose a growing challenge, especially with the increasing use of AI.

About 50% of non-human identities within a healthcare environment are devices, such as iPads, insulin pumps, and dialysis machines. Left unmanaged, these can pose a major threat: IoT vulnerabilities can reveal a patient’s personally identifiable information (PII) or even interfere with their care. Traffic between these devices and the healthcare system must be secured, and patient anonymity must be protected.

You Can’t Take It With You – Or Can You? When Patients and Doctors Move

When dealing with multiple “islands,” adding a layer of abstraction above the individual facility level allows hospitals and clinics to retain their unique systems while enacting identity and access measures across these systems. This enables hospitals and clinics to securely communicate essential data as doctors and patients move between facilities.

Additionally, creating identity “personas” within your IT system ensures that healthcare workers serving in multiple roles or locations can transition from one setting to the next without delay. With one set of credentials, the surgeon at the teaching hospital can access student information when they’re teaching at the university, or they can review patient information at the clinic or hospital. Their access and privileges will adjust depending on where they are and what role they are filling at the time.

Similarly, in a “break glass” scenario where time is of the essence, the care team needs to access patient information, but it is crucial to control that information with a defined model. Outlining parameters in advance for time-limited emergency access based on location and need – along with automatically creating an auditable record of every time these superseding permissions are granted – removes hurdles in an emergency situation, but preserves security and maintains compliance.

Laying the Foundations of Healthcare Identity Brick by Brick (and Cloud by Cloud)

Healthcare IT teams generally do an excellent job of implementing multifactor authentication and ensuring that the person accessing the system is who they say they are. As new software and system requirements come through, IT teams also must foresee potential issues and points of conflict, both in day-to-day healthcare operations and among networks and devices. Increasingly, tech is becoming part of the doctor and patient experience, from AI tools to telehealth platforms, adding an additional layer of risk to address.

Adding third-party vendors and their tech can alleviate heavy provider workloads and improve business operations, but it also increases the potential attack surface. (Estimates vary, but a significant number of attacks originate from third-party partners, including the 2024 Change Healthcare breach.) What are vendors’ security measures? Do they manage risk and cybersecurity on the backend? Are they open to working within your system? Asking questions and testing implementations before rolling out new tech can avert disaster.

If you are integrating AI software into your healthcare process, setting permissions early on for both human and non-human identities will reduce vulnerabilities and improve patient care. For example, an AI notetaker that will provide a summary to the healthcare provider to upload to the patient’s EHR does not need access to diagnostic imaging, let alone full admin access. And human access to the data from that AI notetaker should be limited to ensure HIPAA compliance – just as a doctor’s after-appointment notes would be.

Performing regular audits of both human and non-human identities to ensure that accounts reflect appropriate roles and permissions will help eliminate security vulnerabilities, such as orphan accounts. If staff have left or if the hospital no longer uses a third-party vendor, removing that account from the system removes a potential breach point. Conversely, giving new practitioners prompt access to the files they need will enable them to provide the best care possible to patients.

By planning these scenarios before the doctor arrives at the clinic (or the patient gets to the operating table), you can keep processes running smoothly while protecting sensitive patient data and securing digital and medical devices. With proactive identity management, you can deliver a safe, seamless transition across identity and access points throughout your medical system, no matter how complex.

A​bout Paul Dant

Paul Dant serves as Senior Solution Consultant at Radiant Logic. He is a lifelong ethical hacker and sought-after advisor with nearly four decades of experience helping organizations anticipate, understand, and outmaneuver real-world adversaries. He’s spent his career demystifying cybersecurity for technical and non-technical audiences alike, presenting at dozens of conferences and consulting for hundreds of organizations.

As an award-winning cybersecurity product innovator, a top-rated RSA Conference speaker, and co-founder of the DEF CON IoT Hacking Village, Paul is known for bridging deep security insight with captivating storytelling and is passionate about making security a driver of innovation, growth, and trust.



< + > Serve Robotics to Acquire Diligent Robotics | Harmony Healthcare IT Acquires Blue Elm

Check out today’s featured companies who have recently completed an M&A deal, and be sure to check out the full list of past healthcare IT M&A.


