Researchers have found that an algorithm that calculates patient-reported symptom complexity scores may help oncologists identify patients who are at an increased risk for unplanned visits to the emergency department (ED), creating the potential for additional proactive care and reduced health-care costs, according to an article published by Watson et al in JNCCN–Journal of the National Comprehensive Cancer Network.
Study Methods and Results
In the new study, researchers used the Edmonton Symptom Assessment System-Revised (ESAS-r) as a measurement tool for the most common symptoms experienced by patients with cancer. After classifying each patient’s symptom complexity based on the number and severity of symptoms reported, the researchers correlated the symptom complexity with the odds of having an unplanned ED visit within 1 week. Among the 29,164 patients who completed a patient-reported outcome questionnaire, 2.5% of them (n = 738) experienced an unplanned visit to the ED within 1 week. The researchers found that patients with high symptom complexity—such as those with multiple, co-occurring, severe symptoms—were threefold more likely to use the ED than patients with low symptom complexity, and over fourfold more likely to be admitted to the hospital. Additionally, patients with moderate symptom complexity were twofold as likely to need either type of acute, hospital-based, unplanned care compared with those who had low symptom complexity.
“Using a tool to generate a symptom complexity score—summarizing a large amount of symptom information and condensing it into a quick, easily interpreted alert—allows clinicians to have a real-time, comprehensive overview of the symptom severity a patient is experiencing,” highlighted lead study author Linda Watson, RN, PhD, Adjunct Assistant Professor in the Faculty of Nursing at the University of Calgary Arnie Charbonneau Cancer Institute and Scientific Director of Applied Research and Patient Experience at Cancer Care Alberta at Alberta Health Services. “With this information at their fingertips, clinicians can then proactively offer additional support or symptom management in the lower-cost outpatient care setting and hopefully avoid costly—and potentially distressing—hospital visits. Health-care teams have to manage many competing priorities, so finding quick, reliable ways to identify which patients may benefit from targeted symptom management in lower-cost ambulatory care clinics would be helpful,” she added.
Conclusions
Previous studies have suggested that up to 20% of ED visits and/or hospital admissions for patients with cancer could potentially be avoided with proactive symptom management in the community. The researchers noted the importance of recognizing that not all ED visits can or should be prevented. Some urgent health problems may necessitate emergency or inpatient care—and some patient circumstances may warrant ED visits.
“Clinicians who treat patients with cancer are aware that identifying and supporting those who are at the highest risk for [unplanned] ED visits or hospitalizations will lead to better patient outcomes and experiences,” emphasized Kay Yeung, MD, PhD, Associate Professor of Medicine at the Moores Cancer Center at the University of California, San Diego Health as well as a member of the NCCN Clinical Practice Guidelines in Oncology Panel for Breast Cancer, who was not involved in the study. “One of the barriers is how to do a comprehensive assessment effectively in a busy oncology clinic. This retrospective observational cohort study shows that a novel symptom complexity algorithm based on patient-reported outcome questionnaires [may] correlate tightly with acute care utilization and may help clinicians proactively identify such patients. It will be important to further investigate how implementing this algorithm prospectively can impact acute care utilization, financial burden, and clinical outcomes,” she concluded.
Disclosure: For full disclosures of the study authors, visit jnccn.org.
