How accurate is the 'Surprise Question' at identifying patients at the end of life? A systematic review and meta-analysis

Acute internal medicine physicians' clinical intuition based on acute care telephone referral: A prospective study

INTRODUCTION

In the Netherlands, most emergency department (ED) patients are referred by a general practitioner (GP) or a hospital specialist. Early risk stratification during telephone referral could allow the physician to assess the severity of the patients' illness in the prehospital setting. We aim to assess the discriminatory value of the acute internal medicine (AIM) physicians' clinical intuition based on telephone referral of ED patients to predict short-term adverse outcomes, and to investigate on which information their predictions are based.

METHODS

In this prospective study, we included adult ED patients who were referred for internal medicine by a GP or a hospital specialist. Primary outcomes were hospital admission and triage category according to the Manchester Triage System (MTS). Secondary outcome was 31-day mortality. The discriminatory performance of the clinical intuition was assessed using an area under the receiver operating characteristics curve (AUC). To identify which information is important to predict adverse outcomes, we performed univariate regression analysis. Agreement between predicted and observed MTS triage category was assessed using intraclass and Spearman's correlation.

RESULTS

We included 333 patients, of whom 172 (51.7%) were referred by a GP, 146 (43.8%) by a hospital specialist, and 12 (3.6%) by another health professional. The AIM physician's clinical intuition showed good discriminatory performance regarding hospital admission (AUC 0.72, 95% CI: 0.66-0.78) and 31-day mortality (AUC 0.73, 95% CI: 0.64-0.81). Univariate regression analysis showed that age ≥65 years and a sense of alarm were significant predictors. The predicted and observed triage category were similar in 45.2%, but in 92.5% the prediction did not deviate by more than one category. Intraclass and Spearman's correlation showed fair agreement between predicted and observed triage category (ICC 0.48, Spearman's 0.29).

CONCLUSION

Clinical intuition based on relevant information during a telephone referral can be used to accurately predict short-term outcomes, allowing for early risk stratification in the prehospital setting and managing ED patient flow more effectively.

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 utility of the surprise question by nurses to identify hospitalised older patients nearing the end-of-life and promotion of advance care planning: An interventional study

AIMS AND OBJECTIVES

To assess the prognostic accuracy of the surprise question (SQ) when used by nurses working in hospital wards to determine 1-year mortality in acutely hospitalised older patients.

BACKGROUND

The predictive accuracy of the SQ, when used by general nurses caring for older hospitalised patients, has not been comprehensively studied.

DESIGN

A prospective cohort study.

METHODS

This cohort study recruited consecutive 10,139 older patients (aged ≥65 years) who were admitted to Taipei City Hospital and were evaluated for the needs of palliative care in 2015. All patients were followed up for 12 months or until their death. The c-statistic value was calculated to indicate the predictive accuracy of the SQ and Palliative Care Screening Tool (PCST).

RESULTS

Of all participants, 18.8% and 18.6% had a SQ response of 'no' and a PCST score ≥4, respectively. After controlling for other covariates, an SQ response of 'no' (adjusted hazard ratio [aHR], 2.05; 95% confidence interval [CI], 1.83-2.31) and a PCST score ≥4 (AHR = 1.50; 95% CI: 1.29-1.75) were found to be the independent predictors for patients' 12-month mortality. The C-statistic values of the SQ and the PCST at recognising patients in their last year of life were .663 and .670, respectively. Moreover, there was moderate concordance (k = .44) between the SQ and the PCST in predicting 12-month mortality.

CONCLUSIONS

SQ response of 'no' and a PCST score ≥4 were independent predictors of 12-month mortality in older patients.

RELEVANCE TO CLINICAL PRACTICE

The SQ, when used by nurses working in hospital wards, is effective in identifying older patients nearing the end of life, as well as in providing advance care planning for patients.

PATIENT OR PUBLIC CONTRIBUTION

Patients' palliative care needs at admission were assessed by general nurses using the SQ and PCST.

Indian Society of Critical Care Medicine and Indian Association of Palliative Care Expert Consensus and Position Statements for End-of-life and Palliative Care in the Intensive Care Unit

End-of-life care (EOLC) exemplifies the joint mission of intensive and palliative care (PC) in their human-centeredness. The explosion of technological advances in medicine must be balanced with the culture of holistic care. Inevitably, it brings together the science and the art of medicine in their full expression. High-quality EOLC in the ICU is grounded in evidence, ethical principles, and professionalism within the framework of the Law. Expert professional statements over the last two decades in India were developed while the law was evolving. Recent landmark Supreme Court judgments have necessitated a review of the clinical pathway for EOLC outlined in the previous statements. Much empirical and interventional evidence has accumulated since the position statement in 2014. This iteration of the joint Indian Society of Critical Care Medicine-Indian Association of Palliative Care (ISCCM-IAPC) Position Statement for EOLC combines contemporary evidence, ethics, and law for decision support by the bedside in Indian ICUs.

How to cite this article

Mani RK, Bhatnagar S, Butola S, Gursahani R, Mehta D, Simha S, et al. Indian Society of Critical Care Medicine and Indian Association of Palliative Care Expert Consensus and Position Statements for End-of-life and Palliative Care in the Intensive Care Unit. Indian J Crit Care Med 2024;28(3):200-250.

Advancing screening tool for hospice needs and end-of-life decision-making process in the emergency department

BACKGROUND

Predicting mortality in the emergency department (ED) is imperative to guide palliative care and end-of-life decisions. However, the clinical usefulness of utilizing the existing screening tools still leaves something to be desired.

METHODS

We advanced the screening tool with the A-qCPR (Age, qSOFA (quick sepsis-related organ failure assessment), cancer, Performance Status Scale, and DNR (Do-Not-Resuscitate) risk score model for predicting one-year mortality in the emergency department of Taipei City Hospital of Taiwan with the potential of hospice need and evaluated its performance compared with the existing screening model. We adopted a large retrospective cohort in conjunction with in-time (the trained and the holdout validation cohort) for the development of the A-qCPR model and out-of-time validation sample for external validation and model robustness to variation with the calendar year.

RESULTS

A total of 10,474 patients were enrolled in the training cohort and 33,182 patients for external validation. Significant risk scores included age (0.05 per year), qSOFA ≥ 2 (4), Cancer (5), Eastern Cooperative Oncology Group (ECOG) Performance Status score ≥ 2 (2), and DNR status (2). One-year mortality rates were 13.6% for low (score ≦ 3 points), 29.9% for medium (3 < Score ≦ 9 points), and 47.1% for high categories (Score > 9 points). The AUROC curve for the in-time validation sample was 0.76 (0.74-0.78). However, the corresponding figure was slightly shrunk to 0.69 (0.69-0.70) based on out-of-time validation. The accuracy with our newly developed A-qCPR model was better than those existing tools including 0.57 (0.56-0.57) by using SQ (surprise question), 0.54 (0.54-0.54) by using qSOFA, and 0.59 (0.59-0.59) by using ECOG performance status score. Applying the A-qCPR model to emergency departments since 2017 has led to a year-on-year increase in the proportion of patients or their families signing DNR documents, which had not been affected by the COVID-19 pandemic.

CONCLUSIONS

The A-qCPR model is not only effective in predicting one-year mortality but also in identifying hospice needs. Advancing the screening tool that has been widely used for hospice in various scenarios is particularly helpful for facilitating the end-of-life decision-making process in the ED.

The 'Surprise question' in heart failure: a prospective cohort study

OBJECTIVE

The Surprise Question (SQ) is a prognostic screening tool used to identify patients with limited life expectancy. We assessed the SQ's performance predicting 1-year mortality among patients in ambulatory heart failure (HF) clinics. We determined that the SQ's performance changes according to sex and other demographic (age) and clinical characteristics, mainly left ventricular ejection fraction (LVEF) and the New York Heart Association (NYHA) functional classifications.

METHODS

We conducted a prospective cohort study in two HF clinics. To assess the performance of the SQ in predicting 1-year mortality, we calculated the sensitivity, specificity, positive and negative likelihood ratios, and the positive and negative predictive values. To illustrate if the results of the SQ changes the probability that a patient dies within 1 year, we created Fagan's nomograms. We report the results from the overall sample and for subgroups according to sex, age, LVEF and NYHA functional class.

RESULTS

We observed that the SQ showed a sensitivity of 85% identifying ambulatory patients with HF who are in the last year of life. We determined that the SQ's performance predicting 1-year mortality was similar among women and men. The SQ performed better for patients aged under 70 years, for patients with reduced or mildly reduced ejection fraction, and for patients NYHA class III/IV.

CONCLUSIONS

We consider the tool an easy and fast first step to identify patients with HF who might benefit from an advance care planning discussion or a referral to palliative care due to limited life expectancy.

