The American Journal of Managed Care March 2015
Strategy for a Transparent, Accessible, and Sustainable National Claims Database
The article outlines the strategy employed by FAIR Health, Inc, an independent nonprofit, to maintain a national database of over 18 billion private health insurance claims to support consumer education, payer and provider operations, policy makers, and re-searchers with standard and customized data sets on an economi-cally self-sufficient basis. It explains how FAIR Health conducts all operations in-house, including data collection, security, validation, information organization, product creation, and transmission, with a commitment to objectivity and reliability in data and data products. It also describes the data elements available to re-searchers and the diverse studies that FAIR Health data facilitate.
Am J Manag Care. 2015;21(3):e186-e188
The article explains the history and operation of an independent national claims database, FAIR Health’s National Private Insurance Claims (FH NPIC) database, and its use by:
- Consumers to estimate fees for medical and dental services in their geograph-ic areas;
- Payers, institutional and professional providers and business for claims ad-ministration, business planning, tracking treatment trends and disparities, and other purposes; and
- Researchers and policy makers for a wide range of diverse studies such as adherence to protocols, geographic and other variations in treatments, impact of changes in law and policy, and healthcare economics.
A recent American Journal of Managed Care article1identifying “barriers” to creating a national health-care claims database offered an unduly discouraging perspective. Focusing on a selective research organization, it overlooked, and to some extent mistakenly portrayed, what has already been accomplished in “Big Data” for the healthcare sector. The experience of FAIR Health, Inc, in creating, operating, and expanding its national health-care claims database offers a more positive account. FAIR Health’s database already provides data to researchers as well as to payers, providers, government agencies, and policy makers. It also offers significant ongoing service to consumers in the form of a free online search tool to find the estimated cost of healthcare services and procedures in their own area using ordinary, consumer-friendly language, both in English and Spanish (and not solely arcane codes, as was mistakenly referenced in the recent article). In estab-lishing its database and making it broadly available, FAIR Health has found solutions to problematic barriers and has identified operational requirements and features essential to a successful database.
FAIR Health is a national, independent, not-for-profit corporation created in 2009 as part of a settlement of an investigation of healthcare insurers by the New York State Attorney General. Its mission is to bring transparency to healthcare costs and health insurance information through robust, unbiased data products and solutions that meet the needs of all stakeholders in the healthcare sector.
To carry out its mission, FAIR Health recruited a strong and diverse board of directors as well as experienced man-agement and an expert staff which, in consultation with a national academic consortium, designed and established a growing, consolidated physical database (with a fully redun-dant, geographically separated business continuity site) that now contains more than 18 billion private claims records. All operations—from data collection, validation, organiza-tion, and testing through production, distribution, and tech-nical support—are conducted in-house using FAIR Health’s own state-of-the-art, scalable, secure technology.
By having all of its human, technical, and data resources belong to a single orga-nization that controls all aspects of its op-erations, FAIR Health is able to increase efficiency, responsiveness, compliance, in-novation, accountability, and adherence to mission. These resources enabled the organization to overcome the distribution and transport problems outlined in the earlier article and to make its data acces-sible in appropriate formats to all partici-
pants in the healthcare industry. FAIR Health can receive and consolidate data transmitted in varied formats and can produce and distribute data sets in media and formats compatible with different information technology (IT) systems. Its in-house capability enables it to maintain a busy, year-round production schedule for a growing ar-ray of standard products updated twice yearly (as well as hundreds of custom analytics) which are organized by standard codes and approximately 500 geographic areas nationwide, while at the same time fueling its efforts in consumer engagement and research support. Because of its IT capacity and its expert and motivated staff, FAIR Health is able to react quickly and creatively to fulfill unique and complex research data requests.
Essential to the acceptance of any data source is us-ers’ confidence in its credibility. FAIR Health’s status as an independent, self-sustaining organization, unaffiliated with any private group or governmental body, underlies its reputation for objectivity and reliability. The general unrestricted availability of FAIR Health data and its use by a wide variety of groups in the healthcare sector, as well as its incorporation in statutes and regulations and use by government agencies, evidence its acceptance.
