Development and Validation of the Pediatric Medical Complexity Algorithm (PMCA) Version 3.0

Area of Science:

• Pediatric Health Services Research
• Medical Informatics
• Health Outcomes

Background:

• Classifying pediatric medical complexity is crucial for resource allocation and care management.
• Existing algorithms require updates to incorporate newer coding systems like ICD-10-CM.
• The Pediatric Medical Complexity Algorithm (PMCA) is a key tool for this classification.

Purpose of the Study:

• To modify the PMCA to include International Classification of Diseases, Tenth Revision, Clinical Modification (ICD-10-CM) codes.
• To assess the sensitivity and specificity of the new PMCA version 3.0 for classifying pediatric chronic disease (CD) levels.
• To evaluate the algorithm's performance in identifying children with complex chronic disease (C-CD).

Main Methods:

• PMCA version 2.0 was updated with ICD-10-CM codes to create version 3.0.
• The algorithm was applied to hospital discharge data for children with emergency department, day surgery, or inpatient encounters.
• A random sample of 300 children was reviewed to ascertain medical complexity levels and validate algorithm performance.

Main Results:

• PMCA version 3.0 demonstrated 86% sensitivity and 86% specificity for identifying complex chronic disease (C-CD).
• The algorithm achieved 65% sensitivity and 84% specificity for noncomplex chronic disease (NC-CD).
• For children without chronic disease, PMCA 3.0 showed 77% sensitivity and 93% specificity.

Conclusions:

• PMCA version 3.0 is a validated, publicly available algorithm for identifying children with C-CD.
• The updated algorithm exhibits strong sensitivity and specificity in classifying pediatric medical complexity using hospital discharge data.
• Performance is comparable to earlier PMCA versions, supporting its utility in clinical settings.