Healthcare organizations depend on data to understand their markets, patient populations, and competitive position. But even the biggest datasets can’t deliver accuracy when the total population represented in the data, the denominator, is unknown. In claims analytics, this uncertainty is the rule, not the exception.
Healthcare organizations are moving faster than ever to make strategy, growth, and network decisions based on data. But here’s an uncomfortable truth: even datasets with massive “coverage” can distort market reality. They can double-count encounters, fragment patient journeys, and misrepresent how care actually flows across systems. Leaders relying on these signals often end up with inaccurate forecasts, skewed market insights, and blind spots they never knew existed.
The problem isn’t the volume of data. It’s what that volume truly represents. The industry’s traditional view of coverage equates size with completeness, but real confidence comes from data fidelity. Data fidelity measures how accurately the data reflects actual patient activity across encounters, payers, and systems. Fidelity has little to do with how big a dataset is and everything to do with whether the information is coherent, representative, and trustworthy.
When evaluating data vendors and in most RFPs, one of the first questions is still:
“What’s your claims coverage?” It’s a reasonable question, but not the right question.
Healthcare leaders have long treated coverage as a proxy for confidence. A bigger number feels safer. A national dataset feels more complete. But when leaders shift the question from “How much data do you have?” to “How true is the data you have?” the illusion becomes obvious. More data can actually distort the truth by:
These distortions propagate through dashboards, forecasts, and strategic plans. Decisions start to feel precise, even when the underlying information is incomplete. The problem is not just missing data; it's actually missing awareness of what’s missing. Kythera Labs tackles this head-on by redefining coverage not as volume, but as precision, representativeness, and truthfulness.
Data fidelity refers to how accurately a dataset reflects true patient activity across encounters, payers, and systems. It measures:
Fidelity acknowledges both what the data does show and what it cannot show, and unlike volume, fidelity can be evaluated, quantified, and improved.
Many leaders assume that plugging in additional data sources will “close the gap.” Without reconciliation and mastering, however, more sources usually multiply the distortion. Each new source brings its own: identifiers, coding standards, submission rules, clearinghouse behavior, and payer-specific pathways.
Without normalization and mastering, these differences lead to duplicate claims, conflicting records, missing encounters, false attribution, and blind spots in payer or specialty groups.
At scale, slight distortions may grow into large failures that mislead market forecasts, leakage estimates, and assessments of referral dynamics. The danger isn’t the absence of data. Instead, it creates the illusion of completeness.
To counter distortion, Kythera approaches coverage as a multi-dimensional fidelity problem, not a single number. Fidelity is analyzed across three critical levels:
Do observed encounters align with modeled expectations based on incidence, prevalence, and utilization? Where does the data over- or under-represent true demand?
Are certain providers or specialties overrepresented? Is payer mix balanced?
Is clearinghouse bias creating blind spots?
Are encounters linked into coherent journeys? Are duplicates removed? Is missingness quantified, not hidden?
This framework moves coverage from a vague percentage to a measure of analytic reliability. Analysts understand what is known, what is uncertain, and how uncertainty may impact a decision.
Fidelity requires rigorous methodology and mastering. Kythera transforms raw claims into decision-ready assets through a disciplined process that includes:
The outcome is not just a clean dataset; it is a faithful representation of real healthcare activity, the foundation for trustworthy insights. Kythera applies the same discipline to forecasting by modeling only what can be known with confidence.
When Fidelity Leads, Better Decisions Follow
Coverage is not about how much data a vendor has, but instead how well the data reflects what is real. The industry’s longstanding reliance on volume has created a false sense of certainty. Fidelity replaces that illusion with measurable integrity. It helps leaders distinguish what they can trust from what they cannot see.
By examining coverage across the market, practitioner, and patient dimensions, Kythera enables organizations to make decisions rooted in the healthcare system as it truly operates, not as a dataset assumes it does.
When fidelity becomes the standard, healthcare leaders gain more than better datasets. They gain clarity, confidence, and the ability to turn data into decisions grounded in truth.
Ryan Leurck, Chief Analytics Officer https://www.linkedin.com/in/ryanleurck/
