Background: Oncology navigation reduces barriers to cancer care, yet patient navigation is not universally provided. Geographic location may limit physical access to care, and patients can be confused about their cancer diagnosis and treatment options. A virtual navigation program was created with the Oncology Nursing Society Nurse Navigation Core Competencies. The program provides access to care, individualized education, and care coordination promoting self-advocacy in the cancer journey.
Objectives: The program included the following objectives: (1) to provide individualized patient education through phone contact as well as through written communication; (2) to increase awareness of the cancer diagnosis, associated health issues, and treatment options; and (3) to provide patient referrals and connections to others (eg, consultation with a medical oncologist, clinical trial evaluation, or genetic counseling).
Methods: The study was guided by a mixed methods approach using an online instrument with a key research question: How effective is virtual navigation in providing critical factors to promote self-advocacy along the cancer continuum? Ninety-five oncology patients participated in the research by completing an online assessment after navigation that examined individualized education and coordinated cancer care.
Results: Diversity in age, tumor type, and geographical location emerged in the national data. After virtual navigation, 84% of patients better understood their diagnosis and treatment options; 83% were better able to make informed decisions. A statistically significant increase in knowledge on “health issues that come from cancer” emerged postnavigation (P <.0001). Navigation also improved “coordinated cancer care” (P = .018).
Discussion: Virtual navigation increased patient access and has the potential to facilitate self-advocacy in the oncology patient despite geographical location, age, and tumor type.
Conclusion: The findings suggest virtual navigation is a viable solution to reduce barriers to cancer care and increase patient outcomes, despite geographical location. Through virtual connection, navigation may empower patients to help them overcome the challenges many face in the cancer journey.
Patient navigation has been shown to improve patient engagement and participation in clinical trials1-3 and reduce barriers to cancer care.4,5 Despite growing evidence of value, oncology patient navigation is not universally understood or provided.6 Some patients are limited by location, with minimal physical access. Even with access to navigation services, variations may impact patient care and satisfaction.7,8 Key factors promote self-advocacy to empower individuals through the cancer journey. However, patients and their families can be confused about their treatment options or uncomfortable with healthcare systems.9,10 Using the Oncology Nursing Society Nurse Navigation Core Competencies,11 a framework including components of a navigator’s role for clinical trials was developed at our institute to provide access to cancer patients.
This is a virtual navigation program. Virtual navigation would also include telephone triage, which can result in significant cost savings for a patient.12 This program, with access regardless of geographic location, provides individualized patient education, care coordination, referrals, and documentation through medical records and personal contact. Navigators meet with oncologists for case review and maintain a library of available clinical trials to ensure that referrals are made when necessary. Navigation improves patient outcomes, yet more research is warranted to evaluate its efficacy on mitigating barriers to care.3,5,13 Thus, our institute conducted rigorous research on a novel navigation program to examine the impact on patient care.
Virtual Navigation Program
Over the past 10 years, under the leadership of a medical oncologist, the institute developed a strong oncology research position. Although the institute serves 1.6 million residents in the Phoenix market, we established regional, national, and international collaborations with oncology research spanning pancreatic, breast, ovarian, lung, head and neck, colorectal, prostate, and rare cancers. Leaders have partnered to build a robust virtual navigation infrastructure and navigation program (program) that serves the institute and partners such as Translational Genomics Research Institute (TGen), an affiliate of City of Hope. Oncology nurse navigators are oncology team members and are immersed in faculty meetings, safety monitoring boards, and protocol review committees, and thus have immediate access to oncologists. Program navigators respond to all calls in person and provide personalized service. Without giving medical advice, they provide talking points or other tools to the caller to take back to their clinicians to promote best patient outcomes. In fact, their motto is “Every patient is his or her own advocate.”
The program has integrated key elements to increase self-advocacy and infused items into the online navigation assessment. One definition of self-advocacy indicates that it is the ability to get your individual needs met during a challenge.14 It is a critical skill for those facing the overwhelming disease and psychological burden of cancer. Hagan stated that self-advocacy consists of 3 primary skills: communicating effectively with the oncology medical team, making informed decisions, and finding strength through connection with others.14 For the purpose of this research, we added 3 skills: better understanding of the cancer diagnosis, understanding health issues that come with cancer, and feeling more motivated to manage their cancer care.
