scholarly journals Potentially Avoidable Hospital Readmissions in Patients With Advanced Cancer

2019 ◽  
Vol 15 (5) ◽  
pp. e420-e427 ◽  
Author(s):  
P. Connor Johnson ◽  
Yian Xiao ◽  
Risa L. Wong ◽  
Sara D'Arpino ◽  
Samantha M.C. Moran ◽  
...  
Keyword(s):  
Advanced Cancer ◽  
Odds Ratio ◽  
Hospital Readmissions ◽  
Symptom Burden ◽  
Symptom Assessment ◽  
Physical Symptom ◽  
Assessment System ◽  
Primary Reason ◽  
Nonlinear Mixed Effects Models ◽  
Patient Reported

PURPOSE: Patients with cancer often prefer to avoid time in the hospital; however, data are lacking on the prevalence and predictors of potentially avoidable readmissions (PARs) among those with advanced cancer. METHODS: We enrolled patients with advanced cancer from September 2, 2014, to November 21, 2014, who had an unplanned hospitalization and assessed their patient-reported symptom burden (Edmonton Symptom Assessment System) at the time of admission. For 1 year after enrollment, we reviewed patients’ health records to determine the primary reason for every hospital readmission and we classified readmissions as PARs using adapted Graham’s criteria. We examined predictors of PARs using nonlinear mixed-effects models with binomial distribution. RESULTS: We enrolled 200 (86.2%) of 232 patients who were approached. For these 200 patients, we reviewed 277 total hospital readmissions and identified 108 (39.0%) of these as PARs. The most common reasons for PARs were premature discharge from a prior hospitalization (30.6%) and failure of timely follow-up (28.7%). PAR hospitalizations were more likely than non-PAR hospitalizations to experience symptoms as the primary reason for admission (28.7% v 13.0%; P = .001). We found that married patients were less likely to experience PARs (odds ratio, 0.30; 95% CI, 0.15 to 0.57; P < .001) and that those with a higher physical symptom burden were more likely to experience PARs (odds ratio, 1.03; 95% CI, 1.01 to 1.05; P = .012). CONCLUSION: We observed that a substantial proportion of hospital readmissions are potentially avoidable and found that patients’ symptom burdens predict PARs. These findings underscore the need to assess and address the symptom burden of hospitalized patients with advanced cancer in this highly symptomatic population.

Potentially avoidable hospitalizations in patients with advanced cancer.

2017 ◽  
Vol 35 (15_suppl) ◽  
pp. e18275-e18275 ◽  
Author(s):  
Connor Johnson ◽  
Yian Xiao ◽  
Areej El-Jawahri ◽  
Risa Wong ◽  
Sara D'Arpino ◽  
...  
Keyword(s):  
Logistic Regression ◽  
Advanced Cancer ◽  
Hospital Admissions ◽  
Symptom Burden ◽  
Symptom Assessment ◽  
Physical Symptom ◽  
Assessment System ◽  
Data Repository ◽  
Avoidable Hospitalizations

e18275 Background: Cancer patients and their clinicians often wish to avoid preventable hospital admissions, but efforts to understand the predictors of avoidable hospitalizations are lacking. We sought to examine reasons for hospital admissions in patients with advanced cancer, identify potentially avoidable hospitalizations (PAH), and explore predictors of PAH. Methods: We prospectively enrolled hospitalized patients with advanced cancer from 9/2014 - 11/2014 as part of a longitudinal data repository to define symptom burden in this population. Upon admission, we assessed patients’ symptom burden (Edmonton Symptom Assessment System [ESAS]; scored 0-10). We created a summated ESAS physical symptom variable. We used consensus-driven medical record review to identify the primary reason for each hospital admission and categorize it as PAH or not based on of an adaptation of Graham’s criteria for PAH. We used mixed multivariable logistic regression analyses to identify predictors of PAH. Results: We assessed 477 hospital admissions in 200 consecutively admitted patients (mean age = 64.6; 47% female; 67% married). Over half of admissions came through the emergency department (56%). The most common reasons for admissions were fever/infection (30%), symptoms (26%), and planned admission for chemotherapy or procedure (10%). We identified 149 (31%) as PAH. Among these PAH, 45 (30%) were readmissions due to failure of timely outpatient follow-up (within 7 days of discharge) and 44 (30%) were due to premature discharge from prior hospitalization. In a mixed logistic regression model, being married (odds ratio [OR] 0.48 [0.28-0.81]; p < 0.01) was associated with lower likelihood of PAH, while higher physical symptom burden (OR 1.02 [1.00-1.04]; p = 0.04) was associated with greater likelihood of PAH. Conclusions: We identified that a substantial proportion of hospitalizations in patients with advanced cancer are potentially avoidable, often related to failure of timely outpatient follow-up and premature hospital discharge. Our results demonstrate that patients’ symptom burden predicts PAH, thus underscoring the need to address patients’ symptoms in order to reduce preventable hospital admissions.

