Clinician accuracy when estimating survival duration: the role of the patient's performance status and time-based prognostic categories

Comparison of Simplified Palliative Prognostic Index and Palliative Performance Scale in Patients with Advanced Cancer in a Home Palliative Care Setting

Objective: The Palliative Performance Scale (PPS) has been reported to be as accurate as Palliative Prognostic Index (PPI). PPS is a component of the simplified PPI (sPPI). It is unknown whether PPS is as accurate as sPPI. This study aimed to compare the prognostic performance of the PPS and sPPI in patients with advanced cancer in a home palliative care setting in South Korea. Methods: This was a secondary analysis of a prospective cohort study that included Korean patients with advanced cancer who received home-based palliative care. We used the medical records maintained by specialized palliative care nurses. We computed the prognostic performance of PPS and sPPI using the area under the receiver operating characteristic curve (AUROC) and calibration plots for the 3- and 6-week survival. Results: A total of 80 patients were included, with a median overall survival of 47.0 days. The AUROCs of PPS were 0.71 and 0.69 at the 3- and 6-week survival predictions, respectively. The AUROCs of sPPI were 0.87 and 0.73 at the 3- and 6-week survival predictions, respectively. The calibration plot demonstrated satisfactory agreement across all score ranges for both the PPS and sPPI. Conclusions: This study showed that the sPPI assessed by nurses was more accurate than the PPS in a home palliative care setting in predicting the 3-week survival in patients with advanced cancer. The PPS can be used for a quick assessment.

Comparing Clinician Estimates versus a Statistical Tool for Predicting Risk of Death within 45 Days of Admission for Cancer Patients

OBJECTIVES

 While clinical practice guidelines recommend that oncologists discuss goals of care with patients who have advanced cancer, it is estimated that less than 20% of individuals admitted to the hospital with high-risk cancers have end-of-life discussions with their providers. While there has been interest in developing models for mortality prediction to trigger such discussions, few studies have compared how such models compare with clinical judgment to determine a patient's mortality risk.

METHODS

 This study is a prospective analysis of 1,069 solid tumor medical oncology hospital admissions (n = 911 unique patients) from February 7 to June 7, 2022, at Memorial Sloan Kettering Cancer Center. Electronic surveys were sent to hospitalists, advanced practice providers, and medical oncologists the first afternoon following a hospital admission and they were asked to estimate the probability that the patient would die within 45 days. Provider estimates of mortality were compared with those from a predictive model developed using a supervised machine learning methodology, and incorporated routine laboratory, demographic, biometric, and admission data. Area under the receiver operating characteristic curve (AUC), calibration and decision curves were compared between clinician estimates and the model predictions.

RESULTS

 Within 45 days following hospital admission, 229 (25%) of 911 patients died. The model performed better than the clinician estimates (AUC 0.834 vs. 0.753, p < 0.0001). Integrating clinician predictions with the model's estimates further increased the AUC to 0.853 (p < 0.0001). Clinicians overestimated risk whereas the model was extremely well-calibrated. The model demonstrated net benefit over a wide range of threshold probabilities.

CONCLUSION

 The inpatient prognosis at admission model is a robust tool to assist clinical providers in evaluating mortality risk, and it has recently been implemented in the electronic medical record at our institution to improve end-of-life care planning for hospitalized cancer patients.

Are Surprise Questions and Probabilistic Questions by Nurses Useful in Home Palliative Care? A Prospective Study

Background: Surprise questions (SQs) are used as screening tools in palliative care. Probabilistic questions (PQs) are more accurate than temporal predictions. However, no study has examined the usefulness of SQs and PQs assessed by nurses. Objectives: To examine the accuracy of nurses' SQ and PQ assessments in patients with advanced cancer receiving home palliative care. Design: A prospective single-center cohort study. Setting/Subjects: Adult patients with advanced cancer who received palliative care at home in South Korea between 2019 and 2020. Measurements: Palliative care specialized nurses were asked the SQ, "Would you be surprised if the patient died in a specific timeframe?" and PQ, "What is the probability that this patient will be alive (0 to 100%) within a specific timeframe?" at the 1-, 2-, 4-, and 6-week timeframes at enrollment. We calculated the sensitivities and specificities of the SQs and PQs. Results: 81 patients were recruited with 47 days of median survival. The sensitivity, specificity, and overall accuracy (OA) of the 1-week SQ were 50.0, 93.2, and 88.9%, respectively. The accuracies for the 1-week PQ were 12.5, 100.0, and 91.3%, respectively. The 6-week SQ showed sensitivity, specificity, and OA of 84.6, 42.9, and 62.9%, respectively; the accuracies for the 6-week PQ were 59.0, 66.7, and 63.0%, respectively.Conclusion: The SQ and PQ showed acceptable accuracy in home palliative care patients. Interestingly, PQ showed higher specificity than SQ at all timeframes. The SQ and PQ assessed by nurses may be useful in providing additional prognostic information for home palliative care.

The Next Best Thing: Three Key Conversations to Convey Prognosis Over the Course of an Incurable Cancer

INTRODUCTION

Waiting until a person is very near end of life to discuss limited life expectancy risks lower goal-concordant care and increased utilization of medical interventions with lower likelihood of benefit at the end of life. Medical training on communication skills in serious illness often focuses on early and late conversations regarding prognosis, with no guidance on navigating the conversations occurring in the middle of the illness course.

GOAL OF THE REVIEW

We propose a new framework for identifying and discussing prognosis at various points along the cancer course, as a continuum from beginning to end, that is prompted by changes in clinical status and number of available remaining cancer directed interventions.

DISCUSSION

SPIKES is a framework utilized for early conversations in a cancer course. REMAP is a framework utilization for late conversations in a cancer course. There is a gap in guidance on how to navigate conversations that occur between the early and late phases of a cancer course. We describe 3 general phases of care during a cancer course ("early," "middle," and "late"), with each phase warranting specific communication skills in order to improve patient understanding of prognosis, goal concordant care, and best practices for healthcare utilization in the acute and end of life care settings.

CONCLUSION

Framing prognosis by available medical interventions through a framework of "early," "middle," and "late" adds clarity to the phase of illness, expectations around delivery of information to the patient, and framing of recommendations at each given phase.

Accuracy of clinical predictions of prognosis at the end-of-life: evidence from routinely collected data in urgent care records

BACKGROUND

The accuracy of prognostication has important implications for patients, families, and health services since it may be linked to clinical decision-making, patient experience and outcomes and resource allocation. Study aim is to evaluate the accuracy of temporal predictions of survival in patients with cancer, dementia, heart, or respiratory disease.

METHODS

Accuracy of clinical prediction was evaluated using retrospective, observational cohort study of 98,187 individuals with a Coordinate My Care record, the Electronic Palliative Care Coordination System serving London, 2010-2020. The survival times of patients were summarised using median and interquartile ranges. Kaplan Meier survival curves were created to describe and compare survival across prognostic categories and disease trajectories. The extent of agreement between estimated and actual prognosis was quantified using linear weighted Kappa statistic.

