The COMFORT Model has recently been revised based on feedback from bedside nurses working in palliative care and oncology and includes the following components: Connect, Options, Making Meaning, Family Caregiver, Openings, Relating, and Team. Based on clinical and nonclinical research in hospital, hospice, palliative care, and interdisciplinary education settings, the authors present the updated COMFORT Model. Originally introduced in 2012 to support the work of the nurse, the model is not a linear guide, an algorithm, a protocol, or a rubric for sequential implementation by nurses, but rather a set of communication principles that are practiced concurrently and reflectively during patient/family care. In its restructuring, we focus on the role of health literacy throughout the COMFORT components in relationship to the health literacy attributes of a health care organization. A brief summary of COMFORT components is provided and includes strategies and competencies contributing to a health-literate care organization. Both health literacy and COMFORT are explored using specific communication challenges that underscore the role of the nurse in accomplishing person-centered and culturally responsive care, especially in chronic and terminal illness. The integration of the COMFORT Model into nursing education is proposed.
Heart failure (HF), a clinical syndrome with variable trajectory has become more common. As people with HF experience functional decline during periods of deterioration in their HF status, or with aging, their needs for palliative care increase. This review considers the palliative aspects of evidence-based HF care, which benefit patients while also addressing the underlying etiology of the HF. We also identify symptoms common to patients with HF and management beyond evidence-based HF care. Prognostic models and tools to identify patients appropriately evaluated by HF specialty experts might help clinicians understand the patient's status. Rather than trying to identify a point at which palliative care should be included in care for a patient with HF, we suggest that identifying specific needs of the patient and family is a better way to target palliative care interventions. We review available publications that have explored integration of palliative care into HF care, and propose an outpatient clinic model that assesses needs and symptoms and directs HF specialist or palliative care based on this assessment.
A hallmark of science is the open exchange of knowledge. At this time of crisis, it is more important than ever for scientists around the world to openly share their knowledge, expertise, tools, and technology. Scientific models are critical tools for anticipating, predicting, and responding to complex biological, social, and environmental crises, including pandemics. They are essential for guiding regional and national governments in designing health, social, and economic policies to manage the spread of disease and lessen its impacts. However, presenting modeling results alone is not enough. Scientists must also openly share their model code so that the results can be replicated and evaluated.
Introduction: Early access to cancer palliative care is recommended. Descriptions of structures and processes of outpatient palliative care clinics operated within smaller hospitals are scarce. This paper presents the development and operation of a fully integrated cancer and palliative care outpatient clinic at a local hospital in a rural region of Mid-Norway offering palliative care concurrent with cancer treatment. A standardized care pathway was applied.
Methods: Palliative care is in Norway part of the public healthcare system. Official recommendations recent years point out action points to improve delivery of palliative care. An integrated cancer and palliative care outpatient clinic at a local hospital and an innovative care delivery model was developed and operated in this setting. Patients were recruited for a descriptive study of the patient population. Clinical data were collected by clinical staff and 13 symptom intensities were reported by the patients.
Results: Cancer and palliative care were provided by one team of healthcare professionals trained in both fields. There was a close collaboration with the other departments at the hospital, with its affiliated tertiary hospital, and with community health and care services to provide timely referral, enhanced continuity, and improved coordination of care. Eighty-eight patients were included. Mean age was 65.6 years, the most common cancer diagnoses were digestive organs (22.7%), male genital organs (20.5%) or breast (25.0%), 75.0% had metastatic or locally advanced cancer, 59.1% were treated with non-curative intention and 93.1% had Karnofsky Performance Status = 80%. Median scores of individual symptoms ranged from 0 to 3 (numerical rating scale, 0–10) and 61.0% reported at least one clinically significant symptom rating (= 4).
Conclusion: This delivery model of integrated outpatient cancer and palliative care is particularly relevant in rural regions allowing cancer patients access to palliative care earlier in the disease trajectory and closer to home
Context: Universal screening to identify vulnerable patients who may receive limited benefits from life-sustaining treatments can facilitate palliative care in dialysis populations.
Objectives: We aimed to develop prediction models for 1-year mortality in peritoneal dialysis patients.
Methods: This prospective cohort study included 401 adult Taiwanese prevalent peritoneal dialysis patients (average age 56.2 ± 14 years). In addition to obtaining clinical characteristics and laboratory data, the primary care nurses evaluated the “surprise question” and “palliative care screening tool” for each patient in March 2015. Multivariate logistic regression models were conducted to predict the primary outcome of 1-year all-cause mortality.