The program included the following objectives serving patients in the cancer care continuum: (1) to provide individualized patient education through phone contact as well as through written communication; (2) to increase awareness of the cancer diagnosis, associated health issues, and treatment options; and (3) to provide patient referrals and connections to others (eg, consultation with a medical oncologist, clinical trial evaluation, or genetic counseling). These elements assist patients with their coordinated cancer care and facilitate self-advocacy. The navigators meet with medical oncologists for effective case review. In collaboration with oncologists, the navigator responds to each patient’s request for information through assessing medical needs and maintains a library on available oncology clinical trials, both internally and externally, to ensure that referrals are made for appropriate services.
This investigation employed a mixed methods approach with the following research question: To what extent does the program provide key tasks (eg, individualized patient education; information concerning cancer diagnosis, health issues associated with cancer, and treatment options; care coordination and referrals) to promote self-advocacy in the cancer care continuum? Data collection procedures include both quantitative and qualitative data using an online questionnaire that included open-ended sections. A mixed methods data collection and analysis approach provides a more complete account of the experiences by patients when navigating their cancer journey.15-17 The ongoing program is tracking and documenting critical elements for replicability (eg, number served and consented in clinical trials). Program efficacy is also based on patient experience, self-advocacy, and satisfaction. The assessment item, created internally, adapted several items from the Patient Self-Advocacy Scale and employed Hagan’s research.14 The researcher followed a rigorous instrument (scale) development procedure, which increased validity and reliability.
Instrument Development: Content Validity
Information about the content validity of the measure was critical for drawing conclusions about the scale’s quality. Content validity was defined in this study’s instrument development as the degree to which an instrument adequately samples the research domain of interest.18 Thus, we determined that content validity concerns the degree to which a sample of items, taken together, constitutes an adequate operational definition of a construct. One approach typically involves having a team of experts indicate whether each item on a scale is congruent with (or relevant to) the construct, computing the percentage of items deemed relevant for each expert. The most widely reported measure of content validity has been the content validity index (CVI). The CVI users in the nursing area often cite Davis19 and Waltz et al.20 Scale developers, using this method, provide evidence of content validity by computing a CVI using ratings of item relevance by internal content experts.
In this study, content experts were asked to rate each scale item in terms of relevance to the underlying construct. Despite the minimum of 3 experts suggested, our study employed 6 navigation content experts. We used a 5-point rating scale with 1 = not relevant, 2 = somewhat relevant, 3 = moderately relevant (average), 4 = quite relevant, and 5 = highly relevant. For each item, the item-level CVI is computed. Items were subject to 2 rounds of rating by content experts and refined until the final instrument was constructed. When there are 6 or more judges, the standard can be relaxed, but the rating should not be lower than .78, which was followed in this study.
Assessment Item Categories
Oncology patients were first asked questions that elicited their prior knowledge about health issues associated with cancer and assertiveness before their contact with the program. Items included “I have enough knowledge about the health issues that come from cancer” and “I am more assertive about my healthcare needs than most individuals.” In addition, we asked if it is important for people with cancer to learn as much as they can about their illness and treatment. This provided some baseline information on the respondents.
To answer to what extent the program is providing effective education, patients were asked whether the patient education (provided over the phone and through written information) helped them understand their cancer diagnosis and health issues that come with cancer.
To answer whether the program facilitated self-advocacy in the cancer care continuum, the following 6 items were included: Are you better able to make informed decisions about your cancer care and treatment? Do you have better understanding of your diagnosis and, if needed, treatment options? Are you better able to formulate questions with the oncologist or the medical team? Are you finding strength through connecting with others? Patients were also asked if they were more motivated to manage their care in the cancer journey and if navigation improved their coordinated care experience.
Assessment Administration (Online Survey)
The assessment was administered online to the navigation oncology patients, and the researcher and team sent the link to 188 subjects. We accounted for bad contact information (as our oncology patient list went back 6 months). In addition, we were contacted by family members and informed that several patients had passed away. In total, our count was 168 patients with viable contact information; we had 95 submit completed assessments (57% response rate). The researcher sent out 2 gentle reminders to patients during the survey administration.
