PubMed · 11884331
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J Martin Bland, Douglas G Altman. 2002-03-09. Statistics Notes: Validating scales and indexes.. https://doi.org/10.1136/bmj.324.7337.606
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OBJECTIVES: To assess the growth of quality of life measures and to examine the availability of measures across specialties. DESIGN: Systematic searches of electronic databases to identify developmental and evaluative work relating to health outcome measures assessed by patients. MAIN OUTCOME MEASURES: Types of measures: disease or population specific, dimension specific, generic, individualised, and utility. Specialties in which measures have been developed and evaluated. RESULTS: 3921 reports that described the development and evaluation of patient assessed measures met the inclusion criteria. Of those that were classifiable, 1819 (46%) were disease or population specific, 865 (22%) were generic, 690 (18%) were dimension specific, 409 (10%) were utility, and 62 (1%) were individualised measures. During 1990-9 the number of new reports of development and evaluation rose from 144 to 650 per year. Reports of disease specific measures rose exponentially. Over 30% of evaluations were in cancer, rheumatology and musculoskeletal disorders, and older people's health. The generic measures--SF-36, sickness impact profile, and Nottingham health profile--accounted for 612 (16%) reports. CONCLUSIONS: In some specialties there are numerous measures of quality of life and little standardisation. Primary research through the concurrent evaluation of measures and secondary research through structured reviews of measures are prerequisites for standardisation. Recommendations for the selection of patient assessed measures of health outcome are needed.
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Surgery has been trying to catch up to evidence-based medicine. Assessment of outcome in surgery is the child for quality assurance of patient care. We surgeons have our own set of mental variables that can predict good and poor outcomes. We value our experience and that of others, yet, are always inquisitive about which best predict morbidity and mortality. We all have our own functional equations for outcome that varies qualitatively and quantitatively. The main problem is lack of a uniform mathematical equation for individual patient risk factors that we refer to because of the limitations inherent in the equation or our understanding and awareness. Reviewing the literature in surgical outcome measurement, the impression is one of increasingly diverse messages with conclusions that are institution dependent. This can initiate confusion and controversy when comparing outcomes or extrapolating to one's own practice while hindering training surgeons to contribute to the evolving evidence of objective quality measurement early in a career. Overall, we are falling behind in recognizing this evolving problem. In this article, I address this controversy and attempt to offer new avenues in achieving a consensus among us in patient risk-adjusted outcomes by adopting and modifying well-recognized risk scoring systems from either side of the Atlantic Ocean. The millennium should see the birth of a new generation of surgeons charged with evidence-based ideas in quality outcome measurement and ready to improve current mathematical models.