The Physician Surprise Question in the Emergency Department: prospective cohort study

OBJECTIVES

This study aims to test the ability of the surprise question (SQ), when asked to emergency physicians (EPs), to predict in-hospital mortality among adults admitted to an emergency room (ER).

METHODS

This prospective cohort study at an academic medical centre included consecutive patients 18 years or older who received care in the ER and were subsequently admitted to the hospital from 20 April 2018 to 20 October 2018. EPs were required to answer the SQ for all patients who were being admitted to hospital. The primary outcome was in-hospital mortality.

RESULTS

The cohort included 725 adults (mean (SD) age, 60 (17) years, 51% men) from 58 128 emergency department (ED) visits. The mortality rates were 20.6% for 30-day all-cause in-hospital mortality and 23.6% for in-hospital mortality. The diagnostic test characteristics of the SQ have a sensitivity of 53.7% and specificity of 87.1%, and a relative risk of 4.02 (95% CI 3.15 to 5.13), p<0.01). The positive and negative predictive values were 57% and 86%, respectively; the positive likelihood ratio was 4.1 and negative likelihood ratio was 0.53; and the accuracy was 79.2%.

CONCLUSIONS

We found that asking the SQ to EPs may be a useful tool to identify patients in the ED with a high risk of in-hospital mortality.

Identifying patients in need of palliative care: Adaptation of the Necesidades Paliativas CCOMS-ICO© (NECPAL) screening tool for use in Israel

OBJECTIVES

The Necesidades Paliativas CCOMS-ICO© (NECPAL) screening tool was developed to identify patients in need of palliative care and has been used in Israel without formal translation, reliability testing, or validation. Because cultural norms significantly affect subscales such as social vulnerability and health-care delivery, research is needed to comprehensively assess the NECPAL's components, adapt it, and validate it for an Israeli health-care setting. This study linguistically and culturally translated the NECPAL into Hebrew to examine cultural and contextual acceptability for use in the Israeli geriatric health sector. The newly adapted tool was measured for itemized and scale-level content validity, inter-rater reliability (IRR), and construct validity.

METHODS

The NECPAL was back-translated and its content validated by a 5-member expert panel for clarity and relevance, forming the Israeli-NECPAL (I-NECPAL). Six health-care professionals used the I-NECPAL with 25 post-acute geriatric patients to measure IRR. For construct validity, the known-groups method was used, as there is no "gold standard" method for identifying palliative needs for comparison with the NECPAL. The known groups were 2 fictitious cases, predetermined of palliative need. Thirty health-care professionals, blinded to the predetermined palliative status, used the I-NECPAL to determine whether a patient needs a palliative-centered plan of care.

RESULTS

The findings point to acceptable content and construct validity as well as IRR of the I-NECPAL for potential inclusion as a tool for identifying geriatric patients in need of palliative care. Content-validity assessment brought linguistic changes and the exclusion of the frailty parameter from the annex of chronic diseases. The kappa-adjusted scale-level content-validity index indicated a high level of content validity (0.96). IRR indicated a high level of agreement (all parameters with an "excellent-good" agreement level). The sensitivity (0.93), specificity (0.17), positive predictive value (0.53), and negative predictive value (0.71) revealed how heavily the scale weighed upon the surprise question. These metrics are improved when removing the surprise question from the instrument.

SIGNIFICANCE OF RESULTS

Similar to other countries, the Israeli health-care system is regulated by policies that portray the local beliefs and culture as well as evidence-based practice. The decision about when to switch a patient to a palliative-centered plan of care is one such example. It is thus of utmost importance that only locally adapted and vigorously tested screening tools be offered to health-care providers to assist in this decision. The I-NECPAL is the first psychometrically tested palliative needs identification tool for use in the geriatric population in Israel, on both a scale and an itemized level. The results indicate that it can immediately replace the current unvalidated version in use. Further research is needed to determine whether all parts of the scale are relevant for this patient population.

[Palliative Care Needs in Primary Health Care: Characteristics of Patients with Advanced Cancer and Dementia]

INTRODUCTION

The increase in life expectancy brought a higher prevalence of chronic diseases, with an emphasis on those who reached advanced stages and required palliative care. We aimed to characterize patients diagnosed with advanced neoplasms and/or dementia accompanied in primary health care and to test the sensitivity of two tools for identifying patients with palliative needs.

METHODS

We recruited three voluntary family physicians who provided data relative to 623 patients with active codification for neoplasm and/or dementia on the MIM@UF platform. We defined 'patient with palliative needs' as any patient with this codification in advanced stadium and made their clinical and sociodemographic characterization. Assuming the existence of advanced-stage disease as the gold standard, we calculated and compared the sensitivities of each of the tools under study: the surprise question, the question 'do you think this patient has palliative needs?' and an instrument that corresponded to identification by at least one of the questions.

RESULTS

Among the analyzed data, there were 559 (89.7%) active codifications of neoplasm and 64 (10.3%) of dementia; the prevalence of advanced neoplasm and dementia was 1.0% in the studied sample. The subgroup of patients with advanced dementia showed female sex predominance, an older age, and less access to health care. In both subgroups there was a scarcity of data related to education and income, and we observed polypharmacotherapy and multimorbidity. The sensitivity of the surprise question was 33.3% for neoplasia and 69.3% for dementia; of the new tool 50.0% for neoplasia and 92.3% for dementia; and, when used together, 55.6% for neoplasia and 92.3% for dementia.

CONCLUSION

Our results help characterize two subpopulations of patients in need of palliative care and advance with a possible tool for their identification, to be confirmed in a representative sample.

Screening for End-of-Life in Acute Hospitals: A Cross-Sectional Survey

BACKGROUND

Patients are frequently admitted to hospital in the last year of life. Actively recognising patients at this stage gives the opportunity to plan future care.

METHODS

We performed a cross-sectional survey of all acute medical and surgical inpatients at one tertiary hospital. Two simple screening tools, the indicators for a palliative approach and the surprise question identified a group of patients at greatly increased risk of dying over the next year.

RESULTS

The one-year mortality of the study group was 27%, however was 52% and 65% for those identified at risk by the indicators for a palliative approach and surprise question tools. The surprise question had an area under the receiver operator curve value of .84.

CONCLUSION

These screening tools could be used to help clinicians identify hospital inpatients that would benefit from advance care planning and a tailored approach to their care.

The "Surprise Question" for Prognostication in People With Parkinson's Disease and Related Disorders

CONTEXT

Parkinson's disease and related disorders (PDRD) are fatal neurodegenerative disorders characterized by a fluctuating course that can complicate prognostication. The "surprise question" (SQ: "Would you be surprised if your patient died in the next year?") has been used to identify patients with limited prognosis but has not been assessed in PDRD.

OBJECTIVES

To determine the validity of the SQ in predicting 12-month mortality in PDRD.

METHODS

Data was analyzed from 301 patients and 34 community-based neurologists who were participating in a clinical trial of outpatient palliative care for patients with PDRD. Clinicians answered the SQ for each patient at baseline. Descriptive statistics at baseline, chi-square tests of independence, 2 × 2 and 2 × 3 cross tables were used. Survival analysis compared SQ responses using Kaplan-Meier curves. Risk estimate analyses identified patient characteristics associated with clinicians' responses.

RESULTS

Mortality was 10.3% (N = 31) at 1 year. The sensitivity and specificity of the SQ was 80.7% and 58.9%, respectively with AUC = 0.70, positive predictive value of 18.4% and negative predictive value of 96.4%. Older age, atypical parkinsonism, and dementia were associated with responding "no" to the SQ.

CONCLUSION

The SQ is sensitive to 12-month mortality in PDRD, with a high negative predictive value. The SQ may be useful for identifying patients less likely to die within a year and may be useful for identifying patients with palliative care needs outside of end-of-life care. This latter use may assist in mobilizing early and timely referral to specialist palliative care.

Predicting transfer to haemodialysis using the peritoneal dialysis surprise question

BACKGROUND

People on peritoneal dialysis (PD) at risk of transfer to haemodialysis (HD) need support to remain on PD or ensure a safe transition to HD. Simple point-of-care risk stratification tools are needed to direct limited dialysis centre resources. In this study, we evaluated the utility of collecting clinicians' identification of patients at high risk of transfer to HD using a single point of care question.

METHODS

In this prospective observational study, we included 1275 patients undergoing PD in 35 home dialysis programmes. We modified the palliative care 'surprise question' (SQ) by asking the registered nurse and treating nephrologist: 'Would you be surprised if this patient transferred to HD in the next six months?' A 'yes' or 'no' answer indicated low and high risk, respectively. We subsequently followed patient outcomes for 6 months. Cox regression model estimated the hazard ratio (HR) of transfer to HD.

