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. 2024 Mar;15(2):342-356.
doi: 10.1055/a-2291-1482. Epub 2024 Mar 20.

Pediatric Consent on FHIR

Anton Voronov  1 , Mohammad Jafari  1 , Lin Zhao  2 , Melissa Soliz  3 , Qixuan Hong  4 , John Pope  2 , Darwyn Chern  5 , Megan Lipman  6 , Adela Grando  1
Affiliations

Pediatric Consent on FHIR

Anton Voronov et al. Appl Clin Inform. 2024 Mar.

Abstract

Background: Standardizing and formalizing consent processes and forms can prevent ambiguities, convey a more precise meaning, and support machine interpretation of consent terms.

Objectives: Our goal was to introduce a systematic approach to standardizing and digitizing pediatric consent forms, which are complex due to legal requirements for child and legal guardian involvement.

Methods: First, we reviewed the consent requirements from the Arizona regulation, and we used 21 pediatric treatment consents from five Arizona health care organizations to propose and evaluate an implementation-agnostic Consent for Treatment Framework. Second, we assessed the adequacy of the Fast Healthcare Interoperability Resources (FHIR) to support the proposed framework.

Results: The resulting Consent for Treatment Framework supports compliance with the state consent requirements and has been validated with pediatric consent forms. We also demonstrated that the FHIR standard has the required expressiveness to compute the framework's specifications and express the 21 consent forms.

Conclusion: Health care organizations can apply the shared open-source code and FHIR implementation guidelines to standardize the design of machine-interpretable pediatric treatment consent forms. The resulting FHIR-based executable models may support compliance with the law and support interoperability and data sharing.

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Conflict of interest statement

None declared.

Figures

Fig. 1
Fig. 1
The methodological approach consisted of proposing and validating pediatric consent forms, a Consent for Treatment Framework, and mapping it into FHIR consent resources. FHIR, Fast Healthcare Interoperability Resources.
Fig. 2
Fig. 2
Modeling consents using FHIR resources; adoption of the Consent for Treatment Framework and interplay of FHIR consent artifacts—Questionnaire, QuestionnaireResponse, Consent Profile, and Consent. Dark boxes represent FHIR artifacts; gray boxes refer to other artifacts not modeled directly as FHIR resources. FHIR, Fast Healthcare Interoperability Resources.
Fig. 3
Fig. 3
Mapping of Consent 1 into the proposed Consent for Treatment Framework.
Fig. 4
Fig. 4
FHIR Treatment Consent Profile logical view. FHIR, Fast Healthcare Interoperability Resources.
Fig. 5
Fig. 5
FHIR shorthand definition of the treatment consent profile. FHIR, Fast Healthcare Interoperability Resources.
Fig. 6
Fig. 6
Logical view of the FHIR Questionnaire resource representing Consent 1. FHIR, Fast Healthcare Interoperability Resources.
Fig. 7
Fig. 7
Excerpt from the FHIR Questionnaire resource representing Consent 1 in JSON. FHIR, Fast Healthcare Interoperability Resources.
Fig. 8
Fig. 8
Screenshot of the rendering of the FHIR Questionnaire resource representing Consent 1. FHIR, Fast Healthcare Interoperability Resources.
Fig. 9
Fig. 9
Except from a sample FHIR Questionnaire resource capturing a sample response to Consent 1. FHIR, Fast Healthcare Interoperability Resources.
Fig. 10
Fig. 10
Sample FHIR Consent Resource extracted from the sample QuestionnaireResponse resource shown in Fig. 9 . FHIR, Fast Healthcare Interoperability Resources.
Fig. 11
Fig. 11
Logical view of the extensions defined to record witness and translator.
See this image and copyright information in PMC

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