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Background: A universal consensus regarding standardized pain outcomes does not exist. The personalized pain goal has been suggested as a clinically relevant outcome measure. Aim: To assess the feasibility of obtaining a personalized pain goal and to compare a clinically based personalized pain goal definition versus a research-based study definition for stable pain. Design: Prospective longitudinal descriptive study. Measures: The attending physician completed routine assessments, including a personalized pain goal and the Edmonton Classification System for Cancer Pain, and followed patients daily until stable pain control, death, or discharge. Stable pain for cognitively intact patients was defined as pain intensity less than or equal to desired pain intensity goal (personalized pain goal definition) or pain intensity ⩽3 (Edmonton Classification System for Cancer Pain study definition) for three consecutive days with Setting/participants: A total of 300 consecutive advanced cancer patients were recruited from two acute care hospitals and a tertiary palliative care unit. Results: In all, 231/300 patients (77%) had a pain syndrome; 169/231 (73%) provided a personalized pain goal, with 113/169 (67%) reporting a personalized pain goal ⩽3 (median = 3, range = 0–10). Using the personalized pain goal definition as the gold standard, sensitivity and specificity of the Edmonton Classification System for Cancer Pain definition were 71.3% and 98.5%, respectively. For mild (0–3), moderate (4–6), and severe (7–10) pain, the highest sensitivity was for moderate pain (90.5%), with high specificity across all three categories (95%–100%). Conclusion: The personalized pain goal is a feasible outcome measure for cognitively intact patients. The Edmonton Classification System for Cancer Pain definition closely resembles patient-reported personalized pain goals for stable pain and would be appropriate for research purposes. For clinical pain management, it would be important to include the personalized pain goal as standard practice.

The transition from active cancer treatment to palliative care often results in a shift in drug risk-benefit assessment which requires the deprescribing of various medications. Deprescribing in palliative cancer patients can benefit patients by reducing their pill burden, decrease potential side effects, and potentially decrease healthcare costs. In addition, a change in patients’ goals of care (GOC) necessitates the alteration of drug therapy which includes both deprescribing and the addition of medications intended to improve quality of life. Depending on a patient’s GOC, a medication can be considered as inappropriate. Primary: Comparison between potentially inappropriate medications (PIMs) prior to the palliative care consult (PCC) versus after the PCC. Secondary: Association between PIMs and GOC. The study was a 1-year retrospective database review. The study included cancer patients seen by the PCC team at the University of Alberta Hospital. The OncPal guidelines were used to identify and determine the number of PIMs prior to the PCC and after the PCC. The reduction in PIMs prior to PCC versus after the PCC was statistically significant (p value

Context Current health care delivery models have increased the need for safe and concise patient handover. Handover interventions in the literature have focused on the use of structured tools but have not evaluated their ability to facilitate retention of patient information. Objectives In this study, mock pictorial displays were generated in an attempt to create a snapshot of each patient's medical and social circumstances. These pictorial displays contained the patient's photograph and other disease- and treatment-related images. The objective of this randomized trial was to assess the ability of these snapshots to enhance delayed information recall by care providers. Methods Participating physicians were given four advanced cancer patient histories to review, two at a time over two weeks. Pictorial image displays, referred to as the Electronic Whiteboard (EWB) were added, in a randomized manner to half of the textual histories. The impact of the EWB on information recall was tested in immediate and delayed time frames. Results Overall, patient information recall declined significantly over time, with or without the EWB. Still, this trial demonstrates significantly higher test scores after 24 hours with the addition of pictures to textual patient information, compared with textual information alone (P = 0.0002). A more modest improvement was seen with the addition of the EWB for questionnaires administered immediately after history review (P = 0.008). Most participants agreed that the EWB was a useful enhancement and that seeing a patient's photograph improved their ability to retain information. Conclusion Most studies examining the institution of handover protocols in the health care setting have failed to harness the power of pictures and other representative images. This study demonstrates the ability of pictorial displays to improve both immediate and delayed recall of patient histories without increasing review time. These types of displays may be amenable to generation by software programs and have the potential to enhance information transfer in various settings.

Objectives: Single, program wide multi-site prospective study examining the (1) accuracy of non-cancer clinician prediction survival (CPS) by palliative practitioners on 1st assessment. (2) Factors affecting CPS; (3) potential impact on clinical care.Design and methods: Single, program wide multi-site prospective study (n = 282). CPS was divided into four clinically relevant time periods (≤2 weeks, >2 to ≤6 weeks, >6 to ≤12 weeks, and >12 weeks). Multivariate analysis was done on six predictor variables.Results: More than ½ of patients died before their clinically relevant predicted time periods (of more than 2 weeks). Only one out of the six predictor variables impacted on clinician accuracy on logistic regression and that being the survival prediction time periods.Conclusion: Non-cancer CPS, even by palliative practitioners, remains overly optimistic. This raises the question in that these individuals may have been potentially over-treated.

