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Evaluation of a Patient Navigation Program Catherine Koh, DNP, RN, Joan M. Nelson, DNP, APRN-BC, and Paul F. Cook, PhD This study examined the value and effectiveness of a patient navigation program in terms of timeliness of access to cancer care, resolution of barriers, and satisfaction in 55 patients over a six-month period. Although not statistically significant, the time interval between diagnostic biopsy to first consultation with a cancer specialist after program implementation was reduced from an average of 14.6 days to 12.8 days. The time interval between diagnostic biopsy to initiation of cancer treatment also was reduced from 30 days to 26.2 days (not statistically significant). In addition, 71% of patient barriers were resolved by the time treatment was initiated. Overall, patients were highly satisfied with their navigated care experience. Consistent evaluation and monitoring of quality-of-care indicators are critical to further develop the program and to direct resource allocation. Oncology nurses participating in patient navigation programs should be encouraged to evaluate their importance and impact in this developing concept. Nurses should seek roles that allow them to optimize the effective use of their specialized knowledge and skills to the benefit of patients along the cancer care continuum.

T

he six aims of the Institute of Medicine ([IOM], 2001) action plan call for improvements to provide safe, effective, patient-centered, timely, efficient, and equitable care. Embedded in those aims is the responsibility of healthcare providers to ensure continuity of care and provide patients easy access to information and treatment by anticipating and customizing care according to patient needs and values. The unprecedented rate of advancement in cancer research and development has contributed to the complexity of cancer care. Various seminal reports highlighted the deficiencies of a fragmented healthcare system that failed to provide access to timely, equitable, and standard cancer care to everyone in the United States (Freeman & Reuben, 2001; Haynes & Smedley, 1999; Hewitt & Simone, 1999; Smedley, Stith, & Nelson, 2003). Patient navigation was introduced as an intervention to reduce patient barriers and achieve optimal healthcare outcomes. Following the reported success of the patient navigation program first initiated by Freeman, the President’s Cancer Panel recommended that patient navigation should become an integral part of breast health centers and other areas of cancer care (Freeman & Reuben, 2001). Subsequently, the Patient Navigator Outreach and Chronic Disease Prevention Act of 2005 was enacted to provide funds to create patient navigation programs in various centers throughout the United States. The current study

At a Glance F Patient navigation may improve timely access to cancer care, help resolve barriers to care, and increase patients’ satisfaction with their care experience. F Patient navigation programs may help patients achieve optimal healthcare outcomes, but more systematic evaluation and research are needed. F Nurses should be active participants in the development and evaluation of patient navigation programs, with the aim of improving cancer care for all patients.

examined the value and effectiveness of a patient navigation program newly initiated at the breast center of a tertiary care facility in terms of timeliness of access to cancer care, resolution of barriers to care, and patient satisfaction.

Literature Review Because patient navigation has the potential to improve cancer outcomes and transform complex, fragmented health care to

Catherine Koh, DNP, RN, is the deputy director of nursing at National University Hospital in Singapore; and Joan M. Nelson, DNP, APRN-BC, is an associate professor in the College of Nursing and Paul F. Cook, PhD, is an assistant professor and director for the Center for Nursing Research, both at the University of Colorado in Denver. The authors take full responsibility for the content of the article. Cook receives honoraria from the University of Colorado Hospital for speaking and statistical consulting, although no honoraria were received for this work. The content of this article has been reviewed by independent peer reviewers to ensure that it is balanced, objective, and free from commercial bias. No financial relationships relevant to the content of this article have been disclosed by the independent peer reviewers or editorial staff. (First submission May 2010. Revision submitted June 2010. Accepted for publication July 1, 2010.) Digital Object Identifier: 10.1188/11.CJON.41-48

Clinical Journal of Oncology Nursing • Volume 15, Number 1 • Evaluation of a Patient Navigation Program