Results: There were 34 (8.5%) patients who died during the first year of follow-up. Patients allocated to the “not surprised” group according to the surprise question and those who received a score = 4 on the palliative care screening tool had increased odds of death [odds ratio 24.68 (95% CI 10.66 - 57.13) and 12.18 (95% CI 5.66 - 26.21), respectively]. We also developed a clinical risk model for 1-year mortality that included sex, dialysis vintage, coronary artery disease, malignancy, normalized protein nitrogen appearance, white blood cell count, and serum albumin and sodium levels. Integrating the surprise question, palliative care screening tool, and clinical risk model exhibited good discrimination with an area under the receiver operating characteristic curve of 0.95. Kaplan-Meier analysis showed worse survival in high risk patients predicted by the integrated model (log-rank P<.001).
Conclusion: screening with the use of the integrated measurement can identify high-risk peritoneal dialysis patients. This approach may facilitate palliative care interventions for at-risk the subpopulations.
Prediction of short-term mortality in elderly patients with heart failure (HF) would be useful for clinicians when discussing HF management or palliative care.
A prospective multicenter cohort study was conducted between July 2014 and July 2018. A total of 504 consecutive elderly patients (age = 75 years) with HF (mean age 85 years, 50% women) were enrolled. We used a multiple logistic regression analysis with stepwise variable selection to select predictive variables and to determine weighted point scores. After analysis, the following variables predicted short-term mortality and comprised the risk score: previous HF admission (3 points), New York Heart Association III or IV (2 points), body mass index < 17.7 kg/m2 (4 points), serum albumin < 3.5 g/dL (9 points), and left ventricular ejection fraction < 50% (2 points). The c-statistic was 0.820. We compared mortality in low-risk (0-6 points, n = 188), intermediate-risk (7-13 points, n = 241), and high-risk (14-20 points, n = 75) groups. A total of 43 (8.5%) patients died within 6 months after discharge. Mortality was significantly higher in groups with higher scores (low-risk group, 0.5%; intermediate-risk group, 9.1%; high-risk group, 26.7%; P < 0.001).
We developed a predictive model for 6-month mortality in elderly patients with HF. This risk score could be useful when discussing advanced HF therapies, palliative care, or hospice referral with patients.
OBJECTIVE: Although the psychometric properties of the Family Satisfaction with End-of-Life Care measure have been examined in diverse settings internationally; little evidence exists regarding measurement equivalence in Hispanic caregivers. The aim was to examine the psychometric properties of a short-form of the FAMCARE in Hispanics using latent variable models and place information on differential item functioning (DIF) in an existing family satisfaction item bank.
METHOD: The graded form of the item response theory model was used for the analyses of DIF; sensitivity analyses were performed using a latent variable logistic regression approach. Exploratory and confirmatory factor analyses to examine dimensionality were performed within each subgroup studied. The sample included 1,834 respondents: 317 Hispanic and 1,517 non-Hispanic White caregivers of patients with Alzheimer's disease and cancer, respectively.
RESULTS: There was strong support for essential unidimensionality for both Hispanic and non-Hispanic White subgroups. Modest DIF of low magnitude and impact was observed; flagged items related to information sharing. Only 1 item was flagged with significant DIF by both a primary and sensitivity method after correction for multiple comparisons: "The way the family is included in treatment and care decisions." This item was more discriminating for the non-Hispanic, White responders than for the Hispanic subsample, and was also a more severe indicator at some levels of the trait; the Hispanic respondents located at higher satisfaction levels were more likely than White non-Hispanic respondents to report satisfaction.
SIGNIFICANCE OF RESULTS: The magnitude of DIF was below the salience threshold for all items. Evidence supported the measurement equivalence and use for cross-cultural comparisons of the short-form FAMCARE among Hispanic caregivers, including those interviewed in Spanish.
BACKGROUND: Societal attitudes about end-of-life events are at odds with how, where, and when children die. In addition, parents' ideas about what constitutes a "good death" in a pediatric intensive care unit vary widely.
OBJECTIVE: To synthesize parents' perspectives on end-of-life care in the pediatric intensive care unit in order to define the characteristics of a good death in this setting from the perspectives of parents.
METHODS: A concept analysis was conducted of parents' views of a good death in the pediatric intensive care unit. Empirical studies of parents who had experienced their child's death in the inpatient setting were identified through database searches.
RESULTS: The concept analysis allowed the definition of antecedents, attributes, and consequences of a good death. Empirical referents and exemplar cases of care of a dying child in the pediatric intensive care unit serve to further operationalize the concept.