Survival prediction of advanced cancer patients remains an important task for palliative clinicians. It has transformed from an art form into a more scientific branch of the discipline with the evolution of palliative medicine and use of statistical estimates of survival. Both clinician predicted survival and actuarial estimation of survival have their uses and drawbacks. This article gives a practical and quick summary of the pros and cons of clinician survival prediction and actuarial-based prognostic tools used at the bedside.

Aims: This study examined (1) accuracy of clinician prediction of survival (CPS) by palliative practitioners on first assessment with the use of standardised palliative tools, (2) factors affecting accuracy, (3) potential impact on clinical care. Methods: A multi-site prospective study (n=1530) was used. CPS was divided into four time periods (2 to 6wks, >6 to 12wks and >12wks). Multivariate analysis was assessed on six predictor variables. Results: Overall, median survival of the sample was only 5 weeks. CPS category was accurate only 38.6% of the time, with 44.6% patients dying before the predicted time period. Of six candidate variables, on multivariate analysis only (i) the clinical time periods themselves and (ii) Palliative Performance Scale Conclusion: CPS, even by palliative practitioners, remains overly optimistic with the existence of the horizon effect. This raises the question in that these individuals may have been potentially overtreated.

92 Background: The transition from active cancer treatment to palliative care often results in a shift in drug risk-benefit assessment which requires the deprescribing of various medications. In addition, a change in patients’ goals of care (GOC) necessitates the alteration of drug therapy which includes both deprescribing and the addition of medications intended to improve quality of life. Depending on a patient’s GOC, a medication can be considered as inappropriate. Methods: The study was a one year retrospective database review and included cancer patients seen by the PCC team at the University of Alberta Hospital. Primary Objective: Comparison between potentially inappropriate medications (PIMs) prior to the palliative care consult (PCC) versus after the PCC. Secondary objective: Association between PIMs and GOC. The OncPal guidelines were used to identify and determine the number of PIMs prior to the PCC and after the PCC. Results: The reduction in PIMs prior to PCC versus after the PCC was 49% and was statistically significant (p < 0.001), demonstrating the PCC has a positive significant impact on deprescribing PIMs. For our secondary outcome, an overall decrease in PIMs was observed with the changes of GOC. This decrease in PIMs associated with GOC although not statistically significant, demonstrates that one of the benefits of a PCC is the GOC conversation. Conclusions: Deprescribing in palliative cancer patients can benefit patients by reducing their pill burden, decrease potentially side effects, and potentially decrease healthcare costs. This study shows the positive impact a PCC has on deprescribing and reassessing GOC. Furthermore, this study reveals the importance of using guidelines for deprescribing in palliative oncology and brings to light other medications that may be considered PIMs.

Aim: The aim of our study was to assess whether the Karnofsky Performance Status (KPS), the Eastern Cooperative Oncology Group (ECOG) Performance Status, and the Palliative Performance Scale (PPS) are interchangeable individually or within two prognostic tools: the Palliative Prognostic Score (PaP) and the Palliative Prognostic Index (PPI). Methods: We performed a subset analysis of a prospective comparative study of functional and prognostic tools and clinician prediction of survival. We studied 955 patients with advanced life-limiting illnesses (cancer and non-cancer) in the acute care and community settings. We used a descriptive statistical model and Spearman's rank correlation to assess these interchangeabilities. Results: There is a direct positive linear relationship between the KPS and the PPS, and a direct negative linear relationship between these tools and the ECOG. Exchange of the KPS and the PPS was possible within the PaP and the PPI. Conclusion: The PPS and the KPS can be used interchangeably as functional tools and within prognostic tools. The ECOG is interchangeable with the PPS and the KPS, but this interchange-ability is population-specific.

Despite a trend to formalize and codify medical information, natural language communications still play a prominent role in health care workflows, in particular when it comes to hand-overs between providers. Natural language processing (NLP) attempts to bridge the gap between informal, natural language information and coded, machine-interpretable data. This paper reports on a study that applies an advanced NLP method for the extraction of sentinel events in palliative care consult letters. Sentinel events are of interest to predict survival and trajectory for patients with acute palliative conditions. Our NLP method combines several novel characteristics, e.g., the consideration of topological knowledge structures sourced from an ontological terminology system (SNOMED CT). The method has been applied to the extraction of different types of sentinel events, including simple facts, temporal conditions, quantities, and degrees. A random selection of 215 anonymized consult letters was used for the study. The results of the NLP extraction were evaluated by comparison with coded sentinel event data captured independently by clinicians. The average accuracy of the automated extraction was 73.6%.