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more patient-centered care, patient navigation programs rapidly proliferated (Hede, 2006). A review of the literature showed a wide variation of patient navigation programs instituted across the cancer care continuum, ranging from prevention, screening, and treatment to survival. The programs can be disease or population specific, whereas others provide for financially and socially disadvantaged populations who are most at risk for poor cancer outcomes, as first intended by Freeman (2004). Despite the variations, Freund et al. (2008) and Wells et al. (2008) surmised that common characteristics of patient navigation programs include barrier-focused interventions to reduce delays in accessing cancer care services and systematic follow through of patients to resolution of the presenting problem. Patient navigator positions commonly are dedicated jobs filled by lay community members, nurses, or social services staff. Certain population-specific and community-based navigation programs reported a superior advantage to having lay navigators (Burhansstipanov et al., 1998; Ell et al., 2002; Hiatt et al., 2001; Weinrich et al., 1998), whereas others supported the need for navigators to be healthcare professionals (Fillion et al., 2006; Seek & Hogle, 2007). No studies have compared the effectiveness of lay and professional navigators; instead, several programs use both types of personnel in a complementary manner (Gabram et al., 2008; Hiatt et al., 2001; Petereit et al., 2008). In addition, the navigator positions have considerable overlap with existing roles in healthcare organizations (e.g., case or care manager, social worker, clinical or care coordinator, support nurse, patient advocate, community health worker) (Darnell, 2007; Dohan & Schrag, 2005; Farber, Deschamps, & Cameron, 2002; Freund et al., 2008; Pedersen & Hack, 2010). Before more resources are committed to patient navigation programs, evaluation of outcomes and effective management of resources are crucial, particularly for programs that use the gradually diminishing population of oncology nurses (Moore, 2010).

Access to Care More research is required to evaluate the effectiveness of patient navigation programs in improving access to care. Studies in cancer screening settings reported patient navigation programs to be efficacious in improving screening rates for colorectal, prostate, and cervical cancers (Christie et al., 2008; Fang, Ma, Tan, & Chi, 2007; Jandorf, Gutierrez, Lopez, Christie, & Itzkowitz, 2005; Nash, Azeez, Vlahov, & Schori, 2006; Weinrich et al., 1998). However, the findings were not consistently statistically significant because of limitations in research designs and small sample sizes. Results from studies of patient navigation programs that provided care after an abnormal cancer screening test were more promising. A limited number of studies showed improved adherence rates for navigated patients after screening abnormality, with timelier follow-up and shorter waiting times to achieve diagnostic resolution (Battaglia, Roloff, Posner, & Freund, 2007; Ell et al., 2002; Ell, Vourlekis, Lee, & Xie, 2007; Ferrante, Chen, & Kim, 2008; Psooy, Schreuer, Borgaonkar, & Caines, 2004). Systematic evaluation of navigation programs in the cancer treatment setting is even scarcer and limited to its effect on reducing treatment interruptions (Petereit et al., 2008). Overall, definite conclusions cannot be reached regarding the efficacy of patient navigation in improving care access because 42

of varied research designs and methodologic limitations. Some of the programs were combined with other interventions, such as educational outreach or cognitive-behavioral intervention; therefore, the effect of patient navigation cannot be delineated (Wells et al., 2008).

Barriers to Care A key concept of patient navigation is addressing the multitude of patient, provider, cultural, and health system barriers that patients face to access optimum cancer care. The wide array of barriers reported in the literature include a lack of understanding of the purpose of further investigation; fear of pain and cancer; a lack of time, money, or childcare; no medical insurance; inconvenient hours; long waits in clinics; fear of losing a breast; transportation; language; health literacy; cultural norms; health beliefs; cancer misconceptions; inadequate communication and information; and ineffective communication between providers (Brett & Austoker, 2001; Crane, 1996; De Alba, Sweningson, Chandy, & Hubbell, 2004; Deane & Degner, 1998; Ell et al., 2007; Gansler et al., 2005; Khanna & Phillips, 2001; Lindau et al., 2002; McKee, Caban, Burton, & Mulvihill, 2002; Nelson, Geiger, & Mangione, 2002; Rojas, Mandelblatt, Cagney, Kerner, & Freeman, 1996; Zapka et al., 2004). To date, only Lin et al. (2008) reported on how patient navigators in their program added value to patient care by addressing identified barriers and time spent on helping patients address the barriers. However, no studies have evaluated the effectiveness of patient navigation programs in resolving the barriers to care.

