How do palliative care doctors recognise imminently dying patients? A judgement analysis
Objectives To identify a group of palliative care doctors who perform well on a prognostic test and to understand how they make their survival predictions.Design Prospective observational study and two cross-sectional online studies.Setting Phase I: an online prognostic test, developed from a prospe...
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BMJ Publishing Group
2018-11-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/8/11/e024996.full |
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| author | Nicola White Priscilla Harries Adam JL Harris Victoria Vickerstaff Philip Lodge Catherine McGowan Ollie Minton Christopher Tomlinson Adrian Tookman Fiona Reid Patrick Stone |
| author_facet | Nicola White Priscilla Harries Adam JL Harris Victoria Vickerstaff Philip Lodge Catherine McGowan Ollie Minton Christopher Tomlinson Adrian Tookman Fiona Reid Patrick Stone |
| author_sort | Nicola White |
| collection | DOAJ |
| description | Objectives To identify a group of palliative care doctors who perform well on a prognostic test and to understand how they make their survival predictions.Design Prospective observational study and two cross-sectional online studies.Setting Phase I: an online prognostic test, developed from a prospective observational study of patients referred to palliative care. Phase II: an online judgement task consisting of 50 hypothetical vignettes.Participants All members of the Association of Palliative Medicine (APM) were eligible (n=~1100). 99 doctors completed the prognostic test and were included in the phase I analysis. The top 20% were invited to participate in phase II; 14/19 doctors completed the judgement task and were included in the phase II analysis.Measures Phase I: participants were asked to give a probability of death within 72 hours (0%–100%) for all 20 cases. Accuracy on the prognostic test was measured with the Brier score which was used to identify the ‘expert’ group (scale range: 0 (expert)–1 (non-expert)). Phase II: participants gave a probability of death within 72 hours (0%–100%). A mixed model regression analysis was completed using the percentage estimate as the outcome and the patient information included in the vignettes as the predictors.Results The mean Brier score of all participants was 0.237 (95% CI 0.235 to 0.239). The mean Brier score of the ‘experts’ was 0.184 (95% CI 0.176 to 0.192). Six of the seven prognostic variables included in the hypothetical vignettes were significantly associated with clinician predictions of death. The Palliative Performance Score was identified as being the most influential in the doctors’ prognostic decision making (β=0.48, p<0.001).Conclusions This study identified six clinical signs and symptoms which influenced the judgement policies of palliative care doctors. These results may be used to teach novice doctors how to improve their prognostic skills. |
| format | Article |
| id | doaj-art-4f8cd116f35b493eb3e015232c9bd616 |
| institution | Kabale University |
| issn | 2044-6055 |
| language | English |
| publishDate | 2018-11-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-4f8cd116f35b493eb3e015232c9bd6162025-02-04T00:05:09ZengBMJ Publishing GroupBMJ Open2044-60552018-11-0181110.1136/bmjopen-2018-024996How do palliative care doctors recognise imminently dying patients? A judgement analysisNicola White0Priscilla Harries1Adam JL Harris2Victoria Vickerstaff3Philip Lodge4Catherine McGowan5Ollie Minton6Christopher Tomlinson7Adrian Tookman8Fiona Reid9Patrick Stone10Marie Curie Palliative Care Research Department, Division of Psychiatry, UCL, London, UK4 Faculty of Health, Social Care and Education, Kingston University & St Georges, University of London, London, UKDepartment of Experimental Psychology, University College London, London, UKDepartment of Statistical Science, University College London, London, UK8 Palliative Medicine, Royal Free London NHS Foundation Trust, London, London, UKSt. George’s University Hospitals NHS Foundation Trust, London, UK3 Department of Palliative Medicine, Brighton and Sussex University Hospitals NHS Trust, Brighton, Brighton and Hove, UKBioinformatics Data Science Group, Imperial College London, London, UK1Marie Curie Palliative Care Research Department, Division of Psychiatry, UCL, London, UKSchool of Life Course & Population Sciences, King`s College London, London, UK1 Marie Curie Palliative Care Research Department, University College London, London, UKObjectives To identify a group of palliative care doctors who perform well on a prognostic test and to understand how they make their survival predictions.Design Prospective observational study and two cross-sectional online studies.Setting Phase I: an online prognostic test, developed from a prospective observational study of patients referred to palliative care. Phase II: an online judgement task consisting of 50 hypothetical vignettes.Participants All members of the Association of Palliative Medicine (APM) were eligible (n=~1100). 99 doctors completed the prognostic test and were included in the phase I analysis. The top 20% were invited to participate in phase II; 14/19 doctors completed the judgement task and were included in the phase II analysis.Measures Phase I: participants were asked to give a probability of death within 72 hours (0%–100%) for all 20 cases. Accuracy on the prognostic test was measured with the Brier score which was used to identify the ‘expert’ group (scale range: 0 (expert)–1 (non-expert)). Phase II: participants gave a probability of death within 72 hours (0%–100%). A mixed model regression analysis was completed using the percentage estimate as the outcome and the patient information included in the vignettes as the predictors.Results The mean Brier score of all participants was 0.237 (95% CI 0.235 to 0.239). The mean Brier score of the ‘experts’ was 0.184 (95% CI 0.176 to 0.192). Six of the seven prognostic variables included in the hypothetical vignettes were significantly associated with clinician predictions of death. The Palliative Performance Score was identified as being the most influential in the doctors’ prognostic decision making (β=0.48, p<0.001).Conclusions This study identified six clinical signs and symptoms which influenced the judgement policies of palliative care doctors. These results may be used to teach novice doctors how to improve their prognostic skills.https://bmjopen.bmj.com/content/8/11/e024996.full |
| spellingShingle | Nicola White Priscilla Harries Adam JL Harris Victoria Vickerstaff Philip Lodge Catherine McGowan Ollie Minton Christopher Tomlinson Adrian Tookman Fiona Reid Patrick Stone How do palliative care doctors recognise imminently dying patients? A judgement analysis BMJ Open |
| title | How do palliative care doctors recognise imminently dying patients? A judgement analysis |
| title_full | How do palliative care doctors recognise imminently dying patients? A judgement analysis |
| title_fullStr | How do palliative care doctors recognise imminently dying patients? A judgement analysis |
| title_full_unstemmed | How do palliative care doctors recognise imminently dying patients? A judgement analysis |
| title_short | How do palliative care doctors recognise imminently dying patients? A judgement analysis |
| title_sort | how do palliative care doctors recognise imminently dying patients a judgement analysis |
| url | https://bmjopen.bmj.com/content/8/11/e024996.full |
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