Journal of evaluation in clinical practice
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Physicians' overconfidence damages the quality of medical care. Due to their high social status and intense impact on people lives, physicians need to develop strategies to avoid overconfidence. Yet until now, the strategies physicians use to avoid overconfidence have not been explored. This study aimed to identify strategies physicians use to minimize potential overconfidence. ⋯ The study demonstrates the on-going nature of establishing physicians' professional identity and implies that it is shaped by a motivation to adapt their identity to fundamental requirements of medical practice. Medical training and education might promote strategies for minimization of potential overconfidence among physicians.
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The Getting It Right First Time programme aims to reduce variation in clinical practice that unduly impacts on outcomes for patients in the National Health Service (NHS) in England; often termed "unwarranted variation." However, there is no "gold standard" method for detecting unwarranted variation. The aim of this study was to describe a method to allow such variation in recorded practice or patient outcomes between NHS trusts to be detected using data over multiple time periods. By looking at variation over time, it was hoped that patterns that could be missed by looking at data at a single time point, or averaged over a longer time period, could be identified. ⋯ The time-series method may complement other methods to help identify unwarranted variation.
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Representation of benefits and harms associated with specific interventions in an understandable and comparable way is crucial for informed decision making that clinical practice guidelines (CPGs) aim to enhance. Therefore, we investigated how statements concerning the effects of interventions considered and described benefits and harms, magnitude of effect and its uncertainty, numeric and non-numeric information, and outcomes in Finnish CPGs. ⋯ In the Finnish CPGs, the statements were rarely framed with both absolute and relative numeric measures of an intervention's effect. Harms were rarely reported with a grade indicating the level of evidence. The users of CPGs would benefit from more consistent and understandable framing of statements considering both benefits and harms of interventions.
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New therapies are increasingly approved by regulatory agencies such as the Food and Drug Administration (FDA) and the European Medicines Agency (EMA) based on testing in non-randomized clinical trials. These treatments have typically displayed "dramatic effects" (ie, effects that are considered large enough to obviate the combined effects of biases and random errors that may affect the study results). The agencies, however, have not identified how large these effects should be to avoid the need for further testing in randomized controlled trials (RCTs). We investigated the effect size that would circumvent the need for further RCTs testing by the regulatory agencies. We hypothesized that the approval of therapeutic interventions by regulators is based on heuristic decision making whose accuracy can be best characterized by the application of signal detection theory (SDT). ⋯ Drug developers and practitioners alike can use the change in one logarithm of effect size as a benchmark to decide if further testing in RCTs should be pursued, or as a guide to interpreting the results reported in non-randomized studies. However, further research would be useful to better characterize the threshold of effect size above which testing in RCTs is not needed.