The Inevitable Application of Big Data to Health CareOur website uses cookies to enhance your experience. By continuing to use our site, or clicking "Continue," you are agreeing to our Cookie Policy | Continue JAMA HomeNew OnlineCurrent IssueFor Authors Publications JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry (1919-1959) Podcasts Clinical Reviews Editors' Summary Medical News Author Interviews More JN Learning / CMESubscribeJobsInstitutions / LibrariansReprints & Permissions Terms of Use | Privacy Policy | Accessibility Statement 2023 American Medical Association. All Rights Reserved Search All JAMA JAMA Network Open JAMA Cardiology JAMA Dermatology JAMA Forum Archive JAMA Health Forum JAMA Internal Medicine JAMA Neurology JAMA Oncology JAMA Ophthalmology JAMA Otolaryngology–Head & Neck Surgery JAMA Pediatrics JAMA Psychiatry JAMA Surgery Archives of Neurology & Psychiatry Input Search Term Sign In Individual Sign In Sign inCreate an Account Access through your institution Sign In Purchase Options: Buy this article Rent this article Subscribe to the JAMA journal
How attractive does a new technology have to be to warrant adoption and utilization? Tentative guidelines for using clinical and economic evaluations.Because economic evaluations of health care services are being published with increasing frequency it is important to (a) evaluate them rigorously and (b) compare the net benefit of the application of one technology with that of others. Four "levels of evidence" that rate economic evaluations on the basis of their methodologic rigour are proposed. They are based on the quality of the methods used to estimate clinical effectiveness, quality of life and costs. With the use of the magnitude of the incremental net benefit of a technology, therapies can also be classified into five "grades of recommendation." A grade A technology is both more effective and cheaper than the existing one, whereas a grade E technology is less or equally effective and more costly. Those of grades B through D are more effective and more costly. A grade B technology costs less than $20,000 per quality-adjusted life-year (QALY), a grade C one $20,000 to $100,000/QALY and a grade D one more than $100,000/QALY. Many issues other than cost effectiveness, such as ethical and political considerations, affect the implementation of a new technology. However, it is hoped that these guidelines will provide a framework with which to interpret economic evaluations and to identify additional information that will be useful in making sound decisions on the adoption and utilization of health care services.
Nutritional AssessmentJeffrey P. Baker, Allan S. Detsky, David E. Wesson et al.|New England Journal of Medicine|1982 THE diagnosis of protein-calorie malnutrition is often based on objective measurements of nutritional status,1 including assessments of hepatic secretory proteins (serum albumin and serum transferrin), anthropometric evaluation, creatinine-height index, and determination of cell-mediated immunity. Although these indicators are epidemiologically useful and correlate with morbidity and mortality,2 3 4 5 6 no single measurement is of consistent value in individual patients.nutritional status may also be assessed by clinical examination. Although this method is used routinely, its validity and reproducibility do not appear to have been tested.To determine the reproducibility and validity of clinical assessment of nutritional status, we studied the nutritional status of . . .
A Clinician's Guide to Cost-Effectiveness AnalysisAllan S. Detsky, I. Gary Naglie|Annals of Internal Medicine|1990 Cost-effectiveness analysis can be used to help set priorities for funding health care programs. For each intervention, the costs and clinical outcomes associated with that strategy must be compared with an alternate strategy for treating the same patients. If an intervention results in improved outcomes but also costs more, the incremental cost per incremental unit of clinical outcome should be calculated. The incremental cost-effectiveness ratios for various programs can be ranked to set funding priorities. By using this list, the person responsible for allocating resources can maximize the net health benefit for a target population derived from a fixed budget. Clinicians may not share this objective because, individually, they are appropriately concerned solely with the effectiveness of a specific intervention for their patients and are not concerned with the benefit derived from spending those resources on other patients in the target population. In addition, allocation may be driven by distributional and political objectives. Nevertheless, cost-effectiveness analysis demonstrates the consequences of allocation decisions. Because clinicians should participate in policy making, they must understand d the role of this technique in setting funding priorities.
Incorporating variations in the quality of individual randomized trials into meta-analysisAllan S. Detsky, C. David Naylor, Keith O’Rourke et al.|Journal of Clinical Epidemiology|1992