Context: The COVID-19 pandemic is spreading across the world. Many patients will not be suitable for mechanical ventilation owing to the underlying health conditions, and they will require a conservative approach including palliative care management for their important symptom burden.
Objectives: To develop a management plan for patients who are not suitable for mechanical ventilation that is tailored to the stage their COVID-19 disease.
Methods: Patients were identified as being stable, unstable, or at the end of life using the early warning parameters for COVID-19. Furthermore, a COVID-19–specific assessment tool was developed locally, focusing on key symptoms observed in this population which assess dyspnoea, distress, and discomfort. This tool helped to guide the palliative care management as per patients' disease stage.
Results: A management plan for all patients' (stable, unstable, end of life) was created and implemented in acute hospitals. Medication guidelines were based on the limitations in resources and availability of drugs. Staff members who were unfamiliar with palliative care required simple, clear instructions to follow including medications for key symptoms such as dyspnoea, distress, fever, and discomfort. Nursing interventions and family involvement were adapted as per patients' disease stage and infection control requirements.
Conclusion: Palliative care during the COVID-19 pandemic needs to adapt to an emergency style of palliative care as patients can deteriorate rapidly and require quick decisions and clear treatment plans. These need to be easily followed up by generalist staff members caring for these patients. Furthermore, palliative care should be at the forefront to help make the best decisions, give care to families, and offer spiritual support.
Background: General practitioners’ (GPs) play a central role in facilitating end-of-life discussions with older patients nearing the end-of-life. However, prognostic uncertainty of time to death is one important barrier to initiation of these discussions.
Objective: To explore GPs’ perceptions of the feasibility and acceptability of a risk prediction checklist to identify older patients in their last 12 months of life and describe perceived barriers and facilitators for implementing end-of-life planning.
Methods: Qualitative, semi-structured interviews were conducted with 15 GPs practising in metropolitan locations in New South Wales and Queensland between May and June 2019. Data were analysed thematically.
Results: Eight themes emerged: accessibility and implementation of the checklist, uncertainty around checklist’s accuracy and usefulness, time of the checklist, checklist as a potential prompt for end-of-life conversations, end-of-life conversations not an easy topic, end-of-life conversation requires time and effort, uncertainty in identifying end-of-life patients and limited community literacy on end-of-life. Most participants welcomed a risk prediction checklist in routine practice if assured of its accuracy in identifying which patients were nearing end-of-life.
Conclusions: Most participating GPs saw the value in risk assessment and end-of-life planning. Many emphasized the need for appropriate support, tools and funding for prognostic screening and end-of-life planning for this to become routine in general practice. Well validated risk prediction tools are needed to increase clinician confidence in identifying risk of death to support end-of-life care planning.
La souffrance est une entité universelle, multidimensionnelle, mais aussi unique et personnelle, paradoxalement sous-diagnostiquée, alors qu’elle est omniprésente dans notre pratique en milieu hospitalier. Le but de cet article est de proposer au lecteur quelques pistes pour l’exploration et l’identification de la souffrance des proches de patients en situation palliative, et surtout quelques outils d’accompagnement et de soutien.
Context: The COVID-19 pandemic created a rapid and unprecedented shift in our medical system. Medical providers, teams, and organizations have needed to shift their visits away from face-to-face visits and toward telehealth (both by phone and through video). Palliative care teams who practice in the community setting are faced with a difficult task: How do we actively triage the most urgent visits while keeping our vulnerable patients safe from the pandemic?
Measures: The following are recommendations created by the Palo Alto Medical Foundation Palliative Care and Support Services team to help triage and coordinate for timely, safe, and effective palliative care in the community and outpatient setting during the ongoing COVID-19 pandemic. Patients are initially triaged based on location followed by acuity. Interdisciplinary care is implemented using strict infection control guidelines in the setting of limited personal protective equipment (PPE) resources. We implement thorough screening for COVID-19 symptoms at multiple levels before a patient is seen by a designated provider.
