Purpose The COVID-19 pandemic has exacerbated cancer treatment disparities, including accessibility to resources. We describe the process and outcomes of a new proactive, virtual nurse-led, resource center navigation model enhanced by using volunteer patient navigators. Using known patient risk factors, this model provides interventions to reduce barriers to care, with an emphasis on non-English-speaking populations. Methods Patients were included if they (1) were in active cancer treatment and (2) had one or more known risk factors: distance from cancer hospital, needing complex care, 65 years or older, malignant hematological diagnosis, new treatment start, lives alone, non-English speaker, or a new hospital discharge . Nurse navigators triaged referrals to appropriate team members who identified and addressed barriers to care. Results The program engaged with 586 adult cancer patients over 1459 encounters. The most common risk factors included distance (59.7%), complex care (48.8%), and new treatment start (43.5%). The most common interventions were core education (69.4%), emotional support (61.2%), and education (35.7%). Statistical differences were found between Spanish-speaking ( n = 118) and non-Spanish-speaking patients ( n = 468). While Spanish-speaking patients had fewer risk factors (1.95 vs. 2.80, p ≤ .0001), they had nearly double the number of visits (4.27 vs. 2.04, p ≤ .0001) and 69% more interventions (8.26 vs. 4.90, p ≤ .0001). Many patients (42.7%) required follow-up visits. Conclusion We successfully established a new navigation model for the resource center during the pandemic that identified and reduced barriers to care, particularly in the Spanish-speaking population. Supplementary Information The online version contains supplementary material available at 10.1007/s00520-021-06147-3.

Purpose Cancer patients have many medical and psychosocial needs, which may increase during the COVID-19 pandemic. We sought to (1) risk-stratify hematology/oncology patients using general medicine and cancer-specific methods to identify those at high risk for acute care utilization, (2) measure the correlation between two risk stratification methods, and (3) perform a telephone-based needs assessment with intervention for high-risk patients. Methods Patients were risk-stratified using a general medical health composite score (HCS) and a cancer-specific risk (CSR) stratification based on disease and treatment characteristics. The correlation between HCS and CSR was measured using Spearman's correlation. A multidisciplinary team developed a focused needs assessment script with recommended interventions for patients categorized as high-risk by either method. The number of patient needs identified and referrals for services made in the first month of outreach are reported. Results A total of 1697 patients were risk-stratified, with 17% high-risk using HCS and 22% high-risk using CSR. Correlation between HCS and CSR was modest (ρ = 0.41). During the first month of the pilot, 286 patients were called for outreach with 245 contacted (86%). Commonly identified needs were financial difficulties (17%), uncontrolled symptoms (15%), and interest in advance care planning (13%), resulting in referral for supportive services for 33% of patients. Conclusion There is a high burden of unmet medical and psychosocial needs in hematology/oncology patients during the COVID-19 pandemic. A telephone-based outreach program results in the identification of and intervention for these needs; however, additional cancer-specific risk models are needed to improve targeting to high-risk patients.

The Intermountain Healthcare system has developed a text-based, electronic reference system for nonphysician staff to provide patient care guidelines intended to reduce variability in bedside care processes and improve patient outcomes. Implementation issues with two interface tools used to deploy the electronic documents at the bedside have caused difficulty with document accessibility. A third interface tool (Viewer) was designed to solve the accessibility problems. This study was designed to compare the time spent searching for information and success of information retrieval from all three interfaces before clinical deployment of the Viewer interface. Study results were used by nursing leadership in a decision to continue supporting the electronic dissemination of text-based practice guidelines for nonphysician staff within our health system's acute care settings.

211 Background: Cancer patients have many medical and psychosocial needs, which may increase during the coronavirus pandemic and may be difficult to identify or address in the absence of in-person patient visits. We sought to (1) risk stratify hematology/oncology patients using general medicine and cancer-specific methods to identify those at high risk for acute care utilization, (2) measure the correlation between risk-stratification methods, and (3) perform a phone-based needs assessment with intervention for these patients. Methods: Patients were risk-stratified using a general medical health composite score (HCS) embedded in the electronic medical record, and a cancer-specific risk (CSR) stratification based on disease and treatment characteristics. The correlation between HCS and CSR was measured using Spearman’s correlation. A multi-disciplinary team developed a focused needs assessment script with recommended interventions for patients categorized as high-risk by either method. The number of patient needs identified and referrals for services made in the first month of outreach are reported. Results: 1,421 patients were risk stratified, with 15% high-risk using HCS and 21.2% high-risk using CSR. Overall correlation between HCS and CSR was modest (r = 0.39). During the first month of the pilot, 287 patients were called for outreach with 245 contacted (85%). Commonly identified needs were financial difficulties (17%), uncontrolled symptoms (15%), and interest in advance care planning (13%), resulting in referral for supportive services for 33% of patients. Conclusions: There is a high burden of unmet medical and psychosocial needs in hematology/oncology patients during the coronavirus pandemic. A phone-based outreach program results in identification of and intervention for these needs, however additional cancer-specific risk models are needed to improve targeting to high-risk patients. This process can serve as a framework for other institutions wishing to implement similar outreach programs during this pandemic. [Table: see text]

This chapter introduces strategies to meet knowledge transfer needs. The clinical knowledge repository infrastructure and tools developed at Intermountain Healthcare are described. The knowledge repository (KR) is a database with services housing knowledge assets. The electronic tools are used to access and manipulate the assets. The tools include (1) the Knowledge Repository Online, used to load, view, and review knowledge assets stored in the KR, (2) the Knowledge Authoring Tool, used to compose knowledge assets using schema-based XML templates, (3) the viewer, used for easy and rapid access to a predetermined collection of knowledge assets, and (4) KR Reports, used to mine monitoring data about KR tool usage and the user experience. The process for knowledge asset development is described, and four project-specific case studies are presented describing asset development incorporating the infrastructure and tools. The value added by knowledge engineers to the knowledge transfer process is discussed.