LTC Deal Valuation Tool: Advanced Pricing Intelligence for Senior Care Properties Author: Diana Lalchan, Levin Associates Edition: July 2025 A machine learning approach to property valuation in the seniors housing and skilled nursing market
Executive Summary Levin Associates is pleased to introduce a breakthrough machine learning-based valuation tool for the senior care property market. This innovative tool provides users with data-driven price estimates for senior care facilities, offering insights based on sophisticated predictive modeling that incorporates numerous market factors. With a 2025 predictive accuracy of 93.0% for the optimized blended model (a substantial improvement from 68.5% latest-year performance of the previous generation), this tool serves as a critical resource for property appraisers, brokers, lenders, and investors focused on the seniors housing and skilled nursing market. The LTC Deal Valuation Tool leverages a proprietary dataset of actual market transactions to deliver reliable price estimates expressed as a price per unit/bed. By accounting for property characteristics, financial metrics, market conditions, and macroeconomic factors, the tool provides comprehensive valuation intelligence that would otherwise require extensive market research and analysis.
July 2025 model refresh at a glance ● ● ● ●
Recency-optimized training window (transactions ≥ 2023) to better reflect current market pricing dynamics Log-target training (log1p of price per unit) for stability on the upper tail Blended inference for Assisted Living (AL) and Independent Living (IL): price-model PPU blended with cap‑rate-implied PPU when operating margins are high Latest-year results on 2025 deals: ○ Price-only (≥2023, log target): R² ≈ 0.889 ○ Blended (AL/IL OM gating, τ=0 optimized): R² ≈ 0.930 ○ Overall blended R² ≈ 0.854 (expected trade-off vs. maximizing 2025 performance)
The Challenge: Accurate Property Valuation in a Complex Market The senior care property market poses unique valuation challenges: ● ● ● ● ●
Market Heterogeneity: Diverse property types (Assisted Living, Skilled Nursing, CCRC, Independent Living, Active Adult) with different operational models and revenue structures Geographic Variations: Significant pricing differences across regions, states, and market types Evolving Financial Dynamics: Fluctuating cap rates, revenue multiples, and yield expectations Macroeconomic Sensitivity: Impact of interest rates and broader economic trends on valuations Data Fragmentation: Limited publicly available comprehensive transaction data
These challenges make traditional valuation approaches potentially less reliable and more time-intensive, creating an opportunity for advanced analytics to improve valuation accuracy and efficiency.
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