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Phreesia, Inc (PHR) Fair Value & Analysis

Healthcare · US · Market cap $580M

Price$9.15
Fair Value$5.16
Upside-43.6%
Quality97/100
Evidence: High Range $3.76 – $6.57

Analysis

Phreesia, Inc (PHR) currently trades at $9.15, while our model-based Fair Value estimate is $5.16 — implying the stock looks roughly 43.6% overvalued today. We read business quality at 97/100 (high quality), in the Healthcare sector. Bear case: priced above our estimate, the market already discounts strong expectations. Bull case: above-average quality can justify a premium — the entry price still matters most (evidence: high).

About the company

Phreesia, Inc. provides an integrated SaaS-based software and payment platform for the healthcare industry in the United States and Canada. It offers solutions including appointment optimization and referral management using AI-enabled workflows; and AI-based smart answering solution patient communications supported by voice and messaging solutions; integrated payment solutions embedded in intake and post-visit workflows, and financing solutions that enable healthcare organizations to accelerate cash collections while offering flexible payment options to patients; and digital intake and clinical data capture, patient engagement and activation tools, and measurement and analytics solutions. It also offers PhreesiaPads, a self-service intake tablets; and Arrivals Kiosks, which are on-site kiosks. The company serves a range of healthcare organizations including ambulatory practices, health systems, and hospitals, as well as life sciences companies, government entities, patient advocacy…

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How we calculate Fair Value

Each company is valued through a stack of independent intrinsic-value models (DCF variants, residual-income, multiples and more), blended into one family-balanced consensus and weighted by how much trustworthy data backs it. A separate quality layer scores the fundamentals. Every input is real reported data — nothing guessed.

Educational research only · not financial advice · no buy/sell recommendation. Model-based estimates are not certainties; their reliability depends on data quality and assumptions.