Inpatient Palliative Care Consult: A Marker for High Risk of Readmission or Death in Discharged Oncology Inpatients

2019 ◽  
pp. 082585971986906
Author(s):  
Debbie Selby ◽  
Anita Chakraborty ◽  
Audrey Kim ◽  
Jeff Myers
Keyword(s):  
Emergency Department ◽  
Palliative Care ◽  
High Risk ◽  
Acute Care ◽  
Disease Process ◽  
Emergency Department Visits ◽  
Advanced Illness ◽  
Phone Calls ◽  
Palliative Care Teams ◽  
Advance Care

Background: Emergency department visits or readmission to hospital are common particularly among those with advanced illness. Little prospective data exist on early outcomes specifically for patients seen by a palliative care consult service during their acute care admission, who are subsequently discharged home. Methods: This study followed 62 oncology patients who had had a palliative care consult during their admission to acute care with weekly phone calls postdischarge for 4 weeks. Events recorded included death, readmission, emergency department visits, and admission to a palliative care unit. Results: By the end of the study, 32 (52%) of 62 had had at least 1 event, (readmission, emergency department visit, or death), with the majority of these occurring in the first 2 weeks postdischarge. The overall 4-week death rate was 14 (22.6%) of 62. Conclusions: These data suggest that the need for a palliative care consult identifies inpatients at very high risk for early deterioration and underlines the critical importance of advance care planning/goals-of-care discussions by the oncology and palliative care teams to ensure patients and families understand their disease process and have the opportunity to direct their care decisions.

An Active In-Home Physician Model of Palliative Care and Its Resulting Performance Indicators Related to Home Deaths, Unplanned Emergency Department Visits and Unplanned Hospital Admissions

2020 ◽  
Vol 36 (1) ◽  
pp. 46-49
Author(s):  
Colleen Webber ◽  
Aurelia Ona Valiulis ◽  
Peter Tanuseputro ◽  
Valerie Schulz ◽  
Tavis Apramian ◽  
...  
Keyword(s):  
Emergency Department ◽  
Palliative Care ◽  
Hospital Admissions ◽  
Case Series ◽  
Palliative Care Team ◽  
Emergency Department Visits ◽  
Care Team ◽  
Retrospective Case ◽  
Palliative Care Teams ◽  
Unplanned Hospital Admissions

Background: Limited research has characterized team-based models of home palliative care and the outcomes of patients supported by these care teams. Case presentation: A retrospective case series describing care and outcomes of patients managed by the London Home Palliative Care Team between May 1, 2017 and April 1, 2019. Case management: The London Home Palliative Care (LHPC) Team care model is based upon 3 pillars: 1) physician visit availability 2) active patient-centered care with strong physician in-home presence and 3) optimal administrative organization. Case outcomes: In the 18 month study period, 354 patients received care from the London Home Palliative Care Team. Most significantly, 88.4% ( n = 313) died in the community or at a designated palliative care unit after prearranged direct transfer; no comparable provincial data is available. 21.2% ( n = 75) patients visited an emergency department and 24.6% ( n = 87) were admitted to hospital at least once in their final 30 days of life. 280 (79.1%) died in the community. These values are better than comparable provincial estimates of 62.7%, 61.7%, and 24.0%, respectively. Conclusion: The London Home Palliative Care (LHPC) Team model appears to favorably impact community death rate, ER visits and unplanned hospital admissions, as compared to accepted provincial data. Studies to determine if this model is reproducible could support palliative care teams achieving similar results.

Developing a new model of care for patients with cancer who present to the emergency department: The Mayo Clinic experience.

2014 ◽  
Vol 32 (31_suppl) ◽  
pp. 61-61
Author(s):  
Debra A. Wong ◽  
Tom R. Fitch ◽  
Eric Prommer ◽  
Yu-Hui Chang ◽  
Christopher A. Lipinski
Keyword(s):  
Emergency Department ◽  
Palliative Care ◽  
Supportive Care ◽  
Cancer Patients ◽  
Advance Care Planning ◽  
Emergency Department Visits ◽  
Cancer Type ◽  
Care Planning ◽  
Patients With Cancer ◽  
Advance Care