Patient Satisfaction Another key concept of patient navigation is providing customized care according to individual needs and values. In general, studies found patients who are involved in patient navigation programs to be satisfied with their care experiences. However, the differences in the satisfaction measurement tools used were widely varied, ranging from validated standardized tools that were not specific to navigation experience (Ell et al., 2007; Ferrante et al., 2008; Fillion et al., 2009) to nonvalidated tools specific to the goals of the individual program (Campbell, Craig, Eggert, & Bailey-Dorton, 2010; Christie et al., 2008; Steinberg et al., 2006). Variations in research design also make comparisons and conclusions on patient satisfaction more challenging.

Evaluation Project Questions A patient navigation program was initiated at the breast center of a tertiary care facility in April 2009 to coordinate the care of patients with newly diagnosed breast cancer. The program is staffed by an experienced oncology nurse who had been working in the breast center. The oncology nurse navigator acts as the primary care coordinator and first point of contact for patients with breast cancer from diagnosis to the time care is transferred to either the hospital’s cancer treatment center or other care providers. One of the navigator’s key roles is ensuring that patients who are diagnosed within the facility or referred from external

February 2011 • Volume 15, Number 1 • Clinical Journal of Oncology Nursing

providers have timely access to their first consultation with specialists at the breast center. The goal of this project was to determine the value and effectiveness of the patient navigation program. The current study attempted to answer the following questions. • How effective was the patient navigation program in achieving timely access to care for patients with newly diagnosed breast cancer? • How effective was the patient navigation program for patients considered to be at high risk for breast cancer? (The current study defined high-risk patients as those who were of ethnic or minority populations, were unemployed, and had no insurance or were receiving government insurance.) • What patient barriers were identified and addressed by the patient navigation program, and how much time was spent on them? • How effective was the patient navigation program in resolving patient barriers to care? • How satisfied were patients with their care based on the patient navigation experience?

Methods Sample The current study evaluated the patient navigation program for six months from October 2009 to March 2010. Patients with newly diagnosed breast cancer were accrued prospectively and sequentially from the time of Colorado Multiple Institutional Review Board approval in September 2009. Inclusion criteria were patients older than 21 years, able to provide informed consent, and who had diagnostic pathology of either ductal carcinoma in situ or invasive cancer, regardless of stage of presentation. All patients were diagnosed at the breast center, were self-referred, or were referred to the breast center within one month of diagnosis. The project excluded patients who were pregnant, had a prior history of cancer, or had received partial breast cancer treatment from another care provider.

Procedure and Measures Demographics and clinical variables: Data were obtained regarding participants’ age, gender, race, marital status, employment status, insurance status, date of diagnostic biopsy procedure, date of first consultation with a cancer specialist, and date of initial cancer treatment. Other clinical variables included tumor size, type, and grade; nodal status; and type of surgery or neoadjuvant treatment received. The data were obtained from the clinical information system in the hospital. Timely access to care: This study compared the sample with matched historical controls prior to program implementation based on the time interval

Table 1. Sample Characteristics Before and After Program BEFORE CHARACTERISTIC

—

X

SD

Age (years) Tumor size (cm)

56.5 1.8

CHARACTERISTIC

AFTER —

X

SD

p

12.28 1.52

56.5 2.3

12.28 2.02

1 0.211

n

%

n

%

p

Race Caucasian African American Hispanic Asian

51 3 1 –

93 5 2 –

48 3 3 1

87 5 5 2

Marital status Married Divorced Widowed Unknown

31 10 7 7

56 18 13 13

37 7 3 8

67 13 5 15

Employment status Employed Unemployed Retired Unknown

25 7 19 4

45 13 35 7

25 11 18 1

45 20 33 2

Insurance status Private Government

35 20

64 36

35 20

64 36

Diagnosed on site Yes No

27 28

49 51

34 21

62 38

Risk High Not high

28 27

51 49

31 24

56 44

Tumor type Invasive ductal carcinoma Ductal carcinoma in situ Invasive lobular carcinoma Other

38 8 5 4

69 15 9 7

37 10 7 1

67 18 13 2

Tumor grade 1 2 3 Unknown

14 20 21 –

25 36 38 –

4 21 27 3

7 38 49 5

Nodal status Negative Positive Unknown

37 10 8

67 18 15

18 15 22

33 27 40

4 – 4 1

7 – 7 2

3 1 3 1

5 2 5 2

34 –

62 –

15 2

27 4

12

22

30

54

Type of surgery Total mastectomy Total mastectomy and axillary clearance Total mastectomy and reconstruction Total mastectomy, axillary clearance, and reconstruction Breast-conserving surgery Breast-conserving surgery and axillary clearance Unknown

0.554

0.346

0.66

1

0.179

0.566

0.499

0.044*

0.022*

0.275

N = 55 * p < 0.05 Note. Because of rounding, not all percentages total 100.

