FAIR Health makes data and analytics available to researchers for studies on the full range of topics supported by our repository.
For researchers with third-party funding looking for data resources, FAIR Health offers a broad array of services tailored to the researcher’s particular needs. These might include:
- Assisting with framing study questions;
- Assessing whether FAIR Health data resources are responsive to the inquiry (e.g., performing diagnostics to determine whether the requisite volume of data is available to support the study);
- Providing assistance in estimating budgets for required data resources;
- Refining study design and providing analytic support;
- Generating de-identified, aggregated datasets;
- Populating data tables and developing other data visualizations; and
- Reviewing prepublication drafts to ensure data are represented accurately.
We do not limit or opine on researchers’ topics or theses. Our licensing fees are compatible with most research budgets, with pricing at cost.
For those without third-party funding, FAIR Health can often provide data and other in-kind support. Although in-kind support is subject to available resources, demand and data use policies, we provide many of the same services that we offer to third-party-funded research projects, including assistance with framing inquiries, diagnostics, aggregated datasets and data visualizations, among others.
Given the recent national focus on healthcare inequities, FAIR Health will prioritize supporting projects that profile underserved communities and explore disparities in healthcare quality and outcomes.
De-Identified, Aggregated Datasets
Based on researchers’ specifications, FAIR Health can extract custom datasets that can include elements such as patients’ age and gender distribution, ICD-9 and ICD-10 procedure codes, geographic locations, professionals’ specialties and more. Our data can inform a broad spectrum of studies, such as:
- Identifying trends in utilization and cost across places of service;
- Using de-identified member data to track patients’ beginning-to-end treatment paths;
- Tracking trends in diagnoses over time;
- Illustrating a hypothesis with the support of real-world data;
- Conducting population health analyses;
- Studying current issues affecting the national healthcare system; and
- Assessing the intended and unintended influence of laws and regulations.
Using our state-of-the-art technology, FAIR Health also can provide analytics customized to researchers’ particular needs.
Health White Papers and Data Briefs
In addition to making data available to researchers, FAIR Health produces its own independent white papers and briefs on various topics of national interest and public health concern. These widely disseminated publications cover critical public policy topics such as COVID-19, the opioid crisis, Lyme disease and food allergy, as well as annual reports on place of service trends and medical pricing.
Included in our white papers and briefs are a number of data visualizations and statistics that researchers are permitted to cite as references to support their own studies. For a sampling of how such data have already been incorporated in researchers’ publications, click here.
FH Benchmarks are relied upon by clients nationwide, including researchers who incorporate our benchmark data into their studies and publications.
FAIR Health uses the private claims data in our repository to generate cost benchmarks by procedure code and percentile (50th‐95th percentiles, although lower percentiles are available upon request), reflecting the distribution of billed charges and estimated allowed amounts for medical and dental services and procedures across all 50 states; Washington, DC; Puerto Rico; and the US Virgin Islands.
A suite of self-contained modules organized by service type, FH Benchmarks aggregate claim records from our database by official healthcare code (e.g., CPT®1 and CDT®2) and geozip (geographic area usually determined by the first three digits of a zip code), and array benchmarks for each procedure/geozip combination into percentiles.
For more information on FAIR Health benchmark data products, click here.
2 The Code on Dental Procedures and Nomenclature is published in Current Dental Terminology (CDT), American Dental Association (ADA). All rights reserved.
New York University (NYU) Capstone Project
FAIR Health has been selected to participate as a “client” in the capstone program for NYU Robert F. Wagner Graduate School of Public Service. Completing a capstone project is part of NYU Wagner’s core curriculum and provides students with a critical learning experience and opportunity to perform a public service. FAIR Health is working with a small team of students within the school for a full academic year. The capstone team will generate actionable findings to help inform policies and clinical guidelines in response to the COVID-19 pandemic. This analysis will not only build upon FAIR Health’s previous studies, but also will help to directly inform public health responses and decision making based on patient outcomes data. The final report from the capstone team could help serve as the basis for guidelines and recommendations for treatments, vaccination distribution and clinical practices in management and testing.