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California spends approximately $367 billion a year on health care. That’s more than the gross domestic product of South Africa or Denmark. It’s more than the state spends on six years of K-12 education, or 23 years of transportation. In other words, it’s a lot. Many say it’s too much.

When you don’t really know where the money is going, or what value it is generating, how can you determine where to save money? That’s a key question for California policymakers. To answer it, the state is taking another look at developing an all-payer claims database. This is a large database that collects and aggregates health care claims from public and private payer sources, everyone from Medicare and Medicaid to UnitedHealth Group and Anthem. States use these databases to examine market dynamics, build consumer transparency tools, and better understand trends in health and the use of health care.


About 20 states have built, or are in the process of building, all-payer claims databases. A few others, including California, have multipayer claims datasets. These often cover only a portion of the state, and never include all of its payers.

Freedman Healthcare, a data-focused consulting firm I founded in 2005, helps states create all-payers claims databases and support them. Building such a database sounds like it might be an expensive endeavor. It isn’t. The cost is minimal when viewed in relation to health care spending.

In a 2016 article in the New England Journal of Medicine, I noted that the annual cost of securely collecting, storing, and analyzing data for a small to mid-sized all-payer claims database runs between $1.5 and $3 million per year. California estimates the annual cost of building and maintaining its statewide database will be in the “low millions.” Based on the experience of other large states, and factoring in California’s complexity, a ballpark estimate of $20 million a year, at least in the early years of development, seems fair. That’s less than one-hundredth of a percent of the state’s annual health care expenditures. So, if an all-payers claims database could reduce California’s health care spending by just 1 percent, it would provide a 100-to-1 return on the investment.


Just how are states using all-payer claims databases to improve health, create more efficient and effective delivery systems, and spend less? Those were among the questions recently posed by a bipartisan group of U.S. senators who launched the Health Care Price Transparency Initiative. Here are a few of the examples my colleagues and I shared with them:

Providing consumers with price and quality differences. Dozens of state-funded websites list cost and quality comparisons of medical services that are powered by all-payer claims data. The price differences they report are astounding. In New Hampshire, for example, a basic blood test costs 10 times as much at some labs than others, according to NH HealthCost, a state Department of Insurance website that uses all-payer claims data. Some of these databases make substantial investments in website marketing and design. As consumers learn about these resources, visit them, and find them easier to navigate once they arrive, traffic increases.

Evaluating market function. Many states use all-payer claims databases to better understand the market share of insurers and providers and its impact on price, inflation, and access. In Massachusetts, the attorney general’s office uses data from Massachusetts’ all-payer claims database, run by the Center for Health Information and Analysis, to evaluate proposed mergers. Meanwhile, the state’s Health Policy Commission uses the same dataset to conduct frequent assessments of market drivers such as utilization trends, alternative payment models, and health plan membership.

Measuring and improving performance. Tracking patient outcomes by medications prescribed, procedures received, providers seen, and financing models used can assess variation in care across a state and provide important knowledge to policymakers, providers, payers, and employers interested in population health management and quality measurement and reporting. The Maryland Health Care Commission, for example, used its all-payer claims database to document variation in avoidable complications across health care facilities for four high-volume procedures — hip replacements, knee replacements, vaginal deliveries, and hysterectomies. It is now sharing that information via its Wear the Cost website to engage policymakers, providers, consumers, health plans, and employers in conversations around health care costs and preventing complications. Other states, including Washington and Virginia, have analyzed their all-payer claims data to discover that hundreds of millions of dollars can be saved by reducing low-value care.

Monitoring public health. The ability to watch changes in incidence and prevalence of disease and other public health crises like opioid abuse provides tremendous value to state and local health departments. The Center for Improving Value in Health Care, Colorado’s all-payer claims database, showed that nearly 80 percent of patients who received a prescription for Subsys, an opioid prescription specific for cancer patients, did not have a cancer diagnosis.

So why hasn’t every state built an all-payer claims database? Not surprisingly, some health care providers and payers are reluctant to bring scrutiny to how they provide and buy care. They use their power to squash efforts to build these databases, or impose strict regulations that significantly limit how the data can be used.

States interested in fostering health, supporting efficient health care systems, lowering the sometimes obscene prices, and removing rampant waste should look closely at creating an all-payer claims database and giving it the necessary resources and regulatory freedom. Though they may face opposition from the foxes, these are henhouses worth building.

John Freedman, M.D., is the principal of Freedman HealthCare LLC, a national health care consulting firm.

  • All payer claims databases are at their most effective when all payers are included. Unfortunately, pursuant to the Gobeille decision self-insured employers can and do cite ERISA preemption to exclude the claims they pay from state databases. This leaves an important segment of the market hidden from poplicy makers and the public.

  • Strange to call for something that the courts have made unachievable, and not even mention Gobeille v. Liberty Mutual Insurance Company. However, Congress could require companies to give up their data.

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