The impact of routine Edmonton symptom assessment system use on receiving palliative care services: results of a population-based retrospective-matched cohort analysis

BACKGROUND

In 2007, Cancer Care Ontario began standardised symptom assessment as part of routine care using the Edmonton Symptom Assessment System (ESAS).

AIM

The purpose of this study was to evaluate the impact of ESAS on receipt of palliative care when compared with a matched group of unexposed patients.

DESIGN

A retrospective-matched cohort study examined the impact of ESAS screening on initiation of palliative care services provided by physicians or homecare nurses. The study included adult patients diagnosed with cancer between 2007 and 2015. Exposure was defined as completing ≥1 ESAS during the study period. Using 4 hard and 14 propensity score-matched variables, patients with cancer exposed to ESAS were matched 1:1 to those who were not. Matched patients were followed from first ESAS until initiation of palliative care, death or end of study.

RESULTS

The final cohort consisted of 204 688 matched patients with no prior palliative care consult. The pairs were well matched. The cumulative incidence of receiving palliative care within the first 5 years was higher among those exposed to ESAS compared with those who were not (27.9% (95% CI: 27.5% to 28.2%) versus 27.9% (95% CI: 27.5% to 28.2%)), when death is considered as a competing event. In the adjusted cause-specific Cox proportional hazards model, ESAS assessment was associated with a 6% increase in palliative care services (HR: 1.06, 95% CI: 1.04 to 1.08).

CONCLUSION

We have demonstrated that patients exposed to ESAS were more likely to receive palliative care services compared with patients who were not exposed. This observation provides real-world data of the impact of routine assessment with a patient-reported outcome.

Pilot study of smartphone-based health outcome tracking (OurBrainBank) for glioblastoma patients

Background

Patients with glioblastoma (GBM) typically have high symptom burden impacting on quality of life. Mobile apps may help patients track their condition and provide real-time data to clinicians and researchers. We developed a health outcome reporting app (OurBrainBank [OBB]) for GBM patients. Our primary aim was to explore the feasibility and take-up of OBB. Secondary aims were to examine the potential value of OBB app usage for patient well-being and clinical research.

Methods

Participants (or caregiver proxies) completed baseline surveys and tracked 10 health outcomes over time. We evaluated usage and engagement, and relationships between clinical/sociodemographic variables and OBB use. Participant satisfaction and feedback were described. To demonstrate usefulness for clinical research, health outcomes were compared with corresponding items on a validated measure (EQ-5D-5L).

Results

From March 2018 to February 2021, OBB was downloaded by 630 individuals, with 15 207 sets of 10 health outcomes submitted. Higher engagement was associated with being a patient rather than a caregiver (χ ²(2,568) = 28.6, P < .001), having higher self-rated health scores at baseline (F(2,460) = 4.8, P = .009) and more previous experience with mobile apps (χ ²(2,585) = 9.6, P = .008). Among the 66 participants who completed a feedback survey, most found health outcome tracking useful (average 7/10), and would recommend the app to others (average 8.4/10). The OBB health outcomes mapped onto corresponding EQ-5D-5L items, suggesting their validity.

Conclusions

OBB can efficiently collect GBM patients’ health outcomes. The long-term goal is to create a unique database of thousands of deidentified GBM patients, with open access to qualified researchers.

The effectiveness of a provincial symptom assessment program in reaching adolescents and young adults with cancer: A population-based cohort study

Background

Symptom control is prioritized by cancer patients and may improve overall survival. Ontario, Canada thus offers all cancer patients screening using the Edmonton Symptom Assessment System (ESAS) at outpatient cancer‐related visits. We determined whether this initiative reached adolescents and young adults (AYA) and factors associated with screening in this population.

Methods

We linked all Ontario AYA diagnosed with cancer 2010–2018 aged 15–29 years to population‐based databases identifying outpatient visits and ESAS screening. For each 2‐week period in the year post‐diagnosis, AYA with cancer‐related visits were categorized as “unscreened” (no ESAS score) versus “screened” (≥1 ESAS score). Demographic and disease‐related covariates were examined.

Results

Among 5435 AYA, 4204 (77.4%) had ≥1 ESAS screen. Within any 2‐week period, only 30%–44% of AYA attending cancer‐related visits were screened. Patients with hematologic malignancies were least likely to be screened [odds ratio (OR) vs. breast cancer 0.77, 95% confidence interval (95% CI) 0.67–0.88; p < 0.001]. AYA in remote Northern or rural areas had equivalent or higher rates of ESAS screening compared to those in high‐income urban areas. However, AYA living in the lowest income urban neighborhoods were less likely to be screened (OR 0.86, 95% CI 0.77–0.97; p = 0.01).

Conclusions

Within a population‐wide symptom assessment program, while AYA living in rural and remote areas had high rates of screening, than those in low‐income urban areas were substantially less likely to be screened. Though patients with hematologic cancers suffer from particularly high symptom burdens, they were also less likely to be screened. Interventions targeting AYA are required to increase uptake.

The intersectionality of gender and poverty on symptom suffering among adolescents with cancer

BACKGROUND

To determine if the intersectionality of gender and poverty is associated with health disparities among adolescents with cancer. We hypothesized unobserved latent classes of patients exist with respect to cancer-related symptoms; and class classification varies by gender-poverty combinations.

PROCEDURE

Cross-sectional data were collected among adolescents with cancer and families (N = 126 dyads) at four tertiary pediatric hospitals. Adolescents were aged 14-21 years, English speaking, cancer diagnosis, not developmentally delayed, psychotic, homicidal, suicidal, or severely depressed. Latent class analysis and multinomial logit models were used for analysis. Patient-Reported Outcomes Measurement Information System (PROMIS) pediatric symptom measures, Short forms, evaluated anxiety, depressive symptoms, pain interference, and fatigue. Family-reported household income used 2016 Federal Poverty Level (FPL) guidelines.