scholarly journals Prescreening of Patient-reported Symptoms using the Edmonton Symptom Assessment System (ESAS) in Outpatient Palliative Cancer Care

2019 ◽  
Author(s):  
Garden Lee ◽  
Han Sang Kim ◽  
Si Won Lee ◽  
Eun Hwa Kim ◽  
Bori Lee ◽  
...  
Keyword(s):  
Palliative Care ◽  
Cancer Care ◽  
Severe Symptom ◽  
Symptom Burden ◽  
Symptom Assessment ◽  
Assessment System ◽  
Advanced Cancer Patients ◽  
Edmonton Symptom Assessment System ◽  
Patient Reported

Abstract Background: Although early palliative care is associated with a better quality of life and improved outcomes in end-of-life cancer care, the criteria of palliative care referral are still elusive. Methods: We collected patient-reported symptoms using the Edmonton Symptom Assessment System (ESAS) at the baseline, first, and second follow-up visit. The ESAS evaluates ten symptoms: pain, fatigue, nausea, depression, anxiety, drowsiness, dyspnea, sleep disorder, appetite, and wellbeing. A total of 71 patients were evaluable, with a median age of 65 years, male (62%), and the Eastern Cooperative Oncology Group (ECOG) performance status distribution of 1/2/3 (28%/39%/33%), respectively. Results: Twenty (28%) patients had moderate/severe symptom burden with the mean ESAS ≥5. Interestingly, most of the patients with moderate/severe symptom burdens (ESAS ≥5) had globally elevated symptom expression. While the mean ESAS score was maintained in patients with mild symptom burden (ESAS<5; 2.7 at the baseline; 3.4 at the first follow-up; 3.0 at the second follow-up; P =0.117), there was significant symptom improvement in patients with moderate/severe symptom burden (ESAS≥5; 6.5 at the baseline; 4.5 at the first follow-up; 3.6 at the second follow-up; P <0.001). Conclusions: Advanced cancer patients with ESAS ≥5 may benefit from outpatient palliative cancer care. Prescreening of patient-reported symptoms using ESAS can be useful for identifying unmet palliative care needs in advanced cancer patients.

scholarly journals Implementing a Patient-Reported Outcome Measure for Hemodialysis Patients in Routine Clinical Care

2020 ◽  
Vol 15 (9) ◽  
pp. 1299-1309 ◽  
Author(s):  
Jenna M. Evans ◽  
Alysha Glazer ◽  
Rebecca Lum ◽  
Esti Heale ◽  
Marnie MacKinnon ◽  
...  
Keyword(s):  
Outcome Measure ◽  
Symptom Burden ◽  
Symptom Assessment ◽  
Patient Reported Outcome ◽  
Assessment System ◽  
Edmonton Symptom Assessment System ◽  
Patient Reported Outcome Measure ◽  
Symptom Screening ◽  
Patient Reported ◽  
Patient Provider Communication

Background and objectivesThe Edmonton Symptom Assessment System Revised: Renal is a patient-reported outcome measure used to assess physical and psychosocial symptom burden in patients treated with maintenance dialysis. Studies of patient-reported outcome measures suggest the need for deeper understanding of how to optimize their implementation and use. This study examines patient and provider perspectives of the implementation process and the influence of the Edmonton Symptom Assessment System Revised: Renal on symptom management, patient-provider communication, and interdisciplinary communication.Design, setting, participants, & measurements Eight in-facility hemodialysis programs in Ontario, Canada, assessed patients using the Edmonton Symptom Assessment System Revised: Renal every 4–6 weeks for 1 year. Screening and completion rates were tracked, and pre- and postimplementation surveys and midimplementation interviews were conducted with patients and providers. A chart audit was conducted 12 months postimplementation.ResultsIn total, 1459 patients completed the Edmonton Symptom Assessment System Revised: Renal; 58% of eligible patients completed the preimplementation survey (n=718), and 56% of patients who completed the Edmonton Symptom Assessment System Revised: Renal at least once completed the postimplementation survey (n=569). Provider survey response rates were 71% (n=514) and 54% (n=319), respectively. Nine patients/caregivers from three sites and 48 providers from all sites participated in interviews. A total of 1207 charts were audited. Seven of eight sites had mean screening rates over 80%, suggesting that routine use of the Edmonton Symptom Assessment System Revised: Renal in clinical practice is feasible. However, the multiple data sources painted an inconsistent picture of the value and effect of the Edmonton Symptom Assessment System Revised: Renal. The Edmonton Symptom Assessment System Revised: Renal standardized symptom screening processes across providers and sites; improved patient and provider symptom awareness, particularly for psychosocial symptoms; and empowered patients to raise issues with providers. Yet, there was little, if any, statistically significant improvement in the metrics used to assess symptom management, patient-provider communication, and interdisciplinary communication.ConclusionsThe Edmonton Symptom Assessment System Revised: Renal patient-reported outcome measure may be useful to standardize symptom screening, enhance awareness of psychosocial symptoms among patients and providers, and empower patients rather than to reduce symptom burden.

