Cancer symptom algorithm can help identify patients at risk for unplanned ED visits
Click Here to Manage Email Alerts
Researchers at Cancer Care Alberta and University of Calgary have demonstrated the value of a cancer symptom algorithm in correctly identifying which patients may be at high risk for an unplanned ED visit.
The novel tool uses the Edmonton Symptom Assessment System Revised (ESAS-r) to evaluate common cancer symptoms and assign a symptom complexity score to each patient. This score can then be used to guide symptom management and potentially avoid costly trips to the ED for patients.
The researchers evaluated the new approach in a study published in Journal of the National Comprehensive Cancer Network.
“The ability to predict which patients are likely to have an unplanned ED visit gives us the ability to potentially prevent some of these visits, for example, by providing additional symptom management to high-risk patients in the ambulatory setting,” Linda Watson, RN, PhD, an oncology nurse at Cancer Care Alberta and University of Calgary, told Healio. “Preventing unplanned ED visits has considerable cost-saving implications, as care delivered in ambulatory settings is lower cost than care delivered in acute care settings, including EDs.”
Watson spoke with Healio about the inspiration for this project, its effectiveness so far and plans for its future use.
Healio: What inspired you and your colleagues to evaluate the correlation between symptom complexity score and ED visits?
Watson: We were inspired by previous Canadian studies that examined the association between individual ESAS-r symptoms and ED use among patients with cancer. One of the key barriers to successfully using patient-reported outcomes (PROs) in practice is the limited amount of time in a clinic visit to review the PRO information for each patient and respond to the variety of symptoms each patient has indicated.
Our symptom complexity algorithm summarizes the information on each patient’s ESAS-r into a quick, easy-to-interpret score of low, moderate or high. A clinician can quickly look at this score and immediately have an idea of the patient’s overall condition, and identify which patients need closer review of their specific PRO information. With this in mind, we wanted to examine if higher complexity scores were associated with ED visits, as well as hospital admissions, to try to extend the utility of the algorithm, further justifying why finding time in the ambulatory clinics for targeted symptom management could save the health system money while improving patient outcomes.
Healio: How did the ESAS-r determine symptom complexity?
Watson: The ESAS-r asks patients to rate the severity of nine symptoms from zero to 10 (10 being the most severe): pain, tiredness, drowsiness, nausea, lack of appetite, shortness of breath, depression, anxiety and well-being. Our algorithm uses the number and severity of symptom reported on the ESAS-r to determine symptom complexity. There are four ways to trigger high symptom complexity:
- if any symptom is rated 10;
- if pain is rated 7 to 9;
- if three to five symptoms are rated 7 to 9; or
- if six or more symptoms are rated 4 to 6.
Moderate complexity is triggered if one or two symptoms are rated 7 to 9, or three to five symptoms are rated 4 to 6. Any patients who do not meet the criteria to trigger moderate or higher symptom complexity are coded as low complexity.
Healio: How did you determine high symptom complexity score correlated with increased likelihood of ED use?
Watson: We utilized logistic regression models to assess which factors were associated with a greater likelihood of ED use, as well as hospital admissions. The independent variables in the regressions were patient characteristics, including symptom complexity, rurality, and age, and the outcome was either ED use or hospital admission, depending on the model. To examine symptom complexity, we set low complexity as the reference group so that moderate and high complexity could be compared with it. The logistic regression model showed that high- and moderate-complexity patients had higher odds of using the ED compared with low-complexity patients.
Healio: What other important findings came from this study?
Watson: Other factors were significantly associated with acute care use, as well. Unsurprisingly, patients with more comorbidities were more likely to use the ED, as were patients who recently received chemotherapy. Notably, patients living in more rural areas were more likely to have an ED or hospital admission. This may be due to the limited health care options available to patients in rural areas and highlights the need for improved access to cancer care for all patients.
Healio: What is the potential value of being able to predict the likelihood of ED visits for patients with cancer?
Watson: In addition to the potential cost savings, it can increase the likelihood of timely delivery of targeted symptom management, thus improving patient outcomes, and minimize unplanned ED visits, which can be distressing and time-consuming — not to mention risky if patients are immunocompromised.
Healio: What is next for your research?
Watson: We recently redesigned our symptom complexity algorithm to be used with a new patient-reported outcomes measure, specifically a modified version of the ESAS-r that includes additional symptoms relevant to patients with cancer. Once data collection using the new measure has stabilized, we may consider conducting a similar study using the modified algorithm. The original algorithm shared in this study can still be used by any program that regularly uses the ESAS-r.
Healio: Is there anything else you would like to mention?
Watson: We are working on an economic analysis to complement and expand on the findings of this paper. In this next study, we expanded the scope of our data to include the health system utilization of an additional subset of patients who had a visit at one of our facilities in the same time period but did not complete a PRO measure. We then created a matched sample to compare the health resource use between the groups. Utilizing established or estimated costs for health services in our province, we hope to quantify the economic benefit of routine utilization of PRO screening and targeted symptom management. We are still analyzing this data but are committed to sharing the study findings through another peer-reviewed publication.
For more information:
Linda Watson, RN, PhD, can be reached at University of Calgary, 2500 University Drive NW, Calgary, AB, T2N1N4, Canada; email: linda.watson@ahs.ca.
Collapse
Read more about
Click Here to Manage Email Alerts