March 2017 VOL 8, NO 3

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Original Research

Efficacy of Patient Navigation in Cancer Treatment: A Systematic Review

C. E. Jojola, MA1; H. Cheng, BA1; L. J. Wong, MS1; E. D. Paskett, PhD, MSHP2; K. M. Freund, MD, MPH3; F. M. Johnston, MD, MHS1
1Medical College of Wisconsin, Surgical Oncology/Surgery, Milwaukee, WI
2Ohio State University College of Public Health, Department of Medicine/Cancer Prevention and Control, Columbus, OH
3Tufts University School of Medicine, Department of Medicine, Boston, MA

Introduction: Patient navigation (PN) assists patients with financial, social, and health-related barriers to care by providing a personal escort to alleviate obstacles to achieve timely treatment. Herein we analyze the underexamined literature assessing PN efficacy for cancer patients undergoing treatment.

Method: This review was conducted for all English language–published, peer-reviewed medical articles on PN for cancer from 1946 to 2014. Electronic databases included PubMed, Scopus, CINAHL, EMBASE, Ovid MEDLINE, and the Cochrane Review.

Results: This systematic review yielded 15 relevant articles. Patients underwent breast, gynecologic, lung, colorectal, and prostate cancer treatment. Of the participating patients, 26% were Hispanic (SD ± 18), 28% black (SD ± 17), 54% white (SD ± 23), 3% Asian (SD ± 2), and 12% Other (SD ± 17). Two articles had 100% Native American participation. Many patients were non-English speakers (47% Spanish) and uninsured (33%). The most common barriers to care were finances, insurance, and lack of coordination of care. Navigators were mostly culturally competent bilingual nurses. When averaged, the mean days from diagnosis to treatment was 34 ± 14 days with PN compared with 55 ± 40 days for the control groups (P = .22). Two articles discussed palliative care.

Conclusion: Many patients benefiting from PN were from a minority racial/ethnic group and non-English speaking. The most common barriers to care were finances and insurance. Most navigators were nurses. Patients receiving navigation-initiated treatment sooner than their non-navigated counterparts. PN’s role in palliative care warrants further study.

Malignancy-related mortality has declined over the years, yet not all patient groups have equally experienced this improvement in cancer care.1,2 Healthcare disparities are a well-documented issue in the United States and have a profound negative effect on racial/ethnic minorities, patients of low socioeconomic status, and patients who lack insurance.3 These underserved patient populations have increased difficulty receiving care, are more likely to experience increased delays in diagnosis and initiation of treatment, and have worse outcomes.4-7

These disparities led Harold P. Freeman, MD, to create patient navigation (PN),8 an intervention to improve care, with navigators serving as point persons to address barriers to care, provide patient education, and offer psychosocial support. The National Cancer Institute (NCI) Patient Navigation Research Program (PNRP) defines navigation as “support and guidance offered to vulnerable persons with abnormal cancer screening or a cancer diagnosis, with the goal of overcoming barriers to timely, quality care.”9 The goal of PN is to provide underserved populations with better cancer care, alleviate disparities, and increase overall survival while decreasing morbidity from screening to survivorship.

Primary outcomes of the PNRP included: 1) time to diagnostic resolution, 2) time to initiation of cancer treatment, 3) patient satisfaction with care, and 4) cost-effectiveness.9 Whereas many studies of PN focus on the efficacy of cancer prevention and screening, there is scant literature about the efficacy of navigation to improve time from diagnosis to treatment. The purpose of this systematic review was to evaluate the current literature assessing PN efficacy for cancer patients undergoing malignancy-related therapy.

Materials and Methods

Data Sources and Study Selection

A medical librarian conducted the search for all published peer-reviewed medical articles in English on PN for cancer from 1946 to November 2014. Electronic databases included PubMed, Scopus, CINAHL, EMBASE, Ovid MEDLINE, and the Cochrane Review. These searches were supplemented with a dual-reviewer manual review of references from included articles and review articles.

Study Selection and Review Process

Studies reporting data on cancer patients who received PN and cancer treatment, as well as both cancer and noncancer patients who received both PN and palliative care, were included. The following study types were included: clinical trials, meta-analyses, systematic reviews, prospective studies, and case series. Studies excluding PN as the main focus or PN efficacy were not included. Unacceptable study designs included letters, correspondence, and case reports. Studies proposing or explaining PN models with qualitative interviews and lacking comparative outcome data were excluded.

