Comorbidity-adjusted complication risk: a new outcome quality measure

Area of Science:

• Health Services Research
• Medical Informatics
• Quality Improvement

Background:

• Traditional outcome measures like mortality rates are insufficient for differentiating hospital care quality.
• Inpatient complications offer a more sensitive indicator of care quality due to their frequency and direct link to care processes.

Purpose of the Study:

• To develop and validate a novel measure for assessing inpatient complication risk.
• To provide a tool for evaluating patient care delivered by hospitals and physicians using readily available data.

Main Methods:

• Developed a decision-theoretic model to estimate complication probability based on International Classification of Diseases, 9th Revision, Clinical Modification (ICD-9-CM) diagnoses.
• Created Comorbidity-Adjusted Complication Risk (CACR) using patient-level UB-82/92 data, controlling for comorbidities.
• Validated CACR using large datasets from Pennsylvania, California, and Florida, and direct hospital data.

Main Results:

• CACR effectively estimates complication risk at patient and provider levels, adjusting for case mix.
• Risk adjustment had less impact on CACR compared to mortality and morbidity measures.
• CACR demonstrated wide variation across hospitals, stability over time, and correlation with established quality metrics.

Conclusions:

• Comorbidity-Adjusted Complication Risk (CACR) is a reliable and sensitive measure for assessing inpatient care quality.
• CACR's reliance on common data makes it broadly applicable for quality monitoring and comparison.
• The measure's stability and correlation with other quality indicators support its use in healthcare performance evaluation.