Incorporating Routine Survival Prediction in a U.S. Hospital-Based Palliative Care Service

Abstract

Background: Prognostication is a core component of palliative care consultation. We sought to incorporate predicted survival into the routine practice of our hospital-based palliative care team. Methods: The predicted survival was determined by the physician and/or nurse at the time of initial palliative care consultation using categories that parallel the rough time frames often shared with patients and used in planning care: (1) 3 days, (2) 4 days to 1 month, (3) >1 month to 6 months, (4) >6 months. One year later, survival status at 6 months was determined using death certificates, the Social Security online database, and other methods. Results: Over 1 year, complete data were obtained for 429 of 450 (95.3%) consecutive new patient consults. Patients' mean and median age was 63, 48.5% had cancer, 83% were Caucasian, and 50% were female. For the 283 patients who were discharged alive, median survival was 18 days and 58 patients were still alive after 6 months. Fifty-eight percent of patients were assigned to the correct survival category, whereas 27% of prognoses were too optimistic and 16% were too pessimistic. In logistic regression analysis, predicted survivals of 3 days were much more likely to be accurate than longer predictions. Discussion: The team recorded a predicted survival in 95% of new patient consults. Fifty-eight percent accuracy is in line with prior literature. Routinely incorporating survival prediction into palliative care consultation raised a number of questions. What decisions were made based on the 42% incorrect prognoses? Did these decisions negatively affect care? Survival prediction accuracy has potential as a quality measure for hospital-based palliative care programs, however to be truly useful it needs to be shown to be ''improveable'' and the downstream effects of predictions need to be better understood.

Deciding what information is necessary: do patients with advanced cancer want to know all the details?

“…17 Many physicians therefore f ind prognostication difficult and stressful, and feel inadequately trained to prognosticate. 14 It is true that prognostic estimates in terminally ill patients are often incorrect and usually optimistic, [18][19][20][21][22] with one report of estimates being over three times longer than actual survival. 16 The experience and specialty of physician as well as the nature of the physician-patient relationship can influence the accuracy of a clinical prediction of survival.…”

“…16 The experience and specialty of physician as well as the nature of the physician-patient relationship can influence the accuracy of a clinical prediction of survival. 19,23 Accuracy may improve closer to death 20,21 and with the addition of calculated prognostic indices such as the palliative prognostic index.…”

Frequency of Outpatient Antibiotic Prescription on Discharge to Hospice Care

“…Our other primary exposure of interest, receiving a palliative care consultation, was defined as the presence of a consultation note from a member of the Palliative Care Service at OHSU in the medical record for the index admission. The OHSU Palliative Care Service consults adult patients and families with any diagnosis, many of whom are at or near the end of life (10). The most common reasons for consults are to clarify prognosis and goals of care and to assist with discharge planning.…”

Palliative thoracic radiotherapy for patients with advanced non-small cell lung cancer and poor performance status

“…Some studies suggest that schedules of longer fractionation and higher doses should be considered for patients with good performance status (PS) and longer of life expectancy [1,2,6,[15][16][17][18][19]. To the contrary, in patients with a poor PS and short expected survival time, hypofractionated short-course PTR is used most frequently [1,[3][4][5][6]11,[14][15][16][17][20][21][22][23].…”

“…In these patients, the question whether to offer radiotherapy or not should be considered rather than the issue of fractionation schedule. The main factors that influence this decision are: performance status, estimated prognosis, symptom severity and patient's choice [1,3,10,13,14,18,19,27,28].…”