RESULTS

Three distinct groups of patients were identified using PROMIS symptom patterns: High Distress-25%; High Physical/Low Psychological Distress-14%; and Low Distress-62%. Female adolescents living in households with incomes at or below the 2016 FPL had 30 times the odds of being classified in the High Distress class (higher probabilities of experiencing anxiety, depressive symptoms, pain interference, and fatigue) compared to those in the High Physical/Low Psychological Distress class (female and poverty: AOR = 30.27, 95% CI 1.23, 735.10), and this was statistically significant (β = 3.41, 95% CI 0.21, 6.60; p = .04) but not compared to those in Low Distress.

CONCLUSION

Adolescent females with cancer with households in poverty had significantly greater odds of experiencing high symptom distress, compared to those with high physical but low psychological distress. More comprehensive screening and intervention, as needed, may decrease disparities.

Innovations in research and clinical care using patient-generated health data

Patient-generated health data (PGHD), or health-related data gathered from patients to help address a health concern, are used increasingly in oncology to make regulatory decisions and evaluate quality of care. PGHD include self-reported health and treatment histories, patient-reported outcomes (PROs), and biometric sensor data. Advances in wireless technology, smartphones, and the Internet of Things have facilitated new ways to collect PGHD during clinic visits and in daily life. The goal of the current review was to provide an overview of the current clinical, regulatory, technological, and analytic landscape as it relates to PGHD in oncology research and care. The review begins with a rationale for PGHD as described by the US Food and Drug Administration, the Institute of Medicine, and other regulatory and scientific organizations. The evidence base for clinic-based and remote symptom monitoring using PGHD is described, with an emphasis on PROs. An overview is presented of current approaches to digital phenotyping or device-based, real-time assessment of biometric, behavioral, self-report, and performance data. Analytic opportunities regarding PGHD are envisioned in the context of big data and artificial intelligence in medicine. Finally, challenges and solutions for the integration of PGHD into clinical care are presented. The challenges include electronic medical record integration of PROs and biometric data, analysis of large and complex biometric data sets, and potential clinic workflow redesign. In addition, there is currently more limited evidence for the use of biometric data relative to PROs. Despite these challenges, the potential benefits of PGHD make them increasingly likely to be integrated into oncology research and clinical care.

The Role of a Symptom Assessment Tool in Shaping Patient-Physician Communication in Palliative Care

CONTEXT

Patients with cancer experience many symptoms that disrupt quality of life, and symptom communication and management can be challenging. The Edmonton Symptom Assessment System (ESAS) was developed to standardize assessment and documentation of symptoms, yet research is needed to understand patients' and caregivers' experiences using the tool and its ability to impact patient-provider aligned care.

OBJECTIVES

The objective of this study was to understand how the ESAS shapes communication between patients and providers by exploring patients' and caregivers' experiences using the ESAS and assessing the level of agreement in symptom assessment between patients and palliative care physicians.

METHODS

This study used a mixed-methods design. Thirty-one semistructured interviews were conducted and audio-recorded with patients (n = 18) and caregivers (n = 13). Data were analyzed following a social constructionist grounded theory approach. Patient and provider ESAS scores were obtained by medical chart review. Intraclass correlation coefficients were used to assess the level of agreement between patient-completed ESAS scores and provider-completed ESAS scores.

RESULTS

Participants reported that the ESAS was a beneficial tool in establishing priorities for symptom control and guiding the appointment with the palliative care physician, despite challenges in completing the ESAS. Filling out the ESAS can also help patients more clearly identify their priorities before meeting with their physician. There was a good to excellent level of agreement between patients and physicians in all symptoms analyzed.

CONCLUSION

The ESAS is beneficial in enhancing symptom communication when used as a guide to identify and understand patients' main concerns.

Patient-Reported Symptoms Improve Performance of Risk Prediction Models for Emergency Department Visits Among Patients With Cancer: A Population-Wide Study in Ontario Using Administrative Data

CONTEXT

Prior work shows measurements of symptom severity using the Edmonton Symptom Assessment System (ESAS) which are associated with emergency department (ED) visits in patients with cancer; however, it is not known if symptom severity improves the ability to predict ED visits.

OBJECTIVES

To determine whether information on symptom severity improves the ability to predict ED visits among patients with cancer.

METHODS

This was a population-based study of patients who were diagnosed with cancer and had at least one ESAS assessment completed between 2007 and 2015 in Ontario, Canada. After splitting the cohort into training and test sets, two ED visit risk prediction models using logistic regression were developed on the training cohort, one without ESAS and one with ESAS. The predictive performance of each risk model was assessed on the test cohort and compared with respect to area under the curve and calibration.

RESULTS

The full cohort consisted of 212,615 unique patients with a total of 1,267,294 ESAS assessments. The risk prediction model including ESAS was superior in sensitivity, specificity, accuracy, and discrimination. The area under the curve was 73.7% under the model with ESAS, whereas it was 70.1% under the model without ESAS. The model with ESAS was also better calibrated. This improvement in calibration was particularly noticeable among patients in the higher deciles of predicted risk.

CONCLUSION

This study demonstrates the importance of incorporating symptom measurements when developing an ED visit risk calculator for patients with cancer. Improved predictive models for ED visits using measurements of symptom severity may serve as an important clinical tool to prompt timely interventions by the cancer care team before an ED visit is necessary.