Providers’ Perception of Alert Fatigue After Implementation of User-Filtered Warnings

Alert fatigue is a complex problem that many health institutions face when using an electronic health record (EHR). The addition of user-filtered warnings (UFW) is a physicians’ proposed intervention at Inova Health System (IHS), a large 5-hospital health system in Northern Virginia, that allows prescribers to filter out specific drug-drug interactions and pregnancy and lactation medication alerts for a 30-day period. This study aims to determine the impact of UFW on physicians’ perception of alert fatigue and to calculate the reduction of medication alerts. It was hypothesized that the reduction in alerts will significantly impact physicians’ perception of alert fatigue in a positive manner. Physician perception of alert fatigue was assessed using online surveys before and after the implementation of UFW. Data from Medications Warnings Statistics reports were used to assess the reduction of alerts fired post-implementation of UFW. For the primary outcome, there was no significant difference in the overall perception of alert fatigue before and after the implementation of UFW. For the secondary outcome, the number of medication alerts was decreased by 16.7% post UFW implementation. Overall, the data does not support UFW to reduce alert fatigue

Mapping the human genetic architecture of COVID-19

The genetic make-up of an individual contributes to the susceptibility and response to viral infection. Although environmental, clinical and social factors have a role in the chance of exposure to SARS-CoV-2 and the severity of COVID-191,2, host genetics may also be important. Identifying host-specific genetic factors may reveal biological mechanisms of therapeutic relevance and clarify causal relationships of modifiable environmental risk factors for SARS-CoV-2 infection and outcomes. We formed a global network of researchers to investigate the role of human genetics in SARS-CoV-2 infection and COVID-19 severity. Here we describe the results of three genome-wide association meta-analyses that consist of up to 49,562 patients with COVID-19 from 46 studies across 19 countries. We report 13 genome-wide significant loci that are associated with SARS-CoV-2 infection or severe manifestations of COVID-19. Several of these loci correspond to previously documented associations to lung or autoimmune and inflammatory diseases3,4,5,6,7. They also represent potentially actionable mechanisms in response to infection. Mendelian randomization analyses support a causal role for smoking and body-mass index for severe COVID-19 although not for type II diabetes. The identification of novel host genetic factors associated with COVID-19 was made possible by the community of human genetics researchers coming together to prioritize the sharing of data, results, resources and analytical frameworks. This working model of international collaboration underscores what is possible for future genetic discoveries in emerging pandemics, or indeed for any complex human disease