Applied clinical informatics
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Clinical trials are an important research method for improving medical knowledge and patient care. Multiple international and national guidelines stipulate the need for data quality and assurance. Many strategies and interventions are developed to reduce error in trials, including standard operating procedures, personnel training, data monitoring, and design of case report forms. However, guidelines are nonspecific in the nature and extent of necessary methods. ⋯ Clinical trial sites are implementing ad hoc methods pragmatically to ensure data quality. Findings highlight the necessity for further research into "standard practice" focusing on developing and implementing publically available data quality monitoring procedures.
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Identifying pneumonia using diagnosis codes alone may be insufficient for research on clinical decision making. Natural language processing (NLP) may enable the inclusion of cases missed by diagnosis codes. ⋯ System-wide application of NLP to clinical text can increase capture of initial diagnostic hypotheses, an important inclusion when studying diagnosis and clinical decision-making under uncertainty.