PubMed · 10167983
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H Hartley. 1997-06-30. Hefty raises.. https://pubmed.ncbi.nlm.nih.gov/10167983/
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OBJECTIVES: To assess the methodological quality of intention to treat analysis as reported in randomised controlled trials in four large medical journals. DESIGN: Survey of all reports of randomised controlled trials published in 1997 in the BMJ, Lancet, JAMA, and New England Journal of Medicine. MAIN OUTCOME MEASURES: Methods of dealing with deviations from random allocation and missing data. RESULTS: 119 (48%) of the reports mentioned intention to treat analysis. Of these, 12 excluded any patients who did not start the allocated intervention and three did not analyse all randomised subjects as allocated. Five reports explicitly stated that there were no deviations from random allocation. The remaining 99 reports seemed to analyse according to random allocation, but only 34 of these explicitly stated this. 89 (75%) trials had some missing data on the primary outcome variable. The methods used to deal with this were generally inadequate, potentially leading to a biased treatment effect. 29 (24%) trials had more than 10% of responses missing for the primary outcome, the methods of handling the missing responses were similar in this subset. CONCLUSIONS: The intention to treat approach is often inadequately described and inadequately applied. Authors should explicitly describe the handling of deviations from randomised allocation and missing responses and discuss the potential effect of any missing response. Readers should critically assess the validity of reported intention to treat analyses.
OBJECTIVES: To document the extent to which maternity data are collected and how they are recorded, and to identify problems that may affect their availability throughout the NHS. METHODS: Postal survey in September 1997 with structured questionnaires. SETTING: 207 NHS trusts with maternity units in England. PARTICIPANTS: Heads of midwifery in maternity units. MAIN OUTCOME MEASURES: Extent to which maternity data were routinely recorded, how they were recorded and evaluated, and to whom they were made available. RESULTS: 167 (81%) of questionnaires were returned, representing 166 trusts. Of these trusts, 165 collected >/=17 of the 19 data items in HES maternity tail, and 158 collected >/=40 of the 45 items selected from Körner dataset. Only 18 collected all five items selected from the "indicators of success," and 17 did not collect any. In 58 of trusts data were primarily recorded on paper. A computerised maternity information system was used by 106 (63%) of trusts, but many recorded data on paper first. Thirty four did not audit data for accuracy. Most trusts analysed data not routinely collected at national level, but 18 did not analyse HES maternity tail and 17 did not analyse Körner data. CONCLUSIONS: Improvement is needed in quality, completeness, and availability of maternity data at a national level, particularly if the NHS information strategy is to be successfully implemented. Although most of the data items in national datasets are recorded locally, variations in the way data are defined, recorded, and analysed and lack of linkage between computer systems restrict their access, availability, and use at local, district, and national levels.
The evaluation and use of published pharmacoeconomic data are discussed. The pharmacoeconomic literature is a vast and powerful source of information for pharmacists and others who must make decisions about services and products. Published studies can provide data quickly and inexpensively, but they may not necessarily meet criteria for quality and may not be generalizable to a specific situation. Guidelines are available that are intended to standardize study methods, minimize potential bias, and increase the comparability and credibility of data. Before relying on a published study, decision-makers should ensure that it meets criteria related to objective, perspective, pharmacoeconomic method, design, interventions, costs, outcomes, discounting, results, sensitivity analysis, extrapolation of conclusions, and sponsorship. A sound study can be used to support decisions in such diverse areas as individual patient treatment, formulary management, drug-use guideline development, disease management initiatives, and pharmaceutical service evaluation. A decision-maker may be able to use the results by applying them at face value, employing a sensitivity analysis, performing a meta-analysis, incorporating the data into a pharmacoeconomic model, or reproducing the study on a smaller scale. The selection of an application strategy should be based on the potential impact of the decision on the quality and cost of care, with more rigorous and complex strategies reserved for more extreme impacts. Published pharmacoeconomic data can help pharmacists make better and more informed decisions about pharmaceutical services and products.