Oncology Nurse Navigator Research Articles

Improving verbal communication for oncology patients who self-identify as having low/marginal health literacy.

177 Background: Within our academic oncology institute, patient’s health-related social needs (HRSN) are identified through the new patient intake questionnaire (NPIQ). 28% (n=2787) of patients who completed the NPIQ (n=9836) reported low/marginal health literacy (HL). While reviewing the HRSN data, it was discovered that there was no formal process to support patients who reported having low/marginal HL. While printed and online health materials use standard reading levels, verbal communications are not individualized to patients’ literacy needs. As an integral member of the interdisciplinary team, Oncology Nurse Navigators (ONNs) communicate vital and complex health information with patients throughout the cancer continuum. This quality improvement project explored the impact ONNs could have with patients who self-identify as having low/marginal HL. Methods: To assess ONN HL knowledge and communication strategies for patients with low/marginal HL, a survey was conducted in March 2024. Findings revealed a HL knowledge gap across all disease programs. For project manageability, our team piloted HL interventions to the sarcoma disease group where 33% of patients (n=223) responded to the NPIQ as having low/marginal HL. Two-part intervention included: 1) creation of a HL training and tools for ONNs (e.g., teach-back method; scripting; reference materials) and 2) development of Epic Smartphrase acknowledging training and tools were utilized. Results: To understand ONNs knowledge of where to find patient HL score in Epic, we conducted a survey (n=69; response rate=43%). 94% of ONNs reported not knowing where to access HL information. The first intervention was training-based. ONN trainings (n=2) were held from 3/12/2024 to 5/14/2024. At baseline, 0% of ONNs (n=4) used HL tools, as they were not in existence. At first reassessment, 75% of ONNs reported using the HL tools to communicate with patients. Part two of the intervention (in-progress) is the creation of a Smartphrase to document when ONNs altered patient communication. Data on Smartphrase usage are forthcoming. Conclusions: Providing HL training and tools to ONNs equips them to 1) identify patients who have low/marginal HL, and 2) conduct conversations with patients at an appropriate literacy level.

The Effect of Oncology Nurse Navigation on Mental Health in Patients with Cancer in Taiwan: A Randomized Controlled Clinical Trial.

In this study, we investigated the prevalence of mental health problems among patients with cancer and whether oncology nurse navigation improved their mental health outcomes and medical experience. In this randomized controlled clinical trial, we recruited 128 outpatients with cancer via purposive sampling from a teaching hospital in northern Taiwan. Participants were randomly assigned to the navigation group (N = 61) or the usual care group (N = 67). Data were collected from January 2019 to July 2020 using questionnaires, including the self-reported Distress Thermometer, Hospital Anxiety and Depression Scale, Demoralization Scale, and Patient Assessment of Chronic Illness Care. Data were collected at baseline and after three and six months of the intervention. Descriptive and analytical statistical analyses were performed. The prevalence rates of anxiety, depression, distress, and demoralization were 17.9%, 15.7%, 29.7%, and 29.7%, respectively. After three months, the participants in the navigation group exhibited significantly reduced levels of anxiety, demoralization, and emotional distress (reduced by 92%, 75%, and 58%, respectively) and reported a better medical experience (odds ratio = 1.40) than those in the usual care group.

Nurse Navigator Responsibilities in Managing Care Transitions for the Patient With Acute Myeloid Leukemia.

Oncology nurse navigators (ONNs) help address barriers that would affect the patient's ability to receive timely and quality cancer care and bridge gaps from the ambulatory to acute settings by reinforcing the treatment pla.

The role of a dedicated Oncology Nurse Navigator in the surgical oncology pathways: 1 year experience from a General Surgery Unit in central Italy with follow up.

