Quality of life measures in health care. II: Design, analysis, and interpretation.
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Biomedical subjects
Publications and source records attributed to D Spiegelhalter.
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Many clinicians remain unsure of the relevance of measuring quality of life to their clinical practice. In health economics quality of life measures have become the standard means of assessing the results of health care interventions and, more controversially, the means of prioritising funding; but they have many other applications. This article--the first of three on measuring quality of life--reviews the instruments available and their application in screening programmes, audit, health care research, and clinical trials. Using the appropriate instrument is essential if outcome measures are to be valid and clinically meaningful.
Only clinical trials can assess the impact of prototype medical decision-aids, but they are seldom performed before dissemination. Many problems are encountered when designing such studies, including ensuring generality, deciding what to measure, feasible study designs, correcting for biases caused by the trial itself and by the decision-aid, resolving the "Evaluation Paradox", and potential legal and ethical doubts. These are discussed in this paper.
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The amount of larynx seen at intubation was assessed in 633 adult patients undergoing routine surgery. Various measurements of the head and neck were made in an attempt to discover which features were associated with difficulty with laryngoscopy (defined as the inability to see even the arytenoids). In addition 38 patients, reported by colleagues because they had been "difficult to intubate", were measured. Five useful risk factors, measured at three levels of severity, were identified. A simple predictive rule was developed and tested on a prospective set of 778 patients, in 1.5% of whom laryngoscopy was found to be difficult. Depending on the threshold chosen, the rule allowed the detection of, for example, 75% of the "difficult" laryngoscopies at a cost of falsely identifying 12% of the "not difficult" patients.
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Many believe that medical expert systems have great potential to improve health care, but few of these systems have been rigorously evaluated, and even fewer are in routine use. We propose the evaluation of medical expert systems in two stages: laboratory and field testing. In the former, the perspectives of both prospective users and experts responsible for implementation are valuable. In the latter, the study must be designed to test, in an unbiased manner, whether the system is used in clinical practice, and if it is used, how it affects the structure, process and outcome of health care encounters. We conclude with proposals for encouraging the objective evaluation of these systems.
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