RESULTS

Overall, 3% were predicted to live "days"; 13% "weeks"; 28% "months"; and 56% "year/years". The agreement between estimated and actual prognosis using linear weighted Kappa statistic was highest for patients with dementia/frailty (0.75) and cancer (0.73). Clinicians' estimates were able to discriminate (log-rank p < 0.001) between groups of patients with differing survival prospects. Across all disease groups, the accuracy of survival estimates was high for patients who were likely to live for fewer than 14 days (74% accuracy) or for more than one year (83% accuracy), but less accurate at predicting survival of "weeks" or "months" (32% accuracy).

CONCLUSION

Clinicians are good at identifying individuals who will die imminently and those who will live for much longer. The accuracy of prognostication for these time frames differs across major disease categories, but remains acceptable even in non-cancer patients, including patients with dementia. Advance Care Planning and timely access to palliative care based on individual patient needs may be beneficial for those where there is significant prognostic uncertainty; those who are neither imminently dying nor expected to live for "years".

Index Symptoms and Prognosis Awareness of Patients With Pancreatic Cancer: A Multi-Site Palliative Care Collaborative

BACKGROUND

Pancreatic cancer has a poor 5-year survival and carries significant morbidity. Pain is a commonly studied symptom in pancreatic cancer; however, few studies examine the frequency of multiple patient-reported symptoms. Our aim is to ascertain patient-reported symptom burden at initial consultation with a palliative care provider and compare patient prognostic awareness to provider estimation of prognosis.

METHODS

Data were extracted from the standardized Quality Data Collection Tool (QDACT). Adults with pancreatic cancer seen by a palliative care provider were included. Descriptive statistics were used to describe demographic features, symptom prevalence and burden, as well as assess patient prognosis awareness defined by congruence or incongruence with provider estimated prognosis.

RESULTS

285 patients were included in our analysis. The average age was 68 years (SD: 12.4), 87.2% were white, 50% male. The mean number of moderate/severe symptoms was 2.6 (SD: 2) out of 9 symptoms. Tiredness (66.7%), appetite (64.5%) and pain (46.2%) had the highest rates of moderate/severe symptom burden. Patients with a prognosis of 1-6 months had the lowest proportion of congruence with provider estimation (56.5%).

CONCLUSION

Our study suggests targets to improve patient-centered care of pancreatic cancer. Patients commonly have multiple symptoms that are moderate/severe at time of palliative care referral. While pain has been well-reported, tiredness and decreased appetite are more prevalent at initial visit. This emphasizes the importance of assessing multiple symptoms and working closely with palliative care for early referral. Overall, one third of patient prognosis estimates differed from the provider assessment of prognosis. Our data support the importance of early referral to palliative care to manage symptoms and better prepare patients for end-of-life care.

The ostrich approach - Prognostic avoidance, strategies and barriers to assessing older hospital patients' risk of dying

BACKGROUND

Predicting older patients' life expectancy is an important yet challenging task. Hospital aged care assessment teams advise treating teams on older patients' type and place of care, directly affecting quality of care. Yet, little is known about their experiences with prognostication.

METHODS

Twenty semi-structured interviews were conducted with seven geriatricians/ registrars, ten nurses and three allied health staff from aged care assessment teams across two hospitals in Melbourne, Australia. Data were analysed thematically.

RESULTS

To generate prognoses, clinicians used analytical thinking, intuition, assessments from others, and pattern matching. Prognostic tools were an underutilised resource. Barriers to recognition of dying included: diffusion of responsibility regarding whose role it is to identify patients at end-of-life; lack of feedback about whether a prognosis was correct; system pressures to pursue active treatment and vacate beds; avoidance of end-of-life discussions; lack of confidence, knowledge and training in prognostication and pandemic-related challenges.

Prognostication of the last days of life: Review article

Accurate prediction of impending death (i.e., last few days of life) is essential for terminally-ill cancer patients and their families. International guidelines state that clinicians should identify patients with impending death, communicate the prognosis with patients and families, help them with their end-of-life decision-making, and provide sufficient symptom palliation. Over the past decade, several national and international studies have been conducted that systematically investigated signs and symptoms of impending death as well as how to communicate such a prognosis effectively with patients and families. In this article, we summarize the current evidence on prognostication and communication regarding the last days of life of patients with cancer, and future directions of clinical research.

An observational study of intensivists’ expectations and effects of fluid boluses in critically ill patients

Background

Fluid bolus therapy (FBT) is common in ICUs but whether it achieves the effects expected by intensivists remains uncertain. We aimed to describe intensivists’ expectations and compare them to the actual physiological effects.

Methods

We evaluated 77 patients in two ICUs (Sweden and Australia). We included patients prescribed a FBT ≥250 ml over ≤30 minutes. The intensivist completed a questionnaire on triggers for and expected responses to FBT. We compared expected with actual values at FBT completion and after one hour.

Results

Median bolus size (IQR) was 300 ml (250–500) given over a median (IQR) of 21 minutes (15–30 mins). Boluses were 57% Ringer´s Acetate and 43% albumin (40-50g/L). Hypotension was the most common trigger (47%), followed by oliguria (21%). During FBT, 55% of patients received noradrenaline and 38% propofol. Intensivists expected a median MAP increase of 2.6 mmHg (IQR: -3.1 to +6.8) at end of bolus and of 1.3 mmHg (-3.5 to + 4.1) after one hour. Intensivist´s’ expectations were judged to be accurate if they were within 5% above or below measured values. At FBT completion, 33% of MAP expectations were overestimations and 42% were underestimations. One hour later, 19% were overestimations and 43% were underestimations. Only 8% of expectations of measured urine output (UO) were accurate and 44% were overestimations. Correction for sedation or vasopressors did not modify these findings.

Conclusions

The physiological expectations of intensivists after FBT carried a high risk of both over and underestimation. Since the physiological effect FBT was often small and did not meet clinical expectations, a reassessment of its rationale, effect, duration, and role appears justified.

Comparison of the accuracy of clinicians' prediction of survival and Palliative Prognostic Score: an East Asian cross-cultural study

PURPOSE

No study has been conducted to compare the clinicians' prediction of survival (CPS) with Palliative Prognostic Scores (PaP) across countries. We aimed to compare the performance of the CPS in PaP (PaP-CPS), the PaP without the CPS, and the PaP total scores in patients with advanced cancer in three East Asian countries.

METHODS

We compared the discriminative accuracy of the three predictive models (the PaP-CPS [the score of the categorical CPS of PaP], the PaP without the CPS [sum of the scores of only the objective variables of PaP], and the PaP total score) in patients admitted to palliative care units (PCUs) in Japan, Korea, and Taiwan. We calculated the area under the receiver operating characteristic curve (AUROC) for 30-day survival to compare the discriminative accuracy of these three models.

RESULTS

We analyzed 2,072 patients from three countries. The AUROC for the PaP total scores was 0.84 in patients in Japan, 0.76 in Korea, and 0.79 in Taiwan. The AUROC of the PaP-CPS was 0.82 in patients in Japan, 0.75 in Korea, and 0.78 in Taiwan. The AUROC of the PaP without the CPS was 0.75 in patients in Japan, 0.66 in Korea, and 0.67 in Taiwan.

