Healthcare – The Ultimate Vertical Market (Part 2)

In Part I of this series, we looked at how Epic became the most successful vertical SaaS company in healthcare. It owns the hospital. It’s the control point for nearly half of the large health systems in the U.S., with deep integrations across clinical, operational, and financial workflows. With near-zero churn, it’s a case study in long-term product depth and execution and a textbook example of the Vertical SaaS Knowledge Project (VSKP) framework in action.

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But Epic is just the beginning. In Part I, we introduced four defining characteristics that make healthcare the ultimate vertical market:

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• Deeply specialized workflows that remain largely under-automated.
• Abundant, sensitive, unstructured, and fragmented data.
• A regulatory environment that is unique, complex, and always changing.
• A web of multiple stakeholders, each with competing priorities and incentives. 

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In this installment, we’ll focus on the first two — how specialization becomes a moat, and how data gravity locks in systems and creates powerful expansion dynamics. We’ll explore the remaining two themes — regulation and multi-stakeholder complexity — in Part III. Let’s jump in!

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For all of Epic’s success, hospitals account for just ~30% of the $4+ trillion U.S. healthcare economy. The other 70% is where the rest of healthcare lives. Outside of the hospital, there are a multitude of different care settings such as physical therapy clinics, mental health practices, dental offices, massage studios, chiropractors, long-term care facilities, veterinary clinics, and so much more. These are real businesses serving real patients (or pets), often running on spreadsheets, legacy desktop software, or nothing at all.

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They don’t need Epic. Everything about their business is fundamentally different from the needs of a 500-bed hospital. They need something built specifically for them. And that’s increasingly what they’re getting. 

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The areas of the healthcare ecosystem that Epic doesn’t serve are a bigger opportunity than most founders realize. Zoom out, and you see dozens of healthcare sub-verticals that are large enough to sustain billion-dollar platforms, and many are still wide open. To win in these markets, specialization must become a moat. This is why the next crop of great healthcare SaaS companies will look nothing like Epic. ‍
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One of the clearest examples of vertical software winning by specializing is Tidemark portfolio company, Jane. It’s a platform purpose-built for Allied Health. And where Epic tries to be everything to every large hospital, Jane has gone all-in on independent clinics and small practices. This singular focus is exactly what makes it work.

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Jane is the operating system for SMB health and wellness practitioners. Running a clinic means wearing 10 hats. SMB business owners prefer buying from a single vendor, and Jane’s Allied Health customers are no exception. And Jane delivers, combining “front office” and “back office” functionality in one integrated platform across scheduling, charting, billing, and insurance.
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Yet Jane doesn’t win by simply bundling features. It does so by digging deeply into the messy, specialized workflows that define these businesses: it handles the unique time-based billing models in physical therapy, SOAP charting used in mental health, integrated insurance claim workflows for chiropractors, etc.. These are nuanced needs that Epic doesn’t try to address.  

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Jane’s Control Point status runs across three dimensions:

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1. ‍Workflow Gravity. As an all-in-one system automating the multitude of jobs required to run a clinic, Jane sits at the center of the most important workflows and where users spend the most amount of time, and becomes the platform other systems must integrate with. ‍
2. Account Ownership Gravity. In SMB settings, the owner/operator is both the user and the purchaser. That alignment drives exceptional stickiness.‍
3. Data Gravity. As the repository for patient, schedule, and payment information, Jane is the system that holds and creates a clinic’s most critical information.

Jane succeeds not by generalizing but by specializing. It’s built for providers who have been overlooked by larger, less specialized platforms and, for that reason, is becoming indispensable. And we’re thrilled to be invested in this healthcare category leader.

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Jane’s success comes not just from the depths of its workflows, but from the gravitational pull of the data it captures: patient records, scheduling, payments and insurance details all flow across its platform. And when you control the data, you control the workflow. This brings us to the second theme we’ll explore: how data gravity shapes the healthcare stack, and why the systems that hold the most critical data become the hardest to displace.

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Understanding Data Gravity in Healthcare

Tech historians may remember Doug Laney’s “3 Vs” framework for big data: volume, velocity, and variety. Though he didn’t formulate it with healthcare in mind, it still fits uncannily well. Few industries generate more data — or more complex formats — than healthcare.

The explosion began more than a decade ago, when federal regulations like HITECH mandated the digitization of health records. Since then, the volume and speed of data creation have only accelerated as the system shifts toward more data-driven models of care. The rise of value-based reimbursement, preventive medicine, and chronic disease management has added even more fuel. And now, billions of consumer health devices — from fitness trackers and smartwatches to rings, implants, and connected monitors — stream real-time data around the clock. Sleep scores were obscure five years ago. Now they’re targets for optimization.

