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    Home»Health & Fitness»US Health & Fitness»Healthcare ‘quality’ is broken. Here’s how to fix it. – The Health Care Blog
    US Health & Fitness

    Healthcare ‘quality’ is broken. Here’s how to fix it. – The Health Care Blog

    News DeskBy News DeskMay 18, 2026No Comments9 Mins Read
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    Healthcare ‘quality’ is broken. Here’s how to fix it. – The Health Care Blog
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    By OWEN TRIPP

    For decades, quality in healthcare has been defined on industry terms — not people’s terms. New technology and innovative health plan designs are finally changing that.

    People know quality when they see it, and they are definitely not seeing it in healthcare. Fifty-six percent of Americans rate the quality of care as “poor” or “fair,” and 90% believe we’re overpaying for it. Likewise, 80% of employers — collectively the largest purchasers of healthcare in the country — say that higher-quality care is a top priority for their workforce.

    And yet, the U.S. healthcare system remains a global leader; a lack of know-how or quality control isn’t the problem. The problem is the wide gap between how the healthcare industry has historically defined quality and how quality is experienced by the people actually receiving and paying for care.

    For the past 75 years, healthcare quality has been shaped by a grab bag of federal agencies, accrediting bodies, medical organizations, health insurers, and — more recently — consumer-focused ratings outfits ranging from U.S. News & World Report to Zocdoc. Though many pay lip service to patient experience, none has clearly defined quality — or explained it intuitively enough — to help individuals make smarter healthcare decisions based on their clinical and financial context.

    Healthcare needs to move beyond narrow metrics and top doc lists to create a dynamic, value-driven view of quality that consistently connects people to the best care for them, where and when they need it — and ideally, even before they know they need it. Too often, “quality” equates to some numbers on a dashboard, when it needs to be more like a combination of GPS and driver-assist technology: guiding people to their health goals, keeping them in the highest-quality lane, and nudging them if they start to drift.

    This was always the vision (for some of us). But we simply haven’t had the right mix of technology and system-wide connectivity to bring it to life. Now we do.

    AI and dynamic alternative health plan designs — to name just two innovation hot spots — are finally putting people and purchasers in the driver’s seat by making healthcare quality multidimensional, personalized, and actionable.

    1. Multidimensional

    In virtually every other purchasing decision, consumers optimize for quality based on need, preference, priorities, and budget. Healthcare is the outlier. Providers and insurers (among others) have made this decision-making impossible by carving up key dimensions of quality — outcomes, experience, and cost — that people rightly view as a whole. (This was the basic idea behind the Triple Aim, which still holds up two decades later.)

    No one in healthcare has successfully optimized for all dimensions. Hospitals and health systems have optimized for outcomes by focusing on specialty care and cutting-edge treatments that boost their U.S. News ranking — while also driving up unit costs. Insurers have optimized for cost through utilization management and tactics like prior authorization — while also degrading the healthcare experience for patients and providers.

    This fragmentation has led us astray. Without a clear roadmap for getting to quality, people fall back on word of mouth, iffy ratings, and unreliable health plan directories. As a result, many people unwittingly see lower-quality doctors, undergo unnecessary procedures, and bypass cost-effective primary care for high-priced specialists at highly rated hospitals. Yet every day, even at world-class academic medical centers, physicians of varying expertise make questionable decisions — such as recommending surgery — that fail to consider the whole person, significantly impacting outcomes and healthcare spending for individuals and populations alike.

    In 2014, I co-founded Grand Rounds (since rebranded as Included Health) to fill the gaps in existing quality metrics and guide people to the best possible care by building a fuller picture of individual clinical judgment and individual patient needs. With the aid of machine learning, we analyzed billions of data points to untangle the associations between physician characteristics and credentials, health claims, patient experience ratings, and the many contextual factors — including the quality of the institution where a physician works, and the patient’s specific medical history — that influence downstream clinical and financial outcomes.

    Considering quality across all dimensions makes all the difference. With more than a decade of data under our belt, we’ve consistently found that people who connect with higher-quality providers and settings via our platform experience better outcomes and are more likely to stay engaged in care, which in turn generates short- and long-term cost savings by (for example) reducing avoidable surgeries, ER visits, and hospitalizations.