CONCLUSION

The PaP total scores and the PaP-CPS consistently showed similar discriminative accuracy in predicting 30-day survival in patients admitted to PCUs in Japan, Korea, and Taiwan. It may be sufficient for experienced clinicians to use the CPS alone for estimating the short-term survival (less than one month) of patients with far-advanced cancer. The PaP may help to improve prognostic confidence and further reduce subjective variations.

Comparison of Two Methods for Implementing Comfort Care Order Sets in the Inpatient Setting: a Cluster Randomized Trial

BACKGROUND

There is an ongoing need for interventions to improve quality of end-of-life care for patients in inpatient settings.

OBJECTIVE

To compare two methods for implementing a Comfort Care Education Intervention for Palliative Care Consultation Teams (PCCT) in Veterans Affairs Medical Centers (VAMCs).

DESIGN

Cluster randomized implementation trial conducted March 2015-April 2019. PCCTs were assigned to a traditional implementation approach using a teleconference or to an in-person, train-the-champion workshop to prepare PCCTs to be clinical champions at their home sites.

PARTICIPANTS

One hundred thirty-two providers from PCCTs at 47 VAMCs.

INTERVENTIONS

Both training modalities involved review of educational materials, instruction on using an electronic Comfort Care Order Set, and coaching to deliver the intervention to other providers.

MAIN MEASUREMENTS

Several processes of care were identified a priori as quality endpoints for end-of-life care (last 7 days) and abstracted from medical records of veterans who died within 9 months before or after implementation (n = 6,491). The primary endpoint was the presence of an active order for opioid medication at time of death. Secondary endpoints were orders/administration of antipsychotics, benzodiazepines, and scopolamine, do-not-resuscitate orders, advance directives, locations of death, palliative care consultations, nasogastric tubes, intravenous lines, physical restraints, pastoral care visits, and family presence at/near time of death. Generalized estimating equations were conducted adjusting for potential covariates.

KEY RESULTS

Eighty-eight providers from 23 VAMCs received teleconference training; 44 providers from 23 VAMCs received in-person workshop training. Analyses found no significant differences between intervention groups in any process-of-care endpoints (primary endpoint AOR (CI) = 1.18 (0.74, 1.89). Furthermore, pre-post changes were not significant for any endpoints (primary endpoint AOR (CI) = 1.16 (0.92, 1.46). Analyses may have been limited by high baseline values on key endpoints with little room for improvement.

CONCLUSION

Findings suggest the clinical effectiveness of palliative care educational intervention was not dependent on which of the two implementation methods was used.

TRIAL REGISTRATION

ClinicalTrials.gov identifier: NCT02383173.

Improving the delivery of palliative care through predictive modeling and healthcare informatics

OBJECTIVE

Access to palliative care (PC) is important for many patients with uncontrolled symptom burden from serious or complex illness. However, many patients who could benefit from PC do not receive it early enough or at all. We sought to address this problem by building a predictive model into a comprehensive clinical framework with the aims to (i) identify in-hospital patients likely to benefit from a PC consult, and (ii) intervene on such patients by contacting their care team.

MATERIALS AND METHODS

Electronic health record data for 68 349 inpatient encounters in 2017 at a large hospital were used to train a model to predict the need for PC consult. This model was published as a web service, connected to institutional data pipelines, and consumed by a downstream display application monitored by the PC team. For those patients that the PC team deems appropriate, a team member then contacts the patient's corresponding care team.

RESULTS

Training performance AUC based on a 20% holdout validation set was 0.90. The most influential variables were previous palliative care, hospital unit, Albumin, Troponin, and metastatic cancer. The model has been successfully integrated into the clinical workflow making real-time predictions on hundreds of patients per day. The model had an "in-production" AUC of 0.91. A clinical trial is currently underway to assess the effect on clinical outcomes.

CONCLUSIONS

A machine learning model can effectively predict the need for an inpatient PC consult and has been successfully integrated into practice to refer new patients to PC.

Accuracy of the Palliative Prognostic Score With or Without Clinicians' Prediction of Survival in Patients With Far Advanced Cancer

CONTEXT

Previous studies suggest that clinicians' prediction of survival (CPS) may have reduced the accuracy of objective indicators for prognostication in palliative care.

OBJECTIVES

We aimed to examine the accuracy of CPS alone, compared to the original Palliative Prognostic Score (PaP), and five clinical/laboratory variables of the PaP in patients with far advanced cancer.

METHODS

We compared the discriminative accuracy of three prediction models (the PaP-CPS [the score of the categorical CPS of PaP], PaP without CPS [sum of the scores of only the objective variables of PaP], and PaP total score) across 3 settings: inpatient palliative care consultation team, palliative care unit, and home palliative care. We computed the area under receiver operating characteristic curve (AUROC) for 30-day survival and concordance index (C-index) to compare the discriminative accuracy of these three models.

RESULTS

We included a total of 1534 subjects with median survival of 34.0 days. The AUROC and C-index in the three settings were 0.816-0.896 and 0.732-0.799 for the PaP total score, 0.808-0.884 and 0.713-0.782 for the PaP-CPS, and 0.726-0.815 and 0.672-0.728 for the PaP without CPS, respectively. The PaP total score and PaP-CPS showed similar AUROCs and C-indices across the three settings. The PaP total score had significantly higher AUROCs and C-indices than the PaP without CPS across the three settings.

CONCLUSION

Overall, the PaP total score, PaP-CPS, and PaP without CPS showed good discriminative performances. However, the PaP total score and PaP-CPS were significantly more accurate than the PaP without CPS.

Factors predicting the risk of loss of decisional capacity for medical assistance in dying: a retrospective database review

BACKGROUND

Bill C-14, the legislation that legalized medical assistance in dying (MAiD) in Canada in 2016, outlines eligibility criteria and includes both a mandated 10-day reflection period and a requirement that the patient have capacity to consent at the time MAiD is provided. We examined clinical factors associated with shortened reflection periods or loss of capacity before provision of MAiD.

METHODS

This retrospective database review involved patients who requested MAiD at a tertiary care hospital in Toronto, Canada, between June 2016 and April 2019. We used logistic regression analyses to examine the association between the combined outcome of unanticipated loss of decisional capacity, shortening of the reflection period or death and the clinical risk factors of interest (age, sex, location of MAiD request [inpatient v. outpatient], score on palliative performance scale [PPS] and diagnosis [cancer v. noncancer]). We generated receiver operating characteristic curves to identify the PPS score (encompassing 5 functional domains: ambulation, activity level, self-care, intake and level of consciousness) that best predicted loss of capacity, shortening of the reflection period or death.

RESULTS

In total, 155 patients requested assessment for MAiD, and 136 of these were included in the statistical analyses. For 68 patients, the reflection period was not shortened; the other 68 patients lost capacity, died or required shortening of the reflection period. In contrast to the results for age, sex, location of request and diagnosis, the PPS score was associated with loss of capacity or shortening of the reflection period (odds ratio 4.63, 95% confidence interval 2.87-8.23, per 10-point decrease in PPS score). PPS scores less than or equal to 40% balanced sensitivity, specificity and negative predictive value while emphasizing sensitivity to prevent false negative errors.