For quantitative data, we used descriptive statistics to summarize and describe the data in a meaningful way such that patterns might emerge. For analyzing differences between groups (ie, state of Arizona data and other states’ data) a, Wilcoxon signed rank test (SPSS v24) was used. Researchers conducted a reliability analysis, and the instrument had a Cronbach α of .94. The Cronbach α coefficient of internal consistency is the most frequently used; a score of .70 or higher is considered “acceptable” in most social science research situations. The closer the Cronbach α coefficient is to 1.0, the greater the internal consistency of the items in the scale; thus, .94 is an exceptional coefficient. The instrument used a 5-point scale with 5 = Strongly agree, 4 = Agree, 3 = Neutral, 2 = Disagree, and 1 = Strongly disagree.
For qualitative data, we analyzed patient responses concerning “how the virtual navigation helped you the most” for this study. Codes derived from questions were created to reduce vast amounts of information into manageable chunks for analysis. Qualitative data analysis included a 3-step process: data reduction, data display, and conclusion drawing and verification.21 Data reduction helped sort, focus, and condense excerpts that allowed the researcher to organize the data to develop conclusions. Data were reduced and transformed through such means as selection, summary, and paraphrasing. Data display was the second major activity during which the researcher reviewed the reduced data and displayed it in a compressed way so that conclusions could be drawn. Excerpts served as the supportive evidence for categories, themes, and assertions concerning the programs. Conclusion drawing and verification were the final analytical activity for the researcher.
Most oncology patients (53%) in our sample were female; 35% were between the ages of 65 and 74 years; 26% were 55 to 64, and 18% were 45 to 54. It is noteworthy that 14% were 75 years of age or older, 4% were 25 to 34, and 3% were 35 to 44. Most patients (77%) were white; 14% were Hispanic or Latino, 7% Asian or Pacific Islander, and 2% black or African American.
The majority of responses were from 2 states, namely Arizona (44%) and California (18%), yet multiple other states were represented: Alabama, Colorado, Connecticut, Florida, Georgia, Hawaii, Illinois, Indiana, Kansas, Michigan, Montana, Nebraska, New Jersey, North Carolina, Ohio, Oklahoma, Oregon, Rhode Island, Tennessee, Texas, Utah, and Washington. Tumor types were assessed, and 49% of the sample indicated pancreas, 10% breast, 7% ovarian, 5% lung, 1% head and neck, 4% colorectal, 11% prostate, and 13% rare cancers.
Quantitative Data Results –
Prior Knowledge and Assertiveness
Baseline data were collected on patients’ prior knowledge of healthcare issues associated with cancer, assertiveness, and the value of learning more about cancer. Overall responses were strong regarding the importance of “learning as much as they can about their illness and treatments” (M = 4.82, SD = 0.52) and being assertive about their healthcare needs (M = 3.90, SD = 1.13) before the virtual navigation experience. Yet, patients were more neutral about having “enough knowledge about the health issues that come from cancer” (M = 3.21, SD = 1.26).
Arizona patients represent 44% of the responses, and other states represent the majority (56%) of the responses. As this is a virtual navigation program serving patients anywhere in the United States, investigators wanted to examine differences between responses in Arizona and those in other states regarding program outcomes.
Addressing the first items concerning initial knowledge and assertiveness, no significant differences were found among the 2 groups (oncology patients in the state of Arizona and oncology patients in other states). It is noteworthy that both groups were more neutral about having enough knowledge about “health issues that come from cancer,” yet the mean from other states was lower (M = 3.07, SD = 1.18) than the Arizona mean (M = 3.58, SD = 1.33). There were no statistically significant differences between groups (Table 1).
Individualized Education. To answer one of the research objectives concerning patient education, respondents were asked whether “The patient education (provided over the phone and through written information) helped them understand their diagnosis and health issues associated with cancer.” Overall, respondents agreed that patient education provided over the phone (M = 4.15, SD = 1.01) and in written format (M = 4.05, SD = 1.03) helped them understand their cancer type and associated health issues. There was no significant difference between education type of delivery (phone or written). Researchers found a statistically significant increase from baseline data on patient education and knowledge associated with “health issues that come from cancer” (M = 3.21, SD = 1.26) postnavigation (M = 4.15, SD = 1.01; P <.0001).
