Impact of integrated palliative care model on end-of-life (EOL) quality metrics for patients with kidney cancer (RCC) and melanoma (M).

2015 ◽  
Vol 33 (29_suppl) ◽  
pp. 137-137
Author(s):  
Jessica A. Lynch ◽  
Susan DeSanto-Madeya ◽  
Jessica A. Zerillo ◽  
Matt Gregas ◽  
David F. McDermott ◽  
...  
Keyword(s):  
Palliative Care ◽  
End Of Life ◽  
Symptom Assessment ◽  
Integrated Model ◽  
Optimal Timing ◽  
Early Palliative Care ◽  
Location Of Death ◽  
Edmonton Symptom Assessment Scale ◽  
Oncology Practice ◽  
The Impact

137 Background: Early palliative care (PC) improves quality of life (QOL) and enhances end-of-life (EOL) care, but the optimal timing and most effective model for integrating PC into oncologic care is uncertain. To understand the impact of an integrated model with PC providers embedded with oncologists vs. usual care (UC) with referral at the discretion of the same oncologists, we examined the timing and delivery of PC and Quality Oncology Practice Initiative (QPOI) EOL metrics among patients with RCC and M in a single clinic. We hypothesized that integrated PC would result in more referrals, earlier contact with PC and better QOPI EOL metrics compared with UC. Methods: In a retrospective cohort study of patients with RCC and M in the Beth Israel Deaconess Biologics Clinic who expired between 10/1/12 and 12/31/14, we compared patients seen 2 days/week, when referral to PC was discretionary, with a third day when PC providers shared the clinic for real-time consultations. Patients were identified as meeting PC eligibility if they had recurrent, metastatic disease and were on active treatment or had a symptom severity of 7+ on Edmonton Symptom Assessment Scale (ESAS). Two oncologists saw all patients, regardless of day. Results: Seventy-six patients expired, 19 in the Integrated PC model and 57 with UC. Patients were similar with respect to diagnosis and demographics except for smoking. The integrated model substantially improved timing and location of PC. In the integrated PC model, 85% were seen by PC compared with 45% in UC (P = 0.002). All patients in the integrated model began PC as an outpatient compared with 36% in UC (P < 0.001). The mean number of days from first PC contact to death was 28 (SD = 54) for UC and 118 (SD = 120) with integrated PC (P < 0.001). The location of death did not differ significantly between models, occurring outside the hospital with hospice among 71% of patients in the integrated model and 53% in UC (P = 0.25). Results were similar in relative risk models adjusted for smoking. Conclusions: A practice model that integrated PC with oncologic care was associated with more PC referrals, earlier contact, and a nonsignificant trend toward fewer deaths in hospital and ICU.

scholarly journals Improving End-of-Life Care: Palliative Care Embedded in an Oncology Clinic Specializing in Targeted and Immune-Based Therapies

2017 ◽  
Vol 13 (9) ◽  
pp. e729-e737 ◽  
Author(s):  
David J. Einstein ◽  
Susan DeSanto-Madeya ◽  
Matthew Gregas ◽  
Jessica Lynch ◽  
David F. McDermott ◽  
...  
Keyword(s):  
Palliative Care ◽  
Usual Care ◽  
End Of Life ◽  
Odds Ratio ◽  
Care Clinic ◽  
Usual Practice ◽  
Embedded Model ◽  
Enrollment Rates ◽  
Oncology Practice ◽  
The Impact

Purpose: Patients with advanced cancer benefit from early involvement of palliative care. The ideal method of palliative care integration remains to be determined, as does its effectiveness for patients treated with targeted and immune-based therapies. Materials and Methods: We studied the impact of an embedded palliative care team that saw patients in an academic oncology clinic specializing in targeted and immune-based therapies. Patients seen on a specific day accessed the embedded model, on the basis of automatic criteria; patients seen other days could be referred to a separate palliative care clinic (usual care). We abstracted data from the medical records of 114 patients who died during the 3 years after this model’s implementation. Results: Compared with usual care (n = 88), patients with access to the embedded model (n = 26) encountered palliative care as outpatients more often ( P = .003) and earlier (mean, 231 v 109 days before death; P < .001). Hospice enrollment rates were similar ( P = .303), but duration was doubled (mean, 57 v 25 days; P = .006), and enrollment > 7 days before death—a core Quality Oncology Practice Initiative metric—was higher in the embedded model (odds ratio, 5.60; P = .034). Place of death ( P = .505) and end-of-life chemotherapy (odds ratio, 0.361; P = .204) did not differ between the two arms. Conclusion: A model of embedded and automatically triggered palliative care among patients treated exclusively with targeted and immune-based therapies was associated with significant improvements in use and timing of palliative care and hospice, compared with usual practice.

