ArticleApplied clinical informatics2022
Design and Evaluation of a Postpartum Depression Ontology.
Article in Applied clinical informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
2 citing papers in PubMed.
- Proposing a two-stage screening approach to distinguish between transient and enduring postnatal depressive symptoms: A prospective cohort study.International journal of nursing studies advances · 2025Article
- Knowledge Representation and Management 2022: Findings in Ontology Development and Applications.Yearbook of medical informatics · 2023Review
Corrections and comments
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Authors and funding
6 authors.
Funding
Abstract
objectivePostpartum depression (PPD) remains an understudied research area despite its high prevalence. The goal of this study is to develop an ontology to aid in the identification of patients with PPD and to enable future analyses with electronic health record (EHR) data.
methodsWe used Protégé-OWL to construct a postpartum depression ontology (PDO) of relevant comorbidities, symptoms, treatments, and other items pertinent to the study and treatment of PPD.
resultsThe PDO identifies and visualizes the risk factor status of variables for PPD, including comorbidities, confounders, symptoms, and treatments. The PDO includes 734 classes, 13 object properties, and 4,844 individuals. We also linked known and potential risk factors to their respective codes in the International Classification of Diseases versions 9 and 10 that would be useful in structured EHR data analyses. The representation and usefulness of the PDO was assessed using a task-based patient case study approach, involving 10 PPD case studies. Final evaluation of the ontology yielded 86.4% coverage of PPD symptoms, treatments, and risk factors. This demonstrates strong coverage of the PDO for the PPD domain.
conclusionThe PDO will enable future researchers to study PPD using EHR data as it contains important information with regard to structured (e.g., billing codes) and unstructured data (e.g., synonyms of symptoms not coded in EHRs). The PDO is publicly available through the National Center for Biomedical Ontology (NCBO) BioPortal ( https://bioportal.bioontology.org/ontologies/PARTUMDO ) which will enable other informaticists to utilize the PDO to study PPD in other populations.
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Registered trials
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