title: Application of statistical graphics to facilitate selection of health status measures for clinical practice and evaluative research.
abstract: Relatively little attention has been directed towards the study of the ability of health status measures to demonstrate clinically meaningful change. We examined the use of Tukey's stem and leaf plots and time-path diagrams to assess the sensitivity of a health status measure in showing change. We compared the evaluative characteristics of the physical ability scales of the Sickness Impact Profile (PSIP), and the SF-36 (PSF-36), in 54 consecutive patients undergoing elective primary or revision total hip replacement. To validate time-path diagrams, we used patients' perception of change in physical function (transition question) as an external standard. At baseline there was no clustering at the end of the scales. At 3 months, the distribution of the PSIP showed a clustering at the upper end of the scale and a strong skewness towards lower scores, whereas the PSF-36 showed a wide distribution of the scores. Seven out of 54 patients had perfectly normal scores on the PSIP at 3 months, whereas one patient had a perfect score on the PSF-36 at 3 months. In time-path diagrams the response pattern of the PSIP was similar to that of the PSF-36, with the exception of the patient-fifth with the best initial health status. The overall impression of the time-path diagram for these patients was that of no change. A closer examination revealed that half of these patients had horizontal or downwards sloping lines, indicating a worsening in physical function. However, all these patients perceived themselves as improved. The PSIP has a ceiling effect for patients with relatively good physical health. It was concluded that stem and leaf plots are useful in the assessment of health status measures, for discriminative purposes, to differentiate patients' health cross-sectionally. Time-path diagrams stratified by baseline health status with information on patients' perception or valuation of change provide useful information about the ability of an instrument to detect change over time.
authors.affiliation: Department of Rheumatology and Physical Medicine, University Hospital Zurich, Switzerland. ruzstg@ruz.unizh.ch
authors.forename: G
authors.initials: G
authors.lastname: Stucki
authors.forename: M H
authors.initials: MH
authors.lastname: Liang
authors.forename: S
authors.initials: S
authors.lastname: Stucki
authors.forename: J N
authors.initials: JN
authors.lastname: Katz
authors.forename: R A
authors.initials: RA
authors.lastname: Lew
mesh_terms: D019644:Arthroplasty, Replacement, Hip; D003430:Cross-Sectional Studies; D005260:Female; D005500:Follow-Up Studies; D006304:Health Status; D006801:Humans; D008297:Male; D008875:Middle Aged; D010003:Osteoarthritis / Q000503:physiopathology / Q000601:surgery; D017063:Outcome Assessment, Health Care / Q000706:statistics & numerical data*; D012086:Reoperation; D012680:Sensitivity and Specificity; D018434:Sickness Impact Profile; D013223:Statistics as Topic / Q000379:methods*; D016896:Treatment Outcome