|The following article features coverage from the American Society of Clinical Oncology 2020 virtual meeting. Click here to read more of Oncology Nurse Advisor‘s conference coverage.|
Researchers at Thomas Jefferson University are conducting an ongoing evaluation of the impact of focused oncology nurse navigation on the use of acute health care resources by patients with active cancer identified as being at high risk of requiring such interventions according to a new risk-scoring tool. This risk assessment tool, as well as the design of this study, was described in a presentation at the ASCO20 Virtual Scientific Program.
Although a number of scoring systems have been developed to predict use of acute care services, including hospitalization and visits to the emergency department (ED), in different subgroups of patients with cancer, only a limited number of these scoring systems have been shown to facilitate more effective use of these health care resources in the clinical practice setting.
The Oncology Risk Score (ORS) described in this presentation incorporates multiple parameters, such as the number of ED visits in the previous 90 days, performance status, the presence of specific comorbid conditions, whether the patient is receiving aprepitant, and results of a complete blood count as well as blood levels of albumin and creatinine. Patients assessed using the ORS are assigned a final score of 0 (low risk), 1 (medium risk), or 2 or higher (high risk), corresponding to their risk of using acute care services.
The efficacy of this assessment tool within the context of an oncology nurse navigation approach in reducing need for acute care services is currently being evaluated in the setting of a case-control study in which the ORS is embedded within the electronic health record (EHR) of patients with active cancer.
In this study, oncology nurse navigators (ONNs) perform weekly chart reviews of patients undergoing treatment for cancer who are receiving care within the Centers for Medicare and Medicaid Services Oncology Care Model (OCM), with priority given to those patients not previously contacted by ONN outreach, to identify those at high risk for the need for acute oncology services according to the EHR-embedded ORS (cases). Control patients are characterized as non-OCM patients identified as being at high risk of acute care services utilization.
Case patients are then followed by an ONN, either through a telephone call consisting of barrier assessment and intervention or an in-person visit if previously scheduled to occur within the next 24 hours, both of which are followed by standard documentation and outreach by the ONN who then schedules either follow-up with the patient or refers them to another health care provider.
The proportions of case and control patients requiring acute care over time is a study endpoint.
Plans for future research related to the ORS include the use of machine learning approaches to make iterative improvements in this assessment tool.
Disclosure: Multiple authors declared affiliations with industry. Please refer to the original abstract for a full list of disclosures.
Handley N, Binder A, Li M, Rogers A, Csik AP. Implementing a clinical risk prediction tool for patients undergoing active cancer treatment. Presented at: ASCO20 Virtual Scientific Program. J Clin Oncol. 2020;38(suppl):abstr TPS2086.