Abstract
Background. The Australian DonateLife Audit captures information on all deaths which occur in emergency departments, intensive
care units and in those recently discharged from intensive care unit. This information provides the opportunity to estimate
the number of donors expected, given present consent rates and contemporary donation practices. This may then allow
benchmarking of performance between hospitals and jurisdictions. Our aim was to develop a method to estimate the number
of donors using data from the DonateLife Audit on the basis of baseline patient characteristics alone.Methods. All intubated patient
deaths at contributing hospitals were analyzed. Univariate comparisons of donors to nondonors were performed. A logistic
regression model was developed to estimate expected donor numbers from data collected between July 2012 and December
2013. This was validated using data from January to April 2014. Results. Between July 2012 and April 2014, 6861 intubated
patient deaths at 68 hospitals were listed on the DonateLife Audit of whom 553 (8.1 ) were organ donors. Factors independently
associated with organ donation included age, brain death, neurological diagnoses, chest x-ray findings, PaO2/FiO2, creatinine, alanine
transaminase, cancer, cardiac arrest, chronic heart disease, and peripheral vascular disease. A highly discriminatory (area
under the receiver operatory characteristic, 0.940 [95 confidence interval, 0.924-0.957]) and well-calibrated prediction model
was developed which accurately estimated donor numbers. Three hospitals appeared to have higher numbers of actual donors
than expected. Conclusions. It is possible to estimate the expected number of organ donors. This may assist benchmarking
of donation outcomes and interpretation of changes in donation rates over time.
| Original language | English |
|---|---|
| Pages (from-to) | 2203 - 2209 |
| Number of pages | 7 |
| Journal | Transplantation |
| Volume | 99 |
| Issue number | 10 |
| DOIs | |
| Publication status | Published - 2015 |
UN SDGs
This output contributes to the following UN Sustainable Development Goals (SDGs)
-
SDG 3 Good Health and Well-being
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