INTERPRETATION

The PPS score at the time of MAiD request was strongly associated with loss of capacity or shortening of the reflection period, with lower scores incrementally increasing the risk of these outcomes. For patients with a PPS score of 40% or below, close monitoring is warranted, potentially with plans made to allow rapid provision of MAiD should their clinical condition deteriorate.

How palliative care professionals deal with predicting life expectancy at the end of life: predictors and accuracy

PURPOSE

To assess the accuracy of hospice staff in predicting survival of subjects admitted to hospice, exploring the factors considered most helpful by the hospice staff to accurately predict survival.

METHODS

Five physicians and 11 nurses were asked to predict survival at admission of 827 patients. Actual and predicted survival times were divided into ≤ 1 week, 2-3 weeks, 4-8 weeks, and ≥ 2 months and the accuracy of the estimates was calculated. The staff members were each asked to score 17 clinical variables that guided them in predicting survival and we analyzed how these variables impacted the accuracy.

RESULTS

Physicians' and nurses' accuracy of survival of the patients was 46% and 40% respectively. Survival was underestimated in 20% and 12% and overestimated in 34% and 48% of subjects. Both physicians and nurses considered metastases, comorbidities, dyspnea, disability, tumor site, neurological symptoms, and confusion very important in predicting patients' survival with nurses assigning more importance to intestinal symptoms and pain too. All these factors, with the addition of cough and/or bronchial secretions, were associated with physicians' greater accuracy. In the multivariable models, intestinal symptoms and confusion continued to be associated with greater predictive accuracy. No factors appreciably raised nurses' accuracy.

CONCLUSIONS

Some clinical symptoms rated as relevant by the hospice staff could be important for predicting survival. However, only intestinal symptoms and confusion significantly improved the accuracy of physicians' predictions, despite the high prevalence of overestimated survival.

A retrospective analysis of emergency surgery for cases of acute abdomen during cancer chemotherapy. Case series

Background

Treatment for acute abdomen during chemotherapy is frequently difficult because of the complicated status of the patients, and there have been only a few case series summarizing the outcomes of emergent surgery during chemotherapy. The aim of this study was to clarify the clinical outcomes of emergency surgery for acute abdomen during chemotherapy and identify predictive factors associated with mortality.

Methods

We retrospectively analyzed the records of patients who underwent emergency surgery for acute abdomen within 30-days after anti-cancer drugs administration between 2009 and 2020.

Results

Thirty patients were identified. The primary malignancies were hematological (n = 7), colorectal (n = 4), lung (n = 4), stomach (n = 2), breast (n = 2), prostate (n = 2) and others (n = 5). Fifteen patients were treated with the regimen, including molecular-targeted anti-cancer drugs (Bevacizumab: 8 cases, Rituximab: 4, Ramucirumab: 2, and Gefitinib: 1). Indications for emergency surgery were perforation of the gastrointestinal tract (n = 24), appendicitis (n = 3), bowel obstruction (n = 2), and gallbladder perforation (n = 1). Severe morbidity (Clavien-Dindo IIIa or more) occurred in 8 cases (27%), and there were 6 in-hospital deaths (20%). Significant factors related to in-hospital death were age >70 years old (P = 0.029), poor performance status (ECOG score 1 or 2) (P = 0.0088), and serum albumin level <2.6 g/dl (P = 0.026). The incidence of acute abdomen (odds ratio 5.31, P = 0.00017) was significantly higher in the patients receiving anti-VEGF drugs than in those without anti-VEGF drugs.

Conclusion

This study identified three predictive factors associated with in-hospital death after emergency surgery during chemotherapy: an older age, poor performance status, and low serum albumin level.

Patient-reported symptoms and problems at admission to specialized palliative care improved survival prediction in 30,969 cancer patients: A nationwide register-based study

BACKGROUND

Large, nationally representative studies of the association between quality of life and survival time in cancer patients in specialized palliative care are missing.

AIM

The aim of this study was to investigate whether symptoms/problems at admission to specialized palliative care were associated with survival and if the symptoms/problems may improve prediction of death within 1 week and 1 month, respectively.

SETTING/PARTICIPANTS

All cancer patients who had filled in the EORTC QLQ-C15-PAL at admission to specialized palliative care in Denmark in 2010-2017 were included through the Danish Palliative Care Database. Cox regression was used to identify clinical variables (gender, age, type of contact (inpatient vs outpatient), and cancer site) and symptoms/problems significantly associated with survival. To test whether symptoms/problems improved survival predictions, the overall accuracy (area under the receiver operating characteristic curve) for different prediction models was compared. The validity of the prediction models was tested with data on 5,508 patients admitted to palliative care in 2018.

RESULTS

The study included 30,969 patients with an average age of 68.9 years; 50% were women. Gender, age, type of contact, cancer site, and most symptoms/problems were significantly associated with survival time. The predictive value of symptoms/problems was trivial except for physical function, which clearly improved the overall accuracy for 1-week and 1-month predictions of death when added to models including only clinical variables.

CONCLUSION

Most symptoms/problems were significantly associated with survival and mainly physical function improved predictions of death. Interestingly, the predictive value of physical function was the same as all clinical variables combined (in hospice) or even higher (in palliative care teams).

Palliative Performance Scale: cross cultural adaptation and psychometric validation for Polish hospice setting

BACKGROUND

Measuring functional status in palliative care may help clinicians to assess a patient's prognosis, recommend adequate therapy, avoid futile or aggressive medical care, consider hospice referral, and evaluate provided rehabilitation outcomes. An optimized, widely used, and validated tool is preferable. The Palliative Performance Scale Version 2 (PPSv2) is currently one of the most commonly used performance scales in palliative settings. The aim of this study is the psychometric validation process of a Polish translation of this tool (PPSv2-Polish).

METHODS

Two hundred patients admitted to a free-standing hospice were evaluated twice, on the first and third day, for test-retest reliability. In the first evaluation, two different care providers independently evaluated the same patient to establish inter-rater reliability values. PPSv2-Polish was evaluated simultaneously with the Karnofsky Performance Score (KPS), Eastern Cooperative Oncology Group (ECOG) Performance Status (ECOG PS), and Barthel Activities of Daily Living (ADL) Index, to determine its construct validity.

RESULTS

A high level of full agreement between test and retest was seen (63%), and a good intra-class correlation coefficient of 0.85 (P < 0.0001) was achieved. Excellent agreement between raters was observed when using PPSv2-Polish (Cohen's kappa 0.91; P < 0.0001). Satisfactory correlations with the KPS and good correlations with ECOG PS and Barthel ADL were noticed. Persons who had shorter prognoses and were predominantly bedridden also had lower scores measured by the PPSv2-Polish, KPS and Barthel ADL. A strong correlation of 0.77 between PPSv2-Polish scores and survival time was noted (P < 0.0001). Moderate survival correlations were seen between KPS, ECOG PS, and Barthel ADL of 0.41; - 0.62; and 0.58, respectively (P < 0.0001).

CONCLUSION

PPSv2-Polish is a valid and reliable tool measuring performance status in a hospice population and can be used in daily clinical practice in palliative care and research.

