Prediction by clinicians of quality of life for children and adolescents with cardiac disease

Costello, J. M.; Mussatto, K.; Cassedy, A.; Wray, J.; Mahony, L.; Teele, S. A.; Brown, K. L.; Franklin, R. C.; Wernovsky, G.; Marino, B. S.

J Pediatr. 2015 Feb 28; 166(3):679-683.e2

Abstract

OBJECTIVE: To determine whether clinicians could reliably predict health-related quality of life (HRQOL) for children with cardiac disease, the level of agreement in predicted HRQOL scores between clinician sub-types, and agreement between clinician-predicted HRQOL scores and patient and parent-proxy reported HRQOL scores. STUDY DESIGN: In this multicenter, cross-sectional study, a random sample of clinical summaries of children with cardiac disease and related patient and parent-proxy reported HRQOL scores were extracted from the Pediatric Cardiac Quality of Life Inventory data registry. We asked clinicians to review each clinical summary and predict HRQOL. RESULTS: Experienced pediatric cardiac clinicians (n = 140), including intensive care physicians, outpatient cardiologists, and intensive care, outpatient, and advanced practice nurses, each predicted HRQOL for the same 21 pediatric cardiac patients. Reliability within clinician subspecialty groups for predicting HRQOL was poor (intraclass correlation coefficients, 0.34-0.38). Agreement between clinician groups was low (Pearson correlation coefficients, 0.10-0.29). When comparing the average clinician predicted HRQOL scores to those reported by patients and parent-proxies by Bland Altman plots, little systematic bias was present, but substantial variability existed. Proportional bias was found, in that clinicians tended to overestimate HRQOL for those patients and parent-proxies who reported lower HRQOL, and underestimate HRQOL for those reporting higher HRQOL. CONCLUSIONS: Clinicians perform poorly when asked to predict HRQOL for children with cardiac disease. Clinicians should be cognizant of these data when providing counseling. Incorporating reported HRQOL into clinical assessment may help guide individualized treatment decision-making.

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