The COVID-19 electronic healthcare data initiative project will demonstrate PCORnet sites’ ability to collect information on COVID data through the implementation of a nationally distributed data infrastructure. The collection of these COVID-19 data will help to answer critical questions to assist in the emergency response to the COVID-19 pandemic.
The COVID-19 electronic healthcare data initiative project will demonstrate PCORnet sites’ ability to collect information on COVID data through the implementation of a nationally distributed data infrastructure. The collection of these COVID-19 data will help to answer critical questions to assist in the emergency response to the COVID-19 pandemic.
LEAD-ZDC is a prospective observational study to assess the effectiveness of zero dollar copayment for select common diabetes medications on patients’ medication adherence, blood glucose (A1c) control, diabetes complications, and healthcare utilization. Tulane University is leading the study in collaboration with Blue Cross Blue Shield of Louisiana and REACHnet partners…
LEAD-ZDC is a prospective observational study to assess the effectiveness of zero dollar copayment for select common diabetes medications on patients’ medication adherence, blood glucose (A1c) control, diabetes complications, and healthcare utilization. Tulane University is leading the study in collaboration with Blue Cross Blue Shield of Louisiana and REACHnet partners in Louisiana.
The Multi-state EHR-based Network for Disease Surveillance (MENDS) is a CDC-funded initiative that seeks to test an automated chronic disease surveillance system using data routinely stored in health records to provide clinically detailed, efficient, and timely information from large, diverse populations with minimal added work and cost for health departments…
The Multi-state EHR-based Network for Disease Surveillance (MENDS) is a CDC-funded initiative that seeks to test an automated chronic disease surveillance system using data routinely stored in health records to provide clinically detailed, efficient, and timely information from large, diverse populations with minimal added work and cost for health departments or clinicians.