Primary palliative care for heart failure: what is it? How do we implement it?

Heart failure (HF) is a chronic and progressive illness, which affects a growing number of adults, and is associated with a high morbidity and mortality, as well as significant physical and psychological symptom burden on both patients with HF and their families. Palliative care is the multidisciplinary specialty focused on optimizing quality of life and reducing suffering for patients and families facing serious illness, regardless of prognosis. Palliative care can be delivered as (1) specialist palliative care in which a palliative care specialist with subspecialty palliative care training consults or co-manages patients to address palliative needs alongside clinicians who manage the underlying illness or (2) as primary palliative care in which the primary clinician (such as the internist, cardiologist, cardiology nurse, or HF specialist) caring for the patient with HF provides the essential palliative domains. In this paper, we describe the key domains of primary palliative care for patients with HF and offer some specific ways in which primary palliative care and specialist palliative care can be offered in this population. Although there is little research on HF primary palliative care, primary palliative care in HF offers a key opportunity to ensure that this population receives high-quality palliative care in spite of the growing numbers of patients with HF as well as the limited number of specialist palliative care providers.

Predictors of palliative care consultation on an inpatient gynecologic oncology service: are we following ASCO recommendations?

OBJECTIVE: Determine predictors of inpatient palliative care (PC) consultation and characterize PC referral patterns with respect to recommendations from the American Society of Clinical Oncology (ASCO). METHODS: Women with a gynecologic malignancy admitted to the gynecologic oncology service 3/2012-8/2012 were identified. Demographic information, disease and treatment details and date of death were abstracted from medical records. Student's t-test, Fischer's exact test or χ(2)-test was used for univariate analysis. Binomial logistic regression was used for multivariate analysis. RESULTS: Of 340 patients analyzed, 82 (24%) had PC consultation. Univariate predictors of PC consultation included race, cancer type and stage, recurrent disease, admission frequency, admission for symptom management or malignant bowel obstruction (MBO), discharge to skilled nursing facility (SNF) and number of lines of chemotherapy. On multivariate analysis, significant predictors of PC consultation were recurrent disease (OR 2.4, 95% CI 1.1-5.3), number of admissions (≥ 3, OR 10.9, 95% CI 3.4-34.9), admission for symptom management (OR 19.4, 95% CI 7.5-50.1), discharge to SNF (OR 5, 95% CI 1.9-13.5) and death within 6 months (OR 16.5, 95% CI 6.9-39.5). Of patients considered to meet ASCO guidelines, 53% (63/118) had PC referral. Of patients referred to PC, 51.2% (42/82) died within 6 months of last admission. CONCLUSIONS: Patients referred to inpatient PC have high disease and symptom burden and poor prognosis. High-risk patients, including those meeting ASCO recommendations, are not captured comprehensively. We continue to use PC referrals primarily for patients near the end of life, rather than utilizing early integration as recommended by ASCO.

Earlier identification of seriously ill patients: an implementation case series.

OBJECTIVE: To describe the strategies used by a collection of healthcare systems to apply different methods of identifying seriously ill patients for a targeted palliative care intervention to improve communication around goals and values. METHODS: We present an implementation case series describing the experiences, challenges and best practices in applying patient selection strategies across multiple healthcare systems implementing the Serious Illness Care Program (SICP). RESULTS: Five sites across the USA and England described their individual experiences implementing patient selection as part of the SICP. They employed a combination of clinician screens (such as the 'Surprise Question'), disease-specific criteria, existing registries or algorithms as a starting point. Notably, each describes adaptation and evolution of their patient selection methodology over time, with several sites moving towards using more advanced machine learning-based analytical approaches. CONCLUSIONS: Involving clinical and programme staff to choose a simple initial method for patient identification is the ideal starting place for selecting patients for palliative care interventions. However, improving and refining methods over time is important and we need ongoing research into better patient selection methodologies that move beyond mortality prediction and instead focus on identifying seriously ill patients-those with poor quality of life, worsening functional status and medical care that is negatively impacting their families.