Skip to main page content
U.S. flag

An official website of the United States government

Dot gov

The .gov means it’s official.
Federal government websites often end in .gov or .mil. Before sharing sensitive information, make sure you’re on a federal government site.

Https

The site is secure.
The https:// ensures that you are connecting to the official website and that any information you provide is encrypted and transmitted securely.

Access keys NCBI Homepage MyNCBI Homepage Main Content Main Navigation
. 2022 Nov 10;10(11):e40338.
doi: 10.2196/40338.

Shared Interoperable Clinical Decision Support Service for Drug-Allergy Interaction Checks: Implementation Study

Affiliations

Shared Interoperable Clinical Decision Support Service for Drug-Allergy Interaction Checks: Implementation Study

Sungwon Jung et al. JMIR Med Inform. .

Abstract

Background: Clinical decision support (CDS) can improve health care with respect to the quality of care, patient safety, efficiency, and effectiveness. Establishing a CDS system in a health care setting remains a challenge. A few hospitals have used self-developed in-house CDS systems or commercial CDS solutions. Since these in-house CDS systems tend to be tightly coupled with a specific electronic health record system, the functionality and knowledge base are not easily shareable. A shared interoperable CDS system facilitates the sharing of the knowledge base and extension of CDS services.

Objective: The study focuses on developing and deploying the national CDS service for the drug-allergy interaction (DAI) check for health care providers in Korea that need to introduce the service but lack the budget and expertise.

Methods: To provide the shared interoperable CDS service, we designed and implemented the system based on the CDS Hooks specification and Health Level Seven (HL7) Fast Healthcare Interoperability Resources (FHIR) standard. The study describes the CDS development process. The system development went through requirement analysis, design, implementation, and deployment. In particular, the concept architecture was designed based on the CDS Hooks structure. The MedicationRequest and AllergyIntolerance resources were profiled to exchange data using the FHIR standard. The discovery and DAI check application programming interfaces and rule engine were developed.

Results: The CDS service was deployed on G-Cloud, a government cloud service. In March 2021, the CDS service was launched, and 67 health care providers participated in the CDS service. The health care providers participated in the service with 1,008,357 DAI checks for 114,694 patients, of which 33,054 (3.32%) cases resulted in a "warning."

Conclusions: Korea's Ministry of Health and Welfare has been trying to build an HL7 FHIR-based ecosystem in Korea. As one of these efforts, the CDS service initiative has been conducted. To promote the rapid adoption of the HL7 FHIR standard, it is necessary to accelerate practical service development and to appeal to policy makers regarding the benefits of FHIR standardization. With the development of various case-specific implementation guides using the Korea Core implementation guide, the FHIR standards will be distributed nationwide, and more shared interoperable health care services will be introduced in Korea.

Keywords: CDS Hooks; Fast Healthcare Interoperability Resources; Health Level 7; clinical decision support; drug-allergy interaction; interoperability.

PubMed Disclaimer

Conflict of interest statement

Conflicts of Interest: None declared.

Figures

Figure 1
Figure 1
The concept architecture for the shared interoperable CDS system is based on CDS Hooks anatomy. Multiple health care providers simultaneously invoke the shared interoperable CDS service deployed on G-Cloud using a hook and receive a card as a response. CDS: clinical decision support; EHR: electronic health record; FHIR: Fast Healthcare Interoperability Resources.
Figure 2
Figure 2
The MedicationRequest and AllergyIntolerance resource profile. The resources profiled for the clinical decision support service are inherited from the Korea Core Implementation Guide 1.0.0. Elements with "must support" are marked with an "S" in the red square.
Figure 3
Figure 3
The MedicationRequest and AllergyIntolerance resources profiled through the shared interoperable clinical decision support system are conformed with the KR Core MedicationRequest profile and KR Core AllergyIntolerance profile. FHIR: Fast Healthcare Interoperability; HL7: Health Level Seven; KR: Korea.
Figure 4
Figure 4
Examples of order-sign hook and warning card. The order-sign hook has userId, patientId, and draftOrders as required fields, but userId is not used in the clinical decision support (CDS) service for the drug-allergy interaction (DAI) check. The card, the response of the CDS service, includes the results of the DAI check, suggested actions, and links to the launch app.
Figure 5
Figure 5
The three-step drug-allergy interaction check screening process: (1) check whether allergens and prescribed medications have the same product or ingredient, (2) check whether they belong to the same drug or ingredient class, and (3) check whether they have cross-reactive allergens. KD: Korea Drug.
Figure 6
Figure 6
Screenshot of the reference implementation for a patient’s allergen inquiry. To drug-allergy interaction check, physicians should retrieve a patient's allergen code through reference implementation provided by the clincal decision support service.

References

    1. Sutton RT, Pincock D, Baumgart DC, Sadowski DC, Fedorak RN, Kroeker KI. An overview of clinical decision support systems: benefits, risks, and strategies for success. NPJ Digit Med. 2020;3:17. doi: 10.1038/s41746-020-0221-y. doi: 10.1038/s41746-020-0221-y.221 - DOI - DOI - PMC - PubMed
    1. Clinical decision support. HealthIT.gov. [2022-10-22]. https://www.healthit.gov/topic/safety/clinical-decision-support .
    1. Mills S. Electronic health records and use of clinical decision support. Crit Care Nurs Clin North Am. 2019 Jun;31(2):125–131. doi: 10.1016/j.cnc.2019.02.006.S0899-5885(19)30008-5 - DOI - PubMed
    1. Marcial L, Blumenfeld B, Harle C, Jing X, Keller M, Lee V, Lin Z, Dover A, Midboe AM, Al-Showk S, Bradley V, Breen J, Fadden M, Lomotan E, Marco-Ruiz L, Mohamed R, O'Connor P, Rosendale D, Solomon H, Kawamoto K. Barriers, facilitators, and potential solutions to advancing interoperable clinical decision support: multi-stakeholder consensus recommendations for the opioid use case. AMIA Annu Symp Proc. 2019;2019:637–646. https://europepmc.org/abstract/MED/32308858 - PMC - PubMed
    1. Shortliffe EH, Sepúlveda Martin J. Clinical decision support in the era of artificial intelligence. JAMA. 2018 Dec 04;320(21):2199–2200. doi: 10.1001/jama.2018.17163.2713901 - DOI - PubMed