The Nurse Navigator is a highly specialized nurse with technical and non-technical skills that offers individualized assistance to cancer patients, their family and caregivers to overcome health system barriers and facilitate access to care. This role was introduced in the General Surgery Unit of the Madonna del Soccorso Hospital in San Benedetto del Tronto from 1st January 2023. The primary endpoint is to compare the times taken for each step of the diagnostic-therapeutic pathway comparing the study group followed by Oncology Nurse Navigator (ONN) and the group not followed by this role. The secondary endpoints, only for the study group, were the number of patient contacts with the ONN and the time slots; the number of examinations and consultations organized by ONN; the evaluation of patient satisfaction at discharge; the number and type of problems noted during follow-up contact at 7 and 30days after discharge. A prospective court study with historical control was conducted from 1st January 2023 in Madonna del Soccorso Hospital, Italy. The study group consists of all cancer patients cared for by ONN. The control group was created by selecting the same number of patients as the study group but taken care of in the previous 3years (from 2020 to 2022) and, therefore, without the presence of the Nurse Navigator. The control group data come from clinical documentation. The number and time slots of contact with the ONN were recorded through the use of a company mobile phone active 24/7 through phone calls and messages. The number of examinations and consultations is known through online requests. The satisfaction assessment was carried out through the use of externally validated questionnaire Patient Satisfaction with Cancer Care (PSCC). The follow-up was performed by telephone and recorded on documentation according to established parameters. A total of 200 patients were analyzed. Both the study and control groups included 100 patients each. The average time between the first contact with the patient and the execution of the diagnostic test was 7days in the cases compared to 28days in the control group. The waiting time for the Multi-Disciplinary Team discussion (MDT) was 3 days for the study group compared to 6days in the control group. The average time taken for the first oncological visit was 3days in the study group compared to 18days in the controls. The time from first contact to the operating session was 20days compared to 45 in controls. Each patient had an average of 10 phone calls with the ONN. For all patients accompanied at the first diagnosis, at least 2 radiological and laboratory tests were organized. Oncology appointment for treatment evaluations after delivery of the histological report was communicated within a maximum of 3 working days. A patient satisfaction questionnaire achieved a response rate of 100%, with an average score of 87.0/90. The telephone follow-up had a response rate of 100% of patients and revealed a decrease in problems at the 30-day check-up compared to that of 7days after discharge. (Activity of Daily Living 20% vs 8%; nutritional problems 40% vs 21%, pain 18% vs 2%; surgical wounds 45% vs 1%; mobilization 8% vs 0%). The data demonstrate that ONN service improves the quality and outcomes of surgical oncology patients' pathway. The professional role of the ONN, with predefined technical and non-technical skills, should also be officially recognized by the healthcare system and hospital administration.

A new figure in oncology pathways: Oncology Nurse Navigator and his preliminary results in the San Benedetto del Tronto Surgery

Background. The role of the Nurse Navigator was developed in order to address the health disparities created by the social determinants of health, , being an expert, specialized and trained nurse who takes charge of the patient diagnosed with cancer and accompanies him throughout the treatment process, helping him to extricate himself from the labyrinth of the healthcare system. This figure was introduced and studied in the general surgery of the Madonna del Soccorso hospital in San Benedetto del Tronto. Objective. Primary outcomes are the reduction of time interval between the first patient contact and each phase of the diagnostic and therapeutic pathway. Secondary outcomes are the assessment of the number and frequency of contacts between the patient and the ONN, as well as of the number and type of organized procedures, and patient satisfaction assessment. Methods. A prospective cohort study was conducted with a historical control group represented by the same number of cancer patients treated in the same surgical unit in the previous year and not followed by an ONN. The patients’ contacts were registered within a dedicated mobile number. A questionnaire on patient satisfaction with cancer care was completed and administered to patients in a blinded manner by a third party to avoid bias. Results. The study group included 30 cancer patients. The average time from first contact to primary diagnostic test was 8 days versus 20 days in 2022 (control group). All patients underwent discussion by a multidisciplinary team (MDT), and the time to reach the MDT discussion was not different between the 2 groups. Five patients were deemed ineligible for surgery, and the average time to referral to a medical oncologist was 2 days in the study compared to 10 days in the control group. Twenty-five patients were eligible for initial surgery, and the mean time from first contact to surgery was 23 days after ONN establishment compared with 45 days in the control group. Each patient had an average of 10 phone calls with the ONN. For patients with a first diagnosis of cancer, the ONN organized an average of 4 tests. A patient satisfaction questionnaire achieved a response rate of 100%, with an average score of 85.2/90. Conclusion. The data demonstrate that ONN service is effective and may improve the quality and outcomes of the management path of surgical oncology patients. The professional role of the ONN, with predefined technical and non-technical skills, should also be officially recognized by the healthcare system and hospital administration.

Identifying Oncology Clinical Trial Candidates Using Artificial Intelligence Predictions of Treatment Change: A Pilot Implementation Study.

Precision oncology clinical trials often struggle to accrue, partly because it is difficult to find potentially eligible patients at moments when they need new treatment. We piloted deployment of artificial intelligence tools to identify such patients at a large academic cancer center. Neural networks that process radiology reports to identify patients likely to start new systemic therapy were applied prospectively for patients with solid tumors that had undergone next-generation sequencing at our center. Model output was linked to the MatchMiner tool, which matches patients to trials using tumor genomics. Reports listing genomically matched patients, sorted by probability of treatment change, were provided weekly to an oncology nurse navigator (ONN) coordinating recruitment to nine early-phase trials. The ONN contacted treating oncologists when patients likely to change treatment appeared potentially trial-eligible. Within weekly reports to the ONN, 60,199 patient-trial matches were generated for 2,150 patients on the basis of genomics alone. Of these, 3,168 patient-trial matches (5%) corresponding to 525 patients were flagged for ONN review by our model, representing a 95% reduction in review compared with manual review of all patient-trial matches weekly. After ONN review for potential eligibility, treating oncologists for 74 patients were contacted. Common reasons for not contacting treating oncologists included cases where patients had already decided to continue current treatment (21%); the trial had no slots (14%); or the patient was ineligible on ONN review (12%). Of 74 patients whose oncologists were contacted, 10 (14%) had a consult regarding a trial and five (7%) enrolled. This approach facilitated identification of potential patients for clinical trials in real time, but further work to improve accrual must address the many other barriers to trial enrollment in precision oncology research.

