# Assessment of 3 standards-based clinical decision support (CDS) tools in an academic electronic health record using Clinical Quality Language, CDS Hooks, and Fast Healthcare Interoperability Resources: a retrospective evaluation

## TL;DR

This study evaluated three clinical decision support tools using health IT standards to assess their accuracy and false-positive alerts in different care settings.

## Contribution

The study demonstrates the feasibility of using standardized syntax and formats for CDS across varying care settings and complexities.

## Key findings

- CDS1 had 11.1% accuracy and 11.1% false-positive alerts, while CDS2 and CDS3 had 96% and 100% accuracy with no false positives.
- There were no significant differences in false-positive alerts or accuracy between the three CDS tools.
- Health IT standards can represent clinical recommendations of varying complexity in different care settings.

## Abstract

To evaluate clinical decision support (CDS) of varying complexities and care settings represented using Health Information Technology (HIT) standards—Clinical Quality Language (CQL) for representing clinical logic and Fast Healthcare Interoperability Resources (FHIR) for health information exchange.

This Institutional Review Board-approved, retrospective study was performed at an academic medical center (January 1, 2023-December 31, 2023). Recommendations extracted from patient-centered outcomes guidelines were translated into standardized syntax (SNOMED CT) and representations (CQL, FHIR). Clinical decision support Hooks applications were developed for: CDS1—provides education for emergency department (ED) patients with venous thromboembolism; CDS2—recommends CT pulmonary angiogram in ED patients with suspected pulmonary embolism (PE) and uses FHIR Questionnaire resources for representing interactive content; CDS3—recommends mammography/breast magnetic resonance imaging surveillance in outpatients with breast cancer history. We randomly selected 50 ED patients with suspected PE and 50 outpatients undergoing breast imaging surveillance. We compared outcomes of false-positive alerts and the accuracy of CDS1, the more complex CDS2, and CDS3 for outpatients.

Clinical decision support Hooks applications used CQL logic for trigger expressions and logic files and provided recommendations to ED and outpatient providers. CDS1 had a false-positive alert and accuracy of 11.1% and 98%, respectively, not significantly different from CDS2 (0.0% false-positive alerts, P = .33 and 96% accuracy, P = .56) or from CDS3 (0.0% false-positive alerts, P = .15 and 100% accuracy, P = .31).

Health Information Technology standards can represent recommendations of varying complexities in various care settings.

The potential to represent CDS using standardized syntax and formats can help facilitate the dissemination of CDS-consumable artifacts.