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Summary of Practice Expenses Associated with Comprehensive Primary Care Capabilities

Core Content

This document presents a study on the costs associated with implementing comprehensive primary care (CPC) capabilities in primary care practices. It was conducted to support the Centers for Medicare & Medicaid Services (CMS) in developing alternative payment models (APMs) that can adequately reimburse practices for these capabilities. The study developed and piloted a new method for estimating practice expenses, focusing on detailed, practice-specific data rather than standardized metrics.

Main Points

• Purpose: To estimate the marginal costs of comprehensive primary care capabilities and provide insights into the variability of these costs across practices.
• Policy Context: The U.S. healthcare system faces high costs and uneven quality, often due to fragmented care and poor coordination. Strengthening primary care is a key policy goal, and CMS has introduced initiatives like CPC and CPC+ to encourage the adoption of comprehensive care capabilities.
• Methodology: A mixed-methods approach was used, involving interviews with practice leaders and frontline personnel, and the use of a researcher-assisted cost-reporting workbook to collect detailed data on labor and non-labor expenses.
• Cost Estimation: The study estimated the marginal costs of these capabilities, net of any fee-for-service (FFS) revenues. These costs were not total operational costs but rather the incremental costs of providing the specific capability.
• Findings:
  • Practices varied significantly in the capabilities they adopted and the associated costs.
  • Labor expenses generally exceeded non-labor costs, and ongoing annual costs were higher than one-time startup costs.
  • There were discrepancies between practice leaders and frontline staff in estimating labor costs, with an average disagreement rate of 28%.
  • The most commonly adopted capabilities included empanelment, same-day or next-day office visits, patient education and self-management support, and software-based communication infrastructure.
  • Medication management had the highest annual median cost per full-time-equivalent (FTE) primary care practitioner (PCP) at $11,496, while extended hours had the lowest cost at $0 due to lack of marginal costs.
• Challenges:
  • Data collection was time-consuming and required significant effort from both practices and researchers.
  • Practices affiliated with larger organizations faced more scheduling and coordination challenges.
  • There was uncertainty in estimating startup costs, especially for those incurred years prior to the study.

Key Information

• Sample Size: 50 practices were included in the study, selected for diversity across CPC+ participation status, geographic region, rural status, size, and parent-organization affiliation.
• Data Collection:
  • Initial interviews with practice leaders identified capabilities and associated costs.
  • Frontline personnel interviews were used to validate labor cost estimates.
  • A cost-reporting workbook was used to gather detailed data on labor and non-labor expenses.
• Cost Analysis:
  • The study found that cost variation was partially due to differences in the level of service provided, not just price differences.
  • It emphasized the importance of detailed capability descriptions for accurate cost estimation.
• Recommendations:
  • Future payment models should be based on detailed capability data to avoid under- or over-reimbursement.
  • Longer data collection periods, greater financial incentives, and complementary methods like time and motion analysis may improve accuracy.
  • Additional methodological development is needed to better estimate startup costs, capture costs from parent organizations, and standardize patient-panel size calculations.

Conclusion

The new method for estimating practice expenses associated with comprehensive primary care capabilities provided CMS with valuable insights into the financial implications of these capabilities. It highlighted the need for detailed data collection and underscored the importance of aligning payment models with the actual services and costs involved in comprehensive primary care. The study also pointed out the challenges in collecting such data and suggested future improvements to enhance accuracy and efficiency in cost estimation for primary care practices.

Key Capabilities and Their Costs

Limitations

• The study could not quantify the relative contributions of service level and price variation to cost differences.
• Discrepancies between practice leaders and frontline staff were noted, particularly in labor cost estimates.
• Startup cost estimates were often uncertain, especially for those incurred years prior.

Future Considerations

• A larger-scale mixed-methods approach could provide a more robust basis for future payment models.
• Additional methodological development is needed to improve accuracy in cost estimation, particularly for startup costs and patient-panel size.
• Complementary methods, such as time and motion analysis, may help reduce discrepancies in labor cost estimates.