How to Evaluate Health Insurance Companies Using Government Data
A framework for assessing health insurers using NAIC complaint data, CMS denial rates, and prior authorization metrics — beyond star ratings and marketing.
The best predictor of how a health insurer will treat you is how they treat their existing policyholders — measured by complaint ratios and denial rates, not marketing materials. PlainInsurer combines three government data sources to give you this picture in one place.
Why Government Data Is More Reliable Than Star Ratings
Health insurance star ratings on Medicare.gov and marketplace sites combine quality measures with member satisfaction surveys. While useful, they can be influenced by the demographic composition of a plan's membership and the plan's investment in survey-boosting initiatives. A plan with wealthy, healthy members may score well on satisfaction surveys regardless of how it handles complex claims.
Regulatory complaint data from NAIC and CMS captures a different dimension: how many policyholders were sufficiently dissatisfied to file formal complaints or had claims denied. These are observable behaviors, not survey responses.
PlainInsurer makes this data searchable across 229 tracked insurers so you can compare before choosing a plan. Unlike star ratings that can be gamed through targeted outreach, complaint ratios and denial rates reflect actual policyholder experiences at scale.
The Three Pillars of Insurer Evaluation
PlainInsurer combines three government data sources that, together, provide a comprehensive view of insurer behavior:
Complaint ratio (NAIC MCAS): How many formal complaints an insurer receives relative to its market share. This measures the frequency of disputes severe enough that policyholders escalate to regulators. Companies with ratios consistently above 1.5 show patterns of consumer friction that deserve investigation before you buy a policy.
Claim denial rate (CMS): What percentage of claims the insurer denies. This directly measures how often the company says "no" to coverage your doctor ordered. High denial rates increase your financial risk and create administrative burden — even if many denials are eventually reversed on appeal, the process costs time and stress.
Prior authorization denial rate (CMS, for MA plans): How often the insurer denies prior authorization requests. Prior authorization is required for many medications, procedures, and specialist referrals. High denial rates delay or prevent care. This metric is especially important for Medicare Advantage plan selection.
Reading the PlainInsurer Reputation Grade
What it tells you: The A-F grade combines all three metrics into a single composite score, normalized against the insurer population. An "A" grade means the company performs better than most peers on complaints, denials, and prior authorizations. An "F" means worse than most peers. Browse company rankings to see the grade distribution.
What it does not tell you: Whether the company's network includes your doctors, whether the premium fits your budget, or whether the coverage terms match your needs. The grade measures how the company treats claims and complaints — not whether the policy is right for your situation.
How to use it: Use the grade as a filter. Among plans that meet your coverage and price requirements, prefer companies with higher grades. A plan that is $20/month cheaper but has an F grade may cost you far more in denied claims and administrative hassle than the slightly more expensive A-grade alternative.
State-Level Variation Matters
Insurance regulation is state-based, and insurer behavior can vary significantly by state. A company with a good national complaint ratio may have elevated complaints in your state due to local market conditions, regulatory environment, or network adequacy issues. PlainInsurer shows state-level complaint data on each company profile page — always check your state specifically.
Network Adequacy: The Missing Metric
One critical dimension that complaint data and denial rates do not capture is network adequacy — whether the insurer has sufficient in-network providers in your area. An insurer can have excellent complaint ratios but limited specialist access in your county.
Network adequacy issues are the most common reason members experience access problems that do not show up in denial statistics — because the member never files a claim, they simply cannot get an appointment. Before selecting a plan, verify that your current doctors are in-network and that the plan has adequate specialist and hospital coverage in your geographic area. Check the insurer's provider directory and call your doctors' offices to confirm participation.
What This Means for You: A Practical Framework
Step 1 — Identify your candidate insurers. From your employer, marketplace, or Medicare options, list the companies offering plans you are considering.
Step 2 — Look up each on PlainInsurer. Check the reputation grade, complaint ratio, and denial rate for each company.
Step 3 — Compare within the same line. Health-to-health, not health-to-auto. Use our rankings page for sorted comparisons.
Step 4 — Check your state specifically. National grades are a starting point. State-level data may reveal a different picture for where you live and seek care.
Step 5 — Revisit annually. Insurer behavior changes over time. Check PlainInsurer before each renewal period to see if your current company's metrics have shifted since you last evaluated them. A company that was a strong performer two years ago may have deteriorated.
Common Questions
The most frequent questions readers ask about evaluating health insurance companies fall into four categories: which government datasets are available, how to compare companies objectively, what counts as a "good" denial rate, and how PlainInsurer's grades relate to financial-strength ratings. The FAQ entries below address each of these, with sourcing back to the NAIC Market Conduct Annual Statement and CMS Transparency in Coverage public-use file.
One question that comes up repeatedly deserves explicit attention: many readers ask whether a company with a high denial rate is necessarily "bad." The honest answer is that denial rate alone is not diagnostic. A health insurer specializing in high-cost or experimental therapies will deny more claims than one specializing in routine primary care, simply because the underlying clinical mix has more debatable cases. The denial rate becomes meaningful only when paired with the appeal-overturn rate (what share of denied claims are reversed on appeal) and the complaint ratio (whether policyholders are dissatisfied enough to escalate to regulators). PlainInsurer surfaces all three on each carrier's profile page.
Another common question concerns Medicare Advantage specifically. CMS publishes prior-authorization denial rates and contract-level overturn rates for every MA plan, and these metrics are particularly important for consumers choosing between an MA plan and Original Medicare with a supplement. A high prior-authorization denial rate signals that the plan's utilization-review process will create more friction in accessing specialist care, even if the eventual coverage decision matches Original Medicare. Consumers willing to accept that friction in exchange for lower premiums may still prefer MA; consumers prioritizing predictable access may prefer the supplement route.
Layering Quantitative Signals: A Comparison Framework
Health insurer evaluation works best when multiple independent quantitative signals are layered. PlainInsurer surfaces four signal types from public regulatory filings: NAIC complaint index, CMS Transparency in Coverage denial rate, prior-authorization activity, and market presence (number of states active, lines of business written). Each signal is computed by an upstream regulator using a documented methodology and is therefore comparable across insurers.
Why layering matters more than any single signal
A single quantitative signal can flag a problem but cannot distinguish between possible causes. A high complaint ratio can reflect coverage disputes, claims-handling friction, network access issues, or aggressive marketing — different sources of consumer friction. Layering complaint data with denial rate, prior-authorization activity, and appeals-overturn rate progressively localizes the friction source. When multiple signals point the same direction, the conclusion is more robust than when only one is elevated.
Reading the composite score
PlainInsurer aggregates these signals into a composite score using documented weights. The weights are an editorial choice — applying different weights to the same underlying NAIC and CMS data would produce a different ranking. The methodology page documents the weight selection and the source of each component. A composite score is a useful summary, but the per-component breakdown is more informative for making comparison decisions.
| Signal | Source | Comparison value | Caveat |
|---|---|---|---|
| NAIC complaint index | NAIC MCAS | Within-line consumer-friction index | Normalized to size; not severity-weighted |
| Claim denial rate | CMS Transparency | Share of claims denied (in-network) | ACA marketplace only; not all coverages |
| PA denial rate | CMS Transparency | Share of prior-auth requests denied | Service-category mix matters |
| Appeals overturn rate | CMS Transparency | Reversal share when challenged | Sample size varies by carrier |
Layered quantitative signals — complaint index, denial rate, PA activity, appeals overturn — describe a health insurer's consumer-friction record more reliably than any single number.
