Evaluating and extending the Informed Consent Ontology for representing permissions from the clinical domain

Article type: Research Article

Authors: Umberfield, Elizabeth E.^{a; b; *} | Stansbury, Cooper^{c; d} | Ford, Kathleen^e | Jiang, Yun^f | Kardia, Sharon L.R.^g | Thomer, Andrea K.^h | Harris, Marcelline R.^f

Affiliations: [a] Health Policy & Management, Richard M. Fairbanks School of Public Health, Indiana University, Indianapolis, IN, USA | [b] Center for Biomedical Informatics, Regenstrief Institute Inc., Indianapolis, IN, USA. E-mail: [email protected] | [c] Computational Medicine and Bioinformatics, Medical School, University of Michigan, Ann Arbor, MI, USA | [d] Institute for Computational Discovery & Engineering, University of Michigan, Ann Arbor, MI, USA. E-mail: [email protected] | [e] School of Nursing, University of Michigan, Ann Arbor, MI, USA. E-mail: [email protected] | [f] Systems, Populations and Leadership, School of Nursing, University of Michigan, Ann Arbor, MI, USA. E-mails: [email protected], [email protected] | [g] Epidemiology, School of Public Health, University of Michigan, Ann Arbor, MI, USA. E-mail: [email protected] | [h] School of Information, University of Michigan, Ann Arbor, MI, USA. E-mail: [email protected]

Correspondence: [*] Corresponding author. E-mail: [email protected].

Note: [] Accepted by: Olivier Bodenreider

Abstract: The purpose of this study was to evaluate, revise, and extend the Informed Consent Ontology (ICO) for expressing clinical permissions, including reuse of residual clinical biospecimens and health data. This study followed a formative evaluation design and used a bottom-up modeling approach. Data were collected from the literature on US federal regulations and a study of clinical consent forms. Eleven federal regulations and fifteen permission-sentences from clinical consent forms were iteratively modeled to identify entities and their relationships, followed by community reflection and negotiation based on a series of predetermined evaluation questions. ICO included fifty-two classes and twelve object properties necessary when modeling, demonstrating appropriateness of extending ICO for the clinical domain. Twenty-six additional classes were imported into ICO from other ontologies, and twelve new classes were recommended for development. This work addresses a critical gap in formally representing permissions clinical permissions, including reuse of residual clinical biospecimens and health data. It makes missing content available to the OBO Foundry, enabling use alongside other widely-adopted biomedical ontologies. ICO serves as a machine-interpretable and interoperable tool for responsible reuse of residual clinical biospecimens and health data at scale.

Keywords: Knowledge bases, evaluation study, informed consent, biological specimen banks, informatics

DOI: 10.3233/AO-210260

Journal: Applied Ontology, vol. 17, no. 2, pp. 321-336, 2022