Key takeaways from the First Analysis Healthcare IT Panel

The aging of its population is increasing the U.S. healthcare burden and shifting the insurance mix toward government-funded programs, eroding the traditional cross-subsidy in which revenue from higher-margin commercial patients offset the effect of lower-margin government reimbursement. At the same time, there is a worsening healthcare workforce shortage.

These conditions mean the healthcare industry faces mounting pressure to do more with less. Widespread data liquidity, true interoperability, and responsible adoption of artificial intelligence and other new technologies will be critical for operators to sustain financial health and improve patient outcomes.

We present a framework for understanding how healthcare technology companies are enabling this transformation, organizing them by the core operating challenges they address and providing brief profiles for a representative set of companies in each category.

The most recent First Analysis Funds Annual Meeting featured a panel discussion among three healthcare industry experts regarding the forces reshaping healthcare delivery and the opportunities they are creating.

The panelists were: Therasa Bell, co-founder and president of Kno2; Jason Keeler, former chief operating officer of University of Chicago Medicine, and Scott Ptacek, senior advisor at Oliver Wyman. Together, they represented the perspectives of enterprise technology providers, healthcare operators and payers. First Analysis Managing Director Andrew Walsh moderated the discussion.

Across their comments, one theme was consistent: As the U.S. population ages and the insurance mix shifts toward government-funded programs, the healthcare industry will face mounting pressure to do more with less. Widespread data liquidity, true interoperability, and responsible adoption of artificial intelligence and other new technologies will be critical for operators to sustain financial health and improve patient outcomes.

The U.S. population is aging rapidly, and the resulting population shift from commercial insurance to Medicare, Medicaid and subsidized exchange plans is transforming the economics of care. Older people use more healthcare services, but government-driven health insurance programs offer lower provider reimbursements, creating a long-term structural squeeze.

Former University of Chicago Medicine COO Keeler explained, “As people get older, they need to utilize the healthcare system more. If you go to UChicago Medicine or Northwestern or Rush—any big academic center or community hospital—you’re going to wait, wait and wait. Hospitals are full. As people age, there’s going to be more utilization. How are we going to handle this onslaught of chronic care and illness that’s going to fall upon us if we don’t get more efficient?”

At the same time, providers face erosion of the traditional cross-subsidy in which revenue from higher-margin commercial patients historically offset the effect of lower-margin government reimbursement. As commercial volumes decline, that cushion disappears, exposing the underfunding embedded in Medicare and Medicaid.

“One of the numbers I would look at every month was our overall margin—what was our payer mix,” Keeler commented. “How much government versus commercial care? Commercial payers are the profitability of healthcare. As people age out of commercial healthcare into government programs, providers struggle to break even.”

Payers will need to shift their focus from member growth to margin sustainability by improving care quality, member experience, and Star Ratings. (The Centers for Medicare & Medicaid Services rates Medicare Advantage and prescription drug plans on a 5-star scale based on health plan quality.) Health systems and physician groups will have little choice but to redesign their cost structures or succeed in value-based arrangements that reward prevention and efficiency rather than volume. Labor optimization, site-of-care shifts, automation of administrative functions, and rethinking real estate utilization will all become critical.

The challenge of restructuring is exacerbated by a worsening workforce shortage. Keeler noted, “We’re seeing a huge wave of retirement in healthcare. Physicians are retiring, nurses are retiring, and the pipeline to backfill those jobs is not sufficient to meet demand.” With more clinicians approaching retirement and fewer new entrants to replace them, providers will be forced to find ways to extend capacity through technology rather than headcount growth. Indeed, technology adoption will play a central role in this transformation.

Kno2 co-founder and President Bell offered an example, noting, “It is only this year that patients can finally get access to their records nationally. That kind of power in the hands of the consumer, with AI sitting over the top, lets people start to self-direct care.”

AI-enabled documentation and transcribing tools are freeing clinicians from manual note-taking, while automated workflows for billing, coding, scheduling and prior authorization are reducing the administrative load. Virtual nursing, remote monitoring, and predictive analytics for staffing and patient risk are helping health systems use existing resources more efficiently. Training and upskilling platforms are accelerating onboarding new staff. None of these technologies replace clinicians, but together they amplify the capacity of scarce labor and help restore sustainability to clinical and administrative operations.

Bell emphasized that providers cannot deliver efficient care when critical patient information is trapped in disconnected systems. Fragmented data leads to duplicated tests, delayed diagnoses and wasted clinician time. A centralized, accessible patient record that moves seamlessly between care settings is essential for both efficiency and quality.