The influence of a cachexia clinic on palliative care integration in oncology.

2017 ◽  
Vol 35 (31_suppl) ◽  
pp. 124-124
Author(s):  
Diane Portman ◽  
Sarah Thirlwell ◽  
Kristine A. Donovan
Keyword(s):  
Palliative Care ◽  
Weight Loss ◽  
Advanced Cancer ◽  
Symptom Burden ◽  
Symptom Assessment ◽  
Cancer Center ◽  
Edmonton Symptom Assessment Scale ◽  
Symptom Assessment Scale ◽  
The Impact

124 Background: Appetite and weight loss are common in patients with advanced cancer and specialized cachexia clinics have been established to address these symptoms. Given the association between anorexia/cachexia and other adverse symptoms, these patients may also benefit from specialty level palliative care (PC). However, referral to outpatient specialty level PC is often delayed or does not occur. We sought to examine the prevalence of other factors associated with appetite and weight loss in patients with advanced cancer and the impact of a specialized cachexia clinic on identification and treatment of other PC needs. Methods: The records of patients referred by their Oncologist to the cachexia clinic of a cancer center from August 2016 to June 2017 were reviewed retrospectively. Subjects who had been referred to PC by their Oncologist were excluded. Patients had been assessed for symptom burden using the Edmonton Symptom Assessment Scale (ESAS-r). Patients identified with PC needs had been referred to the PC clinic for follow-up within 30 days after cachexia clinic consultation. Results: Thirty subjects were evaluated in the cachexia clinic (average age 68 years; 63% female). The predominant diagnosis was lung cancer (70%). An average of 6 symptoms per patient were in the moderate to severe range on ESAS, excluding appetite. Depression, fatigue and pain were most common. The average cachexia clinic total ESAS score was 51.61. Only 17% of patients had completed advance directives. Ninety-three % of patients were referred to PC and 68% were seen. The average number of PC visits was 2.79. Within the PC clinic, advance directive completion increased to 37%, goals of care discussion occurred with 50% and 17% received hospice referrals. At the most recent follow-up in the PC clinic, the average total ESAS score had decreased by 11.44 (22%) and all ESAS item scores were improved on average. Conclusions: The cachexia clinic proved a useful means to identify other PC needs and achieve effective PC referrals. We suggest this is proof of concept that specialty clinics can be a meaningful way to achieve an earlier entry point to comprehensive PC in patients who were not previously referred by their Oncologists.

Using a statewide collaborative approach to improve primary palliative care performance.

2013 ◽  
Vol 31 (31_suppl) ◽  
pp. 53-53
Author(s):  
Katie Abstoss ◽  
Tallat Mahmood ◽  
Claudia Jane Martin ◽  
J. Cameron Muir ◽  
Jane Alcyne Severson ◽  
...  
Keyword(s):  
Palliative Care ◽  
Statistical Significance ◽  
Symptom Assessment ◽  
Measurement Tool ◽  
Improvement Rate ◽  
Care Services ◽  
Edmonton Symptom Assessment Scale ◽  
Palliative Care Services ◽  
Oncology Practice ◽  
Care Performance