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And when it comes to variety — the third “V” — healthcare is in a league of its own: Think clinical data, claims data, patient-generated data, public health data, genomics data, and more, each with numerous subtypes. None of it lives in one place. It’s scattered across a maze of systems like EHRs, PACS, and LIMS, in fragmented formats that are inconsistent and often unstructured. It’s the kind of chaos that generic software can’t handle, but exactly the kind for which vertical SaaS was built.

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Vertical markets like healthcare are defined by industry-specific data: unique formats, standards, norms, and workflows that generic software struggles to manage. That’s why Vertical SaaS companies have a built-in advantage. They’re purpose-built to meet the real-world needs of their sector. Meanwhile, horizontal “Big Tech” has failed to break in. Remember Microsoft HealthVault? Google Health? Didn’t think so! 

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Those offerings failed because, by function of being horizontally-focused tech platforms, they underestimated how spectacularly complex health care data is. It’s rarely clear or consistent, and buried in formats and insider terminologies. Succeeding in healthcare requires total immersion, something horizontal platforms rarely attempt.

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This brings us back to the concept of Data Gravity, the gravitational pull of the software system that holds the most critical information and is the hardest to migrate. Just ask the U.S. Department of Veterans Affairs how big this challenge is – it has been working on an EHR migration for nearly a decade! When you own the data, not only do you become incredibly sticky, but you earn an unfair right to expand over time.In healthcare, data gravity shows up in three powerful patterns across the ecosystem. On the provider side, we’re seeing consolidation into a handful of mega-platforms. On the payer side, fragmentation still reigns, creating room for new aggregators. And in specialized domains like labs, pharmacies, and clinical trials, we find some of the deepest, most defensible control points in the entire ecosystem. Let’s take a closer look.

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Provider-Side Consolidation: The Rise of Mega-Platforms

The provider side of healthcare is consolidating fast. What was once a fragmented patchwork of tools is now coalescing around a handful of mega-platforms. 

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As we covered in Part I, Epic sits at the center of the shift, having evolved from a clinical documentation tool into healthcare’s dominant system of record within large hospitals and hospital networks. Over time, it has integrated adjacent systems, including Beaker for labs, Radiant for radiology, and more. Oracle Health (formerly Cerner) and Athena have followed similar strategies, but with more limited success. 

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Meanwhile, once-thriving standalone systems for RCM, PMS, and specialty workflows are either being absorbed or rendered obsolete. Why should a hospital maintain separate systems when Epic promises and largely delivers on its promise of “one patient, one record, one system”? Switching costs and integration complexity make it all but impossible for specialized players to compete once Epic takes hold. For many vendors, this amounts to a slow extinction. But don’t forget: while Epic is unique, outside its core markets, it’s a different story.

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Payer-Side Fragmentation: The Opposite Story

While providers race toward consolidation, the payer landscape tells the opposite story. Health insurers are juggling dozens of disconnected systems, creating a massive opportunity for vertical SaaS companies. 

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A visit to any major payer will reveal a tech stack that looks like it was assembled during a tornado and never cleaned up. There’s no single unifying platform, just a maze of siloed point solutions:

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• Core Administrative Processing Systems (CAPS): Legacy platforms like TriZetto and HealthEdge that handle claims and eligibility
• Quality Management Engines: Separate systems for HEDIS measures and quality metrics
• Care Management Platforms: Different solutions for managing complex situations with high-risk and chronic patients
• Prior Authorization Systems: Counterintuitively, these tend to be disconnected from claims processing‍
• Provider Network Management: Another silo for credentialing and contracting

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Everyone wants an “Epic for payers,” yet the reasons that no one has yet pulled it off run deep. 

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First, the top five payers together control about 40% of the market. That’s about double the share of the top 10 healthcare providers, who control about 20% of beds. And each is so big that they can afford to live in the chaos. They employ entire teams from consulting firms like Cognizant, Infosys, and Tata, dedicated to making incompatible systems talk to each other. 

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Second, there’s the complexity problem. Payers deal with 100x the number of variables compared to providers. Every hospital negotiates its own rates. Every large employer wants a custom benefit design. Every state imposes different regulations. Now layer on Medicare Advantage risk scoring, ACA mandates, and Medicaid eligibility rules, and you’ve got a nightmare for any vendor who dares to build a solution to do it all. 

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Then there are the organizational turf wars. An app that attempts to scale from care management into a platform that spans multiple departments triggers resistance. Department heads often view collaboration as a threat and are reluctant to share tools. 

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The build-versus-buy dynamic makes things worse. Hospitals mostly hire IT analysts and administrators. Payers have serious engineering benches. Big ones hire hundreds of developers. Every pitch gets met with: “We’ve got devs — why not build it ourselves?” And often, they do.