61 Background: Patients with cancer often have complex symptoms and morbidity that prompt frequent Emergency Department visits. The length of stay in the ED for cancer patients exceeds that of patients without cancer. Patients with cancer are also more likely to be admitted, but are often discharged within 72h. Protracted ED visits, extensive investigations, and the burdens of even a short admission may be distressing and may not be aligned with patients’ care goals and preferences. Furthermore, the healthcare resources dedicated to these patients is considerable and has economic implications. We recently established a Supportive Care Infusion Center (SCIC), an on-campus outpatient unit where patients can receive treatments for symptom relief and comfort; they are assured integrated palliative care with routine oncologic care. We believe there is a subset of cancer patients who can be safely transferred from the ED to the SCIC for appropriate care. Methods: We are retrospectively evaluating cancer patients admitted through the ED to validate clinical parameters likely to lead to admission, and also identify any differences between patients admitted for <72h vs >72h. Patients are analyzed based on symptoms, cancer type, prior cancer therapies, performance status, comorbidities, and presence/absence of advance care planning as well as previous contact with Palliative Care. Data are also being gathered on patient outcomes, including mortality within 60d of admission. Results: Previously established indicators predictive of admission included shortness of breath and SIRS criteria, which our current review validates. We also observe that patients admitted for >72h have greater symptom burden and comorbidities and have received multiple lines of therapy. They also less frequently have advance care planning in place. Data analysis is ongoing. Conclusions: There exists a difference between cancer patients admitted >72h and those discharged within 72h. Awareness of these characteristics may lead to improved workflow in the ED. Identifying patients who may be suitable for transfer to an outpatient supportive care unit rather than short-term admission will also facilitate cost-effectiveness. Future direction includes evaluation of outcomes such as mortality, quality of life, and patient-caregiver satisfaction.

scholarly journals Scalable Model for Delivery of Inpatient Palliative Care During a Pandemic

2021 ◽  
pp. 104990912110057
Author(s):  
Ebru Kaya ◽  
Warren Lewin ◽  
David Frost ◽  
Breffni Hannon ◽  
Camilla Zimmermann
Keyword(s):  
Palliative Care ◽  
High Quality ◽  
Consultation Service ◽  
General Internal ◽  
Virtual Care ◽  
Palliative Care Teams ◽  
Order Sets ◽  
Embedded Model ◽  
Advance Care ◽  
Care Capacity

Background: During the COVID-19 pandemic, hospitals worldwide have reported large volumes of patients with refractory symptoms and a large number of deaths attributable to COVID-19. This has led to an increase in the demand for palliative care beyond what can be provided by most existing programs. We developed a scalable model to enable continued provision of high-quality palliative care during a pandemic for hospitals without a palliative care unit or existing dedicated palliative care beds. Methods: A COVID-19 consultation service working group (CWG) was convened with stakeholders from palliative care, emergency medicine, critical care, and general internal medicine. The CWG connected with local palliative care teams to ensure a coordinated response, and developed a model to ensure high-quality palliative care provision. Results: Our 3-step scalable model included: (1) consultant model enhanced by virtual care; (2) embedded model; and (3) cohorted end-of-life unit for COVID-19 positive patients. This approach was enabled through tools and resources to ensure specialist palliative care capacity and rapid upskilling of all clinicians to deliver basic palliative care. Enabling tools and resources included a triage tool for in-person versus virtual care, new medication order sets and guidelines to facilitate prescribing for common symptoms, and lead advance care planning and goals of care discussions. A redeployment plan of generalist physicians and psychiatrists was created to ensure seamless provision of serious illness care. Conclusion: This 3-step, scalable approach enables rapid upscaling of palliative care in collaboration with generalist physicians, and may be adapted for future pandemics or natural disasters.

scholarly journals Emergency department visits for children with acute asthma: discharge instructions, parental plans, and follow-through of care—a prospective study

CJEM ◽  
2014 ◽  
Vol 16 (06) ◽  
pp. 467-476 ◽  
Author(s):  
Pat G. Camp ◽  
Seamus P. Norton ◽  
Ran D. Goldman ◽  
Salomeh Shajari ◽  
M. Anne Smith ◽  
...  
Keyword(s):  
Emergency Department ◽  
Acute Care ◽  
Family Doctor ◽  
Emergency Department Visits ◽  
Upper Respiratory Tract ◽  
Asthma Exacerbations ◽  
Initial Care ◽  
Children With Asthma ◽  
Tract Infections ◽  
The Impact