Despite meaningful progress, true interoperability remains uneven. Federal mandates such as the Trusted Exchange Framework and Common Agreement (TEFCA), the 21st Century Cures Act and CMS interoperability rules have laid the groundwork for connectivity, but implementation varies widely. Some health systems and payers have invested in modern application programming interfaces (APIs) based on Fast Healthcare Interoperability Resources (FHIR) that enable real-time data sharing, while others still depend on fax, PDF and manual workflows. Legal and incentive barriers continue to slow the flow of data between payers, and post-acute and community-based providers remain largely disconnected from digital infrastructure.

Bell commented, “The need for data at the point of care is tremendous. It’s shocking to see what kind of data is still not available today.”

Kno2 sits at the center of this transformation. Its platform connects providers to a nationwide network of electronic health records, health information exchanges, payers, and care settings, breaking down data silos and enabling access to complete patient histories regardless of where care was delivered. By normalizing and routing clinical data into existing workflows, Kno2 ensures clinicians receive usable, consistent information inside the tools they already use, saving time and reducing errors. The company’s secure, standards-based exchange framework eliminates the need for costly custom integrations and creates a frictionless, centralized record view that enables clinicians to focus more on patient care and less on record chasing.

Mandates alone will not achieve full data liquidity. Success will require alignment among payers, providers and technology vendors around common standards, business models, and incentives. Until data moves as freely as clinical need demands, efficiency and care quality will remain constrained.

Artificial intelligence has become one of the most discussed topics in healthcare, but the panel agreed its real value lies in augmenting, not replacing, human decision-making. Bell noted, “We don’t allow AI-only tools on our network; there must always be a human in the loop.”

Providers are cautiously adopting AI tools for documentation, scheduling and early-stage clinical decision support, balancing the promise of productivity gains with legitimate concerns about bias, false positives and liability. Payers are applying AI to detect fraud, waste and abuse, to streamline claims, and to improve member engagement and risk adjustment accuracy. Privacy is also critical.

“When patients sign consent forms, they assume their data is being shared for their care, not for training AI models,” Bell said.

Technology platforms are integrating AI responsibly within Health Insurance Portability and Accountability Act and Food and Drug Administration guardrails to protect privacy, maintain transparency and ensure fairness.

The future of AI in healthcare will depend on the availability of clean, connected, high-quality data. Without interoperability and data liquidity, algorithms cannot function effectively. When built on strong data foundations, however, AI can meaningfully improve efficiency, predict risk and support earlier interventions across both clinical and administrative functions.

The framework below organizes a set of representative healthcare technology companies by the core operating challenges they address. This illustrates how the healthcare ecosystem is responding to systemic pressures with foundational data infrastructure, automation, workforce amplification, care model reconfiguration, and operational decision support. It highlights not only where innovation is occurring, but why these categories are emerging as critical enablers of sustainable healthcare delivery.

This category includes infrastructure platforms that enable clinical, administrative and operational data to move reliably across fragmented healthcare systems. These solutions form the layer required for automation, analytics and AI by making data accessible, standardized and usable within workflows.

This category includes technology that removes nonclinical administrative work from healthcare operations, helping organizations survive under margin compression and reimbursement pressure by reducing cost per unit of care.

This category includes tools that extend the capacity of scarce clinical labor by reducing documentation burden, improving care team execution and shifting work away from synchronous, clinician-heavy models.

This category includes platforms that enable healthcare organizations to absorb rising demand by shifting care to lower-cost settings, improving throughput and better matching demand to available capacity.

This category includes analytics and intelligence platforms that transform fragmented data into actionable insights, enabling leaders to manage cost, utilization and performance in real time.

This is a pivotal moment for the healthcare system. Demographic and economic pressures are increasing demand while workforce shortages constrain supply. Data fragmentation and inconsistent interoperability continue to limit coordination, but emerging technologies—particularly AI and intelligent automation—offer pathways to scale efficiency and improve outcomes.

At the First Analysis Funds Annual Meeting, Oliver Wyman’s Scott Ptacek commented, “There’s a profitability crisis that’s happening. People are being pinched on all lines of business, and the focus is on efficiency. Technology and AI are key levers to lower overall cost of care.”

Sustained progress will require payer-provider alignment, widespread interoperability, and the deployment of technology that embeds intelligence directly into workflows. Keeler noted, “The key is to make technology extend care and not make it harder for doctors to do their job.” For investors, we believe the most promising opportunities lie with platforms that bridge payer–provider divides, unlock data liquidity, and create measurable improvements in operational and clinical efficiency.