The Transparency ImperativeFREE
Steven Brill's “Bitter Pill” Time cover story (1) shed disturbing light on the lack of price and quality transparency in U.S. health care. He reveals that many stakeholders in the health care system profit from concealed price and quality information, including poor-performing and high-priced insurers, providers, and suppliers (1). All of us are harmed through higher premiums and less-effective competition. Most important, patients may inadvertently place themselves at higher risk for injury or unwittingly pay more for poor-quality services.
The Patient Protection and Affordable Care Act (ACA) made significant albeit preliminary efforts to collect and disseminate price and quality data. More action is essential, by shifting the basis of competition from structural market power to delivery of better value. To achieve this, we propose the transparency imperative: All data on price, utilization, and quality of health care should be made available to the public unless there is a compelling reason not to do so. The transparency imperative is part of the foundation for a post-ACA health care system that achieves better quality and cost control.
Lack of Data on Price, Utilization, and Quality
Few patients have any knowledge of prices for any health care service, from a laboratory test to surgery. More important, obtaining such information is almost impossible. First, services comprise different inputs, so it's hard to obtain a unified price. Second, commercial prices are almost completely opaque. For example, differences in pricing power among hospitals has led to large disparities in price (typically more than 200%) within local markets, with little relationship to differences in quality (2). This remains true even within most preferred provider organization insurance networks.
It's very difficult for patients to discover how many procedures a physician or hospital performs, yet utilization is critical for informed decision making. Physician case volume is one of the most important predictors of quality for many surgeries and medical conditions. For instance, it is estimated that a urologist needs to perform more than 700 robotic prostatectomies before the learning curve flattens out (3, 4), yet determining how many procedures a urologist has performed is virtually impossible. Famously in 1979, the American Medical Association sued Medicare to block the release of data on the number of procedures billed to Medicare, claiming physician privacy (5).
Access to quality data is limited, and better performance has not led to gains in market share thus far. Few good-quality metrics exist, and the ones that do are largely limited to inpatient care processes for coronary artery bypass graft surgery, congestive heart failure, chronic obstructive pulmonary disease, diabetes, community-acquired pneumonia, pregnancy, hip replacement, knee replacement, and organ transplantation. Quality data that are publicly disclosed, such as Medicare's Hospital Compare, are of limited utility because they are reported vaguely in most cases as “No Different than U.S. National Rate” or “Better (or Worse) than U.S. National Rate.”
ACA and the Transparency Imperative
The ACA contains requirements to release Medicare claims and Physician Quality Reporting System (PQRS) data. However, very few of these data have flowed into the public domain, probably the biggest limitation being risk aversion. Unfortunately, the data have been released to only a few “qualified entities” (6). The intent was to be sure that such entities had the technical capacity to analyze the Medicare data responsibly. But the latest regulations significantly restrict the flow of data and preclude smart but inexperienced people on tight budgets from analyzing them (6).
Health Plans and the Transparency Imperative
Initially, one would think that health plans should have the greatest desire to make price and quality transparent to their members because they capture savings when members choose better-value providers. Unfortunately, transparency is not necessarily their top priority. To satisfy the desires of employees, many employers demand broad provider networks that include market-dominant providers, such as prominent academic centers that prohibit transparency in 30% to 40% of cases. They try to keep costs down by negotiating rates instead of providing information and guiding patients to better-value providers.
The Necessity of the Transparency Imperative
Price and quality information are imperative for new payment models. With expansion of risk-based reimbursement models like accountable care organizations and patient-centered medical homes, providers will have to identify high-value providers who can consistently deliver high-quality care with fewer complications at an affordable price to capture more savings, achieve quality metric goals, and earn higher incomes.
Implementing the Transparency Imperative and Protecting Privacy
For meaningful progress on transparency to occur, there must be a change in attitude throughout the system. All payers should be required to make their claims data publically available, with privacy protections, to enable quality measurement. Of importance, to protect privacy, the federal government should substantially increase the penalties for inappropriate patient re-identification.
Personalized pricing information should be made available for comparison before patients enter a care process. Both total price and patient price should be transparent to providers in shared-savings payment models to enable cost management. Only patient price should be available to providers in fee-for-service networks to mitigate the risk for price increases.
Fortunately, there is much that stakeholders can do. The federal government can relax restrictions on access to Medicare data. Other states should follow the lead of California and Massachusetts and require providers to disclose prices to patients before elective care. Health plans and employers should also support such transparency tools as Castlight (www.castlighthealth.com).
If we are going to bend the cost curve, a better functioning health care market is critical. Transparency is essential for patients to consume care from providers who deliver greater value. For providers, transparency is essential for risk-based reimbursement models to work. It is also the best approach to overcome local monopoly pricing power by providers. Most important, the current health care marketplace is ripe for patients to capture large and unjustified differences in price and quality. As more patients do this, we all benefit from more effective competition and health care prices that better reflect value.
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Freire MP, Choi WW, Lei Y, Carvas F, and Hu JC. Overcoming the learning curve for robotic-assisted laparoscopic radical prostatectomy. Urol Clin North Am. 2010;37:37-47. [PMID: 20152518] CrossrefMedlineGoogle Scholar
Alemozaffar M, Duclos A, Hevelone ND, Lipsitz SR, Borza T, Yu HY, et al. Technical refinement and learning curve for attenuating neurapraxia during robotic-assisted radical prostatectomy to improve sexual function. Eur Urol. 2012;61:1222-8. [PMID: 22425427] CrossrefMedlineGoogle Scholar
- 5. Florida Medical Association, Inc. v. U.S. Department of Health Education and Welfare, 601 F.2d 199, (M.D. Fla. 1979). Google Scholar
- 6. Availability of Medicare Data for Performance Measurement, 76 Fed. Reg. 76,542, (Dec. 7, 2011) (to be codified at 42 C.F.R. pt. 401). Google Scholar
Author, Article and Disclosure Information
From Venrock, Palo Alto, California, and University of Pennsylvania, Philadelphia, Pennsylvania.
Disclosures: Disclosures can be viewed at www.acponline.org/authors/icmje/ConflictOfInterestForms.do?msNum=M13-0783.
Corresponding Author: Robert P. Kocher, MD, Venrock, 3340 Hillview Avenue, Palo Alto, CA 94304.
Current Author Addresses: Dr. Kocher: Venrock, 3340 Hillview Avenue, Palo Alto, CA 94304.
Dr. Emanuel: University of Pennsylvania, 122 College Hall, Philadelphia, PA 19104.
Author Contributions: Conception and design: R.P. Kocher.
Analysis and interpretation of the data: R.P. Kocher.
Drafting of the article: R.P. Kocher, E.J. Emanuel.
Critical revision of the article for important intellectual content: E.J. Emanuel.
Final approval of the article: R.P. Kocher, E.J. Emanuel.
Provision of study materials or patients: R.P. Kocher.
Collection and assembly of data: R.P. Kocher.
This article was published at www.annals.org on 28 May 2013.