Exploring the terminological validity of ‘chronic pain’ nursing diagnosis: A retrospective descriptive study using nursing diaries

Abstract

AbstractAimThe aim of this study is to generate empirical evidence, drawing from clinical records, with the goal of elevating the level of evidence supporting the nursing diagnosis (ND) of ‘chronic pain’.BackgroundChronic pain is a prevalent condition that affects all age groups. Patients often feel disbelieved about their pain perception, leading to adverse psychological effects, difficulty accessing healthcare and poor rehabilitation outcomes.DesignRetrospective descriptive study. Standards for Reporting Diagnostic Accuracy Studies guidelines were followed in this study.MethodsData were extracted from Electronic Health Records (EHR) of patients admitted to the University Hospital of Perugia, Italy, between March 2016 and December 2022. The study sample comprised individuals without a specific medical diagnosis or high‐risk population. Out of 1,048,565 EHR, 43,341 clinical‐nursing diaries with the keyword ‘pain’ were identified, from which 283 clinical‐nursing notes were selected based on a keyword‐based retrieval technique and diagnostic definition for further analysis.ResultsOur study findings support the diagnostic descriptors of the ‘chronic pain’ ND in clinical‐nursing diaries. We observed the presence of 9 out of 11 defining characteristics, 7 out of 10 related factors, 4 out of 8 at‐risk populations and 11 out of 17 associated conditions.ConclusionsThe study validated diagnostic criteria for chronic pain and proposed ‘haematological pathology’ as a new associated condition. The findings were presented to the Diagnosis Development Committee of NANDA‐International for further review. However, limitations of the study prompted the need for further analysis using natural language processing and artificial neural network techniques. As a result, a new research direction using artificial intelligence (AI) tools was initiated.Relevance to Clinical PracticeThe study validates diagnostic descriptors for chronic pain and proposes future directions in semantic analysis and AI tools, aiming to enhance clinical practice and decision‐making in nursing care.Patient or Public ContributionNo patient or public contribution.