RESULTS

Patients' mean age was 59 ± 16 years, 41% were female and the median PD vintage was 20 months (interquartile range: 9-40). Responses were received from nurses for 1123 patients, indicating 169 (15%) as high risk and 954 (85%) as low risk. Over the next 6 months, transfer to HD occurred in 18 (11%) versus 29 (3%) of the high and low-risk groups, respectively (HR: 3.92, 95% confidence interval (CI): 2.17-7.05). Nephrologist responses were obtained for 692 patients, with 118 (17%) and 574 (83%) identified as high and low risk, respectively. Transfer to HD was observed in 14 (12%) of the high-risk group and 14 (2%) of the low-risk group (HR: 5.56, 95% CI: 2.65-11.67). Patients in the high-risk group experienced higher rates of death and hospitalisation than low-risk patients, with peritonitis events being similar between the two groups.

CONCLUSIONS

The PDSQ is a simple point of care tool that can help identify patients at high risk of transfer to HD and other poor clinical outcomes.

Screening instruments for early identification of unmet palliative care needs: a systematic review and meta-analysis

BACKGROUND

The early detection of individuals who require palliative care is essential for the timely initiation of palliative care services. This systematic review and meta-analysis aimed to (1) Identify the screening instruments used by health professionals to promote early identification of patients who may benefit from palliative care; and (2) Assess the psychometric properties and clinical performance of the instruments.

METHODS

A comprehensive literature search was conducted in PubMed, Embase, CINAHL, Scopus, CNKI and Wanfang from inception to May 2023. We used the COnsensus-based Standards for the Selection of Health Measurement INstruments to assess the methodological quality of the development process for the instruments. The clinical performance of the instruments was assessed by narrative summary or meta-analysis. Subgroup analyses were conducted where necessary. The quality of included studies was assessed using the Newcastle-Ottawa Scale and the Cochrane Collaboration's risk of bias assessment tool.

RESULTS

We included 31 studies that involved seven instruments. Thirteen studies reported the development and validation process of these instruments and 18 studies related to assessment of clinical performance of these instruments. The content validity of the instruments was doubtful or inadequate because of very low to moderate quality evidence. The pooled sensitivity (Se) ranged from 60.0% to 73.8%, with high heterogeneity (I2 of 88.15% to 99.36%). The pooled specificity (Sp) ranges from 70.4% to 90.2%, with high heterogeneity (I2 of 96.81% to 99.94%). The Supportive and Palliative Care Indicators Tool (SPICT) had better performance in hospitals than in general practice settings (Se=79.8% vs 45.3%, p=0.004; Sp=59.1% vs 97.0%, p=0.000).

CONCLUSION

The clinical performance of existing instruments in identifying patients with palliative care needs early ranged from poor to reasonable. The SPICT is used most commonly, has better clinical performance than other instruments but performs better in hospital settings than in general practice settings.

Pathways Project Pragmatic Lessons Learned: Integrating Supportive Care Best Practices into Real-World Kidney Care

Key Points

A multisite quality improvement project using the Institute for Healthcare Improvement learning collaborative structure helped kidney care teams identify seriously ill patients and implement supportive care best practices. Helpful approaches included needs assessment, Quality Assurance and Performance Improvement tools, peer exchange, clinician role modeling, data feedback, and technical assistance. Dialysis center teams tailored implementation of best practices into routine dialysis workflows with nephrologist prerogative to delegate goals of care conversations to nurse practitioners and social workers.

Background

Despite two decades of national and international guidelines urging greater availability of kidney supportive care (KSC), uptake in the United States has been slow. We conducted a multisite quality improvement project with ten US dialysis centers to foster implementation of three KSC best practices. This article shares pragmatic lessons learned by the project organizers.

Methods

The project team engaged in reflection to distill key lessons about what did or did not work in implementing KSC.

Results

The seven key lessons are (1 ) systematically assess KSC needs; (2 ) prioritize both the initial practices to be implemented and the patients who have the most urgent needs; (3 ) use a multifaceted approach to bolster communication skills, including in-person role modeling and mentoring; (4 ) empower nurse practitioners and social workers to conduct advance care planning through teamwork and warm handoffs; (5 ) provide tailored technical assistance to help sites improve documentation and electronic health record processes for storing advance care planning information; (6 ) coach dialysis centers in how to use required Quality Assurance and Performance Improvement processes to improve KSC; and (7 ) implement systematic approaches to support patients who choose active medical management without dialysis.

Conclusions

Treatment of patients with kidney disease is provided in a complex system, especially when considered across the continuum, from CKD to kidney failure on dialysis, and at the end of life. Even among enthusiastic early adopters of KSC, 18 months was insufficient time to implement the three prioritized KSC best practices. Concentrating on a few key practices helped teams focus and see progress in targeted areas. However, effect for patients was attenuated because federal policy and financial incentives are not aligned with KSC best practices and goals.

Clinical Trial registry name and registration number

Pathways Project: KSC, NCT04125537 .

Discrepancy in responses to the surprise question between hemodialysis nurses and physicians, with focus on patient clinical characteristics: A comparative study

INTRODUCTION

The surprise question (SQ) "Would I be surprised if this patient died within the next xx months" can be used by different professions to foresee the need of serious illness conversations in patients approaching end of life. However, little is known about the different perspectives of nurses and physicians in responses to the SQ and factors influencing their appraisals. The aim was to explore nurses' and physicians' responses to the SQ regarding patients on hemodialysis, and to investigate how these answers were associated with patient clinical characteristics.

METHODS

This comparative cross-sectional study included 361 patients for whom 112 nurses and 15 physicians responded to the SQ regarding 6 and 12 months. Patient characteristics, performance status, and comorbidities were obtained. Cohen's kappa was used to analyze the interrater agreement between nurses and physicians in their responses to the SQ and multivariable logistic regression was applied to reveal the independent association to patient clinical characteristics.

FINDINGS

Proportions of nurses and physicians responding to the SQ with "no, not surprised" was similar regarding 6 and 12 months. However, there was a substantial difference concerning which specific patient the nurses and physicians responded "no, not surprised", within 6 (κ = 0.366, p < 0.001, 95% CI = 0.288-0.474) and 12 months (κ = 0.379, p < 0.001, 95% CI = 0.281-0.477). There were also differences in the patient clinical characteristics associated with nurses' and physicians' responses to the SQ.

DISCUSSION

Nurses and physicians have different perspectives in their appraisal when responding to the SQ for patients on hemodialysis. This may reinforce the need for communication and discussion between nurses and physicians to identify the need of serious illness conversations in patients approaching the end of life, in order to adapt hemodialysis care to patient preferences and needs.

Clinician Trust in Artificial Intelligence: What is Known and How Trust Can Be Facilitated

Predictive analytics based on artificial intelligence (AI) offer clinicians the opportunity to leverage big data available in electronic health records (EHR) to improve clinical decision-making, and thus patient outcomes. Despite this, many barriers exist to facilitating trust between clinicians and AI-based tools, limiting its current impact. Potential solutions are available at both the local and national level. It will take a broad and diverse coalition of stakeholders, from health-care systems, EHR vendors, and clinical educators to regulators, researchers and the patient community, to help facilitate this trust so that the promise of AI in health care can be realized.

Should the Surprise Question be Used as a Prognostic Tool for People With Life-limiting Illnesses?

The surprise question screening tool ("Would I be surprised if this person died within the next 12 months?") was initially developed to identify possible palliative care needs. One controversial topic regarding the surprise question is whether it should be used as a prognostic tool (predicting survival) for patients with life-limiting illnesses. In this "Controversies in Palliative Care" article, three groups of expert clinicians independently answered this question. All experts provide an overview of current literature, practical advice, and opportunities for future research. All experts reported on the inconsistency of the prognostic capabilities of the surprise question. Two of the three expert groups felt that the surprise question should not be used as a prognostic tool due to these inconsistencies. The third expert group felt that the surprise question should be used as a prognostic tool, particularly for shorter time frames. The experts all highlighted that the original rationale for the surprise question was to trigger a further conversation about future treatment and a potential shift in the focus of the care, identifying patients who many benefit from specialist palliative care or advance care planning; however, many clinicians find this discussion a difficult one to initiate. The experts agreed that the benefit of the surprise question comes from its simplicity: a one-question tool that requires no specific information about the patient's condition. More research is needed to better support the application of this tool in routine practice, particularly in noncancer populations.

Towards optimal use of antithrombotic therapy of people with cancer at the end of life: A research protocol for the development and implementation of the SERENITY shared decision support tool

BACKGROUND

Even though antithrombotic therapy has probably little or even negative effects on the well-being of people with cancer during their last year of life, deprescribing antithrombotic therapy at the end of life is rare in practice. It is often continued until death, possibly resulting in excess bleeding, an increased disease burden and higher healthcare costs.