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Still, cracks are showing. AI requirements, real-time data needs, and new interoperability regulations are pushing these duct-taped stacks to their limits. Medicare Advantage (MA) might be the wedge. The incentives are clearer, and the requirements are more standardized. A unified payer platform would probably start with MA. 

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The opportunity is a generational one, and it’s loaded with risks, complexity, and inertia. Whoever figures it out (Epic is trying, of course, as is Innovaccer and others) has a shot at transforming how health insurance works in the U.S.

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Domain-Specific Control Points

Beyond hospitals and payers, you'll find pockets where specialized vendors have built fortresses so entrenched that even Epic struggles to break in. These aren’t niches. They’re essential infrastructure powering life-critical services in billion-dollar markets with data pipelines so delicate that switching vendors is virtually impossible. Here are a few:

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• Pharmacy Management Systems (PMS): The operational backbone of outpatient and retail pharmacies is a critical control point with immense data gravity. These systems contain not only medication histories and insurance data, but also inventory records, clinical interventions, and increasingly, patient engagement workflows. Switching costs are astronomical — data migration, retraining of staff, rebuilding integrations with wholesalers and insurance networks, and risking disruption to life-critical medication fulfillment. Once in place, these systems are permanent. Some of the U.S. market leaders include:
  
  • McKesson EnterpriseRx is the biggest overall, dominating hospital outpatient pharmacies and regional chains.‍
  • PioneerRx (now part of RedSail) is the top platform for more than 5,000 independent pharmacies.‍
  • Transaction Data Systems (Rx30/Computer-Rx) comes in second with independent pharmacies.

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• Laboratory Information Systems (LIS/LIMS): These systems run the full lifecycle of a diagnostic test — from order entry to results delivery — and are deeply embedded in hospital labs and reference labs alike.‍
  
  • Epic Beaker, Cerner PathNet, and SCC Soft Computer dominate in hospitals.‍
  • Quest Diagnostics and LabCorp operate proprietary platforms processing billions of tests annually.‍

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The data gravity here is intense: switching would require migrating years of structured results, maintaining instrument integrations, and ensuring compliance with CLIA and other lab standards.

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• ‍Clinical Trial Management Systems (CTMS): CTMS platforms manage the operational backbone of clinical research, from trial site selection to milestone tracking and regulatory compliance. They’re entrenched because the data spans years and millions of dollars: investigator history, site performance, patient pipelines, and submission archives. Once embedded, they anchor the entire clinical ops stack. The U.S. key players are:
  
  • Medidata CTMS (Dassault Systèmes) – The clear industry leader, involved in about 70% of FDA drug approvals in 2022.
  • Veeva Vault CTMS – A fast-growing cloud-native platform used by 17 of the top 20 pharma firms.
  • Oracle Health Sciences (Siebel CTMS/Clinical One) – A 20-year-old legacy system now trying to modernize, is still in the top three by revenue.
  • IBM Clinical Development (now Merative) – A global top-10 CTMS player emphasizing AI and analytics.

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• Electronic Data Capture (EDC) Systems: EDCs store the clinical data from trials, including vitals, outcomes, and adverse events. Once a study begins in one EDC, it must finish there. Lock-in lasts five to 10 years because of FDA rules, audit trail requirements, and the risk of data corruption. The key players are:
  
  • Medidata Rave – The dominant platform in the Rave Clinical Cloud suite.
  • Veeva EDC – Part of Veeva's unified clinical platform.
  • Oracle Clinical – Integrated with Oracle's broader clinical suite.

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This constellation of control points reveals a fundamental truth about healthcare: data gravity is both the greatest moat and the greatest challenge. Every system mentioned above, from Epic's EHR dominance to Medidata's clinical trial platform, has achieved its position by becoming the gravitational center for mission-critical data.

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But that gravity creates a paradox. The deeper these systems embed, the more siloed the data becomes. A patient’s health history is fragmented across dozens of platforms: one EHR for the PCP, another for the specialist, a standalone pharmacy system, and a payer platform that can’t talk to any of them. Interoperability isn’t just a technical challenge; it’s structural. 

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And this is exactly where vertical SaaS thrives. Horizontal tools attempt to patch over fragmentation with universal translators and fail. But each silo exists for a reason: different workflows, regulations, and data models. Vertical SaaS companies win by embedding deeply in specific domains, mastering the nuances, and creating centers of data gravity on their own.

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In Part III, we’ll turn to the final two themes that make healthcare the ultimate vertical: regulation and multi-stakeholder complexity. While these forces create friction, they have also spawned entire categories. From compliance-driven platforms to industry orchestrators, the next great control points in healthcare may not be built not despite regulatory challenges, but because of them.