We displayed the adjusted odds ratios with 95% confidence intervals obtained through Fed-GLMM for both single EHR from Facility 4 (centralized setting to demonstrate computation improvement) and all facilities (federated setting to demonstrate privacy preservation). We adopted a complete-case analysis where 6.8% of the observations with missing values were removed. Abbreviation: Ref—Reference Group. (DOCX)</p
Background: Missing data is a common nuisance in eHealth research: it is hard to prevent and may inv...
<p>Retention in care is defined as the fraction of patients who remain alive and in HIV care. The na...
Background/Aims: At the 2014 HCSRN annual meeting, Bachman and colleagues presented an excellent inv...
We identified all outpatient encounters spanning 10/1/2020 through 9/30/2021 from the 8 acute care h...
Fed-GLMM enables the joint implementation of GLMM for EHRs from multiple sites without sharing indiv...
The Optum COVID-19 de-identified electronic health records (EHR) is sourced from laboratories and ho...
Large collaborative research networks provide opportunities to jointly analyze multicenter electroni...
Electronic health records (EHRs) offer great promises for advancing precision medicine and, at the s...
Record linkage databases have been increasingly available and used in pharmacoepidemiology, pharmaco...
Abstract Laboratory data from Electronic Health Records (EHR) are often used in prediction models wh...
This is the statistical analysis plan related to the protocol published in the EU PAS register at ht...
Background The Observational Medical Outcomes Partnership (OMOP) has just completed a large scale em...
Real-world data, including electronic health records and administrative claims data, are widelyused ...
We compared the accuracy of Fed-GLMM with the standard meta-analysis by calculating the absolute rel...
Missing data analysis. Logistic regression analysis of missing data, comparing those who were includ...
Background: Missing data is a common nuisance in eHealth research: it is hard to prevent and may inv...
<p>Retention in care is defined as the fraction of patients who remain alive and in HIV care. The na...
Background/Aims: At the 2014 HCSRN annual meeting, Bachman and colleagues presented an excellent inv...
We identified all outpatient encounters spanning 10/1/2020 through 9/30/2021 from the 8 acute care h...
Fed-GLMM enables the joint implementation of GLMM for EHRs from multiple sites without sharing indiv...
The Optum COVID-19 de-identified electronic health records (EHR) is sourced from laboratories and ho...
Large collaborative research networks provide opportunities to jointly analyze multicenter electroni...
Electronic health records (EHRs) offer great promises for advancing precision medicine and, at the s...
Record linkage databases have been increasingly available and used in pharmacoepidemiology, pharmaco...
Abstract Laboratory data from Electronic Health Records (EHR) are often used in prediction models wh...
This is the statistical analysis plan related to the protocol published in the EU PAS register at ht...
Background The Observational Medical Outcomes Partnership (OMOP) has just completed a large scale em...
Real-world data, including electronic health records and administrative claims data, are widelyused ...
We compared the accuracy of Fed-GLMM with the standard meta-analysis by calculating the absolute rel...
Missing data analysis. Logistic regression analysis of missing data, comparing those who were includ...
Background: Missing data is a common nuisance in eHealth research: it is hard to prevent and may inv...
<p>Retention in care is defined as the fraction of patients who remain alive and in HIV care. The na...
Background/Aims: At the 2014 HCSRN annual meeting, Bachman and colleagues presented an excellent inv...