METHODS

The SERENITY consortium comprises researchers and clinicians from eight European countries with specialties in different clinical fields, epidemiology and psychology. SERENITY will use a comprehensive approach combining a realist review, flash mob research, epidemiological studies, and qualitative interviews. The results of these studies will be used in a Delphi process to reach a consensus on the optimal design of the shared decision support tool. Next, the shared decision support tool will be tested in a randomised controlled trial. A targeted implementation and dissemination plan will be developed to enable the use of the SERENITY tool across Europe, as well as its incorporation in clinical guidelines and policies. The entire project is funded by Horizon Europe.

RESULTS

SERENITY will develop an information-driven shared decision support tool that will facilitate treatment decisions regarding the appropriate use of antithrombotic therapy in people with cancer at the end of life.

CONCLUSIONS

We aim to develop an intervention that guides the appropriate use of antithrombotic therapy, prevents bleeding complications, and saves healthcare costs. Hopefully, usage of the tool leads to enhanced empowerment and improved quality of life and treatment satisfaction of people with advanced cancer and their care givers.

Digital health and inpatient palliative care: a cohort-controlled study

OBJECTIVES

End of life has unacceptable levels of hospital admission and death. We aimed to determine the association of a novel digital specific system (Proactive Risk-Based and Data-Driven Assessment of Patients at the End of Life, PRADA) to modify such events.

METHODS

A cohort-controlled study of those discharged alive, who died within 90 days of discharge, comparing PRADA (n=114) with standard care (n=3730).

RESULTS

At 90 days, the PRADA group were more likely to die (78.9% vs 46.2%, p<0.001), had a shorter time to death (58±90 vs 178±186 days, p<0.001) but readmission (20.2% vs 37.9%, p<0.001) or death in hospital (4.4% vs 28.9%, p<0.001) was lower with reduced risk for a combined 90-day outcome of postdischarge non-elective admission or hospital death (OR 0.45, 95% CI 0.27-0.74, p<0.001). Tightening criteria with 1:1 matching (n=83 vs 83) showed persistent significant findings in PRADA contact with markedly reduced adverse events (OR 0.15, 95% CI 0.02-0.96, p<0.05).

CONCLUSIONS

Being seen in hospital by a specialist palliative care team using the PRADA tool was associated with significantly improved postdischarge outcomes pertaining to those destined to die after discharge.

A comparison of palliative care and rapid emergency screening (P-CaRES) tool, broad and narrow criteria, and surprise questions to predict survival of older emergency department patients

BACKGROUND

Palliative care is a form of medical care designed to enhance the quality of life of patients with life-threatening conditions. This study was conducted to compare the accuracy of predicted survival the 1 and 3-month survival rate of Broad and narrow criteria, Surprise questions (SQ), and Palliative Care and Rapid Emergency Screening (P-CaRES) after admission to the emergency department (ED).

METHODS

This prospective cohort study was conducted at an urban teaching hospital in Thailand. Patients aged ≥ 65 years admitted to the ED were classified according to their emergency severity index (ESI) (Level: 1-3). We collected data on SQ, P-CaRES, and broad and narrow criteria. A survival data of participants were collected at 1 and 3 months after admission to the ED. The survival rate was calculated using the Kaplan-Meier and log-rank tests.

RESULTS

A total of 269 patients completed the study. P-CaRES positive and P-CaRES negative patients had 1-month survival rates of 81% and 94.8%, respectively (P = 0.37), and at 3-month survival rates of 70.7% and 90.1%, respectively (P < 0.001). SQ (not surprised) had a 1-month survival rate of 79.3%, while SQ (surprised) had a 97% survival rate (P = 0.01), and SQ (not surprised) had a 75.4% survival rate at 3-months, while SQ (surprised) had a 96.3% survival rate (P = 0.01). Broad and narrow criteria that were positive and negative had 1-month survival rates of 88.1% and 92.5%, respectively (P = 0.71), while those that were positive and negative had 3-month survival rates of 78.6% and 87.2%, respectively (P = 0.19). The hazard ratio (HR) of SQ (not surprised) at 1 month was 3.22( 95%CI:1.16-8.89). The HR at 3 months of P-CaRES (positive) was 3.31 with a 95% confidence interval (CI): 1.74 - 6.27, while the HR for SQ (not surprise) was 7.33, 95% CI: 3.03-19.79; however, broad and narrow criteria had an HR of 1.78, 95% CI:0.84-3.77.

CONCLUSIONS

Among older adults who visited the ED, the SQ were good prognosis tools for predicting 1 and 3-month survival, and P-CaRES were good prognostic tools for predicting 3-month survival.

Thinking ahead about medical treatments in advanced illness: a qualitative study of barriers and enablers in end-of-life care planning with patients and families from ethnically diverse backgrounds

Background

This study explored whether or not, and how, terminally ill patients from ethnically diverse backgrounds and their family caregivers think ahead about deterioration and dying, and explored their engagement with health-care professionals in end-of-life care planning.

Objective

The aim was to address the question, what are the barriers to and enablers of ethnically diverse patients, family caregivers and health-care professionals engaging in end-of-life care planning?

Design

This was a qualitative study comprising 18 longitudinal patient-centred case studies, interviews with 19 bereaved family caregivers and 50 public and professional stakeholder responses to the findings.

Setting

The study was set in Nottinghamshire and Leicestershire in the UK.

Results

Key barriers - the predominant stance of patients was to live with hope, considering the future only in terms of practical matters (wills and funerals), rather than the business of dying. For some, planning ahead was counter to their faith. Health-care professionals seemed to feature little in people's lives. Some participants indicated a lack of trust and experienced a disjointed system, devoid of due regard for them. However, religious and cultural mores were of great importance to many, and there were anxieties about how the system valued and enabled these. Family duty and community expectations were foregrounded in some accounts and concern about being in the (un)care of strangers was common. Key enablers - effective communication with trusted individuals, which enables patients to feel known and that their faith, family and community life are valued. Health-care professionals getting to 'know' the person is key. Stakeholder responses highlighted the need for development of Health-care professionals' confidence, skills and training, Using stories based on the study findings was seen as an effective way to support this. A number of behavioural change techniques were also identified.

Limitations

It was attempted to include a broad ethnic diversity in the sample, but the authors acknowledge that not all groups could be included.

Conclusions

What constitutes good end-of-life care is influenced by the intersectionality of diverse factors, including beliefs and culture. All people desire personalised, compassionate and holistic end-of-life care, and the current frameworks for good palliative care support this. However, health-care professionals need additional skills to navigate complex, sensitive communication and enquire about aspects of people's lives that may be unfamiliar. The challenge for health-care professionals and services is the delivery of holistic care and the range of skills that are required to do this.

Future work

Priorities for future research: How can health professionals identify if/when a patient is 'ready' for discussions about deterioration and dying? How can discussions about uncertain recovery and the need for decisions about treatment, especially resuscitation, be most effectively conducted in a crisis? How can professionals recognise and respond to the diversity of faith and cultural practices, and the heterogeneity between individuals of beliefs and preferences relating to the end of life? How can conversations be most effectively conducted when translation is required to enhance patient understanding?

Funding

This project was funded by the National Institute for Health and Care Research (NIHR) Health and Social Care Delivery Research programme and will be published in full in Health and Social Care Delivery Research; Vol. 11, No. X. See the NIHR Journals Library website for further project information.

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".

A framework to identify ethical concerns with ML-guided care workflows: a case study of mortality prediction to guide advance care planning

OBJECTIVE

Identifying ethical concerns with ML applications to healthcare (ML-HCA) before problems arise is now a stated goal of ML design oversight groups and regulatory agencies. Lack of accepted standard methodology for ethical analysis, however, presents challenges. In this case study, we evaluate use of a stakeholder "values-collision" approach to identify consequential ethical challenges associated with an ML-HCA for advanced care planning (ACP). Identification of ethical challenges could guide revision and improvement of the ML-HCA.

MATERIALS AND METHODS

We conducted semistructured interviews of the designers, clinician-users, affiliated administrators, and patients, and inductive qualitative analysis of transcribed interviews using modified grounded theory.

RESULTS

Seventeen stakeholders were interviewed. Five "values-collisions"-where stakeholders disagreed about decisions with ethical implications-were identified: (1) end-of-life workflow and how model output is introduced; (2) which stakeholders receive predictions; (3) benefit-harm trade-offs; (4) whether the ML design team has a fiduciary relationship to patients and clinicians; and, (5) how and if to protect early deployment research from external pressures, like news scrutiny, before research is completed.

DISCUSSION

From these findings, the ML design team prioritized: (1) alternative workflow implementation strategies; (2) clarification that prediction was only evaluated for ACP need, not other mortality-related ends; and (3) shielding research from scrutiny until endpoint driven studies were completed.

CONCLUSION

In this case study, our ethical analysis of this ML-HCA for ACP was able to identify multiple sites of intrastakeholder disagreement that mark areas of ethical and value tension. These findings provided a useful initial ethical screening.