A Systematic Approach to Comfort Care Transitions in the Emergency Department

BACKGROUND

Approximately 25-30% of Americans die within hospitals. An increasingly geriatric and chronically ill population arrive at emergency departments (EDs) for their terminal presentation. Many patients will not choose, nor are EDs obligated to deliver, futile care. Instead, aggressive comfort care may alleviate patient, family, and clinician distress.

OBJECTIVES

To discuss best practice through a systematic approach to comfort care transitions for the dying ED patient.

METHODS

Authors utilized a structured literature search conducted via PubMed (MEDLINE), Embase, and CINAHL databases, including studies from 1998 onward focusing on symptom palliation and coordination of care for acutely dying patients.

DISCUSSION

Comfort care begins with the language used to introduce the transition. Frame choices to avoid creating feelings of familial abandonment. Prognostication in the dying process helps guide treatment planning and stewarding families. Symptom management in the actively dying patient involves diligent titration of medications as well as thoughtful ordering in de-escalation of life-support modalities. Compassionate extubation necessitates anticipation of postextubation dyspnea or airway loss, and therefore may require step-wise weaning of pulmonary support. Suffering at the end of life for patients and families is multidimensional, and is best approached with an interdisciplinary effort involving clinicians, social work, and chaplaincy.

CONCLUSION

Comfort care deaths are a daily occurrence in the ED. A systematic approach to these transitions ensures optimal care for patients in their final hours and families' experience of these events.

Improving palliative care with deep learning

BACKGROUND

Access to palliative care is a key quality metric which most healthcare organizations strive to improve. The primary challenges to increasing palliative care access are a combination of physicians over-estimating patient prognoses, and a shortage of palliative staff in general. This, in combination with treatment inertia can result in a mismatch between patient wishes, and their actual care towards the end of life.

METHODS

In this work, we address this problem, with Institutional Review Board approval, using machine learning and Electronic Health Record (EHR) data of patients. We train a Deep Neural Network model on the EHR data of patients from previous years, to predict mortality of patients within the next 3-12 month period. This prediction is used as a proxy decision for identifying patients who could benefit from palliative care.

RESULTS

The EHR data of all admitted patients are evaluated every night by this algorithm, and the palliative care team is automatically notified of the list of patients with a positive prediction. In addition, we present a novel technique for decision interpretation, using which we provide explanations for the model's predictions.

CONCLUSION

The automatic screening and notification saves the palliative care team the burden of time consuming chart reviews of all patients, and allows them to take a proactive approach in reaching out to such patients rather then relying on referrals from the treating physicians.

Predicting one-year mortality in heart failure using the 'Surprise Question': a prospective pilot study

BACKGROUND

The Surprise Question: 'would you be surprised if this patient were to die within the next year?' has been shown to predict mortality in patients with chronic kidney disease and cancer. This prospective study aimed to determine whether the Surprise Question could identify heart failure patients with a prognosis of less than 1 year, and whether the Surprise Question can be used by different healthcare professionals.

METHODS AND RESULTS

Overall, 129 consecutive patients admitted with decompensated heart failure were included. Doctors and nurses were asked to provide a 'surprised' or 'not surprised' response to the Surprise Question for each patient. Patients were followed up until death or 1 year following study inclusion. The sensitivity, specificity, positive predictive value and negative predictive value of the Surprise Question were assessed. Cox regression was used to determine covariates significantly associated with survival. The Surprise Question showed excellent sensitivity (0.85) and negative predictive value (0.88) but only fair specificity (0.59) and positive predictive value (0.52) when asked of cardiologists. There were similar levels of accuracy between doctors and specialist nurses. The Surprise Question was significantly associated with all-cause mortality in multivariate regression analysis (hazard ratio 2.8, 95% confidence interval 1.0-7.9, P = 0.046).

CONCLUSION

This study demonstrates that the Surprise Question can identify heart failure patients within the last year of life. Despite over-classification of patients into the 'not surprised' category, the Surprise Question identified nearly all patients who were within the last year of life, whilst also accurately identifying those unlikely to die.

Ambulatory Advanced Cancer Patients' and Oncologists' Estimates of Life Expectancy Are Associated with Patient Psychological Characteristics But Not Chemotherapy Use

BACKGROUND

Patients with advanced cancer often face distressing decisions about chemotherapy. There are conflicting data on the relationships among perceived prognosis, psychological characteristics, and chemotherapy use, which impair the refinement of decision support interventions.

OBJECTIVE

Clarify the relationships among patient and oncologist estimates of life expectancy for 6 and 12 months, chemotherapy use, and patient psychological characteristics.

DESIGN

Secondary analysis of data from two cross-sectional studies.

SETTING/SUBJECTS

One hundred sixty-six patients with advanced stage cancer recruited from ambulatory cancer clinics.

MEASUREMENTS

All data were obtained at study enrollment. Patients completed the Adult Hope Scale, Hospital Anxiety and Depression Scale, and Life Orientation Test-Revised. Patients and their oncologists provided estimates of surviving beyond 6 and 12 months. Chemotherapy use was determined by chart review.

RESULTS

There were no significant associations between life-expectancy estimates and chemotherapy use nor patient anxiety, depression, hope, or optimism and chemotherapy use. Patients' life expectancy estimates for 12 months and oncologists' for 6 months were associated with higher patient anxiety and depression. Finally, both oncologist and patient estimates of life expectancy for 6 and 12 months were associated with increased levels of trait hope.

CONCLUSION

Advanced cancer patients who provide less optimistic estimates of life expectancy have increased anxiety and depression, but do not use chemotherapy more often. Increased patient trait hope is associated with more favorable oncologist estimates. These findings highlight the need for interventions to support both patients and oncologists as they clarify prognostic expectations and patients cope with the psychological distress of a limited life expectancy.

Life Expectancy Predictions for Older Diabetic Patients as Estimated by Physicians and a Prognostic Model

Background: Multiple medical organizations recommend using life expectancy (LE) to individualize diabetes care goals. We compare the performance of patient LE predictions made by physicians to LE predictions from a simulation model (the Chicago model) in a cohort of older diabetic patients. Design: Retrospective cohort study of a convenience sample (n = 447) of diabetes patients over 65 years and their physicians. Measurements: Physicians provided LE estimates for individual patients during a baseline survey (2000–2003). The prognostic model included a comprehensive geriatric type 2 diabetes simulation model (the Chicago model) and combinations of the physician estimate and the Chicago model (“And,” “Or,” and “Average” models). Observed survival was determined based on the National Death Index through 31 December 2010. The predictive accuracy of LE predictions was assessed using c-statistic for 5-year mortality; Harrell’s c-statistic, and Integrated Brier score for overall survival. Results: The patient cohort had a mean (SD) age of 73.4 (5.9) years. The majority were female (62.6%) and black (79.4%). At 5 years, 108 (24.2%) patients had died. The c-statistic for 5-year mortality was similar for physicians (0.69) and the Chicago model (0.68), while the average of estimates by physicians and Chicago model yielded the highest c-statistic of any method tested (0.73). The estimates of overall survival yielded a similar pattern of results. Limitations: Generalizability of patient cohort and lack of updated model parameters. Conclusions: Compared with individual methods, the average of LE estimates by physicians and the Chicago model had the best predictive performance. Prognostic models, such as the Chicago model, may complement and support physicians’ intuitions as they consider treatment decisions and goals for older patients with chronic conditions like diabetes.

