Privacy-Protecting, Reliable Response Data Discovery Using COVID-19 Patient Observations

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Abstract

There is an urgent need to answer questions related to COVID-19’s clinical course and associations with underlying conditions and health outcomes. Multi-center data are necessary to generate reliable answers, but centralizing data in a single repository is not always possible. Using a privacy-protecting strategy, we launched a public Questions & Answers web portal (<ext-link xmlns:xlink="http://www.w3.org/1999/xlink" ext-link-type="uri" xlink:href="https://covid19questions.org">https://covid19questions.org</ext-link>) with analyses of comorbidities, medications and laboratory tests using data from 202 hospitals (59,074 COVID-19 patients) in the USA and Germany. We find, for example, that 8.6% of hospitalizations in which the patient was not admitted to the ICU resulted in the patient returning to the hospital within seven days from discharge and that, when adjusted for age, mortality for hospitalized patients was not significantly different by gender or ethnicity.

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Publicly Sharing Knowledge on COVID19 Without Sharing Patient-Level Data: A Privacy-Protecting Multivariate Analysis Approach

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