Advanced Care Planning for Hospitalized Patients Following Clinician Notification of Patient Mortality by a Machine Learning Algorithm

Importance

Goal-concordant care is an ongoing challenge in hospital settings. Identification of high mortality risk within 30 days may call attention to the need to have serious illness conversations, including the documentation of patient goals of care.

Objective

To examine goals of care discussions (GOCDs) in a community hospital setting with patients identified as having a high risk of mortality by a machine learning mortality prediction algorithm.

Design, Setting, and Participants

This cohort study took place at community hospitals within 1 health care system. Participants included adult patients with a high risk of 30-day mortality who were admitted to 1 of 4 hospitals between January 2 and July 15, 2021. Patient encounters of inpatients in the intervention hospital where physicians were notified of the computed high risk mortality score were compared with patient encounters of inpatients in 3 community hospitals without the intervention (ie, matched control).

Intervention

Physicians of patients with a high risk of mortality within 30 days received notification and were encouraged to arrange for GOCDs.

Main Outcomes and Measures

The primary outcome was the percentage change of documented GOCDs prior to discharge. Propensity-score matching was completed on a preintervention and postintervention period using age, sex, race, COVID-19 status, and machine learning-predicted mortality risk scores. A difference-in-difference analysis validated the results.

Results

Overall, 537 patients were included in this study with 201 in the preintervention period (94 in the intervention group; 104 in the control group) and 336 patients in the postintervention period. The intervention and control groups included 168 patients per group and were well-balanced in age (mean [SD], 79.3 [9.60] vs 79.6 [9.21] years; standardized mean difference [SMD], 0.03), sex (female, 85 [51%] vs 85 [51%]; SMD, 0), race (White patients, 145 [86%] vs 144 [86%]; SMD 0.006), and Charlson comorbidities (median [range], 8.00 [2.00-15.0] vs 9.00 [2.00 to 19.0]; SMD, 0.34). Patients in the intervention group from preintervention to postintervention period were associated with being 5 times more likely to have documented GOCDs (OR, 5.11 [95% CI, 1.93 to 13.42]; P = .001) by discharge compared with matched controls, and GOCD occurred significantly earlier in the hospitalization in the intervention patients as compared with matched controls (median, 4 [95% CI, 3 to 6] days vs 16 [95% CI, 15 to not applicable] days; P < .001). Similar findings were observed for Black patient and White patient subgroups.

Conclusions and Relevance

In this cohort study, patients whose physicians had knowledge of high-risk predictions from machine learning mortality algorithms were associated with being 5 times more likely to have documented GOCDs than matched controls. Additional external validation is needed to determine if similar interventions would be helpful at other institutions.

Prediction Accuracy Between Terminally Ill Patients' Survival Length and the Estimations Made From Different Medical Staff, a Prospective Cohort Study

Background: Previous reports suggested the clinical predictions of survival (CPS) and prognostic scores had similar accuracy in patients with days to weeks of life. Objective: We aimed to evaluate and compare the accuracy of CPS by attending physicians, residents, and nurses in an acute palliative care unit at a medical center. Methods: This was a 1-year prospective cohort study. Survival prediction was made within 3 days after patients' admission and re-evaluated every week until patients' discharge or death. Associated factors of accurate survival predictions were also explored by multivariate logistic regression. Results: A total of 179 inpatients were recruited and 115 of them were included in this analysis. The mean age of participants was 72.9 years and the average length of actual survival was 11.5 ± 12.0 days. For patients with survival within 30 days, the medical staff tended to overestimate their life span. The predictions made by physicians and nurses showed much closer to actual survival length through repeated estimations. Patients with metastatic cancer (odds ratio: OR 2.77, 95% CI 1.23-6.22) or cognitive impairment (OR 2.39, 95% CI 1.12-5.11) had higher associations with accurate CPS. Poor performance status of ECOG (OR 1.82, 95% CI 1.09-3.02) and dysphagia (OR 2.01, 95% CI 1.07-3.77) were significant predictors for accurate CPS in patients with the survival of less than 2 weeks. Conclusions: The accuracy of CPS between different medical staff did not reveal significant differences in the study. The importance of re-evaluation for patients' survival length in clinical practice is worthy of attention.

Prognostic evaluation in patients with advanced cancer in the last months of life: ESMO Clinical Practice Guideline

•This ESMO Clinical Practice Guideline provides key recommendations for using prognostic estimates in advanced cancer. •The guideline covers recommendations for patients with cancer and an expected survival of months or less. •An algorithm for use of clinical predictions, prognostic factors and multivariable risk prediction models is presented. •The author group encompasses a multidisciplinary group of experts from different institutions in Europe, USA and Asia. •Recommendations are based on available scientific data and the authors’ collective expert opinion.

Increasing the chance of dying at home: roles, tasks and approaches of general practitioners enabling palliative care: a systematic review of qualitative literature

BACKGROUND

Many elderly people wish to die at home but end up dying at the hospital. If the patient wishes to die at home, palliative care provided by General Practitioners (GPs) may increase the chance of dying at home, however, there is a lack of knowledge on how GPs should provide palliative care. We aimed to identify roles, tasks and approaches of GPs enabling palliative care, by exploring the experiences of GPs, other healthcare professionals, patients, and relatives through a systematic review of the qualitative literature.

METHODS

We searched PubMed, EMBASE, PsycINFO, Web of Science, and CINAHL in March 2022. Thematic analysis was used for synthesizing the results.

RESULTS

Four thousand five hundred sixty three unique records were retrieved, and 12 studies were included for review. Of these, ten were interview or focus group studies and two were survey studies with additional open-ended questions. Only qualitative findings from the studies were used in synthesizing the results. Thematic analysis produced four main themes describing the roles, tasks and approaches of GPs enabling palliative care to increase the chance for patients to die at home. GPs can support patients in the final phases of life by applying a holistic, patient-centred, and proactive approach to palliative care and by having sufficient education and training. Furthermore, the palliative care consultation should include symptom management, handling psychosocial and spiritual needs, maintaining a fragile balance, and proper communication with the patient. Lastly, GPs must address several palliative care elements surrounding the consultation including initiating the palliative care, being available, being the team coordinator/collaborator, providing continuous care and having sufficient knowledge about the patient.

CONCLUSIONS

The roles, tasks and approaches of the GPs enabling palliative care include being aware of elements in the palliative care consultation and elements surrounding the consultation and by having sufficient education and training and a broad, proactive, and patient-centred approach.

Age is just a number: the concept of time to benefit in older adults

A female nursing home resident aged >70 years was admitted to the geriatric ward with de novo dysphagia 6 days after being discharged from the stroke unit. Metformin and ezetimibe had been added to her treatment regimen which already consisted of clopidogrel, atorvastatin, denosumab, calcium and vitamin D. At the geriatric ward a multidisciplinary team involving clinical pharmacists reviewed all treatments and appraised the time to benefit, ascertaining whether there was sufficient time left to experience therapeutic benefits. As a result, metformin, ezetimibe, denosumab, calcium and vitamin D were discontinued. This case report illustrates that both mortality risk assessment and evaluation of the time to benefit should be part of any medication review in frail older adults. Conversely, with limited available data pertaining to the concept of time to benefit, we advocate a broader awareness among pharmacists and a systematic assessment in future clinical trials.

Development and validation of a nursing home mortality index to identify nursing home residents nearing the end of life in dental clinics

BACKGROUND

Nursing home (NH) residents seek care at dental offices, yet many of them are at the end of life. The uncertain life expectancy further complicates the care of NH residents. This study aimed to develop and validate a Nursing Home Mortality Index (NHMI) to identify NH residents in the last year of life.

METHODS

Logistic modeling was used to develop predictive models for death within 1 year after initial appointment by utilizing the new patient examination data and mortality data of 903 Minnesota NH residents. The final model was selected based on areas under the curve (AUC) and then validated using data from 586 Iowa NH residents. Based on the final model, the NHMI was developed with the estimated 1-year mortality for the low, medium and high risk group.

RESULTS

One-year mortalities were 21% and 26% in the development and validation cohorts, respectively. Predictors included age, gender, communication capacity, physical mobility, congestive heart failure, peripheral vascular disease, cancer, cerebrovascular disease, chronic renal disease and liver disease. AUCs for the development and validation models were 0.73 and 0.68, respectively. For the validation cohort, the sensitivity and specificity were 0.79 and 0.53, respectively. The estimated 1-year mortality risks for three risk groups were 0%-10%, 11%-19%, and ≥20%, respectively CONCLUSION: The high mortality rate of NH residents following a dental exam highlighted a need to incorporate patients' prognoses in treatment planning along with normative needs and patients' preferences. The NHMI provides a practical way to guide treatment decisions for end-of-life NH residents.