Data Extraction

Data were extracted using a template with an electronic outlet to a spreadsheet for tabulation and analysis. In situations where articles presented overlapping data sets or increased patients/follow-up, the most recent article was included. Extracted data included patient demographics (number of patients, sex, median age, language, race/ethnicity, socioeconomic status, type of cancer, insurance status), characterization of barriers to accessing cancer care (financial, cultural, logistical, etc), and outcome measures (mean and median time from diagnosis to treatment and adherence to treatment guidelines). The main comparators/controls were cancer patients who did not receive PN alongside treatment or palliative care. The primary outcome measure was time from diagnosis to treatment for PN versus non-navigated patients. Secondary measures included identification of various barriers: financial, insurance, transportation, care coordination, lack of information/comprehension, and lack of social/emotional support. Each study was also evaluated for quality based on a number of a priori quality measures as determined by the primary authors after review of existent literature, including whether the paper characterized the navigator, described the process of navigation, and included scales to measure patient satisfaction. Descriptive statistics were calculated based on data obtained from the abstracted data. The means and medians were not weighted. The results were analyzed using a 2-sample t test assuming equal variances with a P value of .05.


Of 4029 citations from 6 databases, 15 relevant articles remained for final full text review. Among the articles were 2 randomized controlled trials, 5 retrospective studies, and 8 prospective studies. Articles were published between 2003 and 2014, with 9 (60%) published within the past 5 years. Navigation was performed for patients with breast, gynecologic, lung, colorectal, and prostate cancer. These studies analyzed a total of 8216 PN and 14,905 control patients.

Patient Characteristics: Ethnicity, Age, Insurance, and Income

The mean age of patients was 60 years (SD ± 7). Race and ethnicity percentages of patients studied were described in 7 articles10-16 (Table 1). Most studies described rates of Hispanic, black, and white participation. Asians were only explicitly denoted in 1 manuscript.11 Two articles had 100% Native American participation.15,16 Five articles described rates of English or Spanish speaking or other languages spoken, with 44% of patients speaking English as a primary language and 47% speaking Spanish.14,16,17 Five articles specified participant insurance status, with the majority of patients possessing private or government coverage.11,13,14,16,17

Barriers to Care

Barriers were abstracted based on their description in each manuscript, and analysis demonstrated the most common barriers (Figure 1). Barriers included: finance and insurance (uninsured, underinsured),10,11,16-19 coordination of care (fragmented medical system, missed appointments, lost results, timely facilitation of tests, obtaining path results, waiting for referrals),16,19,20 transportation,10,15,17,19 lack of information,10,16,19 other social/psychologic barriers (fear, distrust, lack of child care, family healthcare education, and marginalization15,17,19), and language/cultural (inadequate understanding).10,11,19 Less common barriers included lack of emotional support,10,11,16 cultural barriers,19 patient fear,10,19 and disability or comorbidity10 (Figure 1). 

Navigator Characteristics and Backgrounds

The most common characteristics of patient navigators included cultural competency (5 articles14-17,21), bilingual ability (3 articles14,17,19), and training for the navigator role (3 articles14,16,19) (Figure 2). Navigator cultural competency was achieved by being a member of the community receiving navigation,15 being generally representative of the patients served,21 receiving cultural competency training,14 or serving as a liaison between the hospital and tribal government.16 Other navigator characteristics included being nonjudgmental15 and friendly.15 Navigators for cancer patients were most likely to have a background in nursing (6 articles), and standardized navigation training (3 articles) than other types of background experience (Figure 3). 


Time to Treatment and Adherence to Quality Indicators

A summary of studies assessing the efficacy of PN can be found in Table 2. When averaged, the mean days from diagnosis to treatment was 34 ± 14 days with PN compared with 55 ± 40 days for the control groups in 7 articles (P = .22). Mean days from diagnosis to treatment ranged from 15 to 52 days for navigated patients compared with controls ranging from 16 to 136 days. Mean days from diagnosis to treatment ranged from 15 to 70 days for 6 of the 7 control groups; however, 1 control group had 136 days from diagnosis to treatment, which caused the standard deviation to rise to ± 40 days. Table 2 cites the individual findings for diagnosis to treatment for each of the articles. Only 1 of 7 studies demonstrated a significant difference in time to treatment,12 with PN decreasing time to treatment by as many as 22 days.12 Two articles mentioned palliative care: one concluded that curative-intent patients had more contacts with a navigator than palliative-intent patients,16 and the second reported that palliative care–navigated patients missed fewer appointments than radiation patients22 (Table 2). 