Symptom burden and characteristics of patients who die in the acute palliative care unit of a tertiary cancer center.

2019 ◽  
Vol 37 (31_suppl) ◽  
pp. 53-53
Author(s):  
YuJung Kim ◽  
Grace S. Ahn ◽  
Hak Ro Kim ◽  
Beodeul Kang ◽  
Sung Soun Hur ◽  
...  
Keyword(s):  
Palliative Care ◽  
Cancer Patients ◽  
Advanced Cancer ◽  
Tertiary Care ◽  
Symptom Burden ◽  
Symptom Assessment ◽  
Assessment System ◽  
Cancer Center ◽  
Advanced Cancer Patients ◽  
Tertiary Cancer Center

53 Background: Acute Palliative Care Units (ACPUs) are novel inpatient programs in tertiary care centers that provide aggressive symptom management and assist transition to hospice. However, patients often die in the APCU before successfully transferring to hospice. The aim of this study was to evaluate the symptom burden and characteristics of advanced cancer patients who die in the APCU. Methods: We retrospectively reviewed the medical records of all advanced cancer patients admitted to the APCU between April, 2015 and March, 2016 at a tertiary cancer center in Korea. Basic characteristics and symptom burden assessed by the Edmonton Symptom Assessment System (ESAS) were obtained from consultation upon APCU admission. Statistical analyses were conducted to compare patients who died in the APCU with those who were discharged alive. Results: Of the 267 patients analyzed, 87 patients (33%) died in the APCU. The median age of patients was 66 (range, 23-97). Patients who died in the APCU had higher ESAS scores of drowsiness (6 vs 5, P = 0.002), dyspnea (4 vs 2, P = 0.001), anorexia (8 vs 6, P = 0.014) and insomnia (6 vs 4, P = 0.001) compared to patients who discharged alive. Total symptom distress scores (SDS) were also significantly higher (47 vs 40, P = 0.001). Patients who died in the APCU were more likely to be male (odds ratio [OR] for female patients 0.38, 95% confidence interval [CI] 0.22-0.67, P < 0.001) and have higher ESAS scores of drowsiness (OR 2.08, 95% CI, 1.08-3.99, P = 0.029) and dyspnea (OR 2.19, 95% CI 1.26-3.80, P = 0.005). These patients showed significantly shorter survival after APCU admission (7 days vs 31 days, P < 0.001). Conclusions: Advanced cancer patients who die in the APCU are more likely to be male and have significantly higher symptom burden that include drowsiness and dyspnea. These patients show rapid clinical deterioration after APCU admission. More proactive and timely end-of-life care is needed for these patients.

scholarly journals Baseline Edmonton Symptom Assessment System and survival in metastatic renal cell carcinoma

2018 ◽  
Vol 25 (4) ◽  
Author(s):  
J. Graham ◽  
J. Gingerich ◽  
P. Lambert ◽  
A. Alamri ◽  
P. Czaykowski
Keyword(s):  
Renal Cell Carcinoma ◽  
Cell Carcinoma ◽  
Metastatic Renal Cell Carcinoma ◽  
Renal Cell ◽  
Symptom Burden ◽  
Symptom Assessment ◽  
Assessment System ◽  
Prognostic Information ◽  
Edmonton Symptom Assessment System ◽  
Patient Reported

