Aim: The aim of this study is to generate empirical evidence, drawing from clinical re-cords, with the goal of elevating the level of evidence supporting the nursing diagnosis (ND) of ‘chronic pain’.Background: Chronic 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.Design: Retrospective descriptive study. Standards for Reporting Diagnostic Accuracy Studies guidelines were followed in this study.Methods: Data 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 medi-cal 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 defini-tion for further analysis.Results: Our 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 char-acteristics, 7 out of 10 related factors, 4 out of 8 at- risk populations and 11 out of 17 associated conditions.Conclusions: The study validated diagnostic criteria for chronic pain and proposed ‘haematological pathology’ as a new associated condition. The findings were pre-sented to the Diagnosis Development Committee of NANDA-International for fur-ther review. However, limitations of the study prompted the need for further analysis using natural language processing and artificial neural network techniques. As a re-sult, a new research direction using artificial intelligence (AI) tools was initiated. Relevance to Clinical Practice: The study validates diagnostic descriptors for chronic pain and proposes future directions in semantic analysis and AI tools, aiming to en-hance clinical practice and decision- making in nursing care.Patient or Public Contribution: No patient or public contribution.
Exploring the terminological validity of ‘chronic pain’ nursing diagnosis: A retrospective descriptive study using nursing diaries
Nicola Ramacciati
;
2023-01-01
Abstract
Aim: The aim of this study is to generate empirical evidence, drawing from clinical re-cords, with the goal of elevating the level of evidence supporting the nursing diagnosis (ND) of ‘chronic pain’.Background: Chronic 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.Design: Retrospective descriptive study. Standards for Reporting Diagnostic Accuracy Studies guidelines were followed in this study.Methods: Data 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 medi-cal 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 defini-tion for further analysis.Results: Our 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 char-acteristics, 7 out of 10 related factors, 4 out of 8 at- risk populations and 11 out of 17 associated conditions.Conclusions: The study validated diagnostic criteria for chronic pain and proposed ‘haematological pathology’ as a new associated condition. The findings were pre-sented to the Diagnosis Development Committee of NANDA-International for fur-ther review. However, limitations of the study prompted the need for further analysis using natural language processing and artificial neural network techniques. As a re-sult, a new research direction using artificial intelligence (AI) tools was initiated. Relevance to Clinical Practice: The study validates diagnostic descriptors for chronic pain and proposes future directions in semantic analysis and AI tools, aiming to en-hance clinical practice and decision- making in nursing care.Patient or Public Contribution: No patient or public contribution.I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.
