Integrating Clinical Decision Support Into Electronic Health Record Systems Using a Novel Platform (EvidencePoint):...

Area of Science:

• Health Informatics
• Clinical Decision Support Systems
• Electronic Health Records

Background:

• Clinical decision support (CDS) tools integrated into electronic health records (EHRs) aid evidence-based practice adoption.
• Developing CDS tools for each EHR presents technical challenges due to EHR-specific requirements.
• Existing methods require independent development for each EHR system, hindering widespread implementation.

Purpose of the Study:

• To develop and implement an EHR-agnostic platform for integrating CDS tools.
• To overcome technical constraints associated with EHR-dependent CDS tool development.
• To enable a single set of CDS tools to function across any EHR system.

Main Methods:

• Developed EvidencePoint, a novel, cloud-based, EHR-agnostic CDS platform.
• Deployed initial CDS tools for clinical use cases including COVID-19 survival prediction, venous thromboembolism prophylaxis, and pulmonary embolism diagnosis.
• Utilized a flexible and customizable platform architecture for rapid tool development and deployment.

Main Results:

• The International Medical Prevention Registry on Venous Thromboembolism-D-Dimer CDS tool achieved a 77.8% adoption rate in intervention groups.
• The Northwell COVID-19 Survival (NOCOS) tool, developed for triage during resource constraints, saw limited use as the scenario did not materialize.
• EvidencePoint demonstrated flexibility and customizability, enabling rapid deployment of CDS tools during the pandemic.

Conclusions:

• The EvidencePoint system proves the feasibility of a flexible, user-friendly platform for hosting CDS tools independently of specific EHRs.
• Future analyses will report on EvidencePoint tool adoption rates and the impact of behavioral nudges.
• The EHR-agnostic nature of EvidencePoint simplifies future CDS development compared to traditional IT integration methods.