Conclusions/Lessons Learned: We recommend active triaging, communication, frequent screening for COVID-19 symptoms for palliative care patients been evaluated in the community setting. An understanding of infection risk, mutual consent between designated providers, patients, and their families are crucial to maintaining safety while delivering community-based palliative care during the COVID-19 pandemic.
The Covid-19 pandemic has led to severe shortages of many essential goods and services, from hand sanitizers and N-95 masks to ICU beds and ventilators. Although rationing is not unprecedented, never before has the American public been faced with the prospect of having to ration medical goods and services on this scale.
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PURPOSE: This study evaluates whether an intervention to identify Canadian patients eligible for a palliative approach changes the use of health care resources and costs within the final month of life.
METHODS: Between 2014 and 2017, physicians identified 1,187 patients in family practice units and cancer centers who were likely to die within 1 year based on diagnosis, symptom assessment, and performance status. A multidisciplinary intervention that included activation of community resources and initiation of palliative planning was started. By using propensity-score matching, patients in the intervention group were matched 1:1 with nonintervention controls selected from provincial administrative data. We compared health care use and costs (using 2017 Canadian dollars) for 30 days before death between patients who died within the 1-year follow-up and matched controls.
RESULTS: Groups (n = 629 in each group) were well-balanced in sociodemographic characteristics, comorbidities, and previous health care use. In the last 30 days, there was no differences in proportions between the two groups of patients regarding emergency department visits, intensive care unit admissions, or inpatient hospitalizations. However, patients in the intervention group had greater use of palliative physician encounters, community home care visits, and/or physician home visits (92.8% v 88.4%; P = .007). In the 507 pairs with cancer, more patients in the intervention group underwent chemotherapy (44% v 33%; P < .001) and radiation (18.7% v 3.2%; P = .043) in the last 30 days. Mean cost per patient was similar for the intervention group (mean, $17,231; 95% CI, $16,027 to $18,436) and for the control group (mean, $16,951; 95% CI, $15,899 to $18,004).
CONCLUSION: Even with the limitations in our observational study design, identification of palliative patients did not significantly change overall costs but may shift resources toward palliative services.
BACKGROUND: Key Information Summaries (KIS) were introduced throughout Scotland in 2013 so that anticipatory care plans written by general practitioners (GPs) could be routinely shared electronically and updated in real time, between GPs and providers of unscheduled and secondary care.
AIMS: We aimed to describe the current reach of anticipatory and palliative care, and to explore GPs' views on using KIS.
METHODS: We studied the primary care records of all patients who died in 2014 in 9 diverse Lothian practices. We identified if anticipatory or palliative care had been started, and if so how many weeks before death and which aspects of care had been documented. We interviewed 10 GPs to understand barriers and facilitating factors.
RESULTS: Overall, 60% of patients were identified for a KIS, a median of 18 }weeks before death. The numbers identified were highest for patients with cancer, with 75% identified compared with 66% of those dying with dementia/frailty and only 41% dying from organ failure. Patients were more likely to die outside hospital if they had a KIS. GPs identified professional, patient and societal challenges in identifying patients for palliative care, especially those with non-cancer diagnoses.
CONCLUSIONS: GPs are identifying patients for anticipatory and palliative care more equitably across the different disease trajectories and earlier in the disease process than they were previously identifying patients specifically for palliative care. However, many patients still lack care planning, particularly those dying with organ failure.
Background: The “END-of-Life ScorING-System” (ENDING-S) was previously developed to identify patients at high-risk of dying in the ICU and to facilitate a practical integration between palliative and intensive care. The aim of this study is to prospectively validate ENDING-S in a cohort of long-term critical care patients.
Materials and methods: Adult long-term ICU patients (with a length-of-stay> 4 days) were considered for this prospective multicenter observational study. ENDING-S and SOFA score were calculated daily and evaluated against the patient’s ICU outcome. The predictive properties were evaluated through a receiver operating characteristic (ROC) analysis.
