Medical decision making : an international journal of the Society for Medical Decision Making
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Effectively controlling the HIV epidemic will require efficient use of limited resources. Despite ambitious global goals for HIV prevention and treatment scale up, few comprehensive practical tools exist to inform such decisions. ⋯ Resource allocation theory can make a significant contribution to decision making about HIV prevention and treatment scale up. What remains now is to develop models that can bridge the gap between theory and practice.
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Difficulty identifying patients in need of colorectal cancer (CRC) screening contributes to low screening rates. ⋯ Applying NLP to EHR records detected more CRC tests than either manual chart review or billing records review alone. NLP had better precision but marginally lower recall to identify patients who were due for CRC screening than billing record review.
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To improve physicians' antimicrobial practice, it is important to identify barriers to and facilitators of guideline adherence and assess their relative importance. The theory of planned behavior permits such assessment and has been previously used for evaluating antibiotic use. According to this theory, guideline use is fueled by 3 factors: attitude, subjective norm (perceived social pressure regarding guidelines), and perceived behavioral control (PBC; perceived ability to follow the guideline). The authors aim to explore factors affecting guideline use in their hospital. ⋯ These divergent origins of influence on guideline adherence point to different approaches for improvement. As habits strongly influence staff members, methods that focus on changing habits (e.g., automated decision support systems) are possible interventions. As residents' intention seems to be guided mainly by external influences and experienced control, this may make feedback, convenient guideline formats, and guideline familiarization more suitable.
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Accuracy studies of Patient Safety Indicators (PSIs) are critical but limited by the large samples required due to low occurrence of most events. We tested a sampling design based on test results (verification-biased sampling [VBS]) that minimizes the number of subjects to be verified. ⋯ Verification-biased sampling permits substantial savings in the required sample size for PSI validation studies. However, sample sizes still need to be very large for many of the rarer PSIs.