Survival prediction for end stage cancer patientsremains an important task in Palliative Medicine. Previously more of an art form, survival prediction has now become increasingly objective, utilizing statistical estimates of survival. Both clinician prediction survival and actuarial estimation of survival have their uses and drawbacks. This article examines the pros and cons of each and how both can be utilized at the bedside.

Context Patients, caregivers, and clinicians require high levels of information regarding prognosis when conditions are incurable. Objectives 1) To validate the Palliative Prognostic Score (PaP) and 2) to evaluate prognostic capacity of used clinical tools and the diagnosis of delirium, in a population referred to a palliative care consultation service at a Canadian acute care hospital. Methods This was a prospective observational cohort study on survival prediction based on the PaP and routinely collected clinical data, including the Palliative Performance Scale (PPS) and the Folstein Mini-Mental State Examination (MMSE). Kaplan-Meier survival curves, log-rank tests for significant differences between survival curves, and the Cox proportional hazards model were used to identify the relationship between the hazard ratio for death and the above variables. Results Nine hundred fifty-eight cases underwent final analysis, of which 181 (19%) had a noncancer diagnosis. Median and mean survival were 35 and 131 days, respectively. The three groups, divided based on different ranges of PaP, had significantly different survival curves, with 30-day-survival rates of 78%, 55%, and 11%. Age, PPS, and PaP remained significantly associated with survival, whereas diagnosis group, MMSE, and delirium became insignificant, despite lower hazard of death for cancer vs. noncancer and higher hazard for abnormal vs. normal MMSE and presence vs. absence of delirium. Conclusion The PaP was successfully validated in a population with characteristics that extend beyond those of the population in which it was originally developed. This is the largest sample in which the PaP has been validated to date.

Heart failure (HF) is a leading cause of death and disability, and despite optimal care, patients may eventually require palliative care. Little is known about how palliative care questionnaires (the Edmonton Symptom Assessment Scale [ESAS] and the Palliative Performance Scale [PPS]) perform compared with HF assessment using the New York Heart Association (NYHA) functional class and the Kansas City Cardiomyopathy Questionnaire (KCCQ).To assess the utility of a palliative care questionnaire in patients with HF.One hundred and five patients (mean age=65 years, 76% male, mean ejection fraction=28%) followed in an HF clinic were surveyed with the NYHA, PPS, ESAS, and KCCQ.The PPS and ESAS were each correlated to the NYHA class (P0.0001 for both) and the KCCQ score (PPS: R(2)=0.57; ESAS: R(2)=-0.72; both P0.0001). There were 33 patients who either died (10 deaths) or were hospitalized (26 patients) for more than one year. In addition to age and gender, a higher (worse) ESAS score trended toward significance (P=0.07) and a lower (worse) PPS was a significant (P=0.04) predictor of all-cause hospitalization or death.In a cohort of HF patients, we found a modest correlation with NYHA class and KCCQ assessment with the PPS and ESAS, two standard palliative care questionnaires. Given the difficulty in identifying patients with HF eligible for palliative or hospice care, these tools may be of use in clinical practice.

Advanced cancer patients remain highly susceptible to infections, leading to significant morbidity and mortality. A lack of consensus on the management of infections in this population stems from the heterogeneity of the patient group, divergent goals of care, and unknown prognosis with antibiotic treatment.This prospective single cohort study examined the impact of infection and its treatment on the survival of hospitalized advanced cancer patients compared with a similar cohort without infection.A total of 441 patients were referred to the palliative care (PC) consult service in a tertiary hospital over a 12-month period. The occurrence of sepsis, organ-related infection, and antibiotic use were recorded on initial PC consult. Survival was calculated from the point of PC consult to the date of death.Of these patients, 16.6% suffered a recent episode of sepsis (with or without an identifiable organ-related infection) and 23.4% had a recent episode of organ-related infection without clinically evident sepsis. Among the patients with sepsis, organ-related infection, or both, 89.7% received antibiotics (intravenous, oral, or both). Median survival of septic and nonseptic patients was 15 and 42 days, respectively. Septic patients who responded poorly to treatment (nonresponders) had a median survival of five days vs. 142 days in good responders. This equates with a hazard ratio of 9.74 for death in antibiotic nonresponders (P0.05). Median survival for patients with an untreated organ-related infection (no sepsis) was 27 days compared with 48 days in a similar cohort receiving antibiotic therapy. Among patients on IV antibiotics, nonresponders had a median survival of six days vs. 108 days in responders. For patients on oral antibiotics, nonresponders had a median survival of six days vs. 70 days in responders.These findings suggest that a recent episode of sepsis and/or organ-related infection significantly reduces overall patient survival. Favorable antibiotic response is associated with an increase in median survival. These findings suggest that antibiotic treatment may prolong survival, and a time-limited trial may be indicated contingent on goals of care.