Neighborhood Disadvantage Is Associated with Inferior Overall Survival for Acute Myeloid Leukemia Patients Treated with Standard Intensive Induction

Background: Identifying biologic and socioeconomic contributors to disparities in outcomes is critical for the management of acute myeloid leukemia (AML). Prior studies in AML revealed that Black patients (pts) have inferior survival compared to White pts, with more striking disparity for Black pts aged <60. We previously explored our large and diverse AML cohort from urban and large rural areas and did not identify inferior survival for pts with self-reported Black race or Hispanic ethnicity. Although no surrogates for social determinants of health (SDOH) or insurance status were recognized as contributing to survival differences, oncology nurse navigation (ONN) was associated with a survival benefit, with no significant difference in access to ONN among racial or ethnic groups. To further evaluate socioeconomic drivers of disparities in this population supported by ONN, we aim to use the Area Deprivation Index (ADI) to determine the impact of neighborhood disadvantage on survival in AML. Methods: AMLpts diagnosed at Levine Cancer Institute between 12/2015 and 12/2020 were included. Pts with acute promyelocytic leukemia (APL) were excluded from this analysis. Details regarding insurance coverage, ONN services, induction therapy, stem cell transplant (SCT) status, and survival outcomes were collected. Race and ethnicity were self-reported. European LeukemiaNet (ELN) 2017 criteria were used to assign AML risk. Pt and disease characteristics were summarized, described, and compared with Fisher exact tests and Wilcoxon rank-sum tests for categorical and continuous data, respectively. Pts were grouped into 4 quartiles based on ADI national percentile. Subsequent models were fit with ADI dichotomized at the median after adjacent ADI groups were removed with backward elimination. Associations between overall survival (OS) and pt and disease characteristics, insurance status, race, ethnicity, ONN services, and ADI were investigated. OS was defined as the time from diagnosis (dx) to death from any cause, with surviving subjects censored at the time of last follow-up. Kaplan-Meier methods were used to summarize OS and calculate landmark survival rates. Survival was compared with unadjusted log-rank tests. Cox proportional hazards models were used to estimate hazard ratios (HR) and 95% confidence intervals (CIs) associated with OS. Results: Three hundred eighty pts with available baseline characteristics were included in our analysis ( Table 1) . For pts <60 who received intensive induction and had available ADI (N=86), there was a significant difference in OS amongst the quartiles of ADI (P=0.007), with differences even more pronounced with dichotomized ADI (P<0.001) ( Figure 1). With a median follow-up of 38.1 months for the intensively treated pts <60, the estimated two-year OS was 96.6% for more advantaged/low ADI pts and 55.4% for less advantaged/high ADI pts (HR 5.21; 95% CI 1.82 to 14.95). Within the cohort of pts <60 who received intensive induction, sixty-eight percent were Non-Hispanic White and 28% were Non-Hispanic Black. Many (66%) were privately insured at dx, with 24% uninsured or with Medicaid. ONN services were accessed by most (72%) pts with known ADI. Care barriers were expressed by pts of all ADI quartiles, with transportation being the only barrier most reported by pts of increased disadvantage (P<0.01). Forty-two percent of pts received SCT (N=38). Nearly 60% of socially advantaged pts (ADI≤51) received SCT versus 33% of socially disadvantaged pts (P=0.03). In univariate models, receipt of SCT (P=0.016) was associated with improved OS while receiving navigation services (P=0.32) was not. Conclusions: Higher ADI was associated with inferior OS in AML pts <60 who received intensive induction. Receipt of SCT was observed more often in pts with more neighborhood advantage, which is of great importance since SCT improved OS in this cohort. Although insurance status is often linked to SCT access, insurance status did not significantly impact OS. Of the ONN reported barriers to care, transportation issues had a greater impact on pts with more neighborhood disadvantage. Expanding access to SCT and addressing barriers to care, such as transportation, is necessary to overcome the detrimental impact of neighborhood disadvantage on survival in AML.

Enhanced Support Services Including Nurse Navigation Mitigate Socioeconomic Disparities in the Treatment of Patients with Acute Lymphoblastic Leukemia