Results: Two hundred twenty patients were enrolled for this study. Among these, 21.46% died during the ICU stay. ENDING-S correctly predicted the ICU outcome in 71.4% of patients. Sensitivity, specificity, positive and negative predictive values associated with the previously identified ENDING-S cut-off of 11.5 were 68.1, 72.3, 60 and 89.3%, respectively. ROC-AUC for outcome prediction was 0.79 for ENDING-S and 0.88 for SOFA in this cohort.
Conclusions: ENDING-S, while not as accurately as in the pilot study, demonstrated acceptable discrimination properties in identifying long-term ICU patients at very high-risk of dying. ENDING-S may be a useful tool aimed at facilitating a practical integration between palliative, end-of-life and intensive care.
Trial registration: Clinicaltrials.gov Identifier: NCT02875912; First registration August 4, 2016.
INTRODUCTION: In observational studies with mortality endpoints, one needs to consider how to account for subjects whose interventions appear to be part of 'end-of-life' care.
OBJECTIVE: The objective of this study was to develop a diagnostic predictive model to identify those in end-of-life care at the time of a drug exposure.
METHODS: We used data from four administrative claims datasets from 2000 to 2017. The index date was the date of the first prescription for the last new drug subjects received during their observation period. The outcome of end-of-life care was determined by the presence of one or more codes indicating terminal or hospice care. Models were developed using regularized logistic regression. Internal validation was through examination of the area under the receiver operating characteristic curve (AUC) and through model calibration in a 25% subset of the data held back from model training. External validation was through examination of the AUC after applying the model learned on one dataset to the three other datasets.
RESULTS: The models showed excellent performance characteristics. Internal validation resulted in AUCs ranging from 0.918 (95% confidence interval [CI] 0.905-0.930) to 0.983 (95% CI 0.978-0.987) for the four different datasets. Calibration results were also very good, with slopes near unity. External validation also produced very good to excellent performance metrics, with AUCs ranging from 0.840 (95% CI 0.834-0.846) to 0.956 (95% CI 0.952-0.960).
CONCLUSION: These results show that developing diagnostic predictive models for determining subjects in end-of-life care at the time of a drug treatment is possible and may improve the validity of the risk profile for those treatments.
New approaches are needed to assist residential aged care (RAC) staff increase their skills and confidence in identifying when residents are nearing the dying phase and managing symptoms. One new evidence-based approach to improve palliative and end-of-life care in RAC is outreach Specialist Palliative Care Needs Rounds (monthly triage and risk stratification meetings – hereafter Needs Rounds); as yet untried in rural settings which may face unique enablers or challenges. Needs Rounds were introduced into two RAC facilities in the rural Snowy Monaro region of New South Wales, Australia. This study explored staff and general practitioners’(GPs’) experiences and perceptions of palliative and end-of-life care in rural RAC, and staff confidence and capability in providing such care, prior to, and after the introduction of Needs Rounds. A mixed-methods, pre- and post-intervention approach was taken, utilizing a Likert-scale written questionnaire and face-to-face semi-structured interviews. Between March and November 2018, 61 questionnaires were completed by 48 RAC staff (33 pre-, 28 post-intervention); eight staff and three GPs were interviewed. Despite system and site-specific barriers, staff self-reported that Needs Rounds increased their capability in providing end-of-life care (p = 0.04; 95% CI 0.20–7.66), and improved staff: (1) awareness of end of life, reflective practice, and critical thinking; (2) end-of-life decision making and planning; and (3) pain management. Needs Rounds are acceptable and feasible in rural RAC. Palliative and end-of-life care for residents may be improved through education, collaboration, communication, and planning. Further studies should explore running Needs Rounds via telehealth and/or utilizing a multidisciplinary approach.
Background: early identification of palliative patients is challenging. The Surprise Question (SQ1; Would I be surprised if this patient were to die within 12 months?) is widely used to identify palliative patients. However, its predictive value is low. Therefore, we added a second question (SQ2) to SQ1: ‘Would I be surprised if this patient is still alive after 12 months?’ We studied the accuracy of this double surprise question (DSQ) in a general practice.
