Rachel J Hunter1, Nicholas Buckley1, Eve L Fitzgerald1, Andrew D MacCormick2, Tim W Eglinton3. 1. Department of General Surgery, Canterbury District Health Board, Christchurch, New Zealand. 2. Counties Manakau District Health Board, The University of Auckland, Auckland, New Zealand. 3. Canterbury District Health Board, University of Otago, Dunedin, New Zealand.
Abstract
BACKGROUND: The prioritization of elective surgical wait-lists remains a contentious issue. Multiple new tools and systems have been developed to attempt to reliably prioritize patients. This study pilots one such system, the General Surgery Prioritization Tool and compares it to the existing triage system of clinical judgement. The aim was to determine if the new tool reflects clinical judgement. Secondary aims were to assess for any bias in its application to different patient groups or its application by different scorers. METHOD: A cohort of 392 patients was identified who were wait-listed for non-cancer elective surgery between July 2015 and February 2016. The General Surgery Prioritization Tool was applied after traditional prioritization using clinical judgement. The scores produced by the new tool were compared to the clinical judgement categories. Differences in scores based on gender, ethnicity, age, surgical condition and surgeon were then analysed. RESULTS: There was statistically significant correlation in the new tool scores with traditional triage groups (P < 0.0001). There were no statistically significant differences in mean scores attributable to gender, age or ethnicity. There were minimal differences in mean scores between common surgical conditions. Except for one outlier the mean scores were consistent across 17 surgeons. CONCLUSION: This pilot study has found the General Surgery Prioritization Tool to reflect clinical judgement and to be generalizable by age, gender, ethnicity and prioritizing surgeon. The tool is at least as clinically reliable as traditional methods in the triage for elective general surgery with the advantage of being a more explicit process.
BACKGROUND: The prioritization of elective surgical wait-lists remains a contentious issue. Multiple new tools and systems have been developed to attempt to reliably prioritize patients. This study pilots one such system, the General Surgery Prioritization Tool and compares it to the existing triage system of clinical judgement. The aim was to determine if the new tool reflects clinical judgement. Secondary aims were to assess for any bias in its application to different patient groups or its application by different scorers. METHOD: A cohort of 392 patients was identified who were wait-listed for non-cancer elective surgery between July 2015 and February 2016. The General Surgery Prioritization Tool was applied after traditional prioritization using clinical judgement. The scores produced by the new tool were compared to the clinical judgement categories. Differences in scores based on gender, ethnicity, age, surgical condition and surgeon were then analysed. RESULTS: There was statistically significant correlation in the new tool scores with traditional triage groups (P < 0.0001). There were no statistically significant differences in mean scores attributable to gender, age or ethnicity. There were minimal differences in mean scores between common surgical conditions. Except for one outlier the mean scores were consistent across 17 surgeons. CONCLUSION: This pilot study has found the General Surgery Prioritization Tool to reflect clinical judgement and to be generalizable by age, gender, ethnicity and prioritizing surgeon. The tool is at least as clinically reliable as traditional methods in the triage for elective general surgery with the advantage of being a more explicit process.
Authors: Tim Raine; Maria Angeliki Gkini; Peter M Irving; Arvind Kaul; Eleanor Korendowych; Philip Laws; Amy C Foulkes Journal: BioDrugs Date: 2021-02-26 Impact factor: 5.807
Authors: John R de Almeida; Christopher W Noel; David Forner; Han Zhang; Anthony C Nichols; Marc A Cohen; Richard J Wong; Caitlin McMullen; Evan M Graboyes; Vasu Divi; Andrew G Shuman; Andrew J Rosko; Carol M Lewis; Ehab Y Hanna; Jeffrey Myers; Vinidh Paleri; Brett Miles; Eric Genden; Antoine Eskander; Danny J Enepekides; Kevin M Higgins; Dale Brown; Douglas B Chepeha; Ian J Witterick; Patrick J Gullane; Jonathan C Irish; Eric Monteiro; David P Goldstein; Ralph Gilbert Journal: Cancer Date: 2020-08-11 Impact factor: 6.860