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The MODS method for diagnosis of tuberculosis and multidrug resistant tuberculosis
Published on: August 11, 2008
Digital case-based learning for improving clinical decision-making in tuberculosis care
Sudhanshu Gonge1, Rahul Subhash Gaikwad2, Nitin N Jadhav3
1Department of Computer Science and Engineering, Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, Maharashtra, India.
None:
This study compares a digital case-based learning module with standard training for improving guideline-concordant clinical decisions in tuberculosis (TB) care. Evidence on whether digital training improves TB decision accuracy is limited when both groups complete the same scored case assessment. In a two-arm parallel trial, clinicians or trainees were assigned to either the digital module or standard lecture or continuing medical education training, then completed a standardized vignette test within 7 days. Guideline-concordant decision accuracy was higher with the digital module, with an intention-to-treat risk difference of 0.06 [0.02, 0.1]. Because the scoring rules and assessment content were the same in both arms, this comparison indicates the added value of digital cases for standardized decisions on the vignette test, within the reported interval. These findings reflect vignette performance rather than patient outcomes and may inform TB program implementers and medical educators planning scalable decision-making training.
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