Abstract Objective: Communication between emergency department (ED) staff and parents of children with asthma may play a role in asthma exacerbation management. We investigated the extent to which parents of children with asthma implement recommendations provided by the ED staff. Method: We asked questions on asthma triggers, ED care (including education and discharge recommendations), and asthma management strategies used at home shortly after the ED visit and again at 6 months. Results: A total of 148 children with asthma were recruited. Thirty-two percent of children were not on inhaled corticosteroids prior to their ED visit. Eighty percent of parents identified upper respiratory tract infections (URTIs) as the primary trigger for their child’s asthma. No parent received or implemented any specific asthma strategies to reduce the impact of URTIs; 82% of parents did not receive any printed asthma education materials. Most (66%) parents received verbal instructions on how to manage their child’s future asthma exacerbations. Of those, one-third of families were told to return to the ED. Parents were rarely advised to bring their child to their family doctor in the event of a future exacerbation. At 6 months, parents continued to use the ED services for asthma exacerbations in their children, despite reporting feeling confident in managing their child’s asthma. Conclusion: Improvements are urgently needed in developing strategies to manage pediatric asthma exacerbations related to URTIs, communication with parents at discharge in acute care, and using alternate acute care services for parents who continue to rely on EDs for the initial care of mild asthma exacerbations.

Identification of patients at high risk for preventable emergency department visits and inpatient admissions after starting chemotherapy: Machine learning applied to comprehensive electronic health record data.

2021 ◽  
Vol 39 (15_suppl) ◽  
pp. 1511-1511
Author(s):  
Dylan J. Peterson ◽  
Nicolai P. Ostberg ◽  
Douglas W. Blayney ◽  
James D. Brooks ◽  
Tina Hernandez-Boussard
Keyword(s):  
Machine Learning ◽  
Emergency Department ◽  
Electronic Health Record ◽  
Acute Care ◽  
Cancer Care ◽  
Model Performance ◽  
Emergency Department Visits ◽  
Health Record ◽  
Patients At Risk ◽  
Ed Visits

1511 Background: Acute care use is one of the largest drivers of cancer care costs. OP-35: Admissions and Emergency Department Visits for Patients Receiving Outpatient Chemotherapy is a CMS quality measure that will affect reimbursement based on unplanned inpatient admissions (IP) and emergency department (ED) visits. Targeted measures can reduce preventable acute care use but identifying which patients might benefit remains challenging. Prior predictive models have made use of a limited subset of the data available in the Electronic Health Record (EHR). We hypothesized dense, structured EHR data could be used to train machine learning algorithms to predict risk of preventable ED and IP visits. Methods: Patients treated at Stanford Health Care and affiliated community care sites between 2013 and 2015 who met inclusion criteria for OP-35 were selected from our EHR. Preventable ED or IP visits were identified using OP-35 criteria. Demographic, diagnosis, procedure, medication, laboratory, vital sign, and healthcare utilization data generated prior to chemotherapy treatment were obtained. A random split of 80% of the cohort was used to train a logistic regression with least absolute shrinkage and selection operator regularization (LASSO) model to predict risk for acute care events within the first 180 days of chemotherapy. The remaining 20% were used to measure model performance by the Area Under the Receiver Operator Curve (AUROC). Results: 8,439 patients were included, of whom 35% had one or more preventable event within 180 days of starting chemotherapy. Our LASSO model classified patients at risk for preventable ED or IP visits with an AUROC of 0.783 (95% CI: 0.761-0.806). Model performance was better for identifying risk for IP visits than ED visits. LASSO selected 125 of 760 possible features to use when classifying patients. These included prior acute care visits, cancer stage, race, laboratory values, and a diagnosis of depression. Key features for the model are shown in the table. Conclusions: Machine learning models trained on a large number of routinely collected clinical variables can identify patients at risk for acute care events with promising accuracy. These models have the potential to improve cancer care outcomes, patient experience, and costs by allowing for targeted preventative interventions. Future work will include prospective and external validation in other healthcare systems.[Table: see text]

Another Day, Another GI Bug

2020 ◽  
pp. 111-122
Author(s):  
Pinaki Mukherji ◽  
Dana Libov
Keyword(s):  
Emergency Department ◽  
High Risk ◽  
Inborn Error ◽  
Final Diagnosis ◽  
Emergency Department Visits ◽  
Inborn Error Of Metabolism ◽  
First Case ◽  
Non Accidental Trauma ◽  
Abnormal Radiograph ◽  
Electrolyte Abnormalities

This chapter presents 3 cases of vomiting in children and explores less common diagnoses not to be missed by the astute clinician. The first case of a child with recurrent progressive vomiting has unusual lab abnormalities which leads to the final diagnosis of an inborn error of metabolism. The second case presents a child with several Emergency Department visits for vomiting and a skin finding leads to a final diagnosis of non-accidental trauma. The final case reviews a vomiting child with electrolyte abnormalities and an abnormal radiograph, leading to a diagnosis of malrotation with volvulus. Each case gives the clinician key pearls to distinguish these high risk cases from everyday gastroenteritis.

