Objective: Generating patient population analytics using patient data from globally networked hospitals for insights into patient journey, treatment efficacy and outcomes, using examples of asthma, multiple myeloma and SARS-CoV-2 (COVID-19).

Method: The research used anonymised patient EHR data from a hospital network comprising 30 M patients in 68 sites, worldwide. The query used 5 dimensions of EHR data: demographics, diagnoses, medications prescribed, laboratory results & procedures performed; receiving aggregated results in return.

Results: Using an EHR-based patient data network, users can generate insights on the patient journey, treatments and outcomes by applying informatics methodologies to extract and interpret information from large amounts of electronic health records. This allows a focused search of patient characteristics or treatment patterns, and enables patient, physician and site outreach. Query of the global EHR network generated data on Asthma, Multiple Myeloma and COVID-19.

Conclusion: An EHR-based patient data network can allow the interrogation of retrospective data, as well as the generation of new prospective data for RWE studies, surveillance, sentinel and cross-sectional studies, feasibility studies, screening for risk management or health-care system evaluation, among other traditional or innovative study designs.

Generating Disease Insights on Patient Journey, Treatments and Outcomes by Use of Global Hospital Network EHR.

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