Beyond time to treatment, PN efficacy is measured by other system improvements,23 including adherence to treatment guidelines,24 missed or interrupted treatments, and patient and physician satisfaction. Of the studies examined, 2 addressed adherence to National Comprehensive Cancer Network treatment guidelines with PN,21,25 and 2 assessed adherence to other quality indicators of treatment.14,18 One article assessed adherence to treatment,17 and 3 examined treatment interruptions15,16 or missed treatments.22 One article addressed patient satisfaction,11 and 1 addressed physician satisfaction.26


Various outcome measures have been used to assess the efficacy of PN, including recruitment,27 screening,28 barrier identification, and patient perceptions of screening.28,29 Previous systematic reviews draw conclusions mostly from comparative and descriptive studies and conclude the need for more robust study designs.29 A 2011 systematic review30 demonstrates a shift from qualitative to quantitative outcome measures in assessing the efficacy of PN. The literature from the 2011 review30 focuses on the effect of navigation on screening and diagnostic evaluation of abnormal screening for cancer, since screening leads to earlier detection, earlier treatment, and, ultimately increased 5-year survival rate.8

This systematic review is the first of its kind to compile studies examining PN’s effect on time from diagnosis to treatment. The review also reflects the trend toward quantitative outcome measures while aiding the establishment of a gold standard (time from diagnosis to treatment) by which we can measure PN efficacy. Between 2011 and 2014, this review identified 7 articles (Table 2) measuring the efficacy of PN in a quantitative fashion by directly examining time from diagnosis to treatment with and without PN (Table 2).11,12,19,20,22,26,31 Although 6 studies demonstrated an absolute decrease in time to treatment, they were either nonsignificant or did not note the significance of their findings.11,19,21,22,26,31 Although only 1 study demonstrated significant findings, PN decreased time to treatment by as many as 22 days in that case.12 Furthermore, this review assists in compiling other ways to assess PN, including navigator characteristics and the barriers to attaining treatment, which PN can help patients overcome (Table 2).11,26

Our findings suggest that navigator characteristics may play an important role in counteracting cultural barriers, as navigators were most commonly culturally competent and bilingual (Figure 2). Identification of barriers and navigator characteristics as done in this review, when correlated with PN efficacy, may aid in identifying qualities of a successful PN program. Although many studies of PN for cancer screening or diagnostic evaluation have trained lay personnel for this task, it is noteworthy that most of the studies have employed nurses for navigation. In the time frame of this review, no studies had conducted comparisons of PN effectiveness by training. Future studies should evaluate the comparative effectiveness of laypersons versus clinically trained individuals as a variable affecting outcomes from navigation.

As this review demonstrates, there is great heterogeneity among PN research, including outcome measurements and approaches to navigation. These vast differences create difficulties in efforts to assess effectiveness and demonstrate the need for coherence in development and assessment of PN programs. A 2015 review of PN training confirms this observation, citing that learning strategies and content vary across PN programs, concluding a need for standardization of PN training as these programs grow in number.32 Programs like the PNRP serve as a guide for developing PN standards and assessment metrics. Although there is benefit in heterogeneity, there must be some consistency in how data are reported to allow for better comparisons in research.

As the beneficial effects of navigation grow increasingly clear, we must begin to examine the future of PN. With implementation of the Affordable Care Act (ACA), more Americans will have insurance coverage, alleviating one of the major barriers to care, but cultural and social barriers still remain. The ACA recognizes navigation as valuable in alleviating disparities, and the Public Health Service Act has aims of expanding navigation, while authorizing PN through the 2015 fiscal year.33 A number of foundations (Avon, Komen, and the American Cancer Society) continue to fund PN activities. Although funding for navigation had also been provided by the NCI Center to Reduce Cancer Health Disparities and the Centers for Medicare & Medicaid Services as part of research, they do not provide ongoing PN support.34

With the future in mind, this review calls on us to be forward-thinking as we explore the next frontier for PN: palliative care.9 Mention of navigation for palliative care patients was a conspicuously rare occurrence, occurring only twice in the aforementioned articles.16,22 Patients who might benefit from palliation face many of the same barriers as patients seeking curative cancer treatment, including cultural, linguistic, and communication barriers.35 Racial disparities exist in this realm as well, with Hispanics and African Americans representing only 5.3% and 8.7% of palliative patients, respectively.36 One study employed navigation in a randomized controlled trial demonstrating an increase in advance care planning, pain management discussions, and hospice enrollment in navigated patients,37 exhibiting how this new implementation of PN can increase access to end-of-life care.