Clinical Journal of Oncology Nursing • Volume 15, Number 1 • Evaluation of a Patient Navigation Program

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Data Analysis Descriptive statistics were generated from the demographic and clinical variables, variables from the patient navigator logs, and satisfaction scores. A power analysis showed the current study had power of 0.74 to detect differences between the two groups (Cohen’s d = 0.5, degrees of freedom [df] = 108). Independent t tests (for continuous variables) and chi-square tests (for categorical variables) were used to compare the demographic and clinical variables between the groups before and after program implementation. An independent t test also was used to compare differences in timely access to care between the two groups and for subgroup analyses between patients considered to be at high risk and those who were not. All analyses used two-sided p values with significance set at 0.05 and were performed using SPSS®, version 18.0.

women did not continue their care at the breast center after initial consultation, 2 (4%) were waiting for their scheduled surgery, and 2 (4%) had not undergone cancer treatment because of other emergent health conditions. Table 1 shows the baseline characteristics of the study population. The majority were Caucasian, married, employed, and using private insurance. No statistically significant differences existed in demographic characteristics between the groups before and after program implementation. However, significant differences were found in their tumor grade (c2 = 6.251, p = 0.044) and nodal status (c2 = 5.275, p = 0.022): the navigated group had more grade 3 tumors and positive nodal status. The finding did not have any effect on navigated patients’ initial treatment. Both groups had a majority of patients who underwent breast-conserving surgery rather than neoadjuvant treatment. Further analyses revealed that tumor grade and nodal status were not significant predictors of time intervals between biopsy and first specialist consult (F = 0.68, p = 0.412; F = 0.472, p = 0.494, respectively) and between biopsy and initial treatment (F < 0.001, p = 0.997; F = 1.696, p = 0.197, respectively).

Timely Access to Care Figures 1 and 2 show box plots for timely access to care, comparing the navigated group (N = 55) with matched historical controls (N = 55). Although no statistically significant difference was detected (t = 1.616, p = 0.109, Cohen’s d = 0.308), a reduction was found in the time interval between patients’ diagnostic biopsy to first consultation with a cancer specialist after program implementation from an average of 14.6 days (SD = 5.9; 95% confidence interval [CI] 13, 16.2) to 12.8 days (SD = 5.54; 95% CI 11.3, 14.3). The time interval between diagnostic biopsy to initiation of cancer treatment also was reduced from an average of 30 days (SD = 11.79; 95% CI 26.8, 33.2) to 26.2 days (SD = 9.15; 95% CI 22.9, 29.4) and was not statistically significant (t = 1.606, p = 0.112, Cohen’s d = 0.366). Subgroup analyses were conducted to compare women considered to be at high risk and those who were not. Women not at high risk (N = 24) had a significantly longer time interval

Time Interval From Biopsy to Specialist Consultation (Days)

between patients’ biopsy procedure and their first consultation with a cancer specialist and the time interval between their biopsy procedure and initial cancer treatment received (breast cancer surgery or neoadjuvant treatment). Controls were matched based on age at diagnosis, gender, race, and insurance status and were randomly selected from a patient list from the multidisciplinary clinic in 2008 using an automated randomization procedure in Microsoft® Excel®. Barriers to care: The project introduced a patient navigator log recommended by the National Cancer Institute Patient Navigation Research Program (Freund et al., 2008). The oncology nurse navigator used the log to guide the initial interview with patients, identify patient barriers to care, and subsequently, follow up with interventions to help patients resolve the barriers. The oncology nurse navigator recorded from a predefined list the identified patient barriers, interventions, time spent addressing the issues, and the extent to which each barrier was resolved by the time patients initiated their first treatment. Other members of the study team validated the entries of 10 logs by checking the navigator’s assessment of patient barriers and her interpretation of the predefined items in the log. The inter-rater reliability was 0.8, demonstrating excellent agreement between rates. Patient satisfaction: The current study adapted the validated Satisfaction with Hospital Care Questionnaire to measure patients’ satisfaction with the overall care experience at the breast center (Hendriks, Oort, Vrielink, & Smets, 2002). The administered questionnaire included subscales of satisfaction with the breast center, nursing care (specifically the nurse navigator), information, patient autonomy, and emotional support, and excluded all subscales on inpatient care. Patients were approached during a clinic visit after starting their initial cancer treatment, and verbal informed consent for their participation was obtained. Patients completed and returned the anonymous, self-administered, structured questionnaire before leaving the clinic.

