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Predictors of Concordance between Patient-Reported and Provider-Documented Symptoms in the Context of Cancer and Multimorbidity
Journal article   Peer reviewed

Predictors of Concordance between Patient-Reported and Provider-Documented Symptoms in the Context of Cancer and Multimorbidity

Stephanie Gilbertson-White, Alaa Albashayreh, Yuwen Ji, Anindita Bandyopadhyay, Nahid Zeinali and Catherine Cherwin
Applied clinical informatics, Vol.15(5), pp.1130-1139
10/2024
DOI: 10.1055/s-0044-1791820
PMCID: PMC11669442
PMID: 39721578
url
https://pmc.ncbi.nlm.nih.gov/articles/PMC11669442/pdf/10-1055-s-0044-1791820.pdfView
Open Access

Abstract

The integration of patient-reported outcomes (PROs) into clinical care, particularly in the context of cancer and multimorbidity, is crucial. While PROs have the potential to enhance patient-centered care and improve health outcomes through improved symptom assessment, they are not always adequately documented by the health care team.  This study aimed to explore the concordance between patient-reported symptom occurrence and symptoms documented in electronic health records (EHRs) in people undergoing treatment for cancer in the context of multimorbidity.  We analyzed concordance between patient-reported symptom occurrence of 13 symptoms from the Memorial Symptom Assessment Scale and provider-documented symptoms extracted using NimbleMiner, a machine learning tool, from EHRs for 99 patients with various cancer diagnoses. Logistic regression guided with the Akaike Information Criterion was used to identify significant predictors of symptom concordance.  Our findings revealed discrepancies in patient and provider reports, with itching showing the highest concordance (66%) and swelling showing the lowest concordance (40%). There was no statistically significant association between multimorbidity and high concordance, while lower concordance was observed for women, patients with advanced cancer stages, individuals with lower education levels, those who had partners, and patients undergoing highly emetogenic chemotherapy.  These results highlight the challenges in achieving accurate and complete symptom documentation in EHRs and the necessity for targeted interventions to improve the precision of clinical documentation. By addressing these gaps, health care providers can better understand and manage patient symptoms, ultimately contributing to more personalized and effective cancer care.
 Electronic Health Records Aged Female Health Personnel Humans Male Middle Aged Multimorbidity Neoplasms Patient Reported Outcome Measures Self Report

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