Prognostic Tools in Patients With Advanced Cancer: A Systematic Review

PURPOSE

In 2005, the European Association for Palliative Care made recommendations for prognostic markers in advanced cancer. Since then, prognostic tools have been developed, evolved, and validated. The aim of this systematic review was to examine the progress in the development and validation of prognostic tools.

METHODS

Medline, Embase Classic and Embase were searched. Eligible studies met the following criteria: patients with incurable cancer, >18 years, original studies, population n ≥100, and published after 2003. Descriptive and quantitative statistical analyses were performed.

RESULTS

Forty-nine studies were eligible, assessing seven prognostic tools across different care settings, primary cancer types, and statistically assessed survival prediction. The Palliative Performance Scale was the most studied (n = 21,082), comprising six parameters (six subjective), was externally validated, and predicted survival. The Palliative Prognostic Score composed of six parameters (four subjective and two objective), the Palliative Prognostic Index composed of nine parameters (nine subjective), and the Glasgow Prognostic Score composed of two parameters (two objective) and were all externally validated in more than 2000 patients with advanced cancer and predicted survival.

CONCLUSION

Various prognostic tools have been validated but vary in their complexity, subjectivity, and therefore clinical utility. The Glasgow Prognostic Score would seem the most favorable as it uses only two parameters (both objective) and has prognostic value complementary to the gold standard measure, which is performance status. Further studies comparing all proved prognostic markers in a single cohort of patients with advanced cancer are needed to determine the optimal prognostic tool.

Ethics, Emotions, and the Skills of Talking About Progressing Disease With Terminally Ill Adolescents: A Review

IMPORTANCE

For clinicians caring for adolescent patients living with progressive, life-threatening illness, discussions regarding prognosis, goals of care, and treatment options can be extremely challenging. While clinicians should respect and help to facilitate adolescents' emerging autonomy, they often must also work with parents' wishes to protect patients from the emotional distress of hearing bad news.

OBSERVATIONS

We reviewed the ethical justifications for and against truth-telling, and we considered the published ethical and practice guidance, as well as the perspectives of patients, parents, and clinicians involved in these cases. We also explored particular challenges with respect to the cultural context, timing, and content of conversations at the end of adolescents' lives. In most cases, clinicians should gently but persistently engage adolescents directly in conversations about their disease prognosis and corresponding hopes, worries, and goals. These conversations need to occur multiple times, allowing significant time in each discussion for exploration of patient and family values. While truth-telling does not cause the types of harm that parents and clinicians may fear, discussing this kind of difficult news is almost always emotionally distressing. We suggest some "phrases that help" when clinicians strive to deepen understanding and facilitate difficult conversations with adolescents, parents, and other family members.

CONCLUSIONS AND RELEVANCE

The pediatrician's opportunities to engage in difficult conversations about poor prognosis may be rare, but such conversations can be crucial. These discussions affect how patients live at the end of their lives, how they die, and how their families go on. Improved understanding of basic principles of communication, as well as augmented understanding of patient, family, and clinician perspectives may better enable us to navigate these important conversations.

A Systematic Review of Predictions of Survival in Palliative Care: How Accurate Are Clinicians and Who Are the Experts?

Background

Prognostic accuracy in palliative care is valued by patients, carers, and healthcare professionals. Previous reviews suggest clinicians are inaccurate at survival estimates, but have only reported the accuracy of estimates on patients with a cancer diagnosis.

Objectives

To examine the accuracy of clinicians’ estimates of survival and to determine if any clinical profession is better at doing so than another.

Data Sources

MEDLINE, Embase, CINAHL, and the Cochrane Database of Systematic Reviews and Trials. All databases were searched from the start of the database up to June 2015. Reference lists of eligible articles were also checked.

Eligibility Criteria

Inclusion criteria: patients over 18, palliative population and setting, quantifiable estimate based on real patients, full publication written in English. Exclusion criteria: if the estimate was following an intervention, such as surgery, or the patient was artificially ventilated or in intensive care.

Study Appraisal and Synthesis Methods

A quality assessment was completed with the QUIPS tool. Data on the reported accuracy of estimates and information about the clinicians were extracted. Studies were grouped by type of estimate: categorical (the clinician had a predetermined list of outcomes to choose from), continuous (open-ended estimate), or probabilistic (likelihood of surviving a particular time frame).

Results

4,642 records were identified; 42 studies fully met the review criteria. Wide variation was shown with categorical estimates (range 23% to 78%) and continuous estimates ranged between an underestimate of 86 days to an overestimate of 93 days. The four papers which used probabilistic estimates tended to show greater accuracy (c-statistics of 0.74–0.78). Information available about the clinicians providing the estimates was limited. Overall, there was no clear “expert” subgroup of clinicians identified.

Limitations

High heterogeneity limited the analyses possible and prevented an overall accuracy being reported. Data were extracted using a standardised tool, by one reviewer, which could have introduced bias. Devising search terms for prognostic studies is challenging. Every attempt was made to devise search terms that were sufficiently sensitive to detect all prognostic studies; however, it remains possible that some studies were not identified.

Conclusion

Studies of prognostic accuracy in palliative care are heterogeneous, but the evidence suggests that clinicians’ predictions are frequently inaccurate. No sub-group of clinicians was consistently shown to be more accurate than any other.

Implications of Key Findings

Further research is needed to understand how clinical predictions are formulated and how their accuracy can be improved.

Factors influencing communication and decision-making about life-sustaining technology during serious illness: a qualitative study

OBJECTIVES

We aimed to identify factors influencing communication and decision-making, and to learn how physicians and nurses view their roles in deciding about the use of life-sustaining technology for seriously ill hospitalised patients and their families.

DESIGN

The qualitative study used Flanagan's critical incident technique to guide interpretive description of open-ended in-depth individual interviews.

SETTING

Participants were recruited from the medical wards at 3 Canadian hospitals.

PARTICIPANTS

Interviews were completed with 30 healthcare professionals (9 staff physicians, 9 residents and 12 nurses; aged 25-63 years; 73% female) involved in decisions about the care of seriously ill hospitalised patients and their families.

MEASURES

Participants described encounters with patients and families in which communication and decision-making about life-sustaining technology went particularly well and unwell (ie, critical incidents). We further explored their roles, context and challenges. Analysis proceeded using constant comparative methods to form themes independently and with the interprofessional research team.

RESULTS

We identified several key factors that influenced communication and decision-making about life-sustaining technology. The overarching factor was how those involved in such communication and decision-making (healthcare providers, patients and families) conceptualised the goals of medical practice. Additional key factors related to how preferences and decision-making were shaped through relationships, particularly how people worked toward 'making sense of the situation', how physicians and nurses approached the inherent and systemic tensions in achieving consensus with families, and how physicians and nurses conducted professional work within teams. Participants described incidents in which these key factors interacted in dynamic and unpredictable ways to influence decision-making for any particular patient and family.