Background: Despite recent advances in therapy (especially in the pediatric population), the treatment of acute lymphoblastic leukemia (ALL) in adult patients remains extremely challenging with only an estimated 30-40% of patients achieving long-term remission. Therefore, it is imperative to identify barriers that may impact delivery of therapy and lead to disparities of outcomes. One area of concern that has been consistently identified is the impact of socioeconomic disparities on the delivery of care. The primary objective of this study is to determine whether increased neighborhood socioeconomic disadvantage as measured by the Area Deprivation Index (ADI) impacts overall survival (OS) in patients with ALL. Methods: All patients who presented to the Levine Cancer Institute, a tertiary hospital-based specialty practice, from January 1, 2016 to December 31, 2022 were eligible for inclusion. Patients were included for final analysis if they were aged ≥ 18 years, and had a verified new diagnosis of ALL. All patients received supportive care per institutional standards including nurse navigation, social work, and financial counseling with referral to Financial Toxicity Tumor Board if indicated. Patient demographic, treatment, and disease characteristics were summarized with frequencies (and percentages) or medians (and ranges). Correlation between national and state ADIs were assessed with Spearman's rank correlation coefficient. National and state ADI were analyzed as continuous ranks and as quartile (median for both national and state ADI; quartiles for national ADI). Kaplan-Meier methods were used to summarize OS and estimate landmark survival rates. Cox proportional-hazards models estimated hazard ratios and 95% confidence intervals associated with ADI. Multivariable models with adjustments for clinical covariates included age at diagnosis, risk group, and treatment received (including Oncology Nurse Navigation [ONN] services). Results: A total of 100 patients were found to meet criteria for inclusion. Specific characteristics of the analyzed population are listed in Table 1. The population had a median age of 54 years and were primarily treated per three treatment paradigms (standard adult intensive (57%), pediatric-based (14%), and reduced-intensity (28%)). Overall median follow-up (95% CI) was 52.2 months (44.1, 55.5) with a median OS of 51.4 months (25.3 to non-estimable) and median relapse free survival (RFS) of 22.8 months (17.0 to 35.7). When dichotomized by median ADI, there was no significant difference in patient characteristics in the two groups including age, gender, race/ethnicity, ALL type, insurance type, induction regimen, and receipt of ONN services. In univariate modeling, ADI as a continuous variable was not found to be associated with OS (HR 1.01; 95% CI 0.99-1.02, P=0.321) or RFS (HR 1.01; 95% CI 0.99-1.02, P=0.288). This lack of association remained true when dichotomized by median ADI into high and low ADI areas (OS HR 1.01; 95% CI 0.58-1.79, P=0.966; RFS HR 1.17; 95% CI 0.70-1.94, P=0.552), as well as by splitting ADI into quartiles (Figure 1). A multivariate model including age at diagnosis, ALL type, ONN services received, and treatment regimen similarly showed no association between ADI and OS (p=0.221) and RFS (p=0.453). Of particular interest is the high extent of navigation services received in this population (62.8% of patients in areas of less disadvantage, and 73.5% of patients from areas of higher disadvantage). Patients who received navigation services also appeared to be a higher risk population, as multi-variable modeling confirmed both decreased OS (HR 2.11; 95% CI 1.12-4.00, P=0.023) and RFS (HR 2.08; 95% CI 1.17-3.71, P=0.012) when compared to those who were not deemed by the nurse navigators to need this service. Conclusions: Contrary to larger database derived studies, patients with ALL treated at our center did not show differences in OS or RFS when compared by neighborhood disadvantage. This is likely a consequence of the strong support systems available at this institution in nurse navigation and financial toxicity related programs which help mitigate some of the risk factors for disparate outcomes. These findings should be validated in a larger cohort with prospective data with a particular focus on designing sustainable and realistic options to be utilized at community-based and underserved systems.

Increasing the assessment rates of the social determinants of health (SDoH) in patients with newly diagnosed breast cancer at a safety-net health system.

79 Background: SDoH are non-medical factors that can influence health outcomes. The negative impact of SDoH on vulnerable populations such as racial and ethnic minorities contributes to health disparities; therefore, consistent, accurate, and comprehensive assessment of SDoH is a first step towards promoting health equity and eliminating disparities. This is particularly important in safety-net systems where the patients’ burden of SDoH is disproportionately high. In this quality improvement project, we aimed to increase the SDoH assessment rate from the initial visit for newly diagnosed breast cancer patients. Methods: Parkland Health (PH) is one of the largest safety-net systems in the US and is affiliated with the UT Southwestern Harold C. Simmons Comprehensive Cancer Center (NCI-CCC). PH provides a wide range of support services such as transportation, childcare, medication assistance, nutrition education, etc., to patients, however, these services are likely underutilized due to a lack of consistent and accurate assessment of patient needs. A multidisciplinary team, supported by the ASCO Quality Training Program and sponsored by the Susan G. Komen Foundation, mapped the relevant clinic processes and performed a root cause analysis. Interventions included developing the relevant policies and procedures, electronic health record training, and interview training (first PDSA cycle). SDoH assessment was initially included in the Oncology Nurse Navigator (ONN) workflow but later was expanded to include clinic nurses (second PDSA cycle). The goal of the project was to increase SDoH assessment within 2 weeks from the initial clinic visit to 50%. Results: In the year before the intervention, the SDoH assessment rate for newly diagnosed breast cancer patients was at 2.7%. Incorporating SDoH assessment into the ONN’s workflow resulted in an initial increase in the completion rate to 31%, however, we observed a subsequent drop in the assessment rate to a monthly average of 15%. Reasons included the ONN’s patient panel size (350 new breast cancer patients annually), competing navigation priorities, and concurrent clinics. In the second PDSA cycle, all RNs were trained on completing SDoH assessments. In the 7 weeks following the second PDSA cycle, the assessment rate rose to an average of 76% per week. Conclusions: We increased the SDoH assessment rate from a baseline of 2.7% to 76% by improving workflows and leveraging current resources. Based on the lessons learned, we plan to add another ONN position to make the patient panel size more manageable. In addition, we plan to use MyChart messaging and tablets to self-administer the SDoH questionnaire to patients during the visit. These strategies allow to expand of the SDoH assessment for established patients, accounting for evolving patient needs throughout their cancer journey.

