Data-enabled responses to pandemics: policy lessons from COVID-19. Comment from DrAzizSheikh EdinUniUshe and colleagues
. An alternative approach is to leave data in situ and deploy a service-orientated architecture approach, which creates interfaces between disparate datasets through application programming interfaces . This requires upfront engineering costs, but offers the potential for periodic synchronized updates and accompanying substantial reductions in downstream resource demands.and requires a variety of processes to be in place, to ensure that data are not inappropriately used.
. Taking the time to develop, for example, a data dictionary and the sharing of source code can greatly increase efficiency of analysis and transparency of methods.with provision for exploratory analyses. For example, it was unclear during the early stages of the pandemic which variables would be most useful to identify patients at greatest risk of poor COVID-19 outcomes, resulting in the need for several exploratory analyses.
Other examples include analyses of data across UK nations to investigate the effect of lockdown measures on health system functioning, investigation of rare vaccine safety signals, such as cerebral venous sinus thrombosis
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