Serve Robotics to Acquire Diligent Robotics, Expanding Physical AI Platform Beyond the Sidewalk

  • Acquisition Broadens Serve’s Autonomous Robotics Platform, Expanding Market Opportunity Beyond Last-Mile Delivery, and Delivering Non-Organic Revenue
  • Diligent’s Moxi Robot Among the Largest Autonomous Robot Deployments in Hospitals Nationwide: Over 1.25 Million Deliveries Completed by Nearly 100 Robots in Over 25 Hospital Facilities, with Annual Sales at Each Hospital Expected to Range Between $200k to $400k
  • Leverages a Common Autonomy and AI Stack, Accelerating Learning, Deployment, and Scalability

Serve Robotics Inc., a leading autonomous robotics company, today announced that it has entered into an agreement to acquire Diligent Robotics, Inc., a pioneering provider of AI-powered robot assistants for the healthcare industry. The transaction marks the first expansion of Serve’s autonomy platform into indoor environments, with hospitals as one of the most high-impact settings for robotics.

Diligent was founded in 2017 by Andrea Thomaz and Vivian Chu, world-renowned social roboticists, with the vision of creating socially intelligent robot assistants that improve human labor productivity. Since its inception, Diligent has raised over $100 million in financing from investors including Tiger Global, Canaan, and True Ventures.

Diligent has developed Moxi, an autonomous hospital delivery robot that supports nurses and hospital staff, allowing them to focus on time with patients and therefore improve the quality of care. Moxi is deployed in over 25 hospital facilities across the U.S., representing one of the largest commercial deployments of mobile manipulation robots working alongside people. Moxi robots have successfully completed over 1.25 million autonomous deliveries. Moxi is powered by NVIDIA’s embedded hardware and software ecosystem (Jetson & Omniverse) and uses advanced sensing and AI to navigate among people in complex hospital spaces. Moxi incorporates insight from years of real-world data in commercial deployments. Customers include leading hospitals and healthcare systems such as Northwestern Medicine, ChristianaCare, and Rochester General Hospital.

The acquisition extends Serve’s commercial operations and autonomy platform into indoor and healthcare applications that demand reliability, safety, and an unobtrusive presence. The combined effort brings together two mission-driven teams with a shared vision for creating and deploying human-centric, autonomous robots in real-world settings. Both Serve and Diligent have successfully designed and commercialized Physical AI systems that operate safely alongside people, perform with high reliability in complex, dynamic environments, and integrate seamlessly into everyday situations.

Indoor environments, such as hospitals, add a powerful new dimension to Serve’s Physical AI flywheel. Dense, human-centric, multi-level spaces with constant edge cases are the conditions that sharpen autonomy fastest…

Full release here, originally announced January 20th, 2026.


Harmony Healthcare IT Expands MEDITECH EHR Data Solutions Through Acquisition of Blue Elm

MEDITECH Hospitals will Benefit from a Single Partner for Complete Data Lifecycle Management

Harmony Healthcare IT, the leading health data management and archiving solutions company for hospitals and health systems, today announced the acquisition of Blue Elm, the premier MEDITECH data solutions provider. The acquisition solidifies Harmony Healthcare IT as the industry’s most comprehensive MEDITECH data partner, combining the company’s deep expertise in healthcare data migration and archiving with Blue Elm’s MEDITECH data optimization, access, and extraction capabilities.

This acquisition addresses critical industry trends MEDITECH hospitals are navigating, including:

  • Rising demand for MEDITECH data extraction, conversion, and migration services as hospitals undergo system upgrades and transitions
  • Growing focus on legacy data archiving as hospitals seek to decommission costly, vulnerable systems
  • Increasing need for enhanced data access and optimization as hospitals face ongoing pressure to improve quality and reduce costs

“MEDITECH hospitals and health systems now have access to unparalleled expertise across the complete data lifecycle,” said Brian Liddell, President and CFO at Harmony Healthcare IT. “From maintaining data integrity and enhancing real-time access to executing complex migration and archiving projects, no other provider can match our combined company’s breadth of MEDITECH expertise.”

Blue Elm, which has served more than 500 hospitals and vendors since its founding in 2001, brings deep MEDITECH-specific capabilities across all versions (Magic, Client/Server, 6.x, and Expanse).

“Joining Harmony Healthcare IT allows us to streamline and accelerate the complex data projects MEDITECH hospitals are undertaking — potentially cutting months from overall project timelines,” said John Mackey, Founder and President at Blue Elm…

Full release here, originally announced January 21, 2026.



Monday, February 2, 2026

< + > The End of Manual Enrollment? Intelligent Automation Takes On First-Mile Insurance Data

The following is a guest article by Deepak Singh, Chief Innovation Officer at Adeptia

In the insurance ecosystem, data is the lifeblood of coverage, yet it is rarely clean. In fact, approximately 80% to 85% of insurance data is unstructured, and for items such as claim files, the number can be as high as 97%, according to Accenture. Unlike banking or retail, where transactions follow more rigid standards, group health insurance data is uniquely chaotic. It involves a constant flux of stakeholders, such as employers, brokers, carriers, and third-party administrators, each speaking a different digital language.

