Journal of evaluation in clinical practice
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The objectives of this study were to describe ways in which doctors make suboptimal diagnostic and treatment decisions, and to discuss possible means of alleviating those biases, using a review of past studies from the psychological and medical decision-making literatures. A number of biases can affect the ways in which doctors gather and use evidence in making diagnoses. Biases also exist in how doctors make treatment decisions once a definitive diagnosis has been made. ⋯ None the less, they can have potentially grave consequences in medical settings, such as erroneous diagnosis or patient mismanagement. No surefire methods exist for eliminating biases in medical decision making, but there is some evidence that the adoption of an evidence-based medicine approach or the incorporation of formal decision analytic tools can improve the quality of doctors' reasoning. Doctors' reasoning is vulnerable to a number of biases that can lead to errors in diagnosis and treatment, but there are positive signs that means for alleviating some of these biases are available.
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Qualitative research has been increasingly recognized in recent years as having a distinctive and important contribution to make to health care research. It is capable of being used as a methodologically sufficient approach in its own right, as a precursor to quantitative studies, during or after trials to explain processes and outcomes, and as a means of enhancing the link between evidence and practice. ⋯ These include methodological prejudice, problems in searching for qualitative evidence, and issues in synthesizing qualitative data. We call for progress to be made on the science and methods of including qualitative research in the evidence base of medicine.
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The objective of the Mayo Health System Diabetes Translation Project is to assess the impact of three different models of care on the overall quality of diabetes care in the community. The unit of study is the primary care practice with a different model of care implemented at each of three sites. The design incorporates a comparison of a diabetes guideline implementation team initiative (Practice model A), a guideline initiative combined with clinical use of a Diabetes Electronic Management System (DEMS) by primary care providers (Practice model B) and a guideline initiative combined with DEMS utilization combined with electronic review of DEMS patient encounters by an endocrinologist (Practice model C). ⋯ Baseline data revealed significant differences across sites in adherence to certain key indicators of the quality of diabetes care including: frequency of documentation of eye examinations (19, 39 and 37% for sites A, B and C, respectively), haemoglobin A1c monitoring (64, 89 and 77%) and microalbumin monitoring (3, 15 and 6%). The interventions being assessed in this study include traditional (diabetes education; guideline implementation) and modern (DEMS; telemedicine specialist review) methods for improving the quality of diabetes care. In spite of variation in baseline quality indicators, the setting and design should lead to broad applicability of the results and help determine an optimal model of diabetes care in the community.
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This paper examines conflict of interest as it may arise in the activities of research advisory committees and ethical review committees. It distinguishes between vested interests and true conflict of interest. It also examines the ways in which stakeholdings differ from vested interests and conflicting interests differ from conflicts of interest. ⋯ The more these interests diverge, the more opportunity will arise for conflict of interest. These observations have implications for the constitution of research advisory and ethical review committees, and the ways in which their discussions are conducted. Some practical help with protocols of discussion can be gained from philosophical and management writings.
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Many real world decisions have to be made on a limited evidence base, and clinical decisions are at best problematic. We explored some of the reasons why decision making in health care is so complex, and examined how decision analytic techniques might contribute to problem structuring and to implementation of evidence-based practice. We argued that decision analysis could, to some extent, overcome complexity of decision making by a clear structuring of the problem and a formal analysis of the implications of different decisions. ⋯ However, decision analysis-derived guidelines will make general recommendations that may not be appropriate for all individuals. Nonetheless, decision analysis does make such implications explicit and propose that the guidelines should be supported by some mechanism for determining individual patient preferences. It will now need to consider whether some of NICE resources should be directed beyond evidence-based guidelines into decision analysis-derived guidelines and into decision analytical techniques to provide support for clinical and cost effective decision making within the patient-clinician encounter.