53 Background: The Michigan Oncology Quality Consortium (MOQC) is a statewide collaborative of oncology practices. Using the Quality Oncology Practice Initiative (QOPI) measurement tool, MOQC identified a gap in the provision of palliative care. We designed and tested interventions to enhance the capacity and capabilities of the oncologist to deliver primary palliative care earlier in a patient’s course. Methods: MOQC created a process to assist oncology care teams in providing primary palliative care services using the Edmonton Symptom Assessment Scale tool. 11 practices participated in two pilots over 18 months. During and after these pilots, we disseminated tools for improvement, including customized palliative care dashboards, to the entire consortium. Pilot teams also shared their successes, insights, and best practices during semiannual live consortium meetings. Results: Shown are palliative care-focused QOPI results, comparing baseline (Fall 2011, F11) and post project (Spring 2013, S13) for all MOQC practices compared with all participating QOPI practices, using a paired t-test. MOQC sites outperformed the QOPI national average on multiple palliative care measures. Furthermore, the MOQC improvement rate since the project initiation was greater than that of national. Although clinically important, the measures did not reach standard statistical significance. Conclusions: Running successive pilot projects improved primary palliative care performance of the teams involved; additionally, this momentum and gain in knowledge facilitated dissemination of innovation and measurable improvement in all members of a statewide consortium. [Table: see text]

scholarly journals QOLP-18. A TIME-BASED MODEL OF EARLY PALLIATIVE CARE INTERVENTION IN PATIENTS WITH NEWLY DIAGNOSED GLIOBLASTOMA, A SINGLE INSTITUTION FEASIBILITY STUDY

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi201-vi201 ◽  
Author(s):  
Margaret Johnson ◽  
Luis Ramirez ◽  
James Herndon ◽  
Woody Massey ◽  
Eric Lipp ◽  
...  
Keyword(s):  
Palliative Care ◽  
Healthcare Utilization ◽  
Functional Assessment ◽  
Symptom Assessment ◽  
Assessment System ◽  
Early Palliative Care ◽  
Chronic Illness Therapy ◽  
Before And After ◽  
The Impact ◽  
Historical Controls

Abstract OBJECTIVE There is no validated model for delivering palliative care (PC) in the glioblastoma (GBM) population. The primary objectives were to assess the feasibility and determine the acceptability of a time-based model of integrated specialty PC to patients and providers. Secondary objectives were to estimate the impact on healthcare utilization and quality of life (QoL) compared to historical controls. METHODS We consented and referred patients to PC at their initial Neuro-Oncology consultation between 4/2018 and 5/2019. We conducted QoL assessments (NCCN Distress Tool; Functional Assessment of Cancer Therapy-Brain (FACT-BR); Functional Assessment of Chronic Illness Therapy-Fatigue (FACIT-F); Epworth Sleepiness Scale (ESS)) at (1) baseline (2) immediately after chemoradiation, and (3) 6 months following chemoradiation. Ongoing PC follow-up was at the discretion of the PC provider. We administered the Edmonton Symptom Assessment System (ESAS) before and after PC visits. We measured patient and referring provider satisfaction using FAMCARE-16 and a PC departmental survey, respectively. RESULTS We did not meet our goal enrollment of 50 patients. 32 were offered participation, 12 consented and 8 attended at least one PC visit. The mean number of PC visits was 1.6. Mean age was 62 (42–79). 75% had a KPS ≥80. Of those that did not complete the study, 2 died and 5 either withdrew consent or declined further visits. At baseline, 91.7 % had a NCCN distress score ≥4. Patients were overall satisfied with the intervention. CONCLUSION Introduction of specialty PC at the time of GBM diagnosis is challenging. Participants reported their experience as overall positive. Results from referring providers are pending. Due to low-enrollment we did not pursue further statistical comparisons regarding healthcare utilization compared to historical controls.

The Impact of Integrated Multidisciplinary Palliative Care Program on Symptoms in Patients at the Palliative Care Ward—An Audit and a Protocol of Prospective Controlled Investigation

2017 ◽  
Vol 32 (3-4) ◽  
pp. 87-88 ◽  
Author(s):  
Andreas Jülich ◽  
Thomas Spreu ◽  
Britta Buchhold ◽  
Taras Usichenko
Keyword(s):  
Palliative Care ◽  
Controlled Trial ◽  
Symptom Control ◽  
Sample Size Calculation ◽  
Care Program ◽  
Symptom Assessment ◽  
University Hospital ◽  
Retrospective Audit ◽  
Edmonton Symptom Assessment Scale ◽  
The Impact

