Classification algorithm for the International Classification of Diseases-11 chronic pain classification: development and results from a preliminary pilot evaluation.

Abstract: The International Classification of Diseases-11 (ICD-11) chronic pain classification includes about 100 chronic pain diagnoses on different diagnostic levels. Each of these diagnoses requires specific operationalized diagnostic criteria to be present. The classification comprises more than...

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Publicado en:PAIN Vol. 162; no. 7; pp. 2087 - 2097
Autores principales: Korwisi, Beatrice, Haya, Ginea, Attal, Nadine, Aziz, Qasim, Bennett, Michael I., Benoliel, Rafael, Cohen, Milton, Evers, Stefan, Giamberardino, Maria Adele, Kaasa, Stein, Kose, Eva, Lavand'homme, Patricia, Nicholas, Michael, Perrot, Serge, Schug, Stephan, Smit, Blair H., Svensson, Peter, Vlaeyen, Johan W. S., Shuu-Jiun Wang, Treede, Rolf-Detlef
Formato: research Journal Article
Publicado: Lippincott Williams & Wilkins Jul2021
Acceso en línea:Ver este registro en EBSCOhost
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      dt: Jul2021
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      pub: Lippincott Williams & Wilkins
      place: Baltimore, Maryland
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        10.1097/j.pain.0000000000002208
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        atl: Classification algorithm for the International Classification of Diseases-11 chronic pain classification: development and results from a preliminary pilot evaluation.
      aug:
        au:
          Korwisi, Beatrice
          Haya, Ginea
          Attal, Nadine
          Aziz, Qasim
          Bennett, Michael I.
          Benoliel, Rafael
          Cohen, Milton
          Evers, Stefan
          Giamberardino, Maria Adele
          Kaasa, Stein
          Kose, Eva
          Lavand'homme, Patricia
          Nicholas, Michael
          Perrot, Serge
          Schug, Stephan
          Smit, Blair H.
          Svensson, Peter
          Vlaeyen, Johan W. S.
          Shuu-Jiun Wang
          Treede, Rolf-Detlef
        affil: Division of Clinical Psychology and Psychotherapy, Department of Psychology, Philipps-University Marburg, Marburg, Germany
      sug:
        subj:
          International Classification of Diseases
          Chronic Pain Diagnosis
          Classification Algorithms
          Chronic Pain Classification
          Human
          Pilot Studies
          Comparative Studies
          Multicenter Studies
          Evaluation Research
          Validation Studies
      ab: Abstract: The International Classification of Diseases-11 (ICD-11) chronic pain classification includes about 100 chronic pain diagnoses on different diagnostic levels. Each of these diagnoses requires specific operationalized diagnostic criteria to be present. The classification comprises more than 200 diagnostic criteria. The aim of the Classification Algorithm for Chronic Pain in ICD-11 (CAL-CP) is to facilitate the use of the classification by guiding users through these diagnostic criteria. The diagnostic criteria were ordered hierarchically and visualized in accordance with the standards defined by the Society for Medical Decision Making Committee on Standardization of Clinical Algorithms. The resulting linear decision tree underwent several rounds of iterative checks and feedback by its developers, as well as other pain experts. A preliminary pilot evaluation was conducted in the context of an ecological implementation field study of the classification itself. The resulting algorithm consists of a linear decision tree, an introduction form, and an appendix. The initial decision trunk can be used as a standalone algorithm in primary care. Each diagnostic criterion is represented in a decision box. The user needs to decide for each criterion whether it is present or not, and then follow the respective yes or no arrows to arrive at the corresponding ICD-11 diagnosis. The results of the pilot evaluation showed good clinical utility of the algorithm. The CAL-CP can contribute to reliable diagnoses by structuring a way through the classification and by increasing adherence to the criteria. Future studies need to evaluate its utility further and analyze its impact on the accuracy of the assigned diagnoses.
      pubtype: Academic Journal
      doctype:
        research
        Journal Article
      ougenre: Article
    language: English
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