Utilizing National Survey Data to Benchmark Comprehensive Care in a Large Health System

Area of Science:

• Health Services Research
• Primary Care Medicine
• Health Informatics

Background:

• Comprehensiveness in primary care, defined as the breadth of services offered by healthcare teams, is crucial for patient outcomes.
• Existing metrics for comprehensiveness are limited; this study introduces a novel approach using International Classification of Diseases, 10th Revision (ICD-10) codes.

Purpose of the Study:

• To develop and validate a novel measure of primary care comprehensiveness based on ICD-10 code distributions.
• To assess the ability of this measure to differentiate primary care from specialty care.

Main Methods:

• Compared ICD-10 code distributions from a large academic health system population with the National Ambulatory Medical Care Survey (NAMCS).
• Employed linear regression and mathematical inner product for comparative analysis.
• Analyzed code distributions across different specialty areas.

Main Results:

• Linear regression showed a strong correlation (R²=0.62) between the study population's ICD-10 code patterns and NAMCS data.
• The mathematical inner product effectively distinguished primary care from specialty care based on ICD-10 code distributions.
• Primary care practices demonstrated a distinct pattern of ICD-10 codes compared to specialty care.

Conclusions:

• ICD-10 code distributions offer a stable and potentially generalizable method for assessing comprehensive care.
• The inner product of ICD-10 code distributions provides a quantitative measure to distinguish primary care from specialty care.
• This novel metric enhances the evaluation of primary care delivery and comprehensiveness.