Developing and Evaluating Composite Measures of Cancer Care Quality

Abstract

Background: Composite measures are useful for distilling quality data into summary scores; yet, there has been limited use of composite measures for cancer care.

Objective: Compare multiple approaches for generating cancer care composite measures and evaluate how well composite measures summarize dimensions of cancer care and predict survival.

Study design: We computed hospital-level rates for 13 colorectal, lung, and prostate cancer process measures in 59 Veterans Affairs hospitals. We computed 4 empirical-factor (based on an exploratory factor analysis), 3 cancer-specific (colorectal, lung, prostate care), and 3 care modality-specific (diagnosis/evaluation, surgical, nonsurgical treatments) composite measures. We assessed correlations among all composite measures and estimated all-cause survival for colon, rectal, non-small cell lung, and small cell lung cancers as a function of composite scores, adjusting for patient characteristics.

Results: Four factors emerged from the factor analysis: nonsurgical treatment, surgical treatment, colorectal early diagnosis, and prostate treatment. We observed strong correlations (r) among composite measures comprised of similar process measures (r=0.58-1.00, P<0.0001), but not among composite measures reflecting different care dimensions. Composite measures were rarely associated with survival.

Conclusions: The empirical-factor domains grouped measures variously by cancer type and care modality. The evidence did not support any single approach for generating cancer care composite measures. Weak associations across different care domains suggest that low-quality and high-quality cancer care delivery may coexist within Veterans Affairs hospitals.