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NPJ Digit Med ; 5(1): 44, 2022 Apr 04.
Article in English | MEDLINE | ID: covidwho-1773999


The development of a shared data infrastructure across health systems could improve research, clinical care, and health policy across a spectrum of diseases, including sepsis. Awareness of the potential value of such infrastructure has been heightened by COVID-19, as the lack of a real-time, interoperable data network impaired disease identification, mitigation, and eradication. The Sepsis on FHIR collaboration establishes a dynamic, federated, and interoperable system of sepsis data from 55 hospitals using 2 distinct inpatient electronic health record systems. Here we report on phase 1, a systematic review to identify clinical variables required to define sepsis and its subtypes to produce a concept mapping of elements onto Fast Healthcare Interoperability Resources (FHIR). Relevant papers described consensus sepsis definitions, provided criteria for sepsis, severe sepsis, septic shock, or detailed sepsis subtypes. Studies not written in English, published prior to 1970, or "grey" literature were prospectively excluded. We analyzed 55 manuscripts yielding 151 unique clinical variables. We then mapped variables to their corresponding US Core FHIR resources and specific code values. This work establishes the framework to develop a flexible infrastructure for sharing sepsis data, highlighting how FHIR could enable the extension of this approach to other important conditions relevant to public health.

Health Policy Plan ; 37(1): 55-64, 2022 Jan 13.
Article in English | MEDLINE | ID: covidwho-1450392


The International Health Regulations-State Party Annual Reporting (IHR-SPAR) index and the Global Health Security Index (GHSI) have been developed to aid in strengthening national capacities for pandemic preparedness. We examined the relationship between country-level rankings on these two indices, along with two additional indices (the Universal Health Coverage Service Coverage Index and World Bank Worldwide Governance Indicator (n = 195)) and compared them to the country-level reported coronavirus disease (COVID-19) cases and deaths (Johns Hopkins University COVID-19 Dashboard) through 17 June 2020. Ordinary least squares regression models were used to compare weekly reported COVID-19 cases and death rates per million in the first 12 weeks of the pandemic between countries classified as low, middle and high ranking on each index while controlling for country socio-demographic information. Countries with higher GHSI and IHR-SPAR index scores experienced fewer reported COVID-19 cases and deaths but only for the first 8 weeks after the country's first case. For the GHSI, this association was further limited to countries with populations below 69.4 million. For both the GHSI and IHR-SPAR, countries with a higher sub-index score in human resources for pandemic preparedness reported fewer COVID-19 cases and deaths in the first 8 weeks after the country's first reported case. The Universal Health Coverage Service Coverage Index and Worldwide Governance Indicator country-level rankings were not associated with COVID-19 outcomes. The associations between GHSI and IHR-SPAR scores and COVID-19 outcomes observed in this study demonstrate that these two indices, although imperfect, may have value, especially in countries with a population under 69.4 million people for the GHSI. Preparedness indices may have value; however, they should continue to be evaluated as policy makers seek to better prepare for future global public health crises.

COVID-19 , Pandemics , Global Health , Humans , Pandemics/prevention & control , Public Health , SARS-CoV-2
Intensive Care Med ; 47(8): 867-886, 2021 Aug.
Article in English | MEDLINE | ID: covidwho-1305144


PURPOSE: To study the efficacy of lopinavir-ritonavir and hydroxychloroquine in critically ill patients with coronavirus disease 2019 (COVID-19). METHODS: Critically ill adults with COVID-19 were randomized to receive lopinavir-ritonavir, hydroxychloroquine, combination therapy of lopinavir-ritonavir and hydroxychloroquine or no antiviral therapy (control). The primary endpoint was an ordinal scale of organ support-free days. Analyses used a Bayesian cumulative logistic model and expressed treatment effects as an adjusted odds ratio (OR) where an OR > 1 is favorable. RESULTS: We randomized 694 patients to receive lopinavir-ritonavir (n = 255), hydroxychloroquine (n = 50), combination therapy (n = 27) or control (n = 362). The median organ support-free days among patients in lopinavir-ritonavir, hydroxychloroquine, and combination therapy groups was 4 (- 1 to 15), 0 (- 1 to 9) and-1 (- 1 to 7), respectively, compared to 6 (- 1 to 16) in the control group with in-hospital mortality of 88/249 (35%), 17/49 (35%), 13/26 (50%), respectively, compared to 106/353 (30%) in the control group. The three interventions decreased organ support-free days compared to control (OR [95% credible interval]: 0.73 [0.55, 0.99], 0.57 [0.35, 0.83] 0.41 [0.24, 0.72]), yielding posterior probabilities that reached the threshold futility (≥ 99.0%), and high probabilities of harm (98.0%, 99.9% and > 99.9%, respectively). The three interventions reduced hospital survival compared with control (OR [95% CrI]: 0.65 [0.45, 0.95], 0.56 [0.30, 0.89], and 0.36 [0.17, 0.73]), yielding high probabilities of harm (98.5% and 99.4% and 99.8%, respectively). CONCLUSION: Among critically ill patients with COVID-19, lopinavir-ritonavir, hydroxychloroquine, or combination therapy worsened outcomes compared to no antiviral therapy.

COVID-19 , Ritonavir , Adult , Antiviral Agents/therapeutic use , Bayes Theorem , COVID-19/drug therapy , Critical Illness , Drug Combinations , Humans , Hydroxychloroquine/therapeutic use , Lopinavir/therapeutic use , Ritonavir/therapeutic use , SARS-CoV-2