Feasibility of Weekly Electronic Health Record-Embedded Patient-Reported Outcomes for Patients Starting Oral Cancer-Directed Therapy.

To examine the feasibility of integrating a symptom management platform into the electronic health record (EHR) using electronic patient-reported outcomes (ePROs) during oral cancer-directed therapy (OCDT) and explore the impact of prompting oncology nurse navigators (ONNs) to respond to severe symptomatic adverse events (SAEs). Adults prescribed OCDT at Dana-Farber Cancer Institute were consecutively invited to participate. Participants received weekly messages to complete ePROs. The first half enrolled in a passive (P) group where ePROs responses could be viewed anytime, but outreach was not expected. The second half enrolled in an active (A) group where severe SAEs prompted emails to ONNs for outreach within 1 business day. Feasibility was the proportion of participants completing ≥2 ePROs during the first 30 days. Participants were followed for up to 90 days. From June 25, 2019, to August 18, 2021, 100 participants enrolled, and 96 remained enrolled for at least 30 days. Overall, average age was 59 years, 80% female, and 9% used the platform in Spanish. Twenty-two A (45%) and 27 P (57%) participants met the feasibility threshold (P = .26). ePROs returned at 30 days were similar (P = .50): 0 ePROs 17 A, 13 P; 1 ePRO 10 A, 7 P; 2 ePROs 3 A, 5 P; 3 ePROs 1 A, 4 P; 4 ePROs 7 A, 8 P; and 5 ePROs 11 A, 10 P. Documented telephone encounters at 30 days were similar (109 A, 101 P; P = .86). EHR-embedded ePROs administered weekly for people on OCDT was feasible, although many went incomplete. ePRO completion was not clearly affected by nursing calls for severe SAEs. Future efforts will investigate improving engagement and addressing symptoms proactively.

Role of Oncology Nurse Navigators: An Integrative Review

Role of Oncology Nurse Navigators: An Integrative Review

Effectiveness of oncology nurse navigator on the incidence of postoperative pulmonary complications in gastric cancer patients undergoing radical gastrectomy

BackgroundManagement of postoperative pulmonary complications (PPCs) can be challenging in gastric cancer patients undergoing radical gastrectomy and is always associated with poor prognosis. Even though oncology nurse navigator (ONN) provide effective and critical individualized care to patients, little is known about their impact on the occurrence of PPCs in gastric cancer patients. This study aimed to determine whether ONN decreases the incidence of PPCs in gastric cancer patients.MethodsThis was a retrospective review in which data for gastric cancer patients at one centre was evaluated before and after an ONN hired. An ONN was introduced to patients at their initial visit to manage pulmonary complications throughout treatment. The research was conducted from 1 August 2020 to 31 January 2022. The study participants were divided into the non-ONN group (from 1 August 2020 to 31 January 2021) and the ONN group (from 1 August 2021 to 31 January 2022). The incidence and severity of PPCs between the groups were then compared.ResultsONN significantly decreased the incidence of PPCs (15.0% vs. 9.8%) (OR = 2.532(95% CI: 1.087–3.378, P = 0.045)), but there was no significant difference in the components of PPCs including pleural effusion, atelectasis, respiratory infection, and pneumothorax. The severity of PPCs was also significantly higher in the non-ONN group (p = 0.020). No significant statistical difference was observed for the major pulmonary complications (grade ≥ 3) between the two groups (p = 0.286).ConclusionsRole of ONN significantly decrease the incidence of PPCs in gastric cancer patients undergoing radical gastrectomy.