Mental healthcare and palliative care: barriers

2020 ◽  
pp. bmjspcare-2019-001986 ◽  
Author(s):  
Kelly O'Malley ◽  
Laura Blakley ◽  
Katherine Ramos ◽  
Nicole Torrence ◽  
Zachary Sager
Keyword(s):  
Mental Health ◽  
Palliative Care ◽  
Psychological Symptoms ◽  
Mental Healthcare ◽  
Well Being ◽  
Psychological Needs ◽  
Treatment Team ◽  
Advanced Illness ◽  
Palliative Care Teams ◽  
The Usa

ContextPsychological symptoms are common among palliative care patients with advanced illness, and their effect on quality of life can be as significant as physical illness. The demand to address these issues in palliative care is evident, yet barriers exist to adequately meet patients’ psychological needs.ObjectivesThis article provides an overview of mental health issues encountered in palliative care, highlights the ways psychologists and psychiatrists care for these issues, describes current approaches to mental health services in palliative care, and reviews barriers and facilitators to psychology and psychiatry services in palliative care, along with recommendations to overcome barriers.ResultsPatients in palliative care can present with specific mental health concerns that may exceed palliative care teams’ available resources. Palliative care teams in the USA typically do not include psychologists or psychiatrists, but in palliative care teams where psychologists and psychiatrists are core members of the treatment team, patient well-being is improved.ConclusionPsychologists and psychiatrists can help meet the complex mental health needs of palliative care patients, reduce demands on treatment teams to meet these needs and are interested in doing so; however, barriers to providing this care exist. The focus on integrated care teams, changing attitudes about mental health, and increasing interest and training opportunities for psychologists and psychiatrists to be involved in palliative care, may help facilitate the integration of psychology and psychiatry into palliative care teams.

Health care coach support in reducing acute care use in patients with cancer.

2020 ◽  
Vol 38 (29_suppl) ◽  
pp. 4-4
Author(s):  
Manali I. Patel ◽  
Kim Smith ◽  
Etsegenet Sisay ◽  
David J. Park
Keyword(s):  
Palliative Care ◽  
Acute Care ◽  
Cancer Care ◽  
Emergency Department Visits ◽  
Control Group ◽  
Goals Of Care ◽  
Risk Of Death ◽  
Community Oncology ◽  
Hospice Use

4 Background: Lay health workers (LHWs) who are trained to proactively discuss goals of care and assess patient symptoms have improved value-based cancer care among Veterans and a Medicare Advantage population. Little data exists regarding the effect of integrating LHWs into community oncology care among commercially insured populations. In this study, we implemented an LHW intervention to assist with goals of care and symptom management in collaboration with a private community oncology practice among patients with advanced cancer. This randomized controlled trial evaluates the effect of the intervention on acute care use and secondarily on goals of care documentation and patient satisfaction. Methods: Newly diagnosed patients with advanced stages of solid and hematologic malignancies were randomized from 8/11/2016 through 6/5/2019 into the intervention and control groups. All patients were followed for 12 months or death, whichever was first. Patients reported satisfaction with care using the Consumer Assessment of Healthcare Providers and Systems survey at time of enrollment and 9 months follow-up. We compared risk of death using Cox Models and compared rates of acute care, palliative care and hospice use using generalized models adjusted for length of follow-up. Results: A total of 104 patients were randomized with 52 in the intervention and 52 in the control. In both groups, the mean age was 67 years; 70% were non-Hispanic white, 25% Asian Pacific Islander, 1% Native Hawaiian, 1% American Indian/Alaskan Native, 3% multiple races/ethnicities. There were no differences in cancer diagnoses or stages. There were no differences in rates of survival between the two groups. Intervention patients as compared to the control had lower mean emergency department visits (0.80 +/- 0.17 versus 1.9 +/- 0.46, p = 0.02) and hospitalizations (0.67 +/- 0.19 versus 1.49 +/- 0.37, p = 0.04), greater rates of goals of care documentation (92% versus 33% p = 0.002) and no differences in palliative care (88% versus 77% p = 0.16) or hospice use (27% versus 21% p = 0.45). At 9 months follow-up as compared to baseline, patients in the intervention experienced greater improvements in satisfaction with their care (difference-in-difference: 0.41, 95% CI 0.22-0.60, p < 0.001). Conclusions: An LHW intervention significantly reduced acute care use and improved patient experiences with cancer care as compared to a control group. This intervention may be a solution to improve care delivery and experiences for patients after a diagnosis of cancer in community oncology settings. Clinical trial information: NCT03154190 .

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