FAIR Health’s standards for data contribution and validation give its database the scale, representativeness, and integrity essential for serious research. As part of the legal settlement that created FAIR Health, Syracuse University created the Upstate Health Research Network (UHRN), a national consortium of experts in statistics, health policy and practice, coding, systems, and technol-ogy at major universities. FAIR Health consulted with this group to determine the best methods for collecting, testing, and validating data, organizing it temporally and geographically so that it could both support consumer and industry needs and provide a rich research resource. At UHRN’s advice, FAIR Health adopted statistical testing, validating, and production practices recognized as sound and objective by experts in the relevant fields. In addi-tion, FAIR Health has sought the advice of independent legal experts on its compliance with the Health Insurance Portability and Accountability Act, the Health Informa-tion Technology for Economic and Clinical Health Act, and antitrust and other regulatory regimes. FAIR Health continues to review, refine, and enhance its database and products with the oversight and advice of its board of di-rectors and the nationally recognized experts serving on its scientific advisory board.
Approximately 60 insurers and claims administra-tors—including some of the largest national companies, collectively representing plans covering more than 151 million individuals—contribute data to FAIR Health. Contributors must comply with FAIR Health submission standards, including the requirement that they submit all claims records. Data related to nondiscounted fees for ser-vices, proper procedure codes, dates of service, places of service, allowed amounts, and other information are used to create FAIR Health’s standard benchmark products. This information, along with additional data elements in the contributed claims, comprise FAIR Health’s National Private Insurance Claims (FH NPIC) database. Both stan-dard product data and FH NPIC data sets are available to researchers.
Research conducted with FAIR Health data has ex-plored a variety of topics. With nationwide data organized into highly specific geographic areas, variations in diagno-ses, treatment protocols, facility usage, and costs can be readily distinguished by geography, jurisdiction, and com-munities’ economic profiles, both at a particular time and over longer periods. FAIR Health data can facilitate the determination and measurement of the impact of changes in public policy by comparing usage data before and after the change. Groups studying alternatives to the custom-ary fee-for-service paradigm can use FAIR Health data to inform the design and evaluation of capitation and bundled payment arrangements. Likewise, FAIR Health private sector data can be vectored with data from public health programs to help reveal critical variations in cost, utilization, and treatment protocols.
While FAIR Health has focused principally on research licenses to academics and scholarly institutions, it recog-nizes that substantial research is conducted outside aca-demia, and it licenses data for research to non-academic institutions as well. University faculty, hospital managers, government agencies, consultants, and businesses are all represented among the diverse licensees of FAIR Health data for research purposes. FAIR Health requires that ap-plicants for research licenses have adequate technical ca-pacity, appropriate security, and a defined and legitimate need for specific data. However, FAIR Health believes that making its data widely available accords with its mission and it does not limit the number of its research licenses, nor does it evaluate or restrict, except as legally and practi-cally necessary, applicants’ areas of inquiry.
Establishing, maintaining, and refreshing a substan-tial database is an expensive endeavor. Sustainability is critical to the viability and quality of the database and should be an essential objective from its inception. Long-term reliance on government or industry support entails risks: future changes in budgetary and policy priorities and shifts in markets and the economy may reduce or eliminate these sources of funding. Structuring a database enterprise that can be self-sustaining obviates reliance on uncertain sources of support and avoids real and appar-ent conflicts that might arise if the operation were overly dependent on interested, potentially conflicted funders.
FAIR Health’s creators had the foresight to empower the organization to pursue revenue-generating activities that support the ongoing development of its database and that are consonant with, and facilitate the accomplish-ment of, its societal mission. An innovative agreement, whereby industry paid settlement funds to the state of New York and government officials allocated monies from those funds to FAIR Health, facilitated the successful launch of FAIR Health, the expansion and diversification of its operations, and its rapid evolution into a financially self-sufficient organization. FAIR Health’s ability to meet diverse clients’ needs, accommodate idiosyncratic IT sys-tems, work collaboratively with researchers and govern-ment officials, and transform its data, data products, and proprietary technology tools to serve new purposes have been integral to its ongoing achievements. FAIR Health’s transparency, flexibility, and financial strategy offer the research community and policy makers an instructive ex-ample of the development of a sound and accessible na-tional claims database.
Author Affiliations: FAIR Health, Inc, New York, NY.
Source of Funding: None.
Author Disclosures: Ms Gelburd is president of FAIR Health, Inc.
Address correspondence to: Robin Gelburd, FAIR Health, Inc, 575 5th Ave, 22nd Fl, New York, NY 10017. E-mail: firstname.lastname@example.org.
1. Newman D, Herrera C-N, Parente ST. Overcoming barriers to a research-ready national commercial claims database. Am J Manag Care. 2014;20(11 spec no. 17):eSP25-eSP30. n