Objectives: To generate a scoring algorithm weighted on the preferences of consumers for assessing the quality of care in nursing homes (i.e., aged care homes or institutions) in six key domains. Methods: A discrete choice experiment was undertaken with residents of nursing homes (n = 126) or family member proxies (n = 416) in cases where severe cognitive impairment precluded resident participation. Analysis was undertaken using conditional and mixed logit regression models to determine preferences for potential attributes. Results: The findings indicate that all six attributes investigated were statistically significant factors for participants. Feeling at home in the resident's own room was the most important characteristic to both residents and family members. Care staff being able to spend enough time with residents, feeling at home in shared spaces, and staff being very flexible in care routines were also characteristics identified as important for both groups. The results of the Swait-Louviere test rejected the null hypothesis that the estimated parameters between residents and family members were the same, indicating that data from these two groups could not be pooled to generate a single weighted scoring algorithm for the Consumer Choice Index-Six Dimension instrument. Preferences were therefore encapsulated to generate scoring algorithms specific to residents and family members. Conclusions: This study provides important insights into the characteristics of nursing home care that are most valued by consumers. The Consumer Choice Index-Six Dimension instrument may be usefully applied in the evaluation, planning, and design of future services.