Background Baseline symptom burden as measured using the Edmonton Symptom Assessment System (esas), a patient-reported, validated, and reliable tool measuring symptom severity in 9 separate domains, might yield prognostic information in patients receiving treatment for metastatic renal cell carcinoma (mrcc) and might add to the existing prognostic models.Methods In this retrospective single-centre cohort study, we included patients receiving first-line sunitinib therapy for mrcc between 2008 and 2012. Baseline variables included information relevant to the pre-existing prognostic models and pre-treatment esas summation scores (added together across all 9 domains), with higher scores representing greater symptom burden. We used Kaplan–Meier curves and Cox regression modelling to determine if symptom burden can provide prognostic information with respect to overall survival.Results We identified 68 patients receiving first-line therapy for mrcc. Most had intermediate- or poor-risk disease based on both the Memorial Sloan Kettering Cancer Center (mskcc) and the International Metastatic Renal Cell Carcinoma Database Consortium (imdc) models. The median baseline esas summation score was 16 (range: 6–57). In univariable analysis, the hazard ratio for overall survival was 1.270 (p = 0.0047) per 10-unit increase in summation esas. In multivariable analysis, the hazard ratio was 1.208 (p = 0.0362) when controlling for mskcc risk group and 1.240 (p = 0.019) when controlling for imdc risk group.Conclusions Baseline symptom burden as measured by esas score appears to provide prognostic information for survival in patients with mrcc. Those results should encourage the investigation of patient-reported symptom scales as potential prognostic indicators for patients with advanced cancer.

587 PATIENT-REPORTED SYMPTOMS FOR ESOPHAGEAL CANCER PATIENTS UNDERGOING CURATIVE INTENT TREATMENT

2021 ◽  
Vol 34 (Supplement_1) ◽  
Author(s):  
Vaibhav Gupta ◽  
Catherine Allen-Ayodabo ◽  
Laura Davis ◽  
Haoyu Zhao ◽  
Julie Hallet ◽  
...  
Keyword(s):  
Esophageal Cancer ◽  
Clinical Care ◽  
Symptom Burden ◽  
Population Level ◽  
Symptom Assessment ◽  
Assessment System ◽  
Curative Intent ◽  
Cancer Symptoms ◽  
Patient Reported ◽  
Symptom Scores

Abstract   Esophageal cancer (EC) patients experience considerable symptom burden from treatment. This study utilized population-level patient-reported Edmonton Symptom Assessment System (ESAS) scores collected as part of standard clinical care to describe symptom trajectories and characteristics associated with severe symptoms for patients undergoing curative intent EC treatment. Methods EC patients treated with curative intent at regional cancer centers and affiliates between 2009–2016 and assessed for symptoms in the 12 months following diagnosis were included. ESAS measures nine common patient-reported cancer symptoms. The outcome was reporting of severe (≥7/10) symptom scores. Multivariable analyses were used to identify characteristics associated with severe symptom scores. Results 1,751 patients reported a median of 7 (IQR 4–12) ESAS assessments in the year following diagnosis, for a total of 14,953 unique ESAS assessments included in the analysis. The most frequently reported severe symptoms were lack of appetite (n = 918, 52%), tiredness (n = 787, 45%) and poor wellbeing (713, 40.7%). The highest symptom burden is within the first five months following diagnosis, with moderate improvement in symptom burden in the second half of the first year. Characteristics associated with severe scores for all symptoms included female sex, high comorbidity, lower socioeconomic status, urban residence, and symptom assessment temporally close to diagnosis. Conclusion This study demonstrates a high symptom burden for EC patients undergoing curative intent therapy. Targeted treatment of common severe symptoms, and increased support for patients at risk for severe symptoms, may enhance patient quality of life.

scholarly journals Measuring patient-reported outcomes to improve cancer care in Canada: an analysis of provincial survey data

2018 ◽  
Vol 25 (2) ◽  
pp. 176 ◽  
Author(s):  
K. Tran ◽  
S. Zomer ◽  
J. Chadder ◽  
C. Earle ◽  
S. Fung ◽  
...  
Keyword(s):  
Cancer Treatment ◽  
Cancer Care ◽  
Patient Reported Outcomes ◽  
Symptom Burden ◽  
Symptom Assessment ◽  
Physical Symptoms ◽  
Assessment System ◽  
System Level ◽  
Care Providers ◽  
Patient Reported