Regarding state differences, Arizona means were not as strong as other states’ means regarding receiving “patient education by phone in helping me understand the diagnosis and health issues that come from cancer” (Table 2).
Self-Advocacy. To answer whether the program facilitated self-advocacy in the cancer care continuum, key items were asked and responses revealed positive trends in facilitating self-advocacy in oncology patients across the United States in this population. Overall, all items related to self-advocacy skills were strong, as most agreed with the assessment statements (mean of 4.0 in a 1- to 5-point scale, with 5 = Strongly agree). Overall, oncology respondents agreed (M = 4.30, SD = .91) they were better able to make informed decisions about their cancer care and had a better understanding of their diagnosis and treatment options after navigation (M = 4.28, SD = 0.94). Similarly, they were better able to formulate questions with the oncologist or medical team (M = 4.24, SD = 1.02) and were finding strength through connections with others (M = 4.20, SD =1.03), 2 strong attributes of self-advocacy, according to Hagan. Oncology patients were also more motivated to manage their care in the cancer continuum (M = 4.31, SD = 0.89) and agreed that navigation improved their coordinated care experience (M = 4.15, SD = 1.11). Sixty percent of patients pursued referrals based on the recent information provided via navigation that included discussing key points with the oncologist (75%), and pursuing clinical trials (56%) and genetic (46%) and nutritional counseling (43%).
Examining state data, statistically significant differences emerged concerning one of Hagan’s key self-advocacy skills, connecting with others. Other states’ mean score (M = 4.44, SD = 0.85) was significantly higher than the Arizona mean (M = 3.90, SD = 1.16; P = .036) regarding “Finding strength through connecting with others,” which is noteworthy as these oncology patients are connecting with others virtually in the program. In addition, other states’ mean score was significantly higher (M = 4.44, SD = .85) than the Arizona mean (M = 3.83, SD = 1.24; P = .018) concerning “Navigation service improved my coordinated care experience.” It is likely that oncology patients with fewer resources in their area turned to the virtual navigation program for support.
Despite 2 significant differences, all other state data were similar between groups and represent strong responses (over 4.0 on 1-5.0 Likert scale). Data reflect that the program has the potential to facilitate self-advocacy in the oncology patient regardless of age, tumor type, or geographic location (Table 3).
Qualitative Data Results
Qualitative data revealed that the individualized education provided over the phone and in written format helped patients understand their diagnosis, health issues that come with cancer, and treatment options also reflected in the quantitative data. Understanding the diagnosis and issues associated with cancer helped patients stay motivated to manage their care in the cancer journey. Many supportive statements emerged from patient data, and 3 are represented here. One oncology patient poignantly stated, “I benefited by the time spent on the call. I also appreciate written information provided. They were diligent, professional, and gave me information to help me understand the health problems that I have, and then I can discuss health issues and options with my doctors. Despite a challenging time, I am equipped with information to help me through this.”
Another succinctly noted, “I felt that I knew more about my cancer and health issues after the call. Although this is a rough time, I feel I have more information, which motivates me in the journey.”
A third patient stated, “Everything is carefully explained, and any questions I have are answered regarding diagnosis and treatment options.”
One other theme surfaced in the qualitative data concerning “coordinating my cancer care.” The majority (60%) had scheduled appointments for clinical trials and for other services (genetic and nutritional counseling) after navigation. One patient noted, “Navigation helped me pull everything together—coordinating my care.” The excerpts have a theme of increased health knowledge to enable better decision-making, better communication, and increased motivation in the journey, reflective of patient education provided by the program.
The program is in progress, and we are tracking and documenting critical elements for replicability. As the program is evidence-based, we are continually evaluating efficacy based on self-advocacy and satisfaction. Virtual navigation has the potential to facilitate self-advocacy in the oncology patient population regardless of age, gender, ethnicity, tumor type, or geographic location. Understanding variations in navigation, providing a personalized journey, and monitoring the patient responses have been critical to improving outcomes for this population.
