Decoding Modern Healthcare with SaaS and Artificial Intelligence

Discussion with Brian Wagner, Founder and CEO of Health Insights Consulting Group, Inc.

With over three decades of leadership across medtech, diagnostics, SaaS platforms, and digital health, Brian Wagner has steered both early-stage ventures and multibillion-dollar organizations through seismic shifts in healthcare delivery. From founding Rubbermaid Healthcare to spearheading global commercial strategy at GE HealthCare and Philips, Wagner's career has centered on improving lives while unlocking value through innovation. In this article, he explores how home diagnostics are redefining chronic care, why SaaS platforms are becoming the connective tissue of patient-centric delivery, and what it truly takes to scale a viable go-to-market strategy in today's decentralized health economy.

Decentralization, Data, and Demand

The post-COVID health landscape is shifting rapidly from centralized hospital diagnostics to more accessible, home-based models. Wagner highlights four key drivers: decentralization, chronic disease burden, provider shortages, and unmet system needs.

"Post-COVID, there's a clear shift from facility-based diagnostics to patient-centric models that prioritize convenience, privacy, and accessibility", Wagner explains. Patients now expect testing options beyond hospitals, at urgent care, retail clinics, or at home.

Simultaneously, the chronic disease epidemic is placing unprecedented strain on care systems. "Six in ten adults in the U.S. are living with chronic conditions", Wagner notes. Wearables and apps enable early detection and remote monitoring, empowering patients and easing system strain.

However, decentralization alone isn't enough. "Despite the innovation, gaps remain in clinical validation, interoperability, and patient trust", he warns. Data must not only be collected but also transformed into insights. Future success depends on integrating diagnostics into EHRs and delivering actionable insights.

SaaS Platforms as the Nervous System of Modern Diagnostics

SaaS has evolved into a driver of scalable, patient-centric care. Modular platforms now integrate with wearables and telehealth to enable real-time coordination across specialties. "If you're dealing with cancer, you want your oncologist, radiologist, and cardiologist all aligned", Wagner says. Fast, efficient information sharing ensures patients get the correct diagnosis and a treatment plan they can truly follow.

One company exemplifying this transformation is Clario, which, as Wagner points out, provides some of the richest clinical evidence. "In 2020 and 2021, 70% of all FDA approvals here in the States used their platform". While that figure may have shifted, Clario remains a key player in enabling decentralized clinical trials that accelerate time-to-market and improve representation.

"70% of all clinical trials happen to be done on white Caucasians. Making it worse, mostly are done on males, not even females", Wagner notes. Historically, trials were limited to patients living within 25 to 50 miles of elite institutions. Today, Clario's remote monitoring and digital enrollment capabilities make participation accessible worldwide. "Through decentralized clinical trials technology, we can recruit you into the study, and we can monitor and measure and do everything remotely", he explains.

This model also boosts outcomes and ROI, enabling faster trials, quicker revenue, and better results. Real-time monitoring helps maintain trial integrity. "We know in real time that this patient hasn't gotten out of bed for 12 hours", he adds. This approach allows teams to proactively verify issues, avoid false negatives or positives, and quickly course-correct.

GTM Strategy: Personalize, Partner, and Prioritize Reimbursement

When it comes to launching diagnostic innovations, Wagner underscores that success depends on crafting go-to-market (GTM) strategies that directly reflect the priorities of each stakeholder in the healthcare value chain. "Clinicians want clinical utility, right? Payers want cost savings and patients want ease of use", he says.

"Develop pilots with a clear return on investment metric pathways to scale", Wagner advises. But even with strong ROI, adoption falters if provider incentives are misaligned. "If the provider, the hospital, the doctor, the PA isn't making money or making as much money as if they were doing something else, the adoption of that technology", he adds, "isn't going to be adopted". Aligning innovation with reimbursement frameworks like CPT codes is essential, not just bureaucratic compliance, but a strategy for adoption.

To ensure long-term use, caregiver training must evolve. Wagner advocates for virtual reality tools that allow providers to revisit procedures on-demand." The night before, they can go in and review a rotator cuff surgery". This approach, Wagner notes, helps keep procedures fresh in caregivers' minds and builds the confidence needed for consistent, high-quality care.