Patient-reported outcomes measures (proms) are an important component of the shift from disease-centred to person-centred care. In oncology, proms describe the effects of cancer and its treatment from the patient perspective and ideally enable patients to communicate to their providers the physical symptoms and psychosocial concerns that are most relevant to them. The Edmonton Symptom Assessment System–revised (esas-r) is a commonly used and validated tool in Canada to assess symptoms related to cancer. Here, we describe the extent to which patient reported outcome programs have been implemented in Canada and the severity of symptoms causing distress for patients with cancer.As of April 2017, 8 of 10 provinces had implemented the esas-r to assess patient-reported outcomes. Data capture methods, the proportion of cancer treatment sites that have implemented the esas-r, and the time and frequency of screening vary from province to province. From October 2016 to March 2017 in the 8 reporting provinces, 88.0% of cancer patients were screened for symptoms. Of patients who reported having symptoms, 44.3% reported depression, with 15.5% reporting moderate-to-high levels; 50.0% reported pain, with 18.6% reporting moderate-to-high levels; 56.2% reported anxiety, with 20.4% reporting moderate-to-high levels; and 75.1% reported fatigue, with 34.4% reporting moderate-to-high levels.There are some notable areas in which the implementation of proms could be improved in Canada. Findings point to a need to increase the number of cancer treatment sites that screen all patients for symptoms; to standardize when and how frequently patients are screened across the country; to screen patients for symptoms during all phases of their cancer journey, not just during treatment; and to assess whether giving cancer care providers real-time patient-reported outcomes data has led to appropriate interventions that reduce the symptom burden and improve patient outcomes. Continued measurement and reporting at the system level will allow for a better understanding of progress in proms activity over time and of the areas in which targeted quality improvement efforts could ensure that patient symptoms and concerns are being addressed.

Development of patient reported outcomes-based machine learning algorithm for the six-month mortality prediction in patients with advanced cancer.

2021 ◽  
Vol 39 (28_suppl) ◽  
pp. 273-273
Author(s):  
Ishwaria Mohan Subbiah ◽  
Cai Xu ◽  
Sheng-Chieh Lu ◽  
Ali Haider ◽  
Ahsan Azhar ◽  
...  
Keyword(s):  
Machine Learning ◽  
Advanced Cancer ◽  
Patient Reported Outcomes ◽  
Symptom Burden ◽  
Mortality Prediction ◽  
Assessment System ◽  
Shortness Of Breath ◽  
Extreme Gradient Boosting ◽  
Patient Reported ◽  
Systemic Therapies

273 Background: To date, studies of machine learning (ML) algorithms within oncology for mortality prediction have focused on structured electronic health record (EHR) data. Given the complex symptom burden of patients with advanced cancers, ML models may be better suited to identify patterns and interactions between symptom burden and outcomes compared to traditional statistical methods. To that end, in this study, we leverage the patient reported outcomes (PRO) data together with clinical EHR-based variables to assess the performance of ML algorithms to predict mortality in patients with advanced cancers. Methods: We randomly selected 689 patients with advanced cancer who had their first Palliative Care encounter between January 2012 and December 2017. 59 patients were lost to follow-up and were excluded from this analysis. The remaining cohort of 630 patients was split 4:1 randomly into a training and validation set to develop and test a supervised ML algorithm (Extreme Gradient Boosting [XGB] tree) to predict the 6-month mortality. Candidate variables for algorithm development included gender, age, ECOG performance status (PS), number of prior systemic therapies, and scores on the Edmonton Symptom Assessment System (ESAS)-FS, a 12-item PRO measure of physical and psychosocial symptom burden include the composite Physical Symptom Score (PHS), a sum of the physical ESAS symptoms (pain, fatigue, nausea, drowsiness, shortness of breath, appetite, wellbeing, sleep). Results: Overall, 630 patients were included in this 6-month mortality prediction; mean age 59 years, 354 (56%) female; 276 (44%) male. Variables with the most significant impact on the XGB tree mortality prediction were the ESAS symptoms of shortness of breath (1-AUC, 0.295), appetite, ESAS PHS, financial distress, age, and appetite as well as ECOG PS and number of prior systemic therapies. The XGB tree algorithm demonstrated the best overall prediction performance of 6-month mortality in the independent testing set, AUC 0.716 (95% CI 0.63 - 0.81), sensitivity 0.75 (95% CI 0.66 - 0.87), and a positive predictive value 0.67 (95% CI 0.57 - 0.79). Conclusions: Our ML model leveraged PRO-based assessment of symptom burden to correctly identify the majority of patients who died within 6 months. These models are uniquely positioned to not only automatically identify patients at high risk for short-term mortality but also the specific symptoms of concern for clinical intervention. Such models can be applied to available clinical and PRO data to facilitate clinical decision-making. Futures studies on improving model performance with the inclusion of interventions to modify symptom burden are in design.

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