30 25 20 15 10 5 0

Results

After Implementation

Note. Boxes contain the core 50% of the data. Lines inside boxes indicate the median value of the data set. Ends of perpendicular lines indicate minimum and maximum normal data values. Circles represent outliers.

Characteristics of Participants The current study enrolled 55 women; before implementation of the navigation program, they were matched with another 55 women as historical controls. At the close of the study, 18 (33%) 44

Before Implementation

Figure 1. Box Plot of Timely Access to Specialist Consultation Before and After Implementation

February 2011 • Volume 15, Number 1 • Clinical Journal of Oncology Nursing

Time Interval From Biopsy to First Treatment (Days)

80 60 40 20 0

Before Implementation

After Implementation

Note. Boxes contain the core 50% of the data. Lines inside boxes indicate the median value of the data set. Ends of perpendicular lines indicate minimum and maximum normal data values. Circles represent outliers.

Figure 2. Box Plot of Timely Access to Initial Cancer Treatment Before and After Implementation

who were not (85.8 minutes, SD = 41.47, versus 90 minutes, SD = 19.14; 95% CI –15.8, 24.1; t = 0.419, p = 0.677). The authors also conducted analyses to examine whether demographic characteristics and clinical factors were associated with any of the outcome variables. No association was found except for tumor size, which positively correlated with the amount of time the navigator spent with patients, whereby patients who presented with larger sized tumors required more of the navigator’s time (r = 0.416, p = 0.004).

Patient Satisfaction Of the 32 women who were approached to participate in the patient satisfaction survey after initiation of their cancer treatment, 30 (94%) responded positively. Subscales from the Satisfaction with Hospital Care Questionnaire had Cronbach’s alphas ranging from 0.678–1. Overall, the mean satisfaction score was 4.52 (SD = 0.51) on a five-point Likert-type scale, and no significant difference existed in patient satisfaction between women at high risk and those who were not (t = –0.41, p = 0.685). Figure 3 shows the box plots comparing mean satisfaction scores of the subscales within the Satisfaction with Hospital Care Questionnaire. Satisfaction with information had the lowest score (4.37, SD = 0.67) and satisfaction with nursing care had the highest score (4.76, SD = 0.43). None of the subscales showed significant difference in the mean satisfaction score between women at high risk and those who were not.

from diagnostic biopsy to first consultation with a specialist compared to those at high risk (N = 31) (14.8 days, SD = 6.67, versus 11.3 days, SD = 3.96; t = 2.403, p = 0.02), but no difference existed in timeliness to treatment initiation (25.6 days, SD = 9.36, versus 26.3 days, SD = 9.27; t = –0.184, p = 0.855). Further analysis indicated that women not at high risk may have taken longer to see a specialist because more women in that group were diagnosed elsewhere before seeking consultation at the breast center (c2 = 8.351, p = 0.004). Twenty of 24 women not at high risk received their diagnosis elsewhere compared to 14 of 31 women at high Table 2. Barriers to Care, Resolution of Barriers, and Average risk. Because of an inherent delay, women who Time Spent by Navigator Among Patients After Program were diagnosed elsewhere would have a longer time interval between their diagnostic biopsy COMPLETELY MINUTES and consultation with a specialist at the breast TOTAL RESOLVED SPENT center (t = 4.069, p < 0.001). —