Live Well, Die Well: The Development of an Online, Arts-Based Palliative Care Programme in the Shadow of the COVID-19 Pandemic

The Covid-19 crisis led to an increase in the 'total pain' of many terminally ill patients who faced a reduction in support, due to the temporary closure of front-line palliative day therapy services. A hospice volunteer, I instigated an online day therapy programme for patients previously attending face-to-face day therapy. Participant feedback revealed the importance of providing a space for ongoing peer support for participants' changing sense of identity, an issue for time-limited day therapy programmes. An exploration of key concepts associated with palliative care established the multiple connections between such changing identity and arts-based approaches to living well. This article charts how I used this understanding to develop an alternative, online arts-based support programme, Live well, die well. It explores the links between ongoing mutual support, arts-based activity and the reactions to a shifting identity in patients with a life-limiting illness.

Family caregivers' experience of communication with nursing home staff from admission to end of life during the COVID-19 pandemic: A qualitative study employing a transitional perspective

OBJECTIVES

Family caregivers' (FCs) caregiving in nursing home (NH) moves across 3 main phases: transitioning relatives to long-term care, worsening of a relative's conditions, and end of life; each phase brings specific challenges that FCs must confront. Moreover, during the COVID-19 pandemic, strict mandatory visitor restrictions affected communication modalities. This study explored FCs' experience of communication with NH staff during the COVID-19 pandemic from admission to end of life.

METHODS

A descriptive qualitative study with inductive content analysis was performed in 7 Italian NHs from May to June 2021. NH managers purposively identified 25 FCs at different phases of their caregiving trajectory: transitional (i.e., admission in the previous 8 weeks, n = 8), deterioration-in-condition (i.e., acknowledged changes in care needs of their relative after trigger events, n = 10), and end-of-life phase (i.e., death expected in the next weeks or a few months, n = 7), who were interviewed.

RESULTS

Regardless the phase of caregiving trajectory, what mattered most to FCs was the opportunity to have regular and sensitive discussions with health-care professionals. The need of in-person communication increased nearing death. The COVID-19 pandemic enhanced FCs' need to interact with health-care professionals they trusted. Knowledge of residents' preferences mitigated FCs' turbulent emotions throughout the overall caregiving trajectory.

SIGNIFICANCE OF RESULTS

Findings suggest that in-person contacts should be prioritized and facilitated when possible, particularly at the end of life; nonetheless, meaningful communication can occur also through remote modalities. Investments in training health-care professionals about effective long-distance communication and supportive skills can help trusting relationships to be established. Open discussions about residents' care preferences should be encouraged.

Triggering palliative care referrals through the identification of poor prognosis in older patients presented to emergency departments in rural Australia

Background: Without objective screening for risk of death, the palliative care needs of older patients near the end of life may be unrecognised and unmet. Aim: This study aimed to estimate the usefulness of the Criteria for Screening and Triaging to Appropriate aLternative care (CriSTAL) tool in determining older patients' risk of death within 3-months after initial hospital admission. Methods: A prospective cohort study of 235 patients aged 70+ years, who presented to two rural emergency departments in two adjacent Australian states, was utilised. The 'risk of death' of each patient was screened with the CriSTAL prognostic tool. Their 3-month follow-up outcomes were assessed through telephone interviews and a clinical record review. Findings: A CriSTAL cut-off score of more than 7 yielded a sensitivity of 80.7% and specificity of 70.81% for a 3-month risk of death. Palliative care services were only used by 31% of the deceased in their last trimester of life. Conclusion: Prognostic tools provide a viable means of identifying individuals with a poor prognosis. Identification can trigger an earlier referral to palliative care, which will benefit the patient's wellbeing and quality of life.

Validation of the Surprise Question and the Development of a Multivariable Model

CONTEXT

The Surprise Question (SQ) (would you be surprised if this patient died within a year?) is a prognostic variable explored in chronic illnesses. Validation is limited to sensitivity, specificity, and predictive values.

OBJECTIVES

Our objective is to validate the SQ in cancer patients and develop a predictive model with additional variables.

METHODS

A prospective cohort study of adult (age>18) cancer patients seen between October 1, 2019, through March 31, 2021, undergoing systemic therapies had the SQ completed by oncologists prior to each change in systemic therapy. The primary outcome was survival for one year. Secondary outcomes were predictions of survival at three, six, and nine months. Patients were grouped into negative SQ (not surprised) and positive SQ (surprised). Sensitivity, specificity, predictive values, and likelihood ratios (LR) were calculated for the SQ. Additional prognostic variables were age, gender, cancer stage, line of therapy, Charleson Comorbid Index (CCI), palliative care consultation (prior to, after the SQ, or not at all), and healthcare utilization (outpatient, inpatient, and emergency department (ED). Logistic regression and receiver operating characteristics (ROC) were used for discrimination and modeling. Akaike information criterion (AIC) was used to compare the model fit as each predictor.

RESULTS

1366 patients had 1 SQ; 784 died within a year. The SQ predicted survival at one year (P = 0.008), with a positive LR of 1.459 (95%CI 1.316-1.602) and a c-statistic of 0.565 (95%CI 0.530-0.600). Additional variables increased the c-statistic to 0.648 (95% CI 0.608-0.686). The total model best predicted survival at three months, c-statistic of 0.663 (95% CI 0.616-0.706). However, the total model c-statistic remained <0.70.

CONCLUSIONS

The SQ, as a single factor, poorly predicts survival and should not be used to alter therapies. Adding additional objective variables improved prognostication, but further refinement and external validation are needed.

Palliative Care in Cholangiocarcinoma

This chapter details all aspects of the general principles of palliative care for advanced stage cholangiocarcinoma patients. These include symptoms management, communication guide, advance care planning, and management for bereavement. Surgical and intervention techniques of palliative biliary drainage are described in detail for patients with obstructive jaundice with advanced stage CCA. Additionally, details are provided regarding the establishment of a multidisciplinary palliative care team which is critical to provide the most appropriate multimodal treatment for good quality of life and survival of patients.

The Impact of Health and Social Care Professionals' Education on the Quality of Serious Illness Conversations in Nursing Homes: Study Protocol of a Quality Improvement Project

Health and social care professionals (HCPs) who work in nursing homes (NHs) are increasingly required to sustain serious illness conversations about care goals and preferences. Although these conversations may also be challenging for experienced HCPs and the literature recognizes high-quality communication as key to providing patient-centered care, so far, no specific educational program has been developed for the NH setting to improve HCPs' communication skills. Our study aims to test the feasibility and potential effectiveness of an innovative, blended communication skills training program (Teach-to-Communicate) targeting the HCPs who work in NHs. This program includes classroom-based theory, experiential learning, and e-learning, and relies on interdisciplinary contexts and several didactic methods. The study consists of two phases: phase I is the development of written resources that employ focus group discussion involving field experts and external feedback from key stakeholders. Phase II consists of a multicenter, pilot, pre-post study with nested qualitative study. The Teach-to-Communicate training program is expected to enhance the quality of communication in NH and HCPs' confidence in sustaining serious illness conversations, reduce family carers' psycho-emotional burden and improve their satisfaction with the care received, and increase advance care planning documentation. Our protocol will provide insight for future researchers, healthcare providers, and policymakers and pave the way for blended educational approaches in the field of communication skills training.

External Validation and User Experiences of the ProPal-COPD Tool to Identify the Palliative Phase in COPD

Background

Difficulty predicting prognosis is a major barrier to timely palliative care provision for patients with COPD. The ProPal-COPD tool, combining six clinical indicators and the Surprise Question (SQ), aims to predict 1-year mortality as a proxy for palliative care needs. It appeared to be a promising tool for healthcare providers to identify patients with COPD who could benefit from palliative care.

Objective

To externally validate the ProPal-COPD tool and to assess user experiences.

Methods

Patients admitted with an acute exacerbation COPD were recruited across 10 hospitals. Demographics, clinical characteristics and survival status were collected. Sensitivity, specificity, positive and negative predictive values of the tool using two cut-off values were calculated. Also, predictive properties of the SQ were calculated. In monitoring meetings and interviews, healthcare providers shared their experiences with the tool. Transcripts were deductively coded using six user experience domains: Acceptability, Satisfaction, Credibility, Usability, User-reported adherence and Perceived impact.

Results

A total of 523 patients with COPD were included between May 2019 and August 2020, of whom 100 (19.1%) died within 12 months. The ProPal-COPD tool had an AUC of 0.68 and a low sensitivity (55%) and moderate specificity (74%) for predicting 1-year all-cause mortality. Using a lower cut-off value, sensitivity was higher (74%), but specificity lower (46%). Sensitivity and specificity of the SQ were 56% and 73%, respectively (AUC 0.65). However, healthcare providers generally appreciated using the tool because it increased awareness of the palliative phase and provided a shared understanding of prognosis, although they considered its outcome not always correct.