Promoting adherence to germline genetic testing for pancreatic cancer.

e18737 Background: Updated NCCN guidelines support universal germline genetic testing (GGT) for pancreatic ductal adenocarcinoma (PDAC), and literature recommends ordering GGT for PDAC at or near first oncology consult (Chittenden et al., 2021). However, recent studies demonstrate that adherence to updated GGT guidelines for PDAC is poor, and testing rates remain suboptimal (Klatte et al., 2023). A three-month pre-intervention audit (4/2022-6/2022) revealed that less than half of patients diagnosed with PDAC at our community cancer facility underwent GGT in alignment with NCCN guidelines, and only 33% had GGT ordered at the first oncology visit and before treatment. Automated workflows can increase GGT rates for PDAC, but community hospitals may lack infrastructure to support this type of model. Oncology Nurse Navigators (ONN) represent a practical tool for fostering guideline-concordant care for cancer patients treated in the community. The present study explored whether the use of a prompt (or alert message) facilitated by the ONN could change compliance with current recommendations for GGT at a community cancer institute. Methods: We conducted a series of four specific strategies, over a three-month period (7/2022-9/2022). 1. Targeted education was provided to oncologists about NCCN updates. 2. ONN identified newly diagnosed PDAC patients. 3. ONN implemented a prompting process (sending a message to patient’s oncologist within one week of identification of PDAC diagnosis) to review/remind about GGT. 4. Chart review was performed at designated intervals to monitor GGT ordering. The health system’s ONN tracking tool was used to gather, monitor data. Analysis was performed with SPSS software. Results: Nine PDAC patients were identified that met inclusion criteria. Following the ONN prompting intervention there was a 56% increase in PDAC patients who had testing ordered as recommended by NCCN guidelines, a 103% increase in PDAC patients who had GGT ordered at first consult and before treatment initiation. While differences between pre and post intervention were not statistically significant (Fishers Exact Test), the prompting process stimulated valuable discussion between Medical Oncologists (MO) and the ONN, possibly shaping ordering decisions. This included two MOs who switched to ordering GGT at first consult and one MO who had not been planning to order GGT and did so following the prompt. Conclusions: An ONN facilitated prompt offers a simple yet effective means for promoting adherence to GGT guidelines for PDAC in the community setting. ONNs can play a key role in identification of patients and communication and collaboration with MOs before the first oncology consult. The prompting process opens conversation and provides opportunities to clarify, educate about NCCN guidelines in the community setting.

Identifying clinical trial candidates using AI predictions of treatment change: A pilot implementation study.

1515 Background: Precision oncology clinical trials often struggle to accrue due to the difficulty of identifying patients whose tumors meet complex tumor genomic matching criteria at propitious moments when they need new treatment. We conducted a pilot of deploying an artificial-intelligence (AI) model to find such patients and facilitate clinical trial matching workflows at a large academic cancer center. Methods: An AI model was trained to predict initiation of new palliative intent systemic therapy within 30 days of a given imaging report (CT, MRI, bone scan, or PET-CT), using the text of that report and prior reports for each patient. The model architecture and performance were previously published (Kehl et al, JCO-CCI 2021 5:622-630). From April to December 2022, the model was applied prospectively each time patients with solid tumors that had undergone next-generation sequencing underwent an imaging study. Model output was linked to the MatchMiner tool, which matches patients to clinical trials using tumor genomics (Klein et al, NPJ Precis Oncol 2022 6(1):69). The output consisted of lists of patients with tumor genomic matches to specific trials, sorted in order of the likelihood of changing treatment within 30 days. This information was provided to an oncology nurse navigator (ONN) charged with coordinating recruitment to early-phase targeted and immunotherapy trials. For 9 high priority trials, the ONN reviewed records for each patient flagged as likely to change treatment and contacted treating oncologists when patients appeared potentially eligible. The proportions of records leading to oncologist contact, and reasons for oncologist non-contact, were analyzed. Results: 2093 patients had tumors with genomic matches to the 9 trials of interest; 492 patients (24%) were deemed “likely” to change treatment by our AI model at least once during the pilot. The treating oncologist for 66 patients (3% of the total; 13% of 492 “likely” patients) was contacted after ONN review for potential eligibility. Reasons for not contacting treating oncologists included cases where they had already decided to continue current treatment (21%); the trial had no slots at the time (14%); or the patient was ineligible on nurse navigator review (12%); or had already been evaluated for the trial (7%), started new treatment (18%), or enrolled in hospice (5%). Of the 66 patients whose oncologists were contacted, 9 patients had a consult regarding early phase trials; 4 consented to participate; and all 4 received protocol treatment. Conclusions: Identifying potential precision clinical trial candidates by using AI to find patients likely to change treatment is feasible, but many other factors also impact potential trial enrollment. A prospective study is planned to evaluate the impact of sharing clinical trial information directly with treating oncologists when our model predicts a high probability of treatment change.

