Evaluation of a nurse navigator model to improve access to cancer care.

185 Background: Patient navigation has been found to improve patients’ clinical outcomes. The service-line nurse navigators (NNs) at our fourteen-hospital network serve patients with newly diagnosed malignancy and have two main objectives: facilitating the timely initiation of treatments and improving patient experience. The evaluation was a critical component of our program charter and included the number of patients contacted by the NNs, the time to treatment initiation among these patients, and the number of referrals to support services by the NNs. The implementation and sustainability of each evaluation strategy are discussed. Methods: We integrated the evaluation metrics into the patient tracker spreadsheet maintained by the NNs. Because the largest subset of patients served through the program were diagnosed with stage IV non-small cell lung cancer, the quality improvement specialist conducted a chart abstraction of this group to assess the duration from diagnosis to treatment initiation. This duration was compared to a historical sample obtained from the tumor registry data. Results: During the first nine months, the navigators served 147 patients. The mean age was 69 years. Eighty-two percent identified themselves as Caucasian, 8 percent as African American, and 4 percent as Asian. Fifty percent identified themselves as male, 48 percent as female, and 2 percent as other or undisclosed. There was no transgender patient. Fifty-five percent had Medicare or Medicare Advantage, 27 percent had commercial insurance, and 10 percent had Medicaid. The largest number of referrals, 51 percent, came from inpatient clinicians. Eighty-three percent of patients established outpatient oncology care within our hospital network. Care barriers included lack of transportation and comorbidities requiring complex care coordination. The tracker did not capture all referrals to psychosocial support; only 15 referrals were noted. Nine patients with stage IV non-small cell lung cancer were diagnosed at our medical center and established care at a local community hospital. The average length between the diagnosis and treatment initiation was 42.9 days (n = 9, SD = 22.4), compared to an average of 51.1 days (n = 34, SD = 44.3) among the historical cohort of tumor registry patients with the same disease and cancer stage who also out-migrated from our medical center. Conclusions: The program evaluation highlighted the opportunity to increase referrals from outpatient providers. We observed a trend toward a shorter duration between diagnosis and treatment among our patients compared to the historical comparison group, indicating the program’s potential effect in preventing significant treatment delays. Lessons learned included focusing on improving navigator onboarding related to data capture. Finally, we plan to utilize the reporting function in our electronic health records to minimize manual data tracking and monitor outcome measures.

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Publication Details

Journal
JCO Oncology Practice
Published
2025-10-01
DOI
https://doi.org/10.1200/op.2025.21.10_suppl.185
Primary Topic
Global Cancer Incidence and Screening
Type
article
Field-Weighted Citation Impact
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article

Evaluation of a nurse navigator model to improve access to cancer care.

Aya Sato-DiLorenzo, William M. Decaneas, Holly Dowling, Jessica A. Zerillo et al.
JCO Oncology Practice
Global Cancer Incidence and Screening
article

Evaluation of a nurse navigator model to improve access to cancer care.

Aya Sato-DiLorenzo, William M. Decaneas, Holly Dowling, Jessica A. Zerillo, C. George
article en

Abstract

185 Background: Patient navigation has been found to improve patients’ clinical outcomes. The service-line nurse navigators (NNs) at our fourteen-hospital network serve patients with newly diagnosed malignancy and have two main objectives: facilitating the timely initiation of treatments and improving patient experience. The evaluation was a critical component of our program charter and included the number of patients contacted by the NNs, the time to treatment initiation among these patients, and the number of referrals to support services by the NNs. The implementation and sustainability of each evaluation strategy are discussed. Methods: We integrated the evaluation metrics into the patient tracker spreadsheet maintained by the NNs. Because the largest subset of patients served through the program were diagnosed with stage IV non-small cell lung cancer, the quality improvement specialist conducted a chart abstraction of this group to assess the duration from diagnosis to treatment initiation. This duration was compared to a historical sample obtained from the tumor registry data. Results: During the first nine months, the navigators served 147 patients. The mean age was 69 years. Eighty-two percent identified themselves as Caucasian, 8 percent as African American, and 4 percent as Asian. Fifty percent identified themselves as male, 48 percent as female, and 2 percent as other or undisclosed. There was no transgender patient. Fifty-five percent had Medicare or Medicare Advantage, 27 percent had commercial insurance, and 10 percent had Medicaid. The largest number of referrals, 51 percent, came from inpatient clinicians. Eighty-three percent of patients established outpatient oncology care within our hospital network. Care barriers included lack of transportation and comorbidities requiring complex care coordination. The tracker did not capture all referrals to psychosocial support; only 15 referrals were noted. Nine patients with stage IV non-small cell lung cancer were diagnosed at our medical center and established care at a local community hospital. The average length between the diagnosis and treatment initiation was 42.9 days (n = 9, SD = 22.4), compared to an average of 51.1 days (n = 34, SD = 44.3) among the historical cohort of tumor registry patients with the same disease and cancer stage who also out-migrated from our medical center. Conclusions: The program evaluation highlighted the opportunity to increase referrals from outpatient providers. We observed a trend toward a shorter duration between diagnosis and treatment among our patients compared to the historical comparison group, indicating the program’s potential effect in preventing significant treatment delays. Lessons learned included focusing on improving navigator onboarding related to data capture. Finally, we plan to utilize the reporting function in our electronic health records to minimize manual data tracking and monitor outcome measures.

JCO Oncology PracticeVol. 21(10_suppl)
Beth Israel Deaconess Medical Center (US)
Openalex Percentile: Top 62%
Global Cancer Incidence and Screening
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