CONCLUSIONS

A focus on more meaningful and productive dialogue with patients and families by (and between) each member of the healthcare team may improve decisions about life-sustaining technology. Work is needed to acknowledge and support the non-curative role of healthcare and build capacity for the interprofessional team to engage in effective decision-making discussions.

Factors Associated with Short-Term Mortality After Surgical Oncologic Emergencies

BACKGROUND

The clinical outcome of patients with oncologic emergencies is often poor and mortality is high. It is important to determine which patients may benefit from invasive treatment, and for whom conservative treatment and/or palliative care would be appropriate. In this study, prognostic factors for clinical outcome are identified in order to facilitate the decision-making process for patients with surgical oncologic emergencies.

METHODS

This was a prospective registration study for patients over 18 years of age, who were consulted for surgical oncologic emergencies between November 2013 and April 2014. Multiple variables were registered upon emergency consultation, and the follow-up period was 90 days. Multivariate logistic regression analysis was performed to identify factors associated with 30- and 90-day mortality.

RESULTS

During the study period, 207 patients experienced surgical oncologic emergencies-101 (48.8 %) men and 106 (51.2 %) women, with a median age of 64 years (range 19-92). The 30-day mortality was 12.6 % and 90-day mortality was 21.7 %. Factors significantly associated with 30-day mortality were palliative intent of cancer treatment prior to emergency consultation (p = 0.006), Eastern Cooperative Oncology Group performance score (ECOG-PS) >0 (p for trend: p = 0.03), and raised lactate dehydrogenase (LDH) (p < 0.001). Additional factors associated with 90-day mortality were low handgrip strength (HGS) (p = 0.01) and low albumin (p = 0.002).

CONCLUSIONS

Defining the intent of prior cancer treatment and the ECOG-PS are of prognostic value when deciding on treatment for patients with surgical oncologic emergencies. Additional measurements of HGS, LDH, and albumin levels can serve as objective parameters to support the clinical assessment of individual prognosis.

Outcomes of Prognostic Disclosure: Associations With Prognostic Understanding, Distress, and Relationship With Physician Among Patients With Advanced Cancer

PURPOSE

To determine how prognostic conversations influence perceptions of life expectancy (LE), distress, and the patient-physician relationship among patients with advanced cancer.

PATIENTS AND METHODS

This was a multicenter observational study of 590 patients with metastatic solid malignancies with progressive disease after ≥ one line of palliative chemotherapy, undergoing follow-up to death. At baseline, patients were asked whether their oncologist had disclosed an estimate of prognosis. Patients also estimated their own LE and completed assessments of the patient-physician relationship, distress, advance directives, and end-of-life care preferences.

RESULTS

Among this cohort of 590 patients with advanced cancer (median survival, 5.4 months), 71% wanted to be told their LE, but only 17.6% recalled a prognostic disclosure by their physician. Among the 299 (51%) of 590 patients willing to estimate their LE, those who recalled prognostic disclosure offered more realistic estimates as compared with patients who did not (median, 12 months; interquartile range, 6 to 36 months v 48 months; interquartile range, 12 to 180 months; P < .001), and their estimates were less likely to differ from their actual survival by > 2 (30.2% v 49.2%; odds ratio [OR], 0.45; 95% CI, 0.14 to 0.82) or 5 years (9.5% v 35.5%; OR, 0.19; 95% CI, 0.08 to 0.47). In adjusted analyses, recall of prognostic disclosure was associated with a 17.2-month decrease (95% CI, 6.2 to 28.2 months) in patients' LE self-estimates. Longer LE self-estimates were associated with lower likelihood of do-not-resuscitate order (adjusted OR, 0.439; 95% CI, 0.296 to 0.630 per 12-month increase in estimate) and preference for life-prolonging over comfort-oriented care (adjusted OR, 1.493; 95% CI, 1.091 to 1.939). Prognostic disclosure was not associated with worse patient-physician relationship ratings, sadness, or anxiety in adjusted analyses.

CONCLUSION

Prognostic disclosures are associated with more realistic patient expectations of LE, without decrements to their emotional well-being or the patient-physician relationship.

Current management of surgical oncologic emergencies

Objectives

For some oncologic emergencies, surgical interventions are necessary for dissolution or temporary relieve. In the absence of guidelines, the most optimal method for decision making would be in a multidisciplinary cancer conference (MCC). In an acute setting, the opportunity for multidisciplinary discussion is often not available. In this study, the management and short term outcome of patients after surgical oncologic emergency consultation was analyzed.

Method

A prospective registration and follow up of adult patients with surgical oncologic emergencies between 01-11-2013 and 30-04-2014. The follow up period was 30 days.

Results

In total, 207 patients with surgical oncologic emergencies were included. Postoperative wound infections, malignant obstruction, and clinical deterioration due to progressive disease were the most frequent conditions for surgical oncologic emergency consultation. During the follow up period, 40% of patients underwent surgery. The median number of involved medical specialties was two. Only 30% of all patients were discussed in a MCC within 30 days after emergency consultation, and only 41% of the patients who underwent surgery were discussed in a MCC. For 79% of these patients, the surgical procedure was performed before the MCC. Mortality within 30 days was 13%.

Conclusion

In most cases, surgery occurred without discussing the patient in a MCC, regardless of the fact that multiple medical specialties were involved in the treatment process. There is a need for prognostic aids and acute oncology pathways with structural multidisciplinary management. These will provide in faster institution of the most appropriate personalized cancer care, and prevent unnecessary investigations or invasive therapy.

Longitudinal temporal and probabilistic prediction of survival in a cohort of patients with advanced cancer

CONTEXT

Survival prognostication is important during the end of life. The accuracy of clinician prediction of survival (CPS) over time has not been well characterized.

OBJECTIVES

The aims of the study were to examine changes in prognostication accuracy during the last 14 days of life in a cohort of patients with advanced cancer admitted to two acute palliative care units and to compare the accuracy between the temporal and probabilistic approaches.

METHODS

Physicians and nurses prognosticated survival daily for cancer patients in two hospitals until death/discharge using two prognostic approaches: temporal and probabilistic. We assessed accuracy for each method daily during the last 14 days of life comparing accuracy at Day -14 (baseline) with accuracy at each time point using a test of proportions.

RESULTS

A total of 6718 temporal and 6621 probabilistic estimations were provided by physicians and nurses for 311 patients, respectively. Median (interquartile range) survival was 8 days (4-20 days). Temporal CPS had low accuracy (10%-40%) and did not change over time. In contrast, probabilistic CPS was significantly more accurate (P < .05 at each time point) but decreased close to death.

CONCLUSION

Probabilistic CPS was consistently more accurate than temporal CPS over the last 14 days of life; however, its accuracy decreased as patients approached death. Our findings suggest that better tools to predict impending death are necessary.

Palliative performance scale and survival among outpatients with advanced cancer

PURPOSE

Previous studies have examined the association between the Palliative Performance Scale (PPS) and survival duration; however, few have examined patients with incurable cancer in the outpatient setting. In addition to exploring this association further, the purpose of this study was to identify key PPS markers that could serve as triggers to signify the need for key care discussions.

