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BACKGROUND We assessed the impact of clinical decision support (CDS) rules within the electronic health record for ionized calcium (iCa), serum magnesium (Mg), and N-terminal pro-B-type natriuretic peptide (NT-proBNP) in intensive care unit (ICU) inpatients at a large academic center. METHODS A repeat order for measurement of iCa or Mg placed within 24 (iCa) or 48 (Mg) h of a previously nonactionable result, or additional orders for NT-proBNP beyond 1 within a single hospitalization, triggered a CDS pop-up alert showing the prior result and offering the opportunity to cancel the order or to place the order after entering an indication for repeat testing. The number of tests performed for each of these analytes and incidence of adverse clinical outcomes potentially associated with hypocalcemia or hypomagnesemia were compared between the 90-day period before CDS implementation and two 90-day periods immediately following. RESULTS iCa test volumes decreased by 48%, Mg by 39%, and NT-proBNP by 28% in the 90-day period immediately following implementation and remained decreased by 54%, 49%, and 22%, respectively, during the following 90-day period (all P values 0.17). CONCLUSIONS Implementation of CDS dramatically decreased repeat testing of iCa, Mg, and NT-proBNP without adversely impacting clinical outcomes in the ICU. Expansion of the rules from the ICU units to include the entire hospitalized patient population and expansion to additional analytes is expected to lead to further reductions in testing.

The genomic era is upon us, promising to individualize medicine and creating a buzz among scientists, physicians, and the general public alike. Although it is easy to become entwined in the excitement and anticipation of the impending medical revolution, scientists and clinicians must be vigilant about novel and unexpected scientific findings to prevent genomics from tarnishing its own reputation with a major blemish: false positives. A recent “Commentary” article in the journal Nature highlights the prevalence and negative impact of false-positive publications and discusses strategies to avoid reporting false positives as novel findings (1). False positives are not new to the world of science; however, the ease with which a study can accidentally generate false positives has dramatically increased owing to the contemporary availability and production of massive and complex data sets. Generating such large amounts of data inevitably leads to greater numbers of tests performed, allowing apparently stronger signals to emerge by chance with greater frequency …