Barriers to Care On initial assessment of each patient (N = 50), navigators identified as many as five barriers to care. Twelve (24%) women did not have any barriers to care, but 35 (70%) had two or more barriers. Overall, the most frequently identified barriers were related to the location of the healthcare facility, perception or beliefs about tests or treatment, and social or practical support. The greatest amount of navigator time was spent on barriers related to employment issues, attitudes toward providers, and perception or beliefs about tests or treatment. Most (71%) of the barriers were resolved completely by the time treatment was initiated (see Table 2). The most frequently occurring navigator activities were records or record keeping and scheduling appointments. The greatest amount of navigator time was spent on records or record keeping and education (see Table 3). The navigator spent an average of 87.5 minutes (SD = 34.12) per patient, ranging from 50–280 minutes; no significant differences were found in the time spent between women at high risk and those

BARRIER

n

%

n

%

X

System issues Location of healthcare facility System problems with scheduling care Medical and mental health comorbidity

21 4 3

42 8 6

21 4 2

100 100 67

3.8 6.75 8.33

1.57 3.95 5.77

6 3 2

12 6 4

3 2 –

50 67 –

8.67 4 37.5

6.38 1.73 10.61

16

32

12

75

11.67

13.84

12 10 7 7 4 4 1 –

24 20 14 14 8 8 2 –

7 4 5 4 4 2 1 –

58 40 71 57 100 50 100 –

8.82 5.7 8.14 14.14 8.75 6.67 5 –

8.51 2.45 4.38 20.75 4.79 2.89 < 0.01 –

1 –

2 –

1 –

100 –

5 –

< 0.01 –

Financial issues Insurance issues Transportation Employment issues Psychosocial issues Perception or beliefs about tests or treatment Social or practical support Fear Child or adult care issues Attitudes toward providers Out of town or country Patient disability Housing Literacy Communication issues Language or interpreter Communication concerns with medical personnel

SD

N = 50

Clinical Journal of Oncology Nursing • Volume 15, Number 1 • Evaluation of a Patient Navigation Program

45

ACTIVITY

n

%

Records or record keeping Scheduling appointments Education Support Arrangements Referrals or direct contact Proactive navigation Directly contacting family Accompany patient

50 48 26 12 8 6 6 4 –

100 96 52 24 16 12 12 8 –

—

X

SD

41.1 14.17 17.5 14.58 8.13 8.33 5.67 10 –

6.65 2.98 10.51 8.11 2.59 2.58 3.61 4.08 –

N = 50

The authors also conducted analyses to investigate associations among the outcome variables. Results showed that the amount of time navigators spent on patients was negatively correlated with patient satisfaction (i.e., the navigator spent more time with patients who were less satisfied with their care experience [r = –0.373, p = 0.042]).

Discussion Timely Access to Care The current study was designed to provide a baseline evaluation of patient navigation as well as guidance to the continuous quality improvement of the program. To the authors’ knowledge, this is the first study of such evaluation of a patient navigation program in the cancer treatment setting. In terms of timely access to care, no national clinical benchmark exists in the United States to date. In the United Kingdom, the target for beginning treatment after diagnosis for all cancers is one month (National Institute for Clinical Excellence, 2002). The Canadian Breast Cancer Network (2008) reported wait times from diagnosis to surgery for various provinces and territories ranging from three weeks to three months. The wait time for breast cancer care in Nova Scotia, Canada, reported by Saint-Jacques, Younis, Dewar, and Rayson (2007) was 20 days from biopsy to surgery. The average time intervals from diagnosis to specialist consultation and treatment reported in the current study of 12.8 days and 26.2 days, respectively, may provide a useful baseline for future studies of patient navigation programs. With the implementation of the navigation program at the breast center, time intervals slightly improved. The reductions may have no significant biologic impact on cancer care outcomes; however, they would serve as a useful baseline for the program to set improvement targets and for continuous monitoring. Although factors influencing wait times to cancer care can be complex, examining the internal processes involved could help detect delays in access to care and allow a more targeted intervention.