Improving compliance with post-hospitalization follow-up visits: A single community cancer center experience.

e13508 Background: Hospital discharge follow-up visits are crucial for the continuity of care and for reducing rehospitalizations. They prevent medication disruptions, missing opportunities for making a post-discharge treatment plan, and identifying complications. Our aim is: 1. To review the compliance of post-hospitalization follow-ups for a medical specialty. 2. To study the timeline from the discharge to the time they were seen in the hematology-oncology clinic. 3. To identify why patients seen in the hospital were lost to follow-up. 4. To improve compliance with post-discharge follow-up visits. Methods: This is a retrospective chart review of patients seen by our Hematology-oncologists at Einstein Medical Center Montgomery between January 2021 to December 2021. Data collected included: Specialty consulted- Hematology versus Oncology; if follow-up is indicated; if they have a Hematology Oncology provider elsewhere; if they were seen in the clinic and how long did it take for the patient to be seen after discharge; if they did not follow-up, the reason for failure to follow-up was reviewed. We defined “No contact from our office” when there was no documentation that our office staff tried to contact the patient to make a follow-up appointment. Results: Out of the total 526 inpatient consultations, 338 were for hematology, 169 were for oncology and 19 were for both hematology and oncology. Follow-up upon discharge was recommended for 429 patients (82%). Out of those 429 patients, 168 patients (39%) were seen in the clinic and 176 patients (41%) were not seen after discharge from the hospital. 85 patients (20%) had a Hematology Oncology provider in a different institution. 118 patients (68%) in this group of 168 patients were seen in less than 30 days. 41% of the patients that were not seen after discharge from the hospital had various reasons, which included 18% of patients who expired, and 10% of patients who chose to be on comfort care. 41% of the patients were lost to follow-up (unable to track after the discharge – data was limited due to this being a retrospective study), 2% of the patients were incarcerated, 23% of the patients had no contact from our office to make a follow-up appointment, 1% of the patients were subsequently hospitalized, and finally, 5% of the patients followed up in a different institution. Conclusions: Hematology was consulted more often than Oncology for the subspecialty in-hospital consultations. 41% of the patients were lost to follow-up due to reasons unknown who should have been seen in the Hematology/Oncology Clinic. Interventions that we recommend in improving this compliance are 1. Formulate a rapid discharge clinic – run by Hematology-Oncology fellows with attending oversight. 2. Involve the Oncology Nurse Navigator to help coordinate patient follow-up. 3. Provide better education for hospital staff about the importance of reviewing discharge instructions with the patients.

Dynamics and processes influencing role integration of advanced practice nurses and nurse navigators in oncology teams.

Exploring the persisting presence of underlying processes, dynamics, experienced barriers and facilitators of Advanced Practice Nurses (APN) in oncology and Oncology Nurse Navigators (ONN) during their role integration in an interprofessional team over a research period of seven years. A qualitative study based on the principles of Grounded Theory, in which individual semi-structured interviews and focus groups were conducted with 51 ONN and APN from 11 university and local hospitals in Belgium between 2011-2018. Data were analyzed to develop a framework that consists of different themes. ONN and APN experienced a lonely journey during role integration. They were searching for partners, medical knowledge and acknowledgement from the interprofessional team. ONN and APN had a watchful attitude and tried to make themselves visible to ensure they were involved in the team and to preserve their role and responsibilities. An unclear role description to the interprofessional team, and a lack of coaching and guidance were influencing factors in the experience of ONN and APN. ONN and APN in oncology feel difficulties to integrate their role in existing interprofessional teams. A lack of role clarity, the interprofessional team environment and a desire for coaching and guidance are influencing factors to implement APN roles. Coaching and mentorship of novice ONN/APN and their interprofessional team and healthcare managers are needed to address these issues. These findings could form the basis for a mentorship program for ONN/APN and their interprofessional team to enhance role integration.

An integrative review on the oncology nurse navigator role in the Canadian context.

Several Canadian provincial cancer agencies have adopted a nurse-led model of patient navigation to decrease care fragmentation in the system. The scope of competencies of the oncology nurse navigator (ONN) in Canada has evolved over the years in response to emerging cancer care challenges. This integrative review aimed to outline the scope of competencies of the ONN role in Canada. Three databases were searched since its inception to identify Canadian studies or theoretical papers on the role of ONNs. The search yielded 62 articles of which 39 were included in the review. Three interdependent role domains were identified. The first domain of care coordinator highlighted the ONN as a coordinator of health and practical needs along the care journey. The second framed the ONN as a change agent, through increasing patients' health literacy, creating partnerships, and trusting relationships. ONNs were also described as a supporter of wellbeing, or a champion of emotional, multidimensional needs, and a transformer of the context of care. All domains were central to the navigator's success in addressing inequities in care and improving patient outcomes across care settings.

Oncology Nurse Navigator Effect on Emergency Department Visits and Hospital Admissions of Adults With Cancer Post-Outpatient Chemotherapy.

To examine the effect of oncology nurse navigators (ONNs) on the number of emergency department (ED) visits and hospital admissions (HAs) of adults with cancer post-outpatient chemotherapy. 1,370 patients with cancer between January 1, 2018, and December 31, 2019, in a comprehensive community cancer center in southern California. A descriptive cross-sectional study was conducted using retrospective electronic health records. Primary analysis included bivariate and multiple linear regression to identify correlates of ED visits and HAs in terms of ONN involvement. About 35% of patients had an ED visit or HA. Anemia, dehydration, and pain were common diagnoses. No significant differences were found in ED visits and HAs by ONN group. Medicare and chemotherapy administration location contributed to the likelihood of ED visits; nausea, pain, and pneumonia contributed to the likelihood of HAs. ED visits and HAs are not appropriate clinical outcomes to measure ONNs' efficacy. Further research is needed to understand the long-term fiscal and operational outcomes of ONNs.