Although PN has been demonstrated to be effective for diagnostic evaluation,30 there remains the need to examine its benefit during cancer treatment, including palliative care. This review identified only 1 study with statistically significant decreases in mean time to treatment.12 In addition, the subjective nature of navigator descriptors used in each article (such as “friendly” or “culturally competent”) is difficult to compare across articles. Although experiential perspectives of PN might be more readily addressed by qualitative surveys, this review did not include such studies.

Our study has several limitations. First, all studies exhibited considerable heterogeneity. This limits the validity of comparisons and the ability to draw conclusions from the aggregate data. Future research or expert opinion should designate terminology and important variables that all who investigate or provide care using PN can utilize. Similarly, only half of the studies reported data on time to treatment. This is an outcome that would seem to be a primary or secondary outcome to measure. Not providing these data limits the potential power of the findings. Lastly, our study data were limited to only manuscripts in the English literature, presenting no unpublished literature. This presents a risk of publication bias.

There is a need for additional quantitative studies to assess the impact of navigation for cancer treatment. We demonstrate in this review that existing quantitative studies support the hypothesis that PN decreases time from diagnosis to treatment, and that financial, insurance, transportation, and cultural barriers often decrease patients’ access to care. PN, often led by bilingual, culturally competent nurses, continues to identify and alleviate these barriers as navigation evolves to meet the ever-changing needs of patients.


Our review suggests that current evidence supports continued utilization of PN as a means to improve time to treatment in patients with malignancies. However, further research is needed that focuses on adequately defining appropriate PN training and outcomes. Improving standardization of PN metrics would allow clinicians, policy makers, patients, and other researchers to better measure the impact of patient navigation across the continuum of cancer care.