CONCLUSIONS: Conceptual knowledge of what constitutes a good death from a parent's perspective may allow pediatric nurses to care for dying children in a way that promotes parents' coping with bereavement and continued bonds and memories of the deceased child. The proposed conceptual model synthesizes characteristics of a good death into actionable attributes to guide bedside nursing care of the dying child.
Context: We previously developed the reintegration model to describe the adjustment process for individuals at the end of life. However, caregivers and loved ones also require significant support and must work to reimagine their relationship with one another.
Objectives: We sought to develop a dyadic version of the reintegration model that delineates key parts of the adjustment process that occur between the patient and another significant person rather than as two separate individuals.
Methods: We refined an initial conceptual model of this dyadic process with findings from a narrative literature review on spousal dyadic mutuality. We assessed emergent themes regarding dyadic adjustment from the literature for their fit with our original reintegration model and through consensus discussion, applied the findings to a final proposed conceptual model of dyadic reintegration at the end of life.
Results: Examples of dyadic adjustment in the literature relate to the comprehension, creative adaptation, and reintegration processes described in the original reintegration model. Evidence also supported three substantive additions in the new dyadic model: (1) shared understanding that the harmony of the dyad is interrupted; (2) consideration of the "we" (the dyad) and the "I" (the individual) in mutual reflection to create a shared narrative; and (3) emphasis on relationship as a factor impacting adjustment processes.
Conclusions: Available evidence supports interdependent relationships between members of dyads for the three adaptation processes of comprehension, creative adaptation, and reintegration in the model. This dyadic reintegration model can be useful in clinical practice to support dyads facing life-limiting illness.
BACKGROUND: In Canada, access to palliative care is a growing concern, particularly in rural communities. These communities have constrained health care services and accessing local palliative care can be challenging. The Site Suitability Model (SSM) was developed to identify rural "candidate" communities with need for palliative care services and existing health service capacity that could be enhanced to support a secondary palliative care hub. The purpose of this study was to test the feasibility of implementing the SSM in Ontario by generating a ranked summary of rural "candidate" communities as potential secondary palliative care hubs.
METHODS: Using Census data combined with community-level data, the SSM was applied to assess the suitability of 12 communities as rural secondary palliative care hubs. Scores from 0 to 1 were generated for four equally-weighted components: (1) population as the total population living within a 1-h drive of a candidate community; (2) isolation as travel time from that community to the nearest community with palliative care services; (3) vulnerability as community need based on a palliative care index score; and (4) community readiness as five dimensions of fit between a candidate community and a secondary palliative care hub. Component scores were summed for the SSM score and adjusted to range from 0 to 1.
RESULTS: Population scores for the 12 communities ranged widely (0.19-1.00), as did isolation scores (0.16-0.94). Vulnerability scores ranged more narrowly (0.27-0.35), while community readiness scores ranged from 0.4-1.0. These component scores revealed information about each community's particular strengths and weaknesses. Final SSM scores ranged from a low of 0.33 to a high of 0.76.
CONCLUSIONS: The SSM was readily implemented in Ontario. Final scores generated a ranked list based on the relative suitability of candidate communities to become secondary palliative care hubs. This list provides information for policy makers to make allocation decisions regarding rural palliative services. The calculation of each community's scores also generates information for local policy makers about how best to provide these services within their communities. The multi-factorial structure of the model enables decision makers to adapt the relative weights of its components.
BACKGROUND: Moral distress is an important and well-studied phenomenon among nurses and other healthcare providers, yet the conceptualization of parental moral distress remains unclear.
OBJECTIVE: The objective of this dimensional analysis was to describe the nature of family moral distress in serious pediatric illness.
DESIGN AND METHODS: A dimensional analysis of articles retrieved from a librarian-assisted systematic review of Scopus, CINAHL, and PsychInfo was conducted, focusing on how children, parents, other family members, and healthcare providers describe parental moral distress, both explicitly through writings on parental moral experience and implicitly through writings on parental involvement in distressing aspects of the child's serious illness.
ETHICAL CONSIDERATIONS: To promote child and family best interest and minimize harm, a nuanced understanding of the moral, existential, emotional, and spiritual impact of serious pediatric illness is needed. The cases used in this dimensional analysis come from the first author's IRB approved study at the Children's Hospital of Philadelphia and subsequent published studies; or have been adapted from the literature and the authors' clinical experiences.