    2. Personalized

    But we also knew from the start that quality is more complex than labeling “good” and “bad” doctors. The reality is, some doctors are excellent for certain needs and certain patients, but not for others. Even for two people with the same underlying medical condition, quality can look very different, depending on their clinical, financial, and social context. That’s where personalization comes in.

    Incorporating each person’s unique context into how we define quality is a profound and long-overdue shift in mindset. Instead of stopping at conventional provider metrics and retrospective claims data — which are important but incomplete — a truly personalized, person-first approach requires tapping into a much broader range of data sources to proactively adjust for patient-provider fit and surface the highest-quality care for that person, at that moment in time.

    This level of personalization is challenging to scale, but AI has changed the game. Now, the machine learning underlying next-generation quality platforms can dynamically leverage data from hundreds of sources across the healthcare ecosystem, including the EHR, prior clinical interactions, and patient-stated needs and preferences. Additionally, personalized AI healthcare assistants are proactively collecting insights 24/7 that help (human) care teams create individual care plans to keep people “in quality” throughout their healthcare journey.

    Even before people express a specific need, chat-based interactions provide a longitudinal record of personal health goals, what’s working (or isn’t), and relevant barriers or constraints. If a person needs a Spanish-speaking provider close to public transportation, for example, or prefers virtual primary care to in-person care, those signals can now seamlessly inform real-time recommendations and guidance.

    3. Actionable

    Personalization behind the scenes isn’t enough, however. A critical third step is feeding quality-related insights back to people in easy-to-understand terms that make them feel confident in their next best action. At Included Health, we’ve found that explaining the rationale behind recommended providers in our digital app, at the right level of detail, increases the likelihood that the person will follow through on that recommendation and actually schedule an appointment.

    A simple, user-friendly view of quality is especially important when it comes to provider networks and cost-sharing. The tiered networks that underpin most HMOs, PPOs, and high-deductible health plans — and the corresponding differences in cost — are notoriously confusing to consumers. The lack of clarity into why certain doctors or facilities are in- vs. out-of-network, how quality is defined, and how that translates into coinsurance and deductibles leads people to make suboptimal decisions, resulting in fragmented and drawn-out care, higher out-of-pocket costs, and increased waste and inefficiency in the system overall.

    This long-standing pattern is driving a surge of interest in alternative health plans that combine quality-based networks and simple, transparent pricing — often copays only — to incentivize and guide people toward quality. The most sophisticated of these plans incorporate dynamic networks, AI-first digital experiences, and clear financial signals to guide people to high-quality, high-value care.

    Musculoskeletal conditions are a prime example. For a routine knee X-ray, variance in quality across facilities is quite low; we should guide people toward a nearby low-cost facility, rather than the expensive academic medical center downtown. But if the X-ray suggests a knee replacement, provider and facility quality suddenly become highly variable and important — and the academic medical center may then offer the best outcome at the lowest possible cost.

    We can’t expect the typical consumer (or any of us, for that matter) to make this type of calculation on their own. They need guidance, and to be truly actionable at the point of care, that guidance has to be built into the front-end experience. With the help of AI, healthcare quality platforms — just like the navigation and safety systems in our cars — need to instantaneously translate the mass of available data into simple visual cues, personalized nudges, and clear direction. Any definition of “quality” that doesn’t keep people moving toward their goal isn’t doing its job.

    A generational opportunity

    The confluence of new technology and new thinking outlined here has created a pivotal moment in healthcare. For the first time, healthcare innovators are empowered to simultaneously optimize for outcomes, experience, and cost with the necessary nuance and speed. That’s a generational opportunity — a mandate, even — but it comes with a responsibility.

    Quality has to be at the center of the healthcare experience. Provider recommendation tools and other quality platforms have proliferated in recent years, and many have failed to deliver lasting value to people and purchasers. If the definition of quality at the core of these platforms is narrow, flawed, or (worst of all) biased in favor of stakeholders with an interest in the status quo, they run the risk of exacerbating the subpar outcomes and unsustainable costs dragging down U.S. healthcare.

    No matter how sophisticated the technology, if we don’t redefine quality in a way that puts people first, we’ll still be heading in the wrong direction. The good news is, for the first time, we have everything we need to get it right.

    Owen Tripp is the co-founder and CEO of Included Health, a personalized all-in-one healthcare company.

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