Life Sciences

Claims Data to Predict Product Use and Revenue

FAIR Health offers the developers, manufacturers and marketers of clinical and life science solutions the rare opportunity to view in a single dataset trends in market-level data including utilization, cost and the demographics and geographic location of the patients who use or might need the services or devices they offer. Our unique, actionable analytics and record-level data offer insights into clinical practice patterns, help assess the commercial market for products related to medical services or diagnoses and support research into life sciences solutions—and thereby provide a reliable basis for revenue projection, inventory management and return on investment.

R&D analysts, product managers, commercial and clinical researchers, pharmaceutical and durable medical equipment (DME) manufacturers and distributors—and their research funders, investors and advisors—can turn to FAIR Health’s claims data, benchmarks and custom analytics for many functions.

  • Research: Findings based on our vast repository of privately billed claims data can supplement or validate research. Our de-identified member data allow longitudinal studies that include population health analyses and the assessment of the patient’s beginning-to-end treatment path.
  • Market assessment: An analysis of privately billed charges and allowed amounts benchmarks for specific procedures and services can help size the market and point out underserved geographic regions that might be suitable for expansion.
  • Market development: Manufacturers of medical equipment and devices can use our data to provide healthcare systems with insights about equipment utilization or to negotiate with carriers for reimbursement for a new device or drug treatment based on the value it brings.
  • Customer demographic analysis: Our data allow the creation of prospective customer marketing profiles, including procedure and location, diagnoses and comorbidities, de-identified member data and demographic information, such as age and gender.
  • Product efficacy tracking : Our de-identified member data can track the patient’s care and provide insight into product efficacy. For example, data about de-identified patients who use a new opioid treatment might show subsequent trends in the incidence of overdoses.

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Life Sciences