Healthcare Feasibility Is a Different Animal

Consumer feasibility is simple compared to healthcare. You want 500 moms aged 25-44? Fine, go buy sample. You want 150 board-certified oncologists who've prescribed a specific biologic in the last 6 months? That's a completely different project.

HCP research has constraints that don't exist anywhere else. Physician verification adds time and cost. Panel penetration for specialists is abysmal compared to consumer. A general population panel might reach 60-70% of U.S. adults. A physician panel might cover 15% of a given specialty, and the ones who are on the panel are already over-researched.

Patient studies are worse. If you're studying a rare disease with 50,000 diagnosed patients in the U.S., and your panel has a 0.3% penetration against that population, you're looking at maybe 150 reachable people before you apply any screening criteria. The incidence math gets brutal fast.

What the tool does

You specify whether you're targeting HCPs or patients. For HCPs, you pick the specialty, set your prescribing or procedural criteria, and the tool estimates your reachable universe based on published physician counts and typical panel coverage rates. For patients, you input the condition prevalence and diagnosis rate.

The cost modeling is the part people underestimate. HCP CPIs run $80-$400+ depending on specialty and LOI. Neurologists are expensive. Dermatologists are slightly less expensive. PCPs are the cheapest because there are more of them and they're more willing to do surveys. The tool factors all of this into the budget estimate.

Tech stack

Same React 18.2 + Babel CDN setup. The physician supply data comes from published AMA statistics and industry benchmarks. Panel penetration rates are based on aggregated industry estimates, not any single vendor's numbers. The CPI ranges reflect what I've seen across 20+ years of fielding these studies.