Healthcare Technology: Challenges in Business Success – Insights from Kim Chi-weon

Article – There’s a quiet but expensive reality that every doctor knows, and every investor in health technology needs to learn. A patient can receive the most cutting-edge diagnostic test, a marvel of modern artificial intelligence, and the treatment plan can remain exactly the same. The test may soothe a physician’s uncertainty, but it does not change the trajectory of care. In the unforgiving economics of healthcare, where every dollar is scrutinized by insurers and hospital administrators, that is often the difference between a viable business and a fascinating science project.

This is the core insight from Kim Chi-weon, a physician and investor whose new book, Healthcare Business, serves as a stark primer for anyone looking to enter this most complex of markets. Speaking with Korea Biomedical Review, Kim laid bare a fundamental truth: healthcare does not operate like other consumer industries. A person’s deep concern for their wellbeing does not translate into a willingness to pay for a health app or a smartwatch subscription. And a superior piece of technology does not guarantee a single hospital will use it. The path from clinical value to commercial success is a gauntlet run past patients, doctors, hospital systems, and, most critically, the entities that pay the bills.

The most common and costly mistake, Kim argues, is misreading the market’s patience. Large corporations are accustomed to a two- or three-year horizon for a new venture to prove itself. In healthcare, even with flawless execution, you may be looking at a five- or ten-year journey. “When revenue has not materialized after about three years, companies often conclude, ‘This doesn’t work,’ and shut the business down,” Kim observed. The casualty is often not a bad idea, but one that simply required more time to navigate the Byzantine reimbursement systems and entrenched clinical workflows.

This long-game perspective is what makes Samsung’s continued push into wearable health so noteworthy, according to Kim. While its mobile health business hasn’t yet yielded clear financial results, the company’s persistence is itself a rare strategy among Korean conglomerates. The real challenge and the potential breakthrough lie in the next step. “If wearables already give users access to a range of health data, one possible path is to connect that data to medical care or health management services,” Kim explained. It’s a vision that moves beyond simply selling hardware to building a service ecosystem—a far more formidable, but necessary, ambition for any serious health player.

The conversation around artificial intelligence in medicine perfectly illustrates Kim’s central thesis about value. He draws a critical distinction between what he calls first-generation and second-generation AI. The first generation are tools that help doctors see what they can already see just a bit faster or more accurately—like an AI that highlights potential anomalies on a chest X-ray. From an insurer’s perspective, Kim notes, they’ve already paid the doctor to read that scan. Why should they pay an extra fee just to make that existing task marginally easier?

The second generation, however, uncovers the invisible. It identifies risks or treatment responses that are beyond human perception. Imagine an AI that analyzes a standard MRI to predict a patient’s likelihood of responding to a new, expensive Alzheimer’s drug, information previously only available through costly and inaccessible specialty scans. “If AI can predict risks that physicians could not previously identify and, as a result, save patients who might otherwise die… the rationale for paying for it changes,” Kim stated. This is technology that alters outcomes, not just workflows. It provides a clear, economic argument to the payer: this tool will help us spend our money more effectively by targeting the right patients.

This payer-focused logic must guide any company looking at the vast U.S. market, a common target for Korean digital health firms. Kim warns against simply being dazzled by its size. The structure of payment is everything. In the U.S., inpatient hospital care is often reimbursed through “bundled payments”—a single fee for an entire episode of care. If a new AI tool is used on a hospitalized patient, the hospital likely cannot bill for it separately. It becomes a cost, not a revenue generator. “Hospitals are unlikely to spend large amounts on inpatient technology with ambiguous benefits,” Kim cautioned. The business model must be designed from the outset to fit within these rigid economic structures.

For the entrepreneurs driving this change, Kim believes the defining quality isn’t technical brilliance, but a specific kind of intellectual agility. Healthcare is too layered for anyone to have all the answers at the start. The crucial skill is a founder’s “ability to listen to people from different backgrounds—clinicians, insurers, investors and technologists—synthesize what they say and reach better conclusions.” The best founders, he finds, are those who can absorb conflicting advice from these disparate stakeholders and evolve their business model accordingly. They understand that resistance from within the healthcare system is rarely about obstinacy; it is often about structural realities that a newcomer has failed to grasp.

The ultimate message of Kim’s analysis is one of sober respect. The healthcare industry is not a consumer market waiting to be disrupted by a better app. It is a massive, delicate, and deeply regulated system charged with protecting human life. New technologies should not expect preferential treatment. Instead, innovators must first understand why the system operates as it does. The goal is not to tear it down, but to advance it—ensuring it continues to function for everyone while thoughtfully integrating the tools that offer genuine, demonstrable value for patients and payers alike. It is a slow, difficult, and absolutely essential pursuit.

• Understanding market patience is vital.
• Healthcare does not operate like other consumer industries.
• First-generation AI tools merely enhance existing workflows.
• Second-generation AI offers insights beyond human perception.
• Business models must accommodate structured payment systems.
• Intellectual agility is more crucial than technical brilliance.