HealthStream, Inc (HSTM) Fair Value & Analysis
Healthcare · US · Market cap $749M
Analysis
HealthStream, Inc (HSTM) currently trades at $25.66, while our model-based Fair Value estimate is $13.81 — implying the stock looks roughly 46.2% overvalued today. We read business quality at 95/100 (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
HealthStream, Inc. provides Software-as-a-Service (SaaS) based applications for healthcare organizations in the United States. The company offers hStream, a technology platform; CredentialStream, provides healthcare organizations with tools to support the provider lifecycle management from recruiting, application submission, verification of licensure and other credentials, privileging, appointments by credentialing committees, enrollment, network, management, onboarding, and performance evaluations of providers; ShiftWizard; and Competency Suite, AI/ML-driven clinical competency development system. It also provides applications for performance appraisal, competency management, disclosure management, clinical competency, assessment, development, simulation-based education, clinical rotation and onboarding management, quality management, and industry training. The company's solutions help healthcare organizations in meeting their ongoing learning, clinical development, credentialing, …
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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.