Methods: We performed a prospective cohort study with retrospective medical record review in a general practice in the eastern part of the Netherlands. Two general practitioners (GPs) answered both questions for all 292 patients aged =75 years (mean age 84 years).
Primary outcome was 1-year death, secondary outcomes were aspects of palliative care.
Results: SQ1 was answered with ‘no‘ for 161/292 patients. Of these, SQ2 was answered with ‘yes’ in 22 patients. Within 12 months 26 patients died, of whom 24 had been identified with SQ1 (sensitivity: 92%, specificity: 49%). Ten of them were also identified with SQ2 (sensitivity: 42%, specificity: 91%). The latter group had more contacts with their GP and more palliative care aspects were discussed.
Conclusions: The DSQ appears a feasible and easy applicable screening tool in general practice. It is highly effective in predicting patients in high need for palliative care and using it helps to discriminate between patients with different life expectancies and palliative care needs. Further research is necessary to confirm the findings of this study.
Background: The surprise question (SQ), “Would I be surprised if this patient died within one year?”, is a simple instrument to identify patients with palliative care needs. The SQ-performance has not been evaluated in patients with advanced cancer visiting the emergency department (ED).
Objective: To evaluate SQ's test characteristics and predictive value in patients with advanced cancer visiting the ED.
Design: Observational cohort study.
Setting: Patients >18 years with advanced cancer in the palliative phase visiting the ED of an academic medical center.
Methods: Attending physicians answered the SQ (not surprised [NS] or surprised [S]) and estimated Eastern Cooperative Oncology Group (ECOG)-performance status. Disease, visit, and follow-up characteristics were retrospectively collected from charts. SQ's sensitivity, specificity, positive predictive value (PPV) and negative predictive value (NPV), and Harrell's c-index were calculated. Prognostic values of SQ and other variables were assessed by using Cox proportional hazards models.
Results: Two-hundred-and-forty-five patients were included (203 NS [83%] and 42 S [17%]), median age 62 years, 48% male. Follow-up on overall survival was updated until February 2019. At ED entry, NS-patients had worse ECOG-performance and more symptoms. At study closure, 233 patients had died (95%). Median survival was three months for NS-patients (interquartile [IQ]-range: 1–8); nine months for S-patients (IQ-range: 3–28) (p < 0.0001). SQ-performance for one-year mortality: sensitivity 89%, specificity 40%, PPV 85%, NPV 50%, c-index 0.56, and hazard ratio 2.1 for approaching death. ECOG 3–4 predicted death in NS-patients; addition to the SQ improved c-index (0.65); sensitivity (40%), specificity (92%), PPV (95%), and NPV (29%).
Conclusions: At the ED, the SQ plus ECOG 3–4 helps identifying patients with advanced cancer and a limited life expectancy. Its use supports initiating appropriate care related to urgency of palliative care needs.
The identification of death is critical for epidemiological research. Despite recent developments in health insurance claims databases, the quality of death information in claims is not guaranteed because health insurance claims are collected primarily for reimbursement. We aimed to examine the usefulness and limitations of death information in claims data and to examine methods for improving the quality of death information for aged persons.
We used health insurance claims data and enrollment data (as the gold standard) from September 2012 through August 2015 for nondependent persons aged 65–74 years enrolled in Japanese workplace health insurance. Overall, 3,710,538 insured persons were registered in the database during the study period. We analyzed 45,441 eligible persons. Inpatient and outpatient deaths were identified from the discharge/disease status in the claims, with sensitivities of 94.3% and 47.4%, specificities of 98.5% and 99.9%, and PPVs of 96.3% and 95.7%, respectively, using enrollment data as the gold standard. For outpatients, death defined as a combination of disease status and charge data for terminal care still indicated low sensitivity (54.7%).
The validity of death information in inpatient claims was high, suggesting its potential usefulness for identifying death. However, given the low sensitivity for outpatient deaths, the use of death information obtained solely from records in outpatient claims is not recommended.