METHODS

Study subjects were followed prospectively from the time of referral for a specialist palliative care consultation until death. PPS ratings and survival estimates were determined for each visit.

RESULTS

For the final study population of 368 patients, at baseline, the median PPS rating was 60. Overall median and mean survival duration were approximately 4 and 6 months, respectively. Median survival duration for patients with PPS ratings of 70, 60, and 50 were found to be approximately 6, 3, and 2 months, respectively. Twenty-four percent of all survival estimates were found to be accurate.

CONCLUSIONS

Given the ongoing challenge of inaccurate survival estimates, this data suggests what may be of greatest clinical utility is to use specific PPS ratings as triggers for key care discussions among patients with incurable and progressive cancer.

Intervention to improve care at life's end in inpatient settings: the BEACON trial

BACKGROUND

Widespread implementation of palliative care treatment plans could reduce suffering in the last days of life by adopting best practices of traditionally home-based hospice care in inpatient settings.

OBJECTIVE

To evaluate the effectiveness of a multi-modal intervention strategy to improve processes of end-of-life care in inpatient settings.

DESIGN

Implementation trial with an intervention staggered across hospitals using a multiple-baseline, stepped wedge design.

PARTICIPANTS

Six Veterans Affairs Medical Centers (VAMCs).

INTERVENTION

Staff training was targeted to all hospital providers and focused on identifying actively dying patients and implementing best practices from home-based hospice care, supported with an electronic order set and paper-based educational tools.

MAIN MEASURES

Several processes of care were identified as quality endpoints for end-of-life care (last 7 days) and abstracted from electronic medical records of veterans who died before or after intervention (n = 6,066). Primary endpoints were proportion with an order for opioid pain medication at time of death, do-not-resuscitate order, location of death, nasogastric tube, intravenous line infusing, and physical restraints. Secondary endpoints were administration of opioids, order/administration of antipsychotics, benzodiazepines, and scopolamine (for death rattle); sublingual administration; advance directives; palliative care consultations; and pastoral care services. Generalized estimating equations were conducted adjusting for longitudinal trends.

KEY RESULTS

Significant intervention effects were observed for orders for opioid pain medication (OR: 1.39), antipsychotic medications (OR: 1.98), benzodiazepines (OR: 1.39), death rattle medications (OR: 2.77), sublingual administration (OR: 4.12), nasogastric tubes (OR: 0.71), and advance directives (OR: 1.47). Intervention effects were not significant for location of death, do-not-resuscitate orders, intravenous lines, or restraints.

CONCLUSIONS

This broadly targeted intervention strategy led to modest but statistically significant changes in several processes of care, indicating its potential for widespread dissemination to improve end-of-life care for thousands of patients who die each year in inpatient settings.

Revisiting the Palliative Performance Scale: change in scores during disease trajectory predicts survival

BACKGROUND

The Palliative Performance Scale (PPS) on admission is a predictor of survival. However, it is not highly discriminating for mid-range scores. 'PPS Change' between two time points considers the disease trajectory, and may improve the scale's utility.

AIM

The aim of this study is to determine if a change in PPS scores between two significant time points predicts survival.

DESIGN

This prospective cohort study examined 'Change on Admission', 'Change at Week 1', and 'Change at Week 2'. We followed patients until death or 6 months, whichever was earlier. Cox regressions were used to determine if the Change scores were predictors of survival, adjusting for age, sex, diagnosis category, Charlson Index, and Do-Not-Resuscitate order.

SETTING/PARTICIPANTS

The sample consisted of patients referred to the palliative care service.

RESULTS

All three Change scores were independent predictors of survival. The greater the change, the poorer the prognosis. At week 1, when compared to 'PPS Change ≤ 10%', 'Change 11% -30%' and 'Change > 30%' increased the hazard ratios by 1.70 (95% CI 1.10-2.63) and 3.14 (95% CI 1.77-5.59), respectively. At week 2, when compared to 'PPS Change ≤ 10%', 'Change 11% -30%' and 'Change > 30%' increased the hazard ratios by almost 3- and 8-fold, respectively. The same magnitude of Change scores also has higher hazard ratios as patients' hospitalization progressed.

CONCLUSIONS

The magnitude of change in PPS score during the disease trajectory is associated with one's survival and is a potentially useful prognostication tool. Further research is needed to extend on our work.

A qualitative analysis of the elements used by palliative care clinicians when formulating a survival estimate

OBJECTIVE

For patients with advanced and/or incurable disease, clinicians are often called upon to formulate and communicate an estimate of likely survival duration. The objective of this study was to gain a deeper appreciation of this process by identifying and exploring the specific elements that may inform and/or impact a clinician's estimate of survival (CES).

METHODS

Semistructured interviews were conducted among a group of palliative care clinicians in the setting of a tertiary academic health sciences centre. Qualitative data were subsequently analysed using a grounded theory approach.

RESULTS

Five major themes were identified as being central to the process of CES formulation: use of objective patient-specific elements, strength of the patient-clinician relationship, purpose and context of an individual CES, perceived role of hope and the overall likelihood of CES inaccuracy.

CONCLUSIONS

For any given patient, several elements have the potential to inform and/or impact the process of CES formulation. Study participants were aware of objective clinical factors known to correlate with actual survival duration and likely integrate this information when formulating a CES. Formulation occurs within a larger context comprised of a number of elements that may influence individual estimates. These elements exist against a background of awareness of the overall likelihood of CES inaccuracy. Clinicians are encouraged to develop a personalised and standardised approach to CES formulation whereby an awareness of the menu of potentially impacting elements is consciously integrated into an individual process.

Survival duration among patients with a noncancer diagnosis admitted to a palliative care unit: a retrospective study

BACKGROUND

Palliative care unit (PCU) beds are a limited resource in Canada, so PCU admission is restricted to patients with a short prognosis. Anecdotally, PCUs further restrict admission of patients with noncancer diagnoses out of fear that they will "oversurvive" and reduce bed availability. This raises concerns that noncancer patients have unequal access to PCU resources.

PURPOSE/METHODS

To clarify survival duration of patients with a noncancer diagnosis, we conducted a retrospective review of all admissions to four PCUs in Toronto, Canada, over a 1-year period. We measured associations between demographic data, prognosis, Palliative Performance Score (PPS), length of stay (LOS), and waiting time.

RESULTS

We collected data for 1000 patients, of whom 21% had noncancer diagnoses. Noncancer patients were older, with shorter prognoses and lower PPS scores on admission. Noncancer patients had shorter LOS (14 versus 24, p<0.001) than cancer patients and a similar likelihood of being discharged alive to cancer patients. Noncancer patients had a trend to lower LOS across a broad range of demographic, diagnostic, prognostic, and PPS categories. Multivariable analysis showed that LOS was not associated with the diagnosis of cancer (p=0.36).

DISCUSSION/CONCLUSION

Noncancer patients have a shorter LOS than cancer patients and a similar likelihood of being discharged alive from a PCU than cancer patients, and the diagnosis of cancer did not correlate with survival in our study population. Our findings demonstrate that noncancer patients are not "oversurviving," and that referring physicians and PCUs should not reject or restrict noncancer referrals out of concern that these patients are having a detrimental impact on PCU bed availability.