Barriers to Care Most (71%) of the identified barriers to care were completely resolved by the time treatment was initiated. In the absence of a comparison group, the percentage of barriers that would have 46

Patient Satisfaction Patients’ satisfaction with their navigated care experience was high in the program, with a mean score of 4.52 on a 0–5 scale. The finding is comparable to the study by Ferrante et al. (2008), who also used an adaptation of the same questionnaire and reported a mean satisfaction score of 4.3 for navigated patients versus 2.9 for non-navigated patients. Analysis of the responses to the subscales of the patient survey will help assess the needs of the breast center’s patient population and facilitate improvements in redesigning the system and care processes that reduce difficulties and improve satisfaction for patients. By using the current study’s findings as an illustration for program improvement to optimize the efficient use of specialized knowledge and skills of an oncology nurse navigator, the program may streamline its processes by reducing the time spent on nonnursing tasks (e.g., providing directions to the location of the facility, record keeping, scheduling of appointments). Instead, the program may reallocate the navigator’s time to more value-added care. For example, the navigator should spend more time on the provision of information because patients reported the lowest satisfaction in the area of information provided. Increasing satis-

5 X Satisfaction Score

MINUTES SPENT

been resolved successfully even without the navigation program is unknown. With a better understanding of the profile of patients at the breast center in terms of their barriers and needs, the oncology nurse navigator and other healthcare team members will be better able to plan and organize care interventions. The navigator spent an average of 87.5 minutes per patient, as compared to Lin et al. (2008), who reported that navigators spent about 2.5 hours per patient with any type of cancer in the prediagnosis setting. The difference may have been because of the type of clinical setting. In addition, the sample population in Lin et al.’s (2008) study may have had more patients with financial barriers, which was supported by the current study’s findings that patients with financial issues (e.g., unemployment) would require more navigator time. The findings will be helpful for this and other developing patient navigation programs to consider in terms of allocation of staff time and case loads, depending on the barriers and needs of the population served.

4 3 2

—

Table 3. Activities and Average Time Spent by Navigator Among Patients After Program

1

Breast Center

Nursing Care

Information Autonomy

Support

Subscale Note. Boxes contain the core 50% of the data. Lines inside boxes indicate the median value of the data set. Ends of perpendicular lines indicate minimum and maximum normal data values. Circles represent outliers.

Figure 3. Box Plots for Subscales of the Satisfaction With Hospital Care Questionnaire After Program

February 2011 • Volume 15, Number 1 • Clinical Journal of Oncology Nursing

faction by increasing provision of information may, in turn, reduce the overall time spent by the navigator on dissatisfied patients.

Study Limitations A limitation of the current study was the small sample size, which likely precluded the authors from obtaining statistical significance on improvements in timely access to specialist consultation and treatment for breast cancer. In addition, the current study was conducted at one tertiary referral center serving a population that is predominantly Caucasian, employed, and using private insurance. The navigator log was a self-report tool newly introduced to the oncology nurse navigator within the short time frame of the project; therefore, the findings from the logs may not be as complete or accurate as they could be. However, the navigator log may prove to be a useful tool that will provide a more structured and consistent approach to assessing patient barriers over time to engage patients and work toward resolution of the barriers to care. Documentation of this process will be invaluable to understanding the content of the work of navigation, which has not reached a state of consensus as reflected in the literature. The current study also lacked a comparison group for the patient satisfaction survey. In addition, the satisfaction level for the 18 women (33%) who did not proceed with their treatment plan after initial consultations with the specialists at the breast center was unclear.

Research Implications Unfortunately, the literature provides little quantitative information about the effectiveness and outcomes of patient navigation, particularly in the treatment setting. More research and consistent use of measures related to timely access to care, barriers to care, and patient satisfaction are needed. Augmenting research and sharing of best practices and performance will be important to the development of bench marks for timely access across the cancer care continuum. Increased quantitative and qualitative research into the content of navigation work and processes also can help to determine the type and amount of resources required in navigation programs, specifically the type of personnel needed, as the question remains whether highly trained oncology nurses are necessary for this role.

Conclusion The current study successfully provided a baseline evaluation of the patient navigation program at a breast center. The findings could provide comparisons and guidance to healthcare professionals and administrators who are developing patient navigation programs. Consistent evaluation and monitoring of quality of care indicators is imperative to any new patient program to help direct resources appropriately and for optimal program development. The authors gratefully acknowledge A.A. Jolijn Hendriks, PhD, and colleagues for sharing information on the Satisfaction With Hospital Care Questionnaire. Author Contact: Catherine Koh, DNP, RN, can be reached at cathkoh@ singnet.com.sg, with copy to editor at [email protected].

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February 2011 • Volume 15, Number 1 • Clinical Journal of Oncology Nursing

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