Background: The measurement and valuation of quality of life forms a major component of economic evaluation in health care and is a major issue in health services research. However, differing approaches exist in the measurement and valuation of quality of life from a health economics perspective. While some instruments such as the EQ-5D-3L focus on health-related quality of life alone, others assess quality of life in broader terms, for example, the newly developed ICECAP-O. Objective: The aim of this study was to utilize two generic preference-based instruments, the EQ-5D-3L and the ICECAP-O, to measure and value the quality of life of older adult patients receiving post-acute care. An additional objective was to compare the values obtained by each instrument with those generated from two community-based general population samples. Method: Data were collected from a clinical patient population of older adults receiving post-acute outpatient rehabilitation or residential transition care and two Australian general population samples of individuals residing in the general community. The individual responses to the ICECAP-O and EQ-5D-3L instruments were scored using recently developed Australian general population algorithms. Empirical comparisons were made of the resulting patient and general population sample values for the total population and dis-aggregated according to age (65-79 and 80+ years) and gender. Results: A total of 1,260 participants aged 65-99 years (n = 86 clinical patient sample, n = 385 EQ-5D-3L general population sample, n = 789 ICECAP-O general population sample) completed one or both of the EQ-5D-3L and ICECAP-O instruments. As expected, the patient group demonstrated lower quality of life than the general population sample as measured by both quality-of-life instruments. The difference in values between the patient and general population groups was found to be far more pronounced for the EQ-5D-3L than for the ICECAP-O. The ICECAP-O was associated with a mean difference in values of 0.04 (patient group mean 0.753, SD 0.18; general population group mean 0.795, SD 0.17, respectively, p = 0.033). In contrast, the EQ-5D-3L was associated with a mean difference in values of 0.19 (patient group mean 0.595, SD 0.20; general population group mean 0.789, SD 0.02, respectively, p ≤ 0.001). Conclusions: The study findings illustrate the magnitude of the difference in patient and general population values according to the instrument utilized, and highlight the differences in both the theoretical underpinnings and valuation algorithms for the EQ-5D-3L and ICECAP-O instruments. Further empirical work is required in larger samples and alternative patient groups to investigate the generalizability of the findings presented here.