Abstract

This study examines two questions that relate to patients' role in medical decision making: (1) Do patients utilize multiple attributes in evaluating different treatment options?, and (2) Do patient treatment preferences evidence heterogeneity and disparate patterns? Although research has examined these questions by using either individual- or aggregate-level approaches, the authors demonstrate an intermediate level approach (ie, relating to patient subgroups). The authors utilize growth augmentation therapy (GAT) as a context for analyzing these questions because GAT reflects a class of nonemergency treatments that (1) are based on genetic technology, (2) aim to improve the quality (rather than quantity) of life, and (3) offer useful insights for the patient's role in medical decision making. Using conjoint analysis, a methodology especially suited for the study of patient-consumer preferences but largely unexplored in the medical field, data were obtained from 154 parents for their decision to pursue GAT for their child. In all, six attributes were utilized to study GAT, including risk of long-term side effects (1:10,000 or 1:100,000), certainty of effect (50% or 100% of cases), amount of effect (1-2 inches or 4-5 inches in adult height), out-of-pocket cost ($100, $2,000, or $10,000/year) and child's attitude (likes or not likes therapy). An experimental design using conjoint analysis procedures revealed five preference patterns that reflect clear disparities in the importance that parents attach to the different attributes of growth therapy. These preference patterns are (1) child-focused (23%), (2) risk-conscious (36%), (3) balanced (23%), (4) cost-conscious (14%), and (5) ease-of-use (4%) oriented. Additional tests provided evidence for the validity of these preference patterns. Finally, this preference heterogeneity related systematically to parental characteristics (eg, demographic, psychologic). The study results offer additional insights into medical decision making with the consumer as the focal point and extend previous work that has tended to emphasize either an individual- or aggregate-based analysis. Implications for researchers and health care delivery in general and growth hormone management in particular are provided.

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