An integrated multidisciplinary palliative care (IMPC) program is a promising tool to improve symptom control in patients at the end of life. The aim was to study the feasibility of the IMPC program in patients at the palliative care (PC) ward. A retrospective audit, using the extended Edmonton Symptom Assessment Scale (ESAS), was conducted on the PC ward of the university hospital. Consecutive patients who were admitted for the IMPC program during 1 year were considered. One hundred forty-eight cases (93% with underlying cancer) were analyzed. The intensity of pain levels, nausea, vomiting, shortness of breath, and sleep disorders decreased at least by 50% ( P < .0001) during the 13 (median) days of IMPC. Integrated multidisciplinary PC program was associated with symptom improvements in patients at the PC ward. The information generated supports sample size calculation for a prospective controlled trial.

Integrating palliative care into care of patients with kidney cancer and melanoma.

2014 ◽  
Vol 32 (31_suppl) ◽  
pp. 56-56 ◽  
Author(s):  
Mary K. Buss ◽  
Susan DeSanto-Madeya ◽  
Jessica Lynch ◽  
Jessica A. Zerillo ◽  
David F. McDermott
Keyword(s):  
Palliative Care ◽  
Kidney Cancer ◽  
Symptom Management ◽  
Psychosocial Support ◽  
Medical Center ◽  
Optimal Timing ◽  
Spiritual Support ◽  
Curative Intent ◽  
Early Palliative Care ◽  
Edmonton Symptom Assessment Scale

56 Background: Early palliative care (PC) has been shown to improve quality of life (QOL), enhance quality end-of-life (EOL) care, and reduce costs, yet many cancer centers lack resources to provide outpatient palliative care services. Data is needed to identify the optimal timing and most effective and efficient model for integrating PC into the care of cancer patients. In order to understand what components of PC have the greatest impact on patients, we examined the acceptability of early PC among patients with kidney cancer (RCC) and melanoma (M) and describe the content of PC visits. Methods: In July 2013, the outpatient PC team at Beth Israel Deaconess Medical Center, including physician (MD), social worker (SW) and chaplain (chap) were invited to see patients within a clinic that specializes in seeing patients with advanced RCC and M. All patients completed data on symptom burden using the Edmonton Symptom Assessment Scale, measures of QOL and degree of psycho-social and spiritual support. Referral to PC was based on these metrics and physician discretion. Results: Of the 21 patients seen by PC, 57% had RCC; 76% male; 86% White; 57% married. Mean age was 62 (range: 36-87). At the 1st PC visit: All had locally adv/metastatic disease; 48% were being treated with curative intent; 29% had not yet started treatment; 57% rated pain 0 on 0-10 scale (range: 0-9). First PC visit content: 76% psychosocial support (including building rapport); 67% symptom management; 33% included advance care planning (ACP) and decision-making support. Ninety-one percent were seen >1 by PC; 19% seen by SW or chap; median PC visits: 3. Eighty-one percent completed health care proxy. Additional data on patient outcomes will be presented. Conclusions: Nearly half of patients seen by PC were being treated with curative intent, suggesting acceptability of early PC integration in patients with RCC and M. Symptom management and psychosocial support dominated the early PC visits.

Utilization of an electronic medical record trigger to promote palliative care consultation in ambulatory oncology.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18201-e18201
Author(s):  
Sherri L. Rauenzahn ◽  
Susanne Schmidt ◽  
Nazneen Ali ◽  
Laura LaNiel Tenner
Keyword(s):  
Palliative Care ◽  
Supportive Care ◽  
Medical Record ◽  
Electronic Medical Record ◽  
Symptom Burden ◽  
Symptom Assessment ◽  
Cost Of Care ◽  
Ambulatory Oncology ◽  
Edmonton Symptom Assessment Scale ◽  
The Impact