FINDINGS: Three dimensions emerged from the literature surrounding parent moral distress: an intrapersonal dimension, an interpersonal dimension, and a spiritual/existential dimension. The overarching theme is that parents experience relational solace and distress because of the impact of their child's illness on relationships with themselves, their children, family, healthcare providers, their surrounding communities, and society.
DISCUSSION: Elucidating this concept can help nurses and other professionals understand, mitigate, or eliminate antecedents to parental moral distress. We discuss how this model can facilitate future empirical and conceptual bioethics research, as well as inform the manner in which healthcare providers engage, collaborate with, and care for families during serious pediatric illness.
CONCLUSION: Parent moral distress is an important and complex phenomenon that requires further theoretical and empirical investigation. We provide an integrated definition and dimensional schematic model that may serve as a starting point for future research and dialogue.
BACKGROUND: Predicting death in a cohort of clinically diverse, multi-condition hospitalized patients is difficult. This frequently hinders timely serious illness care conversations. Prognostic models that can determine 6-month death risk at the time of hospital admission can improve access to serious illness care conversations.
OBJECTIVE: The objective is to determine if the demographic, vital sign, and laboratory data from the first 48 h of a hospitalization can be used to accurately quantify 6-month mortality risk.
DESIGN: This is a retrospective study using electronic medical record data linked with the state death registry.
PARTICIPANTS: Participants were 158,323 hospitalized patients within a 6-hospital network over a 6-year period.
MAIN MEASURES: Main measures are the following: the first set of vital signs, complete blood count, basic and complete metabolic panel, serum lactate, pro-BNP, troponin-I, INR, aPTT, demographic information, and associated ICD codes. The outcome of interest was death within 6 months.
KEY RESULTS: Model performance was measured on the validation dataset. A random forest model-mini serious illness algorithm-used 8 variables from the initial 48 h of hospitalization and predicted death within 6 months with an AUC of 0.92 (0.91-0.93). Red cell distribution width was the most important prognostic variable. min-SIA (mini serious illness algorithm) was very well calibrated and estimated the probability of death to within 10% of the actual value. The discriminative ability of the min-SIA was significantly better than historical estimates of clinician performance.
CONCLUSION: min-SIA algorithm can identify patients at high risk of 6-month mortality at the time of hospital admission. It can be used to improved access to timely, serious illness care conversations in high-risk patients.
The views of family carers who provide end of life care to people of advanced age are not commonly known. We conducted a bicultural study with bereaved New Zealand Maori (indigenous) and non-indigenous family carers who, on behalf of their older family member, reflected on the end of life circumstances and formal and informal care experienced by the older person. Semi-structured interviews were undertaken with 58 people (19 Maori and 39 non-Maori), who cared for 52 family members who died aged over 80 years. A Kaupapa Maori thematic analysis of family/whanau perspectives identified examples of good holistic care as well as barriers to good care. These are presented in a proposed Whare Tapa Wha Older Person’s Palliative Care model. Good health care was regarded by participants as that which was profoundly relationship-oriented and upheld the older person’s mana (authority, status, spiritual power) across four critical health domains: Whanau (social/family), Hinengaro (emotional/mental), Wairua (spiritual) and Tinana (physical) health domains. However, poor health care on one level impacted on all four domains affecting (reducing) mana (status). The “indigenous” model was applicable to both indigenous and non-indigenous experiences of end of life care for those in advanced age. Thus, Indigenous perspectives could potentially guide and inform end of life care for all.
Palliative care is indicated in patients with heart failure since the early phases of the disease, as suggested by international guidelines. However, patients are referred to palliative care very late. Many barriers could explain the gap between the guidelines' indications and clinical practice. The term palliative is perceived as a stigma by doctors, patients, and family members because it is charged with negative meanings, a poor prognosis, and no hope for improvement. Many authors prefer the term supportive care, which could facilitate a discussion between doctors, patients, and caregivers. There is substantial variation and overlap in the meanings assigned to these two terms in the literature. Prognosis, as the main indication to palliative care, delays its implementation. It is necessary to modify this paradigm, moving from prognosis to patients' needs. The lack of access to palliative care programs is often due to a lack of palliative care specialists and this shortage will be greater in the near future. In this study, a new model is proposed to integrate early over the course of the disease the palliative care (PC) specialist in the heart failure team, allowing to overcome the barriers and to achieve truly simultaneous care in the treatment of heart failure (HF) patients.
Background: Communication in do not resuscitate (DNR) and artificial nutrition and hydration (ANH) at the end of life is a key component of advance care planning (ACP) which is essential for patients with advanced cancer to have cares concordant with their wishes. The SOP model (Shared decision making with Oncologists and Palliative care specialists) aimed to increase the rate of documentation on the preferences for DNR and ANH in patients with advanced cancer.