Avoiding Pilot Purgatory: Design for Scale and Measure Outcomes

Many diagnostic startups fall into the trap of pilot purgatory; endlessly testing without achieving scale. Wagner urges founders to build for scalability from the start. "You want to avoid bespoke pilots. You want to build repeatable, interoperable solutions", he advises. "Think sustainable and repeatable from day one".

That starts with clearly defined success metrics. "What is the definition of success? What are we going to measure? What are we going to monitor?", Wagner says. Without this clarity, even strong technologies risk stalling.

Internal champions are also essential. "If you don't have a champion, you're dead in the water", Wagner notes. But champions need proof points. If a solution can cut the cost of a $15,000 procedure in half without compromising care, it becomes a compelling case for adoption.

For Wagner, credibility isn't built on marketing language; it's built on measurable outcomes. He warns against relying on vague promises or optimistic framing. "You don't want to come in and say, we think and we feel and we believe that this is great because it's going to save you time and it's going to be a better patient experience", he explains. While such claims may sound appealing, they rarely move the needle. "It sounds wonderful, but none of that I can take to the bank".

Instead, he stresses the importance of hard data. "You are going to have data that backs up any of those 'claims', not what you're saying, but what the data is saying". 

Trust, Targeting, and the Power of Digital Omnichannel

For home diagnostics to scale, companies must adopt omnichannel marketing that builds trust and drives referrals. Wagner outlines four essentials: proof-driven content, SEO, referral enablement, and social proof. "Use physician testimonials, patient stories, and clinical data to create proof-driven content", he says. That content should then be optimized for search queries to drive visibility.

Co-branding with hospitals and providing partners with ready-to-use public relations kits can boost both reach and credibility. Complementing this with personalized social campaigns, local media appearances, and targeted landing pages helps break through the noise and drive meaningful engagement. "In today's world, it's like, I don't know about you, but I get 1500 emails a day", Wagner notes. "If it's not targeted, if it's not segmented, if it's not personalized", he adds, "forget that channel".

The AI Advantage: Scaling Personalized Diagnostics

Wagner views AI as the engine behind modern diagnostics, enabling earlier intervention, personalized care, and greater efficiency. "AI can flag deterioration before symptoms emerge, it's proactive care", he explains, especially valuable in managing chronic conditions.

Personalized diagnostics are advancing as AI algorithms now assist clinicians in narrowing down the most probable diagnoses in real time. For example, during mammography screenings, AI can analyze the images and highlight specific areas of concern. This allows radiologists to focus their review and deliver same-day results, improving speed, accuracy, and patient experience.

AI also harmonizes fragmented data from wearables, apps, and health systems. "We think it could be these top three things. That's pretty cool", Wagner notes.

What Makes a Diagnostic Startup Fundable?

From Wagner's perspective as a private equity advisor and board member, a startup's viability depends on five pillars: clinical validation, scalability, reimbursement clarity, strong leadership, and defensible data.

"Investors just like deflation",  when there's no clear path to reimbursement, he notes, underscoring that without financial visibility, even strong technologies are likely to stall. 

He also stresses that investors back teams, not just products. "People tend to invest in management, not so much the widget, believe it or not". Founders must demonstrate expertise across commercialization and compliance.

Finally, data defensibility is critical. "Is there a defensible data moat or are there patents?", Wagner adds, "atat makes it secure, so that a large company or even a foreign competitor like China can't easily copy or replicate it?". Without intellectual property or proprietary datasets, many startups face existential risks in crowded markets. For investors, the strength of this moat increasingly defines the ceiling on valuation and speed to exit.

Key Takeaways for Executive Leaders

• Home diagnostics are now mission-critical: No longer a peripheral tool, at-home testing and monitoring have become central to transforming chronic care, supporting earlier intervention, remote management, and improved access.
• SaaS and AI are the connective tissue of scalable care: These platforms enable data interoperability, real-time clinical relevance, and personalized care pathways, making them indispensable for healthcare systems aiming to scale impact.
• Success depends on three fundamentals: Clinical rigor, patient-centered design, and go-to-market discipline. Whether you're a startup or a global incumbent, aligning to unmet clinical and customer needs, across patients, providers, and payers, is non-negotiable for commercialization and scale.