Conclusion

The accuracy of the ProPal-COPD tool to predict 1-year mortality is limited, although screening patients with its indicators increases healthcare providers' awareness of palliative care needs and encourages them to timely initiate appropriate care.

The Surprise Question as a Trigger for Primary Palliative Care Interventions for Children with Advanced Heart Disease

There is significant uncertainty in describing prognosis and a lack of reliable entry criteria for palliative care studies in children with advanced heart disease (AHD). This study evaluates the utility of the surprise question-"Would you be surprised if this child died within the next year?"-to predict one-year mortality in children with AHD and assess its utility as entry criteria for future trials. This is a prospective cohort study of physicians and nurses caring for children (1 month-19 years) with AHD hospitalized ≥ 7 days. AHD was defined as single ventricle physiology, pulmonary vein stenosis or pulmonary hypertension, or any cardiac diagnosis with signs of advanced disease. Primary physicians were asked the surprise question and medical record review was performed. Forty-nine physicians responded to the surprise question for 152 patients. Physicians responded "No, I would not be surprised if this patient died" for 54 (36%) patients, 20 (37%) of whom died within 1 year, predicting one-year mortality with 77% sensitivity, 73% specificity, 37% positive predictive value, and 94% negative predictive value. Patients who received a "No" response had an increased 1-year risk of death (hazard ratio 7.25, p < 0.001). Physician years of experience, subspecialty, and self-rated competency were not associated with the accuracy of the surprise question. The surprise question offers promise as a bedside screening tool to identify children with AHD at high risk for mortality and help physicians identify patients who may benefit from palliative care and advance care planning discussions.

Towards cataloguing and characterising advance care planning and end-of-life care resources

BACKGROUND

Resources for healthcare professionals, patients and those important to them relating to planning and coordinating treatment and care at the end of life are abundant, and can be difficult to navigate. However, they have not been systematically collated or catalogued in terms of their purpose, scope or intended audience.

AIM

To collate, categorise and characterise advance care planning and end-of-life treatment and care (EoLT + C) resources directed towards healthcare professionals, patients and their families.

METHODS

Rapid review and thematic synthesis of resources available in the United Kingdom. Google searches and reviews of websites belonging to selected organisations that develop and publish materials relating to EoLT + C, and advance care planning were used. Materials were included if they were intended for those over 18 living in the UK and pertained to five domains of EoLT + C: identifying those approaching end of life; accessing EoLT + C services; conducting important conversations about EoLT + C and preferences; advance care planning, including recording of preferences and plans; and ensuring that plans and preferences are accessed and used by health and social care services.

RESULTS

246 resources directed at healthcare professionals, patients and their families were identified, collated, catalogued and made internationally available for clinicians, researchers, patients and the public. 61 were classified as interactive, providing decision support in EoLT + C that went beyond simply providing information. Of these, there was notable content overlap among tools for identifying patients in their last year of life. There was variation in the development of tools across all domains of end-of-life care by geography and patient group. Few interactive resources integrated seamlessly with a digital interface or healthcare provider workflows. Incentives for the adoption of best-practice appeared rare.

CONCLUSIONS

We present a repeatable and scalable approach to the cataloguing and characterisation of palliative care resources. The identified resources will be of benefit not only to those in the UK but to those in other countries, developing or evaluating their own resources for aiding professionals and patients to plan and deliver excellent treatment and care at the end of life.

Development of a Clinical Prediction Model for 1-Year Mortality in Patients With Advanced Cancer

IMPORTANCE

To optimize palliative care in patients with cancer who are in their last year of life, timely and accurate prognostication is needed. However, available instruments for prognostication, such as the surprise question ("Would I be surprised if this patient died in the next year?") and various prediction models using clinical variables, are not well validated or lack discriminative ability.

OBJECTIVE

To develop and validate a prediction model to calculate the 1-year risk of death among patients with advanced cancer.

DESIGN, SETTING, AND PARTICIPANTS

This multicenter prospective prognostic study was performed in the general oncology inpatient and outpatient clinics of 6 hospitals in the Netherlands. A total of 867 patients were enrolled between June 2 and November 22, 2017, and followed up for 1 year. The primary analyses were performed from October 9 to 25, 2019, with the most recent analyses performed from June 19 to 22, 2022. Cox proportional hazards regression analysis was used to develop a prediction model including 3 categories of candidate predictors: clinician responses to the surprise question, patient clinical characteristics, and patient laboratory values. Data on race and ethnicity were not collected because most patients were expected to be of White race and Dutch ethnicity, and race and ethnicity were not considered as prognostic factors. The models' discriminative ability was assessed using internal-external validation by study hospital and measured using the C statistic. Patients 18 years and older with locally advanced or metastatic cancer were eligible. Patients with hematologic cancer were excluded.

MAIN OUTCOMES AND MEASURES

The risk of death by 1 year.

RESULTS

Among 867 patients, the median age was 66 years (IQR, 56-72 years), and 411 individuals (47.4%) were male. The 1-year mortality rate was 41.6% (361 patients). Three prediction models with increasing complexity were developed: (1) a simple model including the surprise question, (2) a clinical model including the surprise question and clinical characteristics (age, cancer type prognosis, visceral metastases, brain metastases, Eastern Cooperative Oncology Group performance status, weight loss, pain, and dyspnea), and (3) an extended model including the surprise question, clinical characteristics, and laboratory values (hemoglobin, C-reactive protein, and serum albumin). The pooled C statistic was 0.69 (95% CI, 0.67-0.71) for the simple model, 0.76 (95% CI, 0.73-0.78) for the clinical model, and 0.78 (95% CI, 0.76-0.80) for the extended model. A nomogram and web-based calculator were developed to support clinicians in adequately caring for patients with advanced cancer.

CONCLUSIONS AND RELEVANCE

In this study, a prediction model including the surprise question, clinical characteristics, and laboratory values had better discriminative ability in predicting death among patients with advanced cancer than models including the surprise question, clinical characteristics, or laboratory values alone. The nomogram and web-based calculator developed for this study can be used by clinicians to identify patients who may benefit from palliative care and advance care planning. Further exploration of the feasibility and external validity of the model is needed.

A Consensus Definition of End of Life from an International and Interdisciplinary Perspective: A Delphi Panel Study

Background: Those working in the field of palliative care have recognized that many terms are being used synonymously and that clear definitions (or any definitions) for many of these terms are lacking. The synonymous use of the terms palliative and end of life (EOL) can especially lead to conflicts in clinical practice, such as a tardy referral to palliative care. Such conflicts may then result in poorer treatment of patients, for instance, pain management. In research, the lack of clear definitions or even of any established definition for central concepts, such as EOL, weakens study validity and research outcomes. Objective: The aim of this study was to establish a concise definition for the EOL phase. Design: A modified Delphi study design was chosen. A structured questionnaire based on a previously conducted concept analysis about the EOL was used. Setting: A panel of international and interdisciplinary experts was established. Between 34 (1st round) and 21 (4th round) individuals participated in the anonymous online expert panel. Results: After four panel rounds, we were able to provide a definition which covers physical and psychosocial aspects that should be considered at the beginning of the EOL phase and possible predictions about the remaining time. The definition also covers aspects of EOL care, such as considerations related to the individual's dignity, spirituality, and maintenance of relationships. Conclusion: EOL is a term which is defined by considering multiple aspects that affect the process of identifying the EOL phase, the EOL phase itself and the resulting care options.

The prognostic value of the 12-, 6-, 3- and 1-month 'Surprise Question' in cancer patients: A prospective cohort study in three hospitals

OBJECTIVE

This prospective study aimed to evaluate the performance of the 'Surprise Question' (SQ) 'Would I be surprised if this patient died in the next 12 months?' in predicting survival of 12, 6, 3 and 1 month(s), respectively, in hospitalised patients with cancer.

METHODS

In three hospitals, physicians were asked to answer SQs for 12/6/3/1 month(s) for inpatients with cancer. Sensitivity, specificity, positive and negative predictive values were calculated.

RESULTS

A total of 783 patients were included, of whom 51% died in the 12-month period after inclusion. Sensitivity of the SQ predicting death within 12 months was 0.79, specificity was 0.66, the positive predictive value was 0.71 and the negative predictive value was 0.75. When the SQ concerned a shorter survival period, sensitivities and positive predictive values decreased, whereas specificities and negative predictive values increased. In multivariable logistic regression analysis, the SQ was significantly associated with mortality (OR 3.93, 95% CI 2.70-5.71, p < 0.01).

CONCLUSIONS

The 12-month SQ predicts death in patients with cancer admitted to the hospital reasonably well. Shortening the timeframe decreases sensitivities and increases specificities. The four surprise questions may help to identify patients for whom palliative care is indicated.