e18201 Background: Research insupportive care demonstrates improvements in overall survival, quality of life, symptom management, and reductions in the cost of care. Despite the American Society of Clinical Oncology recommendation for early concurrent supportive care in patients with advanced cancer and high symptom burden, integrating supportive services is challenging. Our aims were to 1) implement an electronic medical record (EMR) provider alert of high symptom burden based on Edmonton Symptom Assessment Scale (ESAS) criteria and 2) determine the impact an alert has on supportive service referrals. Methods: ESAS scores were implemented in medical ambulatory oncology clinics to quantitatively assess symptom burden. An EMR alert was programmed for a total ESAS score > 30 and any single response of ≥9 to capture approximately 15% of our high symptom burden patient population. The provider could elect to accept the alert placing an order for palliative consultation or decline the prompt. Referral rates and symptom assessment scores were followed as metrics for EMR alert efficiency. Results: Over 10 months, 9,710 patient visits used the ESAS system resulting in 7,707 fully completed ESAS scores (79.4% completion rate). There were 78 total consults to palliative care, a referral rate of less than 1% of the population, which was unchanged from prior to trigger implementation. Of the total completed ESAS forms, the trigger alerted 686 times (8.9% of patient visits) with only 55 of those triggers leading to a supportive care referral (8.0%). Conclusions: This project highlights the challenges of an EMR based alert system and the need for continued efforts to improve supportive care referrals through provider education and tool implementation. [Table: see text]

Impact of augmented intelligence (AI) on utilization of palliative care (PC) services in oncology.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 12015-12015
Author(s):  
Ajeet Gajra ◽  
Marjorie Zettler ◽  
Jonathan Kish ◽  
Kelly Miller ◽  
John Frownfelter ◽  
...  
Keyword(s):  
Palliative Care ◽  
End Of Life ◽  
Machine Learning Techniques ◽  
Care Plan ◽  
Patient Specific ◽  
The Mean ◽  
Poor Outcomes ◽  
Oncology Practice ◽  
Practice Methods ◽  
The Impact

12015 Background: Timely integration of palliative care in the management of patients with advanced cancer is a quality benchmark in oncology. However, PC is often underutilized as evidenced by delays in identification of appropriate patients, in referrals to a PC service, and in enrollment to hospice. Jvion has developed a prescriptive analytics solution, the Machine, which combines AI algorithms with machine learning techniques and applies them to clinical and exogenous datasets to identify patients with a propensity for poor outcomes. The Machine was applied to risk for patients’ mortality within next 30 days, and recommended patient-specific, dynamic, and actionable insights. Use of the Machine requires no additional documentation within the electronic health record (EHR) and the insights generated can be integrated back in to any EHR to help inform the care plan. Herein, we report the results of a study evaluating the impact of AI-driven insights on PC utilization at a large community oncology practice. Methods: All patients were scored weekly using the Machine PC vector. The Machine risk stratified the patients and generated recommendations for the provider to consider as they developed a care plan. Patients identified as “at risk” by the Machine were assessed for a supportive care visit (PC referral) and then were referred as deemed clinically appropriate. The average monthly rates of PC consults and hospice referrals were calculated 5 months prior to and for 17 months after the launch of the Machine in the practice. Results: The oncology practice has 21 providers managing an average of 4329 unique patients per month (PPM). The mean rate of PC consults increased from 17.3 to 29.1 per 1000 PPM pre and post Machine deployment respectively (+168%). The mean monthly rate of hospice referrals increased by 8-fold from 0.2 to 1.6 per 1000 PPM pre and post deployment respectively. Eliminating the first 6 months of Machine deployment to account for user learning curve, the mean rates of monthly PC consults nearly doubled over baseline to 33.0, and hospice referrals rose 12-fold to 2.4 per 1000 patients in months 7-17 post Machine deployment. Conclusions: This oncology practice found deployment of this novel AI solution to be feasible and effective at generating actionable insights. These AI driven insights could be incorporated into workflow and improved the decision-making for whether and when a patient should be referred to PC and/or hospice services for end of life care. Further study is needed to confirm the value of AI for management of cancer patients at end of life.