Context: Programs identifying patients needing palliative care and promoting advance care planning (ACP) are rare in Asia.
Objectives: This interventional cohort study aimed to identify hospitalized patients with palliative care needs using a validated Palliative Care Screening Tool (PCST), examine the ability of the PCST to predict mortality, and explore effects of a pragmatic ACP program targeted by PCST on the utilisation of life-sustaining treatment during the last three months of life.
Methods: In this prospective study, we used PCST to evaluate patients’ palliative care needs between 2015 and 2016 and followed patients for 3 months. ACP with advance directives (AD) were systematically offered to all patients with PCST score =4.
Results: Of 47,153 hospitalized patients, 10.4% had PCST score =4. During follow-up, 2,121 individuals died within three months of palliative care screening: 1,225 (25.0%) with PCST score =4 and 896 (2.1%) with PCST score <4. After controlling for co-variates, PCST score =4 was significantly associated with a higher mortality within 3 months of screening (adjusted odds ratio [AOR], 6.86; 95% confident interval [CI], 6.16-7.63). Moreover, ACP consultation (AOR=0.78, 95%CI: (0.66-0.92) and AD completion (AOR=0.49, 95%CI: 0.36-0.65) were associated with a lower likelihood of receiving life-sustaining treatments during the last 3 months of life.
Conclusions: We demonstrated the feasibility of implementing a comprehensive palliative care program to identify patients with palliative care needs and promote ACP and AD in East Asia. ACP consultation and AD completion were associated with reduced utilization of life-sustaining treatments during the last 3 months of life.
BACKGROUND: Rapid frailty screening remains problematic in primary care. The diagnostic test accuracy (DTA) of several screening instruments has not been sufficiently established. We evaluated the DTA of several screening instruments against two reference standards: Fried's Frailty Phenotype [FP] and the Adelaide Frailty Index [AFI]), a self-reported questionnaire.
METHODS: DTA study within three general practices in South Australia. We randomly recruited 243 general practice patients aged 75+ years. Eligible participants were 75+ years, proficient in English and community-dwelling. We excluded those who were receiving palliative care, hospitalised or living in a residential care facility.We calculated sensitivity, specificity, predictive values, likelihood ratios, Youden Index and AUC for: Edmonton Frail Scale [EFS], FRAIL Scale Questionnaire [FQ], Gait Speed Test [GST], Groningen Frailty Indicator [GFI], Kihon Checklist [KC], Polypharmacy [POLY], PRISMA-7 [P7], Reported Edmonton Frail Scale [REFS], Self-Rated Health [SRH] and Timed Up and Go [TUG]) against FP [3+ criteria] and AFI [> 0.21].
RESULTS: We obtained valid data for 228 participants, with missing scores for index tests multiply imputed. Frailty prevalence was 17.5% frail, 56.6% pre-frail [FP], and 48.7% frail, 29.0% pre-frail [AFI]. Of the index tests KC (Se: 85.0% [70.2 - 94.3]; Sp: 73.4% [66.5 - 79.6]) and REFS (Se: 87.5% [73.2 - 95.8]; Sp: 75.5% [68.8 - 81.5]), both against FP, showed sufficient diagnostic accuracy according to our pre-specified criteria.
CONCLUSIONS: Two screening instruments - the KC and REFS, show the most promise for wider implementation within general practice, enabling a personalised approach to care for older people with frailty.
Advance care plans (ACP) align care with individual values and goals for the end of life, yet their rates are low. Communication barriers are a primary reason for these low rates. Precision health approaches that target individuals based on personal needs, behaviors, or choices may improve communication and positively influence rates of advance care plans. A framework to guide these efforts is needed. The purpose of this study is to develop a framework that guides clinicians in identifying individuals who will benefit from targeted advance care planning conversations. Walker and Avant’s theory derivation strategy integrates concepts of social marketing theory, population segmentation, the marketing mix, and the transtheoretical model of behavior change into a novel framework. The Aligning Individuals with Meaningful End-of-Life Discussions to Promote ACP (TakingAIM) model promotes population segmentation by integrating social marketing theory and the marketing mix into conceptual definitions within the context of ACP: plan (product), perception (price), preference (promotion), and pathway (place). The transtheoretical model of behavior change further guides ACP conversations at the individual level. Identifying at-risk groups and targeting their specific needs may improve the rates of advance care plans. This framework is appropriate for use in any clinical setting and is ready for empirical testing.
