PREDICTing mortality in the emergency department: external validation and derivation of a clinical prediction tool

Abstract

Background

he Choosing Wisely campaign has called for better engagement of palliative and hospice care services for patients in the emergency department (ED). PREDICT is a clinical prediction tool that was derived in an Australian ED cohort. It assesses a patient's risk of mortality at one year to select those who would benefit from advanced care planning. Such goals of care discussion can improve patients’ ability to communicate what they want out of their healthcare and, in cases of end-of-life, potentially reduce the number of futile interventions. Using a cut-off of 13 points, PREDICT had a reported 95.3% specificity, 53.9% sensitivity for one year mortality. We externally validated PREDICT and derived a simpler modified PREDICT tool in order to systematically identify high-risk patients eligible for goals of care discussions and palliative care consultation in the ED.

Methods

This was an observational cohort study of a random sample of 927 patients aged 55+ seen in the ED in 2014. We identified advance healthcare directives (AHD) on file. We summarized diagnostic accuracy of the clinical tool to predict one year mortality using sensitivity, specificity, and area under the curve (AUC). We refined PREDICT using multivariable modeling. We followed reporting guidelines including STrengthening the Reporting of OBservational studies in Epidemiology (STROBE) for cohort studies and Standards for Reporting of Diagnostic Accuracy (STARD).

Results

A total of 927 patients were included, 55.0% were male, 63 (7.0%) were nursing home residents, 389 (42.0%) patients had an AHD in their medical record at the time of ED visit, and 245 (26.4%) were deceased at one year. Of the 780 patients with PREDICT scores <13, 164 (21.0%; 95% CI 18.3-24.1) were deceased at one year, of the 147 patients with PREDICT scores ≥13, 81 (55.1%; 95% CI 46.7-63.2) were deceased at one year. The AUC of the PREDICT score was 0.717 (95% CI 0.680-0.754), sensitivity was 33.1% (95% CI 27.3-39.4), and specificity was 90.3% (95% CI 87.8-92.4) to predict one year mortality. The modified PREDICT tool resulted in an AUC of 0.709 (95% CI 0.671-0.747). We decided to select this model as the preferred model, as the variable of ICU admission with multiorgan failure can be difficult to assess in the ED and may delay advanced care planning. Re-weighting the score did not improve fit or the AUC, so points assigned to each variable were not adjusted.

Conclusion

PREDICT is an easy tool to administer to be able to identify patients who are at high risk of one year mortality and who could benefit from AHDs, goals-of-care discussion and, when appropriate in the context of an end-of-life setting, palliative medicine consultation. External validation of PREDICT was successful in our population. We simplified PREDICT and derived a new tool, the modified PREDICT minus ICU tool, without significantly altering the sensitivity, specificity and AUC for death at one year. Next steps include external validation of the newly derived rule and prospective implementation.

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