The findings suggest the unique virtual model significantly facilitates oncology patients’ self-advocacy with individualized education, cancer coordination, and navigation. As reflected in the data, virtual navigation may be a viable solution to reduce barriers to cancer care by increasing patient access despite geographic location for patients with fewer resources in their area. Patients are also pursuing clinical trials and other services associated with their healthcare and are finding strength through connecting with others virtually. Without giving medical advice, virtual navigation programs are postured to provide personalized contact, individualized education, referrals, and coordinated care that yield better patient outcomes that include self-advocacy skills. Virtual navigation may empower patients to help them overcome the challenges many face in the cancer journey.
- Guadagnolo BA, Dohan D, Raich P. Metrics for evaluating patient navigation during cancer diagnosis and treatment: crafting a policy-relevant research agenda for patient navigation in cancer care. Cancer. 2011;117(15 Suppl):3565-3574.
- Holmes DR, Major J, Lyonga DE, et al. Increasing minority patient participation in cancer clinical trials using oncology nurse navigation. Am J Surg. 2012;203:415-422.
- Petereit DG, Molloy K, Reiner ML, et al. Establishing a patient navigator program to reduce cancer disparities in the American Indian communities of western South Dakota: initial observations and results. Cancer Control. 2008;15:254-259.
- Steinberg ML, Fremont A, Khan DC, et al. Lay patient navigator program implementation for equal access to cancer care and clinical trials: essential steps and initial challenges. Cancer. 2006;107:2669-2677.
- Dohan D, Schrag D. Using navigators to improve care of underserved patients: current practices and approaches. Cancer. 2005;104:848-855.
- Braun KL, Kagawa-Singer M, Holder AE, et al. Cancer patient navigator tasks across the cancer care continuum. J Health Care Poor Underserved. 2012;23:398-413.
- Hartman L, Brown E. Creating a scorecard to monitor program growth and evaluate navigation metrics in a multiple-market navigation program. Journal of Oncology Navigation & Survivorship. 2016;7(9):26.
- Zibrik K, Laskin J, Ho C. Integration of a nurse navigator into the triage process for patients with non-small-cell lung cancer: creating systematic improvements in patient care. Curr Oncology. 2016;23:e280-e283.
- Freund KM. Patient navigation: the promise to reduce health disparities. J Gen Intern Med. 2011;26:110-112.
- Freund KM, Battaglia TA, Calhoun E, et al. National Cancer Institute Patient Navigation Research Program: methods, protocol, and measures. Cancer. 2008;113:3391-3399.
- Oncology Nursing Society. 2017 Oncology Nurse Navigator Core Competencies. www.ons.org/sites/default/files/2017ONNcompetencies.pdf. 2017.
- Cariello FP. Computerized telephone nurse triage: an evaluation of service quality and cost. J Ambul Care Manage. 2003;26:124-137.
- Wells KJ, Battaglia TA, Dudley DJ, et al. Patient navigation: state of the art or is it science? Cancer. 2008;113:1999-2010.
- Hagan TH, Rosenzweig M, Zorn K, et al. Perspectives on self-advocacy: comparing perceived uses, benefits, and drawbacks among survivors and providers. Oncol Nurs Forum. 2017;44:52-59.
- Creswell JW. Research Design: Qualitative, Quantitative, and Mixed Methods Approaches. 2nd ed. Thousand Oaks, CA: SAGE Publications, Inc; 2002.
- Creswell JW, Plano Clark VL. Designing and Conducting Mixed Methods Research. 2nd ed. Thousand Oaks, CA: Sage Publications, Inc; 2010.
- Johnson RB, Onwuegbuzie AJ, Turner LA. Toward a definition of mixed methods research. Journal of Mixed Methods Research. 2007;1(2):112-133.
- Wynd CA, Schmidt B, Schaefer MA. Two quantitative approaches for estimating content validity. West J Nurs Res. 2003;25:508-518.
- Davis LL. Instrument review: getting the most from your panel of experts. Applied Nursing Research. 1992;5:194-197.
- Waltz CF, Strickland OL, Lenz ER. Measurement in Nursing and Health Research. 3rd ed. New York: Springer Publishing Co; 2005.
- Miles MB, Huberman AM. Qualitative Data Analysis: An Expanded Sourcebook. 2nd ed. Thousand Oak, CA: Sage Publications, Inc; 1994.