Conflicts of Interest



  1. Kohler BA, Sherman RL, Howlader N, et al. Annual report to the nation on the status of cancer, 1975–2011, featuring incidence of breast cancer subtypes by race/ethnicity, poverty, and state. J Natl Cancer Inst. 2015;107:djv048.
  2. Robbins AS, Siegel RL, Jemal A. Racial disparities in stage-specific colorectal cancer mortality rates from 1985 to 2008. J Clin Oncol. 2012;30:401-405.
  3. Silber JH, Rosenbaum PR, Clark AS, et al. Characteristics associated with differences in survival among black and white women with breast cancer. JAMA. 2013;310:389-397.
  4. Hunt B, Balachandran B. Black:White disparities in lung cancer mortality in the 50 largest cities in the United States. Cancer Epidemiol. 2015;39:908-916.
  5. Roseland ME, Pressler ME, Lamerato LE, et al. Racial differences in breast cancer survival in a large urban integrated health system. Cancer. 2015;121:3668-3675.
  6. Warner ET, Tamimi RM, Hughes ME, et al. Racial and ethnic differen­ces in breast cancer survival: mediating effect of tumor characteristics and sociodemographic and treatment factors. J Clin Oncol. 2015;33:2254-2261.
  7. Feinglass J, Rydzewski N, Yang A. The socioeconomic gradient in all-cause mortality for women with breast cancer: findings from the 1998 to 2006 National Cancer Data Base with follow-up through 2011. Ann Epidemiol. 2015;25:549-555.
  8. Freeman HP. A model patient navigation program. Oncology Issues. 2004;19:44-46.
  9. Freund KM, Battaglia TA, Calhoun E, et al. National Cancer Institute Patient Navigation Research Program: methods, protocol, and measures. Cancer. 2008;113:3391-3399.
  10. Goodwin JS, Satish S, Anderson ET, et al. Effect of nurse case management on the treatment of older women with breast cancer. J Am Geriatr Soc. 2003;51:1252-1259.
  11. Koh C, Nelson JM, Cook PF. Evaluation of a patient navigation program. Clin J Oncol Nurs. 2011;15:41-48.
  12. Haideri NA, Moormeier JA. Impact of patient navigation from diagnosis to treatment in an urban safety net breast cancer population. J Cancer. 2011;2:467-473.
  13. Freund KM, Battaglia TA, Calhoun E, et al. Impact of patient navigation on timely cancer care: the Patient Navigation Research Program. J Natl Cancer Inst. 2014;106:dju115.
  14. Chen F, Mercado C, Yermilov I, et al. Improving breast cancer quality of care with the use of patient navigators. Am Surg. 2010;76:1043-1046.
  15. Molloy K, Reiner M, Ratteree K, et al. Patient navigation & cultural competency in cancer care. Oncology Issues. 2007;22:38-41.
  16. Guadagnolo BA, Boylan A, Sargent M, et al. Patient navigation for American Indians undergoing cancer treatment: utilization and impact on care delivery in a regional healthcare center. Cancer. 2011;117:2754-2761.
  17. Ell K, Vourlekis B, Xie B, et al. Cancer treatment adherence among low-income women with breast or gynecologic cancer: a randomized controlled trial of patient navigation. Cancer. 2009;115:4606-4615.
  18. Weber JJ, Mascarenhas DC, Bellin LS, et al. Patient navigation and the quality of breast cancer care: an analysis of the breast cancer care quality indicators. Ann Surg Oncol. 2012;19:3251-3256.
  19. Ramirez A, Perez-Stable E, Penedo F, et al. Reducing time-to-treatment in underserved Latinas with breast cancer: the Six Cities Study. Cancer. 2014;120:752-760.
  20. Baliski C, McGahan CE, Liberto CM, et al. Influence of nurse navigation on wait times for breast cancer care in a Canadian regional cancer center. Am J Surg. 2014;207:686-691; discussion 691-692.
  21. Raj A, Ko N, Battaglia TA, et al. Patient navigation for underserved patients diagnosed with breast cancer. Oncologist. 2012;17:1027-1031.
  22. Schwaderer KA, Proctor JW, Martz EF, et al. Evaluation of patient navigation in a community radiation oncology center involved in disparities studies: a time-to-completion-of-treatment study. J Oncol Pract. 2008;4:220-224.
  23. Gunn CM, Clark JA, Battaglia TA, et al. An assessment of patient navigator activities in breast cancer patient navigation programs using a nine-principle framework. Health Serv Res. 2014;49:1555-1577.
  24. Battaglia TA, Burhansstipanov L, Murrell SS, et al. Assessing the impact of patient navigation: prevention and early detection metrics. Cancer. 2011;117(15 Suppl):3553-3564.
  25. Goldstein LJ, Bleicher RJ, Cohen SJ, et al. Prospective quality review of breast care navigation and treatment: Fox Chase Cancer Center Partners’ (FCCCP) initiative. J Clin Oncol. 2012;30(suppl 34). Abstract 85.
  26. Hunnibell LS, Rose MG, Connery DM, et al. Using nurse navigation to improve timeliness of lung cancer care at a veterans hospital. Clin J Oncol Nurs. 2012;16:29-36.
  27. Burhansstipanov L, Dignan MB, Schumacher A, et al. Breast screening navigator programs within three settings that assist underserved women. J Cancer Educ. 2010;25:247-252.
  28. English KC, Fairbanks J, Finster CE, et al. A socioecological approach to improving mammography rates in a tribal community. Health Educ Behav. 2008;35:396-409.
  29. Eschiti V, Burhansstipanov L, Watanabe-Galloway S. Native cancer navigation: the state of the science. Clin J Oncol Nurs. 2012;16:73-82, 89.
  30. Paskett ED, Harrop JP, Wells KJ. Patient navigation: an update on the state of the science. CA Cancer J Clin. 2011;61:237-249.
  31. Alsamarai S, Yao X, Cain HC, et al. The effect of a lung cancer care coordination program on timeliness of care. Clin Lung Cancer. 2013;14:527-534.
  32. Ustjanauskas AE, Bredice M, Nuhaily S, et al. Training in patient navigation: a review of the research literature. Health Promot Pract. 2016;17:373-381.
  33. Moy B, Chabner BA. Patient navigator programs, cancer disparities, and the Patient Protection and Affordable Care Act. Oncologist. 2011;16:926-929.
  34. George Washington Cancer Institute. The Affordable Care Act and Patient Navigation: Support for Those in Need. George Washington University.
  35. Fischer SM, Sauaia A, Kutner JS. Patient navigation: a culturally competent strategy to address disparities in palliative care. J Palliat Med. 2007;10:1023-1028.
  36. Hauser J, Sileo M, Araneta N, et al. Navigation and palliative care. Cancer. 2011;117(15 Suppl):3585-3591.
  37. Fischer SM, Cervantes L, Fink RM, et al. Apoyo con Cariño: a pilot randomized controlled trial of a patient navigator intervention to improve palliative care outcomes for Latinos with serious illness. J Pain Symptom Manage. 2015;49:657-665.
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