LTC Deal Valuation Tool: Advanced Pricing Intelligence for Senior Care Properties
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 datadriven price estimates for senior care facilities, offering insights based on sophisticated predictive modeling that incorporates numerous market factors. With an overall predictive accuracy of 88.5%, this tool serves as an important resource for property appraisers, brokers, lenders, sellers and investors focused on the seniors housing and skilled nursing market.
The LTC Deal Valuation Tool leverages a proprietary dataset of actual market transactions from the last three decades 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.
This tool could not be possible without the help of our friends in the industry who broker, finance and participate in M&A transactions and provide us with the data necessary to derive the most accurate statistics and valuation metrics in the market. We appreciate all that they do for the industry.
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/Memory Care, Skilled Nursing, CCRC, Independent Living, Active Adult) with different operational models and revenue structures
• Geographic Variations: Significant pricing differences across regions, states, regulatory environments, market types and even neighborhoods
• Evolving Financial Dynamics: Fluctuating cap rates, inconsistent periods of cash flow to value, 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
The tool also cannot replace the on-the-ground market knowledge and expertise that an experienced broker can provide with an opinion of value. It is meant to be one of many datapoints in the assessing of value. There are other factors that can have a significant effect on price, like whether a property is involved in a foreclosure or had a new competitor open in the immediate vicinity, that only a broker, appraiser or local investor will know.
Our Approach: Data Science Meets Market Expertise
The development of the LTC Deal Valuation Tool followed a systematic, data-driven methodology:
1. Data Collection and Preparation
• Assembled a comprehensive dataset of verified senior care property transactions from Levin Associates’ proprietary database going back 30+ years
• Gathered multiple data points per transaction: price, property attributes, financial metrics, location data
• Incorporated macroeconomic indicators and market classification systems
• Applied rigorous data cleaning and normalization processes while preserving market nuances
Note: The proprietary transaction data has been transformed through the modeling process, ensuring that individual transaction details remain confidential. The tool provides predictions without exposing any sensitive information shared with Levin Associates.
2. Feature Engineering and Selection
Through meticulous analysis, we identified the key factors that most significantly influence property values:
Top Features by Importance:
1. NOI per Unit (38.2%)
2. Facility Type (18.3%)
3. Sale Date (9.2%)
4. Revenues (5.2%)
5. Year Built (4.7%)
6. Net Operating Income (4.6%)
7. Age (4.0%)
8. Revenue per Unit (3.9%)
9. Median Household Income (2.5%)
10. SF per Unit/Bed (2.2%)
Note: Percentages represent relative importance in the model’s predictive capability
3. Model Selection and Optimization
We selected CatBoost for its exceptional performance in this domain. CatBoost offers several key advantages for property valuation:
• Superior handling of categorical variables: Effectively processes non-numeric data like facility types, states, and regions
• Robust performance with mixed data types: Seamlessly integrates financial metrics, dates, and categorical information
• Resistance to overfitting: Maintains predictive accuracy across different market segments and time periods
• Ability to capture complex non-linear relationships: Models the subtle interactions between multiple valuation factors
• Transparent feature importance: Provides clear insights into which factors drive valuations
The model underwent hyperparameter optimization and cross-validation to ensure reliable performance across diverse market scenarios.
Model Performance and Validation
The LTC Deal Valuation Tool demonstrates strong predictive capabilities with the following performance metrics:
• R² Score: 0.8846 (88.46%)
o This metric indicates that our model explains 88.46% of the variation in property values
o In practical terms, this means the tool captures the vast majority of factors that influence senior care property pricing, and future versions of the tool will look to improve the accuracy and flexibility of the model
• Error Metrics:
o Root Mean Square Error (RMSE): $24,581.90 per bed/unit
o Mean Absolute Error (MAE): $16,311.04 per bed/unit
What These Metrics Mean:
• R² Score (coefficient of determination): Measures how well the model explains the variance in property prices. A score of 0.8846 demonstrates exceptional predictive power, capturing nearly 90% of price variations.
• RMSE: Indicates the standard deviation of prediction errors. The lower this value, the more accurate the model.
• MAE: Represents the average difference between predicted and actual values, providing an intuitive measure of accuracy.
These metrics indicate that:
• The model provides reliable valuations across different property types and market conditions
• In approximately 50% of cases, predictions will be within ±$16,311 per bed/unit of actual transaction values
• In approximately 95% of cases, predictions will be within ±$24,582 per bed/unit of actual transaction values
Model Strengths
• Comprehensive factor analysis: Incorporates 16 key valuation drivers
• Strong predictive power: 88.46% accuracy (R²) in explaining price variations
• Market adaptability: Performs consistently across facility types and regions
• Temporal relevance: Captures evolving market trends through the Sale Date feature
• Financial focus: Gives appropriate weight to critical NOI and revenue metrics
• Geographic intelligence: Accounts for location value through region, state, and market type variables
Limitations and Considerations
• Unique property features: Exceptional property attributes or recent renovations may not be fully captured
• Extreme outliers: Unusual transactions or properties may receive less accurate valuations
• Market shifts: Sudden major market changes may require model recalibration
• Specialized properties: Highly unconventional facilities may fall outside the model’s primary training data
• Complementary tool: Should be used alongside professional judgment and market expertise (see disclaimer)
Tool Implementation and User Experience
The LTC Deal Valuation Tool is designed for intuitive use while providing sophisticated analytics. Users can:
1. Enter property details:
o Physical characteristics (units/beds, year built, property type)
o Location information (state, region, market type)
o Financial metrics (revenues, NOI)
o Market conditions (occupancy rate, 10-year Treasury rate)
2. Receive comprehensive valuation outputs:
o Estimated price per unit/bed with confidence intervals
o Total property value
o Key valuation metrics (cap rate, EBITDA multiple, price-to-revenue ratio)
3. Gain market insights:
o Contextual understanding of value drivers
o Comparison to typical market ranges
o Add a datapoint to your evaluation of property acquisitions or market studies
The tool’s clean, professional interface makes sophisticated valuation intelligence accessible to all market participants, from experienced dealmakers to those newer to the senior care real estate sector.
Practical Applications
The LTC Deal Valuation Tool offers valuable support for multiple stakeholders in the senior care property market:
• Brokers: Quick validation of listing prices and offers; data-backed client guidance
• Investors: Initial screening of acquisition targets; support for investment committee materials
• Lenders: Preliminary underwriting reference; validation of proposed deal valuations
• Appraisers: Supplementary data point; efficiency in initial valuation assessments
• Operators: Market positioning analysis; portfolio valuation insights
• Sellers: Help determine if now is the time to sell your asset
Across all applications, the tool serves as a complementary resource to professional expertise, providing data-driven insights while acknowledging the importance of nuanced market knowledge.
Conclusion
The LTC Deal Valuation Tool represents a significant advancement in bringing data science to bear on the challenges of senior care property valuation. By combining Levin Associates’ deep market knowledge with machine learning techniques, we have created a resource that enhances decision-making capabilities across the industry. And we are excited to further improve the tool’s accuracy and usefulness.