In medicine, protocols are applied to assure the provision of the treatment with the greatest probability of success. However, the development of protocols is based on the determination of the best intervention for the group. If the group is heterogeneous, there will always be a subset of patients for which the protocol will fail. Furthermore, over time, heterogeneity of the group may not be stable, so the percentage of patients for which a given protocol may fail may change depending on the dynamic patient mix in the group. This was thrown into stark focus during the severe acute respiratory syndrome-2 coronavirus (SARS-CoV-2) pandemic. When a COVID-19 patient presented meeting SIRS or the Berlin Criteria, these patients met the criteria for entry into the sepsis protocol and/or acute respiratory distress syndrome (ARDS) protocol, respectively and were treated accordingly. This was perceived to be the correct response because these patients met the criteria for the "group" definitions of sepsis and/or ARDS. However, the application of these protocols to patients with SARS-CoV-2 infection had never been studied. Initially, poor outcomes were blamed on protocol noncompliance or some unknown patient factor. This initial perception is not surprising as these protocols are standards and were perceived as comprising the best possible evidence-based care. While the academic response to the pandemic was robust, recognition that existing protocols were failing might have been detected sooner if protocol failure detection had been integrated with the protocols themselves. In this review, we propose that, while protocols are necessary to ensure that minimum standards of care are met, protocols need an additional feature, integrated protocol failure detection, which provides an output responsive to protocol failure in real time so other treatment options can be considered and research efforts rapidly focused.

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http://www.ncbi.nlm.nih.gov/pmc/articles/PMC8780641PMC
http://dx.doi.org/10.4103/jets.jets_75_21DOI Listing

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