Diane Baldwin, RN, OCN, CBCN
A caseload management tool developed at the Mitchell Cancer Institute (MCI) at the University of South Alabama offers a comprehensive portrait of a patient’s condition that helps oncology nurse navigators to allocate their time and resources efficiently and enables managers to optimize patient care by assigning appropriate caseloads. The Association of Community Cancer Centers (ACCC) recognized the value of the analytical instrument at its recent conference by issuing MCI a 2017 Innovator Award for the accomplishment.
MCI’s new Oncology Navigation Acuity Tool incorporates 12 measures of the level of care required by each patient, Baldwin said (Table 1). This enables the MCI tool to provide a broad assessment of a patient’s health and needs status. “Some of the factors include staging and diagnosis, depression score, performance score, comorbidities, family support, number of treatment modalities the patient is undergoing, and recent hospitalizations,” said Baldwin.
Table 1. The Mitchell Cancer Center Institute Activity Tool Evaluates Patient Status From Multiple Angles
She described the case of a patient who was suffering from depression because of the recent death of a spouse on whom she had depended during her cancer treatment. The oncologist advised the patient to return in 6 months for followup care, but the nurse navigator determined from the patient’s acuity assessment that she needed immediate referrals for grief counseling, a support group for widows, and increased phone contact. That was the course of action taken, and this represented a valuable intervention that might not have happened without the expanded assessment possible through the MCI tool. Based on 247 patients treated over 6 months at MCI, the services provided per month broke down as follows: the number of patients handled was 144, the number of in-person visits, 97; phone calls, 56; referrals, 13; clinical interventions, 30; and “stat” interventions, 4. Stat interventions are those that prevent unnecessary ED visits or hospital admissions (Table 2).
Table 2. Acuity Scores Predict Patient Needs (n = 247)
... to read the full story