BACKGROUND: Timely identification of patients with palliative care needs is a prerequisite for being able to carry out effective and equal palliative care. The Supportive and Palliative Care Indicators Tool (SPICT) identifies patients likely to benefit from a palliative approach.
AIM: The main objective was to describe the translation, cross-cultural adaptation and content validation process of the SPICT-SE. In this process, the prefinal SPICT-SE was tested in focus group interviews to explore how the tool was perceived and interpreted by healthcare professionals in a Swedish healthcare context.
METHODS: In this qualitative descriptive study, the translation, cross-cultural adaptation and content validation process of the SPICT-SE was based on a recommended method for cross-cultural adaptation of self-report measures. The process included two independent forward translations, a synthesis, and one independent back-translation. An expert committee consolidated all the versions and developed the prefinal version of the SPICT-SE. The prefinal version of the SPICT-SE was tested in four focus group interviews with physicians and nurses engaged in inpatient or outpatient care in south-west Sweden. A thematic analysis of the transcribed interviews was performed. The SPICT-SE was then revised to the final version.
RESULTS: In the thematic analysis, four themes were constructed that together described how the SPICT-SE was perceived and interpreted by healthcare professionals: The mindset is familiar and relevant; the tool needs to be adjusted in order to be clearer; the purpose and consequences of the tool are ambiguous; and the tool supports a palliative approach.
CONCLUSION: The SPICT-SE has now been successfully translated, culturally adapted and content validated in a Swedish healthcare context.
Frailty is a complex age-related clinical condition characterised by a decline in physiological capacity across several organ systems, with a resultant increased susceptibility to stressors. Because of the heterogeneity of frailty in clinical presentation, it is important to have effective strategies for the delivery of care that range across the continuum of frailty severity. In clinical practice, we should do what works, starting with frailty screening, case identification, and management of frailty. This process is unarguably difficult given the absence of an adequate evidence base for individual and health-system interventions to manage frailty. We advocate change towards individually tailored interventions that preserve an individual's independence, physical function, and cognition. This change can be addressed by promoting the recognition of frailty, furthering advancements in evidence-based treatment options, and identifying cost-effective care delivery strategies.
CONTEXT: Studies have shown that palliative care involvement delivers a multitude of benefits to patients and caregivers. The existing palliative care workforce is inadequate to meet growing demand. Innovative strategies to triage inpatient consults are necessary.
OBJECTIVES: To describe the implementation of a new palliative care triage process and to demonstrate its impact on efficiency, teamwork, and patient care.
METHODS: A quasi-experimental study design, comparing clinical consult data from a 6-month period before and a 6-month period after implementation of the novel consult triage model.
RESULTS: Across the 2 study periods, consult demand increased by 44% while the physician staffing (full time equivalent [FTE]) decreased by 38%. Penetration rate per clinical FTE increased (from 1.9%-2.4%; P = .004). Monthly physician work relative value units (RVUs) per FTE increased from 909 to 1678. Physician encounters with hospitalized patients increased from 284 to 353, and total team visits increased from 596 to 891 (P < .001). Average time to consult decreased by 2.4 hours (P = .54).
CONCLUSION: An efficient and streamlined consult triage process had a positive impact on our palliative care team's ability to reach patients. We were able to generate more physician visits and RVUs despite a decrease in physician clinical time, and our penetration rate per physician clinical FTE improved. Our findings highlight the importance of thoughtful and appropriate triage, not to mention teamwork, in helping to augment patient access to palliative care.