Early palliative care interventions in patients with hematologic malignancies prior to hematopoietic cell transplantation.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e21634-e21634 ◽  
Author(s):  
M.Ahsan Alamgir ◽  
Sijin Wen ◽  
Michael D. Craig ◽  
Sandra L. Pedraza
Keyword(s):  
Palliative Care ◽  
Supportive Care ◽  
Cell Transplantation ◽  
Sleep Problems ◽  
Well Being ◽  
Categorical Variables ◽  
Care Clinic ◽  
Early Palliative Care ◽  
Edmonton Symptom Assessment Scale ◽  
The Impact

e21634 Background: Early palliative care (EPC) interventions have been endorsed by multiple medical societies, mostly for solid tumors but not for hematological malignancies. Patients undergoing hematopoietic stem cell transplantation (HSCT) suffer significant physical and emotional distress affecting negatively their quality of life (QOL). They also receive more aggressive end-of-life interventions than other cancer patients. Few studies have shown the impact of EPC in the pre-transplant phase on post transplant morbidity and mortality. Methods: 53 patients undergoing HSCT were evaluated on the supportive care clinic for symptom and needs assessment using the Edmonton symptom assessment scale (ESAS) to evaluate symptom burden prior to transplant. Consecutive palliative care visits were offered to patients. We also evaluated whether the supportive care clinic (SCC) visits made a difference on hospitalization rate and mortality comparing this group with 108 patient who did not undergo evaluation. Kaplan-Meier method and log-rank test were used in the survival analysis and Fisher’s exact test was used in the data analysis for categorical variables. Results: The most common symptoms reported by patients included: fatigue (4.4), sleep problems (3.7), pain (2.8), anxiety (2.8), well-being (2.7), and drowsiness (2.3). 26% (14) of the patients were followed in the SCC at 3 months. The most common symptoms at that time included fatigue (5.1), pain (4), drowsiness (3.6), sleep problems (3.1), well-being (2.9), and appetite (2.4). Overall mortality for the whole group was 24%. 28% for the palliative care group and 21% for the control group. Odds Ratio for mortality at 3 and 6 months were not significantly different between groups. Differences in hospital admissions were also not statistically significant. Conclusions: EPC in HSCT patients is feasible and may help with symptom detection and control. No effect on mortality or hospital admission rates was found on this study on patients referred for EPC interventions. Prospective studies are needed to clearly define the role of EPC in HSCT patients.

Improving end-of-life care: Palliative care embedded in an outpatient oncology clinic.

2017 ◽  
Vol 35 (8_suppl) ◽  
pp. 77-77
Author(s):  
David Johnson Einstein ◽  
Susan DeSanto-Madeya ◽  
Matt Gregas ◽  
Jessica A. Lynch ◽  
David F. McDermott ◽  
...  
Keyword(s):  
Palliative Care ◽  
Usual Care ◽  
End Of Life ◽  
Care Clinic ◽  
Usual Practice ◽  
Referral Criteria ◽  
Palliative Care Teams ◽  
Embedded Model ◽  
Oncology Practice ◽  
The Impact

77 Background: Patients with advanced cancer benefit from early involvement of palliative care. Nonetheless, the ideal method of palliative care integration remains to be determined. Prior studies proposed automatic referral criteria and embedding palliative care teams within specialty clinics. Methods: We studied the impact of an embedded palliative care team that saw patients in an academic oncology clinic based on automatic referral criteria. Patients seen in this clinic on a specific day had access to the “embedded” model, whereas patients seen on two other days could access a separate palliative care clinic upon oncologist referral (usual care). We abstracted data from the medical records of 118 patients who were cared for in this oncology clinic and died during the 3 years following implementation of the embedded model. Results: Compared with those with access to usual care (n = 88), patients with access to the embedded model (n = 30) encountered palliative care as outpatients more often (p < 0.001) and twice as long before death (mean 223 versus 106 days, p = 0.001). Hospice enrollment rates were similar (p = 0.717) but duration was twice as long (mean 53.5 versus 25.3 days, p = 0.03), and enrollment greater than 7 days before death—a core Quality Oncology Practice Initiative metric—was significantly higher in the embedded model (OR 5.60, p = 0.034). Place of death (p = 0.505) and end-of-life chemotherapy (OR 0.361, p = 0.204) did not differ significantly. Conclusions: A model of embedded palliative care with automatic referral criteria, compared with usual practice, was associated with significant improvements in utilization and timing of palliative care and hospice.

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