Outcome after total hip arthroplasty: Comparison of a traditional disease-specific and a quality-of-life measurement of outcome

The purpose of this study was to examine the relationship between the Harris Hip Score (HHS), a traditional method of patient assessment of a total hip arthroplasty (THA), and the Medical Outcomes Study 36-Item Short-Form Health Survey (SF-36), a commonly used health-related quality-of-life survey. One hundred forty patients returning for routine clinical follow-up evaluation of a primary THA were asked to fill out the SF-36 quality-of-life survey, as well as questions concerning their perceptions of their THA. The patient's surgeon assessed the THA with the traditional HHS. The correlations between the HHS and the SF-36 domains were highest in the physical component summary scores for male patients of all ages and female patients 65 years of age or older. The correlations were lower for the mental component summary scores of all patients, but particularly in female patients younger than 65. When the SF-36 scores were compared with age and sex-matched population norms, both age and sex were found to be important. Men younger than 65 had scores lower than norms in the physical function domains, but were comparable in the mental health domains. The older men had scores comparable to the norms in all domains. Female patients of all ages, however, had lower scores in the physical function domains. The greatest differences were noted in the female patients younger than 65. The HHS is commonly used to assess disease-specific pain and function in THA patients; however, the results of this study suggest that the SF-36 health survey can capture additional important quality-of-life domains that are influenced by a THA and that these domains are influenced by the age and sex of the patient. The combination of a disease-specific scoring system and a quality-of-life survey would allow a more global assessment of a THA in all patients. Studies evaluating the results of THAs should either assess the results of male and female patients separately when sample size is sufficiently large or use sex as a possible covariate in a multivariate analysis.