Transitions in care for ER patients with a suspected cancer diagnosis.

117 Background: The oncology nurse navigators (ONNs) at Penn Medicine’s Abramson Cancer Center (ACC) observed that patients seen in the Emergency Room (ER) and found to have a suspicion of cancer were being told to call a medical oncologist. The oncologist in the ACC are highly specialized and since the patient has not had a confirmed cancer diagnosis, they were being told they couldn’t schedule an appointment. Some patients waited for the ACC to call them to schedule. When this didn’t happen they would call the ACC a week later. These barriers led to delays in care, poor patient experience, and a financial loss for the health system. The ONNs identified this as an opportunity to change the process to improve patient care. Methods: The initiative formally began in June 2021 when the ONNs reached out to the ER leadership to collaborate on a quality improvement project to streamline the process from ER visit to oncology work up and diagnosis. Direct referral to oncology nurse navigation from the ER facilitates timely navigation assessment and coordination of care. The Plan Do Study Act (PDSA) methodology was utilized. A “Consult to Nurse Navigation” order was built into the electronic medical record (EMR) for ER providers to directly refer patients to the navigation team. The ONNs contacted the patient within one business day to assess next steps. The ONNs scheduled the patient with the appropriate oncology specialist. The ONNs follows the patient through the diagnostic phase of care and assists with decreasing barriers to care. Data collection is ongoing to assess the impact of the interventions. Results: The EMR consult to ONNs went live April 2022. It includes 3 hospital ERs in the health system with diverse populations that often have limited access to health care. To date, 90% were appropriate referrals and triaged to cancer specialists for diagnostic workup and treatment. 90% had insurance accepted by the health system. Patients with unacceptable insurance plans were referred to ER social work and financial advocates. 70% were diagnosed with cancer and began treatment. Conclusions: ONNs are vital in identifying and removing barriers to care. The ONN team’s clinical knowledge, assessment skills, and expertise of the Penn health system have closed a gap in care while increasing patient satisfaction, patient retention, and downstream revenue. The ONNs leadership has directly enhanced the diagnostic process and timeliness to care for patients newly effected by cancer.

Positive impact of oncology nurse navigation based on health insurance in head and neck cancer patients.

e18545 Background: Health disparity in squamous cell carcinoma of the head and neck (SCCHN) is well-recognized. Privately insured SCCHN patients are observed to have better outcomes, but underlying factors are poorly understood. Oncology nurse navigators (ONN) are a well-established role focused on optimizing cancer care and patient experience. The effects of ONN on bridging health disparities have not been demonstrated. We sought to characterize health and outcome disparities in patients diagnosed with oropharyngeal cancers and to assess if the implementation of ONN bridges gaps in health disparities. Methods: Patients aged >18 diagnosed with node positive, non-metastatic oropharyngeal cancers at a large hybrid academic-community cancer center between June 2018 and September 2021 were analyzed retrospectively. Baseline demographic, socioeconomic and clinicopathologic factors including the frequency and percentage of patients receiving ONN were summarized. Clinical outcomes were assessed as a function of baseline factors and ONN. Overall survival (OS) and progression free survival (PFS) were evaluated with Kaplan Meier methods. Results: 184 patients were evaluated. Median age at diagnosis 62 (range 33-91). Median follow-up 24 months. The majority were HPV+ (73%). Navigation received in 64%. More males presented with cN1+ disease than females (57% v. 37%; p = 0.053). More Black patients presented with cN1+ disease than White patients (76% v. 50%; p = 0.017). More privately insured patients (92%) went to imaging after definitive treatment versus those with Medicaid (MD)/Self-pay (SP) (78%) or Medicare (MC)/Veteran’s affairs (VA) (78%) (p = 0.043), while more navigated patients went to imaging after definitive treatment than non-navigated patients (70% v. 40%; p = 0.003). Univariate modeling indicated clinical nodal stage, HPV status, race, and insurance status were associated with OS and PFS. In multivariable modeling adjusted for age, nodal stage, and HPV status, there was a disparity in OS associated with insurance type (MD/SP v. Private: HR 9.24, 95% CI = 2.34 to 36.41 and MC/VA; p = 0.004). There was a significant interaction of navigation and insurance type (p = 0.0157). In those not navigated, a difference in hazards exists between MD/SP or MC/VA compared with private insurance. This difference was not detected in those navigated. Similar interaction of navigation and insurance was noted in the analysis of PFS. Conclusions: We observed a disparity in patients with non-private insurance having an inferior PFS, OS and reduced rates of imaging after definitive treatment. An improved rate of post-treatment imaging was significantly associated with ONN. There was a trend towards benefit in outcomes for those receiving ONN but without private insurance suggesting that ONN may help mitigate disparities in the non-private insurance groups.