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在复杂医疗环境中开展可靠临床研究的临床决策标准化。

Standardization of clinical decision making for the conduct of credible clinical research in complicated medical environments.

作者信息

Morris A H, East T D, Wallace C J, Franklin M, Heerman L, Kinder T, Sailor M, Carlson D, Bradshaw R

机构信息

Pulmonary Division, LDS Hospital, Salt Lake City, Utah 84143, USA.

出版信息

Proc AMIA Annu Fall Symp. 1996:418-22.

Abstract

The likelihood that past experience will produce correct guides to current practice depends on the signal-to-noise ratio for the clinical problem of interest. If the signal-to-noise ratio is high, the decision will be sound and patient benefit likely to occur. If the signal-to-noise ratio is low, as is commonly the case with difficult clinical decisions, then personal experience and the best intentions will not assure sound clinical decisions. When the probability of benefit cannot be quantified, clinicians in complex settings are in danger of being misled by data and experience. Quantifiable probabilities established by group experiment or observation will be necessary for clinical decisions that can be expected to confer benefit on the patient. Explicit methods are necessary for interventions that can be replicated in experiments or in practice. Computerized protocols force the articulation of explicit clinical care methods and standardize clinical decision making. We have developed explicit, rule-based protocols, implemented them in our hospital, exported them to other hospitals, and successfully achieved a rigorous experimental environment in the clinical ICU. Exportation of such explicit methods may narrow the gap between efficacy (university hospital) and effectiveness (community hospital) research results.

摘要

过去的经验能否为当前的医疗实践提供正确指导,取决于所关注临床问题的信噪比。如果信噪比高,决策将是合理的,患者也可能从中受益。如果信噪比低,如在困难的临床决策中常见的那样,那么个人经验和良好的意愿并不能确保做出合理的临床决策。当获益概率无法量化时,处于复杂医疗环境中的临床医生有被数据和经验误导的风险。对于有望使患者获益的临床决策,通过群体实验或观察得出的可量化概率是必要的。对于可在实验或实践中重复的干预措施,明确的方法是必要的。计算机化方案促使明确阐述临床护理方法,并使临床决策标准化。我们已经制定了明确的、基于规则的方案,在我们医院实施,并推广到其他医院,在临床重症监护病房成功营造了一个严格的实验环境。输出此类明确的方法可能会缩小疗效(大学医院)和效果(社区医院)研究结果之间的差距。

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