Afaf Girgis1, Ivana Durcinoska1, Eng-Siew Koh1, Weng Ng1, Anthony Arnold1, Geoff P Delaney1. 1. Afaf Girgis, Ivana Durcinoska, and Geoff P. Delaney, The University of New South Wales, Sydney; Eng-Siew Koh, Weng Ng, and Geoff P. Delaney, Liverpool Hospital, Liverpool; and Anthony Arnold, Wollongong Hospital, Wollongong, NSW, Australia.
Abstract
PURPOSE: High-quality symptom management and supportive care are essential components of comprehensive cancer care. We aimed to describe the development of an evidence-based automated decisional algorithm for patients with cancer that had specific, actionable, clinical, evidence-based recommendations to improve patient care, communication, and management. METHODS: We reviewed existing literature and clinical practice guidelines to identify priority domains of patient care and potential clinical recommendations. Two multidisciplinary clinical advisory groups used a two-stage consensus decision-making approach to determine domains of care and patient-reported outcome (PRO) measures and subsequently developed automated algorithms with clear clinical recommendations amendable to intervention in clinical settings. RESULTS: Algorithms were developed to inform management of patient symptoms, distress, and unmet needs. Three PRO measures were chosen: Distress Thermometer and problem checklist, Edmonton Symptom Assessment Scale, and the Supportive Care Needs Survey-Screening Tool 9. PRO items were mapped to five domains of patient well-being: physical, emotional, practical, social and family, and maintenance of well-being. A total of 15 actionable clinical recommendations tailored to specific issues of concern were established. CONCLUSION: Using automated algorithms and clinical recommendations provides a platform for streamlining and systematizing the use of PROs to inform risk-stratified guideline-informed care. The series of algorithms, which set out systematized care pathways for the clinical care of patients with cancer, can be used to potentially inform patient-centered care.
PURPOSE: High-quality symptom management and supportive care are essential components of comprehensive cancer care. We aimed to describe the development of an evidence-based automated decisional algorithm for patients with cancer that had specific, actionable, clinical, evidence-based recommendations to improve patient care, communication, and management. METHODS: We reviewed existing literature and clinical practice guidelines to identify priority domains of patient care and potential clinical recommendations. Two multidisciplinary clinical advisory groups used a two-stage consensus decision-making approach to determine domains of care and patient-reported outcome (PRO) measures and subsequently developed automated algorithms with clear clinical recommendations amendable to intervention in clinical settings. RESULTS: Algorithms were developed to inform management of patient symptoms, distress, and unmet needs. Three PRO measures were chosen: Distress Thermometer and problem checklist, Edmonton Symptom Assessment Scale, and the Supportive Care Needs Survey-Screening Tool 9. PRO items were mapped to five domains of patient well-being: physical, emotional, practical, social and family, and maintenance of well-being. A total of 15 actionable clinical recommendations tailored to specific issues of concern were established. CONCLUSION: Using automated algorithms and clinical recommendations provides a platform for streamlining and systematizing the use of PROs to inform risk-stratified guideline-informed care. The series of algorithms, which set out systematized care pathways for the clinical care of patients with cancer, can be used to potentially inform patient-centered care.
Authors: Augusta Silveira; Teresa Sequeira; Joaquim Gonçalves; Pedro Lopes Ferreira Journal: Health Qual Life Outcomes Date: 2022-05-21 Impact factor: 3.077
Authors: Alexandre Chan; Fred Ashbury; Margaret I Fitch; Bogda Koczwara; Raymond Javan Chan Journal: Support Care Cancer Date: 2020-08 Impact factor: 3.603
Authors: Bróna Nic Giolla Easpaig; Yvonne Tran; Mia Bierbaum; Gaston Arnolda; Geoff P Delaney; Winston Liauw; Robyn L Ward; Ian Olver; David Currow; Afaf Girgis; Ivana Durcinoska; Jeffrey Braithwaite Journal: BMC Health Serv Res Date: 2020-02-10 Impact factor: 2.655
Authors: Afaf Girgis; Ivana Durcinoska; Anthony Arnold; Joseph Descallar; Nasreen Kaadan; Eng-Siew Koh; Andrew Miller; Weng Ng; Martin Carolan; Stephen A Della-Fiorentina; Sandra Avery; Geoff P Delaney Journal: J Med Internet Res Date: 2020-10-29 Impact factor: 5.428