Methods: The SOP model was implemented in a national cancer treatment center in Taiwan from September 2016 to August 2018 for patients with advanced cancer visiting the oncology outpatient clinic. The framework was based on the model of shared decision making as “choice talk” initiated by oncologists with “option talk” and “decision talk” conducted by palliative care specialists.
Results: Among 375 eligible patients, 255 patients (68%) participated in the model testing with the mean age of 68.5 ± 14.7 years (mean ± SD). Comparing to 52.3% of DNR documentation among patients with advanced cancer who died in our hospital, the rate increased to 80.9% (206/255) after the decision talk in our model. Only 6.67% (n = 17) of the participants documented their preferences on ANH after the model. A worse Eastern Cooperative Oncology Group Performance Status was the only statistically significant associating factor with a higher rate of DNR documentation in the multiple logistic regression model.
Conclusions: The SOP model significantly increased the rate of DNR documentation in patients with advanced cancer in this pilot study. Dissemination of the model could help the patients to receive care that is concordant with their wishes and be useful for the countries having laws on ACP.
Over the past decade, substantial progress has been made in building the evidence base for integrating palliative care with cancer care and increasing the availability of palliative care services for patients with cancer. Multiple clinical trials have evaluated proactive care models in which patients begin to receive palliative care services on the basis of an initial diagnosis of advanced cancer or disease progression. The goal of these delivery models is to improve patients’ experiences and outcomes throughout their illness course rather to wait to involve palliative care until they are struggling with uncontrolled symptoms. These studies have demonstrated that earlier and longitudinal involvement of palliative care improves patients’ quality of life, mood, and satisfaction with care. Several studies also have shown that earlier involvement of palliative care enhances the experience of patients’ caregivers and leads to improved communication and delivery of end-of-life care. As these data emerged, ASCO and several other national organizations endorsed the early involvement of palliative care for patients with advanced cancer, which has substantially transformed the practice of palliative care in oncology.
Palliative care began in academic centers with specialty consultation services, and its value to patients, families, and health systems has been evident. The demand for palliative care to be integrated throughout the cancer trajectory, combined with a limited palliative care workforce, means that new models of care are needed. This review discusses evidence regarding the need for integration of palliative care into routine oncology care and describes best practices recognized for dissemination of palliative care. The available evidence suggests that palliative care be widely adopted by clinicians in all oncology settings to benefit patients with cancer and their families. Efforts are needed to adapt and integrate palliative care into community practice. Limitations of these models are discussed, as are future directions to continue implementation efforts. The benefits of palliative care can only be realized through effective dissemination of these principles of care, with more primary palliative care delivered by oncology clinicians.
Palliative care has evolved over the past five decades as an interprofessional specialty to improve quality of life and quality of care for patients with cancer and their families. Existing evidence supports that timely involvement of specialist palliative care teams can enhance the care delivered by oncology teams. This review provides a state-of-the-science synopsis of the literature that supports each of the five clinical models of specialist palliative care delivery, including outpatient clinics, inpatient consultation teams, acute palliative care units, community-based palliative care, and hospice care. The roles of embedded clinics, nurse-led models, telehealth interventions, and primary palliative care also will be discussed. Outpatient clinics represent the key point of entry for timely access to palliative care. In this setting, patient care can be enhanced longitudinally through impeccable symptom management, monitoring, education, and advance care planning. Inpatient consultation teams provide expert symptom management and facilitate discharge planning for acutely symptomatic hospitalized patients. Patients with the highest level of distress and complexity may benefit from an admission to acute palliative care units. In contrast, community-based palliative care and hospice care are more appropriate for patients with a poor performance status and low to moderate symptom burden. Each of these five models of specialist palliative care serve a different patient population along the disease continuum and complement one another to provide comprehensive supportive care. Additional research is needed to define the standards for palliative care interventions and to refine the models to further improve access to quality palliative care.
This study uses a fuzzy logic and neural network to ascertain how service quality dimensions of the SERVQUAL model (reliability, assurance, empathy, responsiveness, and tangibility) affect overall customer satisfaction. Using a threshold logic unit to produce observation outcomes, the algorithm indicated that while reliability was the crux of the service outcome, peripheral variables (e.g., assurance, empathy, responsiveness, and tangibility) integrated emotions and feelings into the hospice service process which equated to an increased quality of life, a positive disconfirmation of expectations (service expectations were met or exceeded) and a good death experience equating to a positive perception of quality.
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.