• Nikhil Satchidanand, Timothy J Servoss, Ranjit Singh, Angela M Bosinski, Penny Tirpak, Linda L Horton, and Bruce J Naughton.
• 1 Department of Family Medicine, Jacobs School of Medicine and Biomedical Sciences, University at Buffalo, Buffalo, NY, USA.
• Am J Hosp Palliat Care. 2018 Sep 1; 35 (9): 1201-1206.

BackgroundEarly, data-driven discussion surrounding palliative care can improve care delivery and patient experience.ObjectiveTo develop a 30-day mortality prediction tool for older patients in intensive care unit (ICU) with pneumonia that will initiate palliative care earlier in hospital course.DesignRetrospective Electronic Health Record (EHR) review.SettingFour urban and suburban hospitals in a Western New York hospital system.ParticipantsA total of 1237 consecutive patients (>75 years) admitted to the ICU with pneumonia from July 2011 to December 2014.MeasurementsData abstracted included demographics, insurance type, comorbidities, and clinical factors. Thirty-day mortality was also determined. Logistic regression identified predictors of 30-day mortality. Area under the receiver operating curve (ROC) was calculated to quantify the degree to which the model accurately classified participants. Using the coordinates of the ROC, a predicted probability was identified to indicate high risk.ResultsA total of 1237 patients were included with 30-day mortality data available for 100% of patients. The mortality rate equaled 14.3%. Age >85 years, having active cancer, Congestive Heart Failure (CHF), Chronic Obstructive Pulmonary Disease (COPD), sepsis, and being on a vasopressor all predicted mortality. Using the derived index, with a predicted probability of mortality >0.146 as a cutoff, sensitivity equaled 70.6% and specificity equaled 65.6%. The area under the ROC was 0.735.ConclusionOur risk tool can help care teams make more informed decisions among care options by identifying a patient group for whom a careful review of goals of care is indicated both during and after hospitalization. External validation and further refinement of the index with a larger sample will improve prognostic value.

29 keywords...

hide…