[DNVF Memorandum: Health Services Research in the Last Year of Life]

This memorandum outlines current issues concerning health services research on seriously ill and dying people in the last year of their lives as well as support available for their relatives. Patients in the last phase of life can belong to different disease groups, they may have special characteristics (e. g., people with cognitive and complex impairments, economic disadvantage or migration background) and be in certain phases of life (e. g., parents of minor children, (old) age). The need for a designated memorandum on health services research in the last year of life results from the special situation of those affected and from the special features of health services in this phase of life. With reference to these special features, this memorandum describes methodological and ethical specifics as well as current issues in health services research and how these can be adequately addressed using quantitative, qualitative and mixed methods. It has been developed by the palliative medicine section of the German Network for Health Services Research (DNVF) according to the guidelines for DNVF memoranda.

Likelihood Ratios: An Important Concept for Palliative Physicians to Understand

Palliative care has several tools and questionnaires which are commonly used for patient-related outcomes and prognosis. As an example, the Surprise Question (I would or would not be surprised that this person would have died in a year) has been used as a screen for palliative care referral but also used as a prognostic tool. Diagnostic tests, prognostic tools, and tools for gauging outcomes have certain sensitivity and specificity in predicting a diagnosis or outcome. Clinicians often use positive and negative predictive values in judging the merits of a diagnostic tool or questionnaire. However positive and negative predictive values are highly dependent on the prevalence of disease or outcome in a population and thus are not portable across studies. Likelihood ratios are both portable across populations but also provide the strength of the diagnostic or predictive measure of a test or questionnaire. In this article, we review the value and limitations of likelihood ratios and illustrate the value of using likelihood ratios using 3 studies centered on the Surprise Question published in 2022.

Considerations in the reliability and fairness audits of predictive models for advance care planning

Multiple reporting guidelines for artificial intelligence (AI) models in healthcare recommend that models be audited for reliability and fairness. However, there is a gap of operational guidance for performing reliability and fairness audits in practice. Following guideline recommendations, we conducted a reliability audit of two models based on model performance and calibration as well as a fairness audit based on summary statistics, subgroup performance and subgroup calibration. We assessed the Epic End-of-Life (EOL) Index model and an internally developed Stanford Hospital Medicine (HM) Advance Care Planning (ACP) model in 3 practice settings: Primary Care, Inpatient Oncology and Hospital Medicine, using clinicians' answers to the surprise question (“Would you be surprised if [patient X] passed away in [Y years]?”) as a surrogate outcome. For performance, the models had positive predictive value (PPV) at or above 0.76 in all settings. In Hospital Medicine and Inpatient Oncology, the Stanford HM ACP model had higher sensitivity (0.69, 0.89 respectively) than the EOL model (0.20, 0.27), and better calibration (O/E 1.5, 1.7) than the EOL model (O/E 2.5, 3.0). The Epic EOL model flagged fewer patients (11%, 21% respectively) than the Stanford HM ACP model (38%, 75%). There were no differences in performance and calibration by sex. Both models had lower sensitivity in Hispanic/Latino male patients with Race listed as “Other.” 10 clinicians were surveyed after a presentation summarizing the audit. 10/10 reported that summary statistics, overall performance, and subgroup performance would affect their decision to use the model to guide care; 9/10 said the same for overall and subgroup calibration. The most commonly identified barriers for routinely conducting such reliability and fairness audits were poor demographic data quality and lack of data access. This audit required 115 person-hours across 8–10 months. Our recommendations for performing reliability and fairness audits include verifying data validity, analyzing model performance on intersectional subgroups, and collecting clinician-patient linkages as necessary for label generation by clinicians. Those responsible for AI models should require such audits before model deployment and mediate between model auditors and impacted stakeholders.

End-of-Life Care for End-stage Heart Failure Patients

Although recent heart failure (HF) guidelines highlight integrative palliative care, including end-of-life (EOL), appropriate discussing EOL issues can be challenging due to possibility of unexpected deterioration throughout HF trajectory. Open communication and discussions with multidisciplinary team are important for setting patient and family expectations and establishing mutually agreed goals of care based firmly on the patient’s ‘human dignity’ and ‘right to self-determination.’ Especially when quality-of-life outweighs expanding quantity-of-life, transition to EOL care should be considered. Advanced care planning including resuscitation, device deactivation, site for last days, and bereavement support should focus on ensuring a good death, and be reviewed regularly.

Efforts to improve end-of-life (EOL) care have generally been focused on cancer patients, but high-quality EOL care is also important for patients with other serious medical illnesses including heart failure (HF). Recent HF guidelines offer more clinical considerations for palliative care including EOL care than ever before. Because HF patients can experience rapid, unexpected clinical deterioration or sudden death throughout the disease trajectory, choosing an appropriate time to discuss issues such as advance directives or hospice can be challenging in real clinical situations. Therefore, EOL issues should be discussed early. Conversations are important for understanding patient and family expectations and developing mutually agreed goals of care. In particular, high-quality communication with patient and family through a multidisciplinary team is necessary to define patient-centered goals of care and establish treatment based on goals. Control of symptoms such as dyspnea, pain, anxiety/depression, fatigue, nausea, anorexia, and altered mental status throughout the dying process is an important issue that is often overlooked. When quality-of-life outweighs expanding quantity-of-life, the transition to EOL care should be considered. Advanced care planning including resuscitation (i.e., do-not resuscitate order), device deactivation, site for last days and bereavement support for the family should focus on ensuring a good death and be reviewed regularly. It is essential to ensure that treatment for all HF patients incorporates discussions about the overall goals of care and individual patient preferences at both the EOL and sudden changes in health status. In this review, we focus on EOL care for end-stage HF patients.

Prognostication in palliative radiotherapy—ProPaRT: Accuracy of prognostic scores

Background

Prognostication can be used within a tailored decision-making process to achieve a more personalized approach to the care of patients with cancer. This prospective observational study evaluated the accuracy of the Palliative Prognostic score (PaP score) to predict survival in patients identified by oncologists as candidates for palliative radiotherapy (PRT). We also studied interrater variability for the clinical prediction of survival and PaP scores and assessed the accuracy of the Survival Prediction Score (SPS) and TEACHH score.

Materials and methods

Consecutive patients were enrolled at first access to our Radiotherapy and Palliative Care Outpatient Clinic. The discriminating ability of the prognostic models was assessed using Harrell’s C index, and the corresponding 95% confidence intervals (95% CI) were obtained by bootstrapping.

Results

In total, 255 patients with metastatic cancer were evaluated, and 123 (48.2%) were selected for PRT, all of whom completed treatment without interruption. Then, 10.6% of the irradiated patients who died underwent treatment within the last 30 days of life. The PaP score showed an accuracy of 74.8 (95% CI, 69.5–80.1) for radiation oncologist (RO) and 80.7 (95% CI, 75.9–85.5) for palliative care physician (PCP) in predicting 30-day survival. The accuracy of TEACHH was 76.1 (95% CI, 70.9–81.3) and 64.7 (95% CI, 58.8–70.6) for RO and PCP, respectively, and the accuracy of SPS was 70 (95% CI, 64.4–75.6) and 72.8 (95% CI, 67.3–78.3).

Conclusion

Accurate prognostication can identify candidates for low-fraction PRT during the last days of life who are more likely to complete the planned treatment without interruption.

All the scores showed good discriminating capacity; the PaP had the higher accuracy, especially when used in a multidisciplinary way.

Live well, die well – an international cohort study on experiences, concerns and preferences of patients in the last phase of life: the research protocol of the iLIVE study

Introduction

Adequately addressing the needs of patients at the end of life and their relatives is pivotal in preventing unnecessary suffering and optimising their quality of life. The purpose of the iLIVE study is to contribute to high-quality personalised care at the end of life in different countries and cultures, by investigating the experiences, concerns, preferences and use of care of terminally ill patients and their families.

Methods and analysis

The iLIVE study is an international cohort study in which patients with an estimated life expectancy of 6 months or less are followed up until they die. In total, 2200 patients will be included in 11 countries, that is, 200 per country. In addition, one relative per patient is invited to participate. All participants will be asked to fill in a questionnaire, at baseline and after 4 weeks. If a patient dies within 6 months of follow-up, the relative will be asked to fill in a post-bereavement questionnaire. Healthcare use in the last week of life will be evaluated as well; healthcare staff who attended the patient will be asked to fill in a brief questionnaire to evaluate the care that was provided. Qualitative interviews will be conducted with patients, relatives and healthcare professionals in all countries to gain more in-depth insights.

Ethics and dissemination

The cohort study has been approved by ethics committees and the institutional review boards (IRBs) of participating institutes in all countries. Results will be disseminated through the project website, publications in scientific journals and at conferences. Within the project, there will be a working group focusing on enhancing the engagement of the community at large with the reality of death and dying.

Trial registration number

NCT04271085.