Development and validation of a risk-adjustment model for mortality and hospital length of stay for trauma patients: a prospective registry-based study in Australia
Objectives Adequate risk adjustment for factors beyond the control of the healthcare system contributes to the process of transparent and equitable benchmarking of trauma outcomes. Current risk adjustment models are not optimal in terms of the number and nature of predictor variables included in the...
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| Format: | Article |
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BMJ Publishing Group
2021-08-01
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| Series: | BMJ Open |
| Online Access: | https://bmjopen.bmj.com/content/11/8/e050795.full |
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| author | Peter Cameron Arul Earnest Kate Curtis Gerard O'Reilly Sudhakar Rao Cameron Palmer Maxine Burrell Emily McKie |
| author_facet | Peter Cameron Arul Earnest Kate Curtis Gerard O'Reilly Sudhakar Rao Cameron Palmer Maxine Burrell Emily McKie |
| author_sort | Peter Cameron |
| collection | DOAJ |
| description | Objectives Adequate risk adjustment for factors beyond the control of the healthcare system contributes to the process of transparent and equitable benchmarking of trauma outcomes. Current risk adjustment models are not optimal in terms of the number and nature of predictor variables included in the model and the treatment of missing data. We propose a statistically robust and parsimonious risk adjustment model for the purpose of benchmarking.Setting This study analysed data from the multicentre Australia New Zealand Trauma Registry from 1 July 2016 to 30 June 2018 consisting of 31 trauma centres.Outcome measures The primary endpoints were inpatient mortality and length of hospital stay. Firth logistic regression and robust linear regression models were used to study the endpoints, respectively. Restricted cubic splines were used to model non-linear relationships with age. Model validation was performed on a subset of the dataset.Results Of the 9509 patients in the model development cohort, 72% were male and approximately half (51%) aged over 50 years . For mortality, cubic splines in age, injury cause, arrival Glasgow Coma Scale motor score, highest and second-highest Abbreviated Injury Scale scores and shock index were significant predictors. The model performed well in the validation sample with an area under the curve of 0.93. For length of stay, the identified predictor variables were similar. Compared with low falls, motor vehicle occupants stayed on average 2.6 days longer (95% CI: 2.0 to 3.1), p<0.001. Sensitivity analyses did not demonstrate any marked differences in the performance of the models.Conclusion Our risk adjustment model of six variables is efficient and can be reliably collected from registries to enhance the process of benchmarking. |
| format | Article |
| id | doaj-art-45121796a0224ceba67fa05bccb3a7b8 |
| institution | OA Journals |
| issn | 2044-6055 |
| language | English |
| publishDate | 2021-08-01 |
| publisher | BMJ Publishing Group |
| record_format | Article |
| series | BMJ Open |
| spelling | doaj-art-45121796a0224ceba67fa05bccb3a7b82025-08-20T01:59:30ZengBMJ Publishing GroupBMJ Open2044-60552021-08-0111810.1136/bmjopen-2021-050795Development and validation of a risk-adjustment model for mortality and hospital length of stay for trauma patients: a prospective registry-based study in AustraliaPeter Cameron0Arul Earnest1Kate Curtis2Gerard O'Reilly3Sudhakar Rao4Cameron Palmer5Maxine Burrell6Emily McKie7Emergency and Cardiology Departments, The Alfred Hospital, Melbourne, Victoria, AustraliaDepartment of Epidemiology and Preventive Medicine, Monash University School of Public Health and Preventive Medicine, Melbourne, Victoria, Australia8 The George Institute for Global Health, Newtown, New South Wales, AustraliaDepartment of Emergency Medicine, Monash University, Clayton, Victoria, AustraliaState Trauma Unit, Royal Perth Hospital, Perth, Western Australia, AustraliaTrauma Service, Royal Children`s Hospital Melbourne, Parkville, Victoria, AustraliaState Trauma Unit, Royal Perth Hospital, Perth, Western Australia, AustraliaDepartment of Epidemiology and Preventive Medicine, Monash University School of Public Health and Preventive Medicine, Melbourne, Victoria, AustraliaObjectives Adequate risk adjustment for factors beyond the control of the healthcare system contributes to the process of transparent and equitable benchmarking of trauma outcomes. Current risk adjustment models are not optimal in terms of the number and nature of predictor variables included in the model and the treatment of missing data. We propose a statistically robust and parsimonious risk adjustment model for the purpose of benchmarking.Setting This study analysed data from the multicentre Australia New Zealand Trauma Registry from 1 July 2016 to 30 June 2018 consisting of 31 trauma centres.Outcome measures The primary endpoints were inpatient mortality and length of hospital stay. Firth logistic regression and robust linear regression models were used to study the endpoints, respectively. Restricted cubic splines were used to model non-linear relationships with age. Model validation was performed on a subset of the dataset.Results Of the 9509 patients in the model development cohort, 72% were male and approximately half (51%) aged over 50 years . For mortality, cubic splines in age, injury cause, arrival Glasgow Coma Scale motor score, highest and second-highest Abbreviated Injury Scale scores and shock index were significant predictors. The model performed well in the validation sample with an area under the curve of 0.93. For length of stay, the identified predictor variables were similar. Compared with low falls, motor vehicle occupants stayed on average 2.6 days longer (95% CI: 2.0 to 3.1), p<0.001. Sensitivity analyses did not demonstrate any marked differences in the performance of the models.Conclusion Our risk adjustment model of six variables is efficient and can be reliably collected from registries to enhance the process of benchmarking.https://bmjopen.bmj.com/content/11/8/e050795.full |
| spellingShingle | Peter Cameron Arul Earnest Kate Curtis Gerard O'Reilly Sudhakar Rao Cameron Palmer Maxine Burrell Emily McKie Development and validation of a risk-adjustment model for mortality and hospital length of stay for trauma patients: a prospective registry-based study in Australia BMJ Open |
| title | Development and validation of a risk-adjustment model for mortality and hospital length of stay for trauma patients: a prospective registry-based study in Australia |
| title_full | Development and validation of a risk-adjustment model for mortality and hospital length of stay for trauma patients: a prospective registry-based study in Australia |
| title_fullStr | Development and validation of a risk-adjustment model for mortality and hospital length of stay for trauma patients: a prospective registry-based study in Australia |
| title_full_unstemmed | Development and validation of a risk-adjustment model for mortality and hospital length of stay for trauma patients: a prospective registry-based study in Australia |
| title_short | Development and validation of a risk-adjustment model for mortality and hospital length of stay for trauma patients: a prospective registry-based study in Australia |
| title_sort | development and validation of a risk adjustment model for mortality and hospital length of stay for trauma patients a prospective registry based study in australia |
| url | https://bmjopen.bmj.com/content/11/8/e050795.full |
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