For insurance professionals, the status quo is a daily battle against disorder. Employees join and leave, life events trigger plan changes, and regulatory variations across states shift eligibility rules overnight. However, the true friction lies not in the volume of data, but in its format. When a broker spends 60% of their time on data cleanup rather than strategic consulting, the industry doesn’t just have a workflow problem; it has a viability problem.

The “Creative” Excel Nightmare

The frontline of this battle is enrollment. Despite the availability of sophisticated HRIS platforms, the industry still mostly runs on spreadsheets and PDFs. The most problematic culprits are often Excel files containing “creative” formatting – merged cells, custom macros, and multiple tabs – or PDFs with handwritten notes that defy optical character recognition.

These formatting inconsistencies lead to the industry’s notorious “dirty data” crisis. Mismatched employee information between HR systems and carrier requirements, missing effective dates, and invalid dependent eligibility (such as ex-spouses still listed on plans) are rampant. Recent insights from benefits brokerage firm Nava Benefits backs this up – it found that 90% of employers have open enrollment errors; collectively, employers may be losing billions of dollars due to carriers’ open enrollment mistakes.

The operational toll is also staggering. An average employer data file currently requires 15 to 20 hours of manual cleanup. When 30% of enrollment files contain errors that require rework, costs balloon. Industry data suggests that manual rework costs average $50 to $100 per error. Furthermore, during enrollment season, member calls to HR and brokers increase by 300%, primarily driven by confusion stemming from these data mismatches.

The Evidence of Insurability (EOI) Black Hole

No area illustrates this friction better than arguably the most fragile link in the chain – EOI. Health questionnaires arrive in various formats, necessitating manual review against complex underwriting rules that vary by carrier and coverage amount.

Because this process is time-sensitive, delays can leave employees in “coverage limbo,” unable to secure health insurance when they need it most. The consequences of EOI errors are severe: from compliance risks to incorrect decisions and financial exposure if coverage activates retroactively after a claim has occurred.

The Friction of Carrier Switching

The friction intensifies when an employer switches carriers. A full transition typically takes 60 to 90 days, with the bulk of that time consumed by data mapping and testing. The primary point of failure is field mapping incompatibility, where one carrier’s “EE_DOB” is another’s “BirthDate.”

When historical claims data doesn’t align with a new carrier’s format, or eligibility rules differ, the result is a frantic manual reconciliation of member lists. This is often the longest phase of a carrier switchover and the one most prone to error.

The Real-World Stakes Are High

The consequences of bad data extend beyond operational headaches; they carry significant legal and financial weight. The industry has seen major retailers fined millions for ERISA violations due to enrollment errors, and healthcare systems facing class-action suits over errors in dependent eligibility. In one audit of a Fortune 500 company, it was revealed that 18% of listed dependents were actually ineligible, a massive financial loss.

For brokers, the impact is also reputational. Lost employer trust and confidence often leads to the termination of broker or carrier relationships. For members, it can result in coverage denials at the point of care due to administrative mismatches.

The Turning Point: Empowering the Business User

Fortunately, the industry is at a turning point. We are moving away from the era where IT departments were the sole gatekeepers of data logic. The future of insurance data lies in empowering business users, the people who actually understand the nuances of benefits data, to own the rule definitions and validation logic.

Emerging technologies, specifically AI capable of processing unstructured data, are changing the game. Intelligent document processing can now extract data from “creative” PDFs, validate it against underwriting rules, and track status in real time.

The results of automation are tangible. Some organizations have reduced enrollment processing times from 5 weeks to just 3 hours. By adopting industry-standard formats (such as LDEx) and using automated mapping templates, the industry can finally move past the “data janitor” phase.

When AI handles the “digital plumbing,” mapping fields, validating eligibility, and structuring data, brokers and HR teams are freed from the data janitor role. They can finally focus on what they do best: advising clients on strategy, plan design, and risk management.

As benefits costs rise and a younger workforce expects a smooth enrollment experience, sticking to manual reconciliation is no longer an option. The tools exist to fix the messiness of group health insurance; it is time for the industry to pick them up.



< + > AI Enhances Outreach to Blood Donors

While collecting blood, Versiti collects data. Versiti is a nonprofit founded in 1947 with the two goals of providing a sustainable blood s...