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Effects of a Provincial-Wide Implementation of Screening for Distress on Healthcare Professionals' Confidence and Understanding of Person-Centered Care in Oncology

Rie Tamagawa, Shannon Groff, Jennifer Anderson, Sarah Champ, Andrea Deiure, Jennifer Looyis, Peter Faris, and Linda Watson

Background: Although published studies report that screening for distress (SFD) improves the quality of care for patients with cancer, little is known about how SFD impacts healthcare professionals (HCPs). Objectives: This quality improvement project examined the impact of implementing the SFD intervention on HCPs' confidence in addressing patient distress and awareness of person-centered care. Patients and Methods: This project involved pre-evaluation and post-evaluation of the impact of implementing SFD. A total of 254 HCPs (cohort 1) were recruited from 17 facilities across the province to complete questionnaires. SFD was then implemented at all cancer care facilities over a 10-month implementation period, after which 157 HCPs (cohort 2) completed post-implementation questionnaires. At regional and community care centers, navigators supported the integration of SFD into routine practice; therefore, the impact of navigators was examined. Results: HCPs in cohort 2 reported significantly greater confidence in managing patients' distress and greater awareness about person-centered care relative to HCPs in cohort 1. HCPs at regional and community sites reported greater awareness in person-centeredness before and after the intervention, and reported fewer negative impacts of SFD relative to HCPs at tertiary sites. Caring for single or multiple tumor types was an effect modifier, with effects observed only in the HCPs treating multiple tumors. Conclusions: Implementation of SFD was beneficial for HCPs' confidence and awareness of person-centeredness. Factors comprising different models of care, such as having site-based navigators and caring for single or multiple tumors, influenced outcomes.

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Patient-Reported Symptom Complexity and Acute Care Utilization Among Patients With Cancer: A Population-Based Study Using a Novel Symptom Complexity Algorithm and Observational Data

Linda Watson, Siwei Qi, Claire Link, Andrea DeIure, Arfan Afzal, and Lisa Barbera

Background: Patients with cancer in Canada are often effectively managed in ambulatory settings; however, patients with unmanaged or complex symptoms may turn to the emergency department (ED) for additional support. These unplanned visits can be costly to the healthcare system and distressing for patients. This study used a novel patient-reported outcomes (PROs)–derived symptom complexity algorithm to understand characteristics of patients who use acute care, which may help clinicians identify patients who would benefit from additional support. Patients and Methods: This retrospective observational cohort study used population-based linked administrative healthcare data. All patients with cancer in Alberta, Canada, who completed at least one PRO symptom-reporting questionnaire between October 1, 2019, and April 1, 2020, were included. The algorithm used ratings of 9 symptoms to assign a complexity score of low, medium, or high. Multivariable binary logistic regressions were used to evaluate factors associated with a higher likelihood of having an ED visit or hospital admission (HA) within 7 days of completing a PRO questionnaire. Results: Of the 29,133 patients in the cohort, 738 had an ED visit and 452 had an HA within 7 days of completing the PRO questionnaire. Patients with high symptom complexity had significantly higher odds of having an ED visit (OR, 3.10; 95% CI, 2.59–3.70) or HA (OR, 4.20; 95% CI, 3.36–5.26) compared with low complexity patients, controlling for demographic covariates. Conclusions: Given that patients with higher symptom complexity scores were more likely to use acute care, clinicians should monitor these more complex patients closely, because they may benefit from additional support or symptom management in ambulatory settings. A symptom complexity algorithm can help clinicians easily identify patients who may require additional support. Using an algorithm to guide care can enhance patient experiences, while reducing use of acute care services and the accompanying cost and burden.

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Validating a Patient-Reported Outcomes–Derived Algorithm for Classifying Symptom Complexity Levels Among Patients With Cancer

Linda Watson, Siwei Qi, Andrea DeIure, Eclair Photitai, Lindsi Chmielewski, and Louise Smith

Background: The patient-reported outcomes (PROs) symptom complexity algorithm, derived from self-reported symptom scores using the Edmonton Symptom Assessment System and concerns indicated on the Canadian Problem Checklist, has not been validated extensively. Methods: This is a retrospective chart review study using data from the Alberta Cancer Registry and electronic medical records from Alberta Health Services. The sample includes patients with cancer who visited a cancer facility in Alberta, Canada, from February 2016 through November 2017 (n=1,466). Results: The effect size (d=1.2) indicates that the magnitude of difference in health status between the severe- and low-complexity groups is large. The symptom complexity algorithm effectively classified subgroups of patients with cancer with distinct health status. Using Karnofsky performance status, the algorithm shows a sensitivity of 70.3%, specificity of 84.1%, positive predictive value of 79.1%, negative predictive value of 76.7%, and accuracy of 77.7%. An area under the receiver operating characteristic of 0.824 was found for the complexity algorithm, which is generally regarded as good, This same finding was also regarded as superior to the alternative algorithm generated by 2-step cluster analysis (area under the curve, 0.721). Conclusions: The validity of the PRO-derived symptom complexity algorithm is established in this study. The algorithm demonstrated satisfactory accuracy against a clinician-driven complexity assessment and a strong correlation with the known group analysis. Furthermore, the algorithm showed a higher screening capacity compared with the algorithm generated from 2-step cluster analysis, reinforcing the importance of contextualization when classifying patients’ symptoms, rather than purely relying on statistical outcomes. The algorithm carries importance in clinical settings, acting as a symptom complexity flag, helping healthcare teams identify which patients may need more timely, targeted, and individualized patient symptom management.

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CHAMBER: A Regional Performance Improvement CME Initiative for Breast Cancer Health Care Providers

Linda M. Sutton, Joseph Geradts, Erika P. Hamilton, Kathleen A. Havlin, Gretchen G. Kimmick, P. Kelly Marcom, Neil L. Spector, Melanie Watson, Daniel U. Rabin, Theodore O. Bruno, Amanda Noe, Stacy Miller, Chitra Subramaniam, Sherry Layton, and Katherine Grichnik

CHAMBER was a regional educational initiative for providers of care to patients with HER2+ breast cancer. The study goals were to (1) enhance testing for HER2/neu overexpression in patients with invasive breast cancer; (2) increase the appropriate use of targeted therapy for patients with HER2+ breast cancer; and (3) enhance patients' coping ability. This Performance Improvement Continuing Medical Education (PI-CME) initiative included clinical practice assessment, educational activities, and reassessment. Chart review revealed a high rate of HER2 testing (98%) before and after education. Targeted therapy for patients with HER2+ breast cancer declined after the program (from 96% to 61%), perhaps attributable to an increase in awareness of medical reasons to avoid use of targeted therapy. Assessment for patients' emotional coping ability increased after education (from 55% to 76%; P=.01). Rates of testing for HER2 amplification and assessment of emotional well-being after education were consistent with ASCO Quality Oncology Practice Initiative benchmark values. Documentation of actions to address emotional problems remained an area for improvement.