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10.1245/s10434-006-9336-x
Annals of Surgical Oncology 14:1662-1669 (2007)
© 2007 Society of Surgical Oncology
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Original Article

Diffusion of Surgical Techniques in Early Stage Breast Cancer: Variables Related to Adoption and Implementation of Sentinel Lymph Node Biopsy

Kimberly A. Vanderveen, MD1, Debora A. Paterniti, PhD2,3, Richard L. Kravitz, MSPH, MD2 and Richard J. Bold, MD1

1 Department of Surgery, Division of Surgical Oncology, University of California, Davis, Cancer Center, 4501 X Street, Suite 3010, Sacramento, California 95817
2 Center for Health Services Research in Primary Care, University of California, Davis, Sacramento, California
3 Department of Sociology, University of California, Davis, Davis, California

Correspondence: Address correspondence and reprint requests to: Richard J. Bold, MD; E-mail: richard.bold{at}ucdmc.ucdavis.edu


   ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Background: Understanding how physicians acquire and adopt new technologies for cancer diagnosis and treatment is poorly understood, yet is critical to the dissemination of evidence-based practices. Sentinel lymph node biopsy (SLNB) has recently become a standard technique for axillary staging in early breast cancer and is an ideal platform for studying medical technology diffusion. We sought to describe the timing of SLNB adoption and patterns of surgeon interactions with the following educational sources: local university training program, surgical literature, national meetings/courses, national specialty centers, and other local surgeons.

Methods: A cross-sectional survey that used semistructured interviews was used to assess timing of adoption, practice patterns, and learning sources for SLNB among surgical oncologists and general surgeons in a single metropolitan area.

Results: A total of 44 eligible surgeons were identified; 38 (86%) participated. All surgical oncologists (11 of 11) and most general surgeons (26 of 27) had implemented SLNB. Surgical oncologists were older (mean 51 vs. 48 years, P = .02) and had used SLNB longer (6.1 vs. 3.3 years, P = .01) than general surgeons. By use of social network diagrams, surgical oncologists and the university training program were shown to be key intermediaries between general surgeons and national specialty centers. Surgeons in group practice tended to use more learning sources than solo practitioners.

Conclusions: Surgical oncologists and university-based surgeons play key educational roles in disseminating new cancer treatments and therefore have a professional responsibility to educate other community physicians to increase the use of the most current, evidence-based practices.

Key Words: Sentinel lymph node biopsy • Breast cancer • Diffusion of innovations • Continuing medical education


   INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The average delay between publication of research findings and widespread adoption into clinical practice may approach 20 years.1 On a population basis, underuse of evidence-based care clearly rivals and arguably surpasses inappropriate use or misuse as a public health issue.2 Researchers and policy makers have devoted considerable attention to reducing the time lag between production and implementation of evidence-based care.3 In cancer therapy, most studies of diffusion have been devoted to screening, testing, and use of chemotherapy regimens. Table 1Go lists some major innovations in breast cancer therapies, their diffusion patterns, and factors that influenced their adoptions.4–14 The only surgical therapy in breast cancer whose diffusion has been described is breast conservation therapy (segmental mastectomy with whole-breast irradiation), which continues to be underused despite the many years that have passed since its first description as an acceptable alternative to mastectomy.4–10


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  		TABLE 1. Summary of major breast cancer innovations and related diffusion factors
 
Sentinel lymph node biopsy (SLNB) was first described in the mid-1990s as a surgical staging procedure for evaluation of axillary spread in early breast cancer.15,16 SLNB is an attractive alternative to axillary lymph node dissection (ALND) because it has less associated morbidity and may be more sensitive for the detection of metastases.17–22 The technical aspects of SLNB do not require excessive resources or technical skill; therefore, SLNB can be easily implemented in most, if not all, surgical practices.23 Several studies described the implementation of the technique in defined patient populations of early stage breast cancer in the late1990s and 2000s (e.g., American College of Surgeons, the University of Louisville Breast Cancer Sentinel Node Study Group, the Department of Defense hospitals, Surveillance, Epidemiology, and End Results program registry practitioners).23–28 These studies demonstrated marked variability in technique, a wide variety of learning sources, and geographic and racial disparities in SLNB use.23–28 Despite these reports of increasing adoption through the 1990s and early 2000s, SLNB did not gain national support as a standard of care and acceptable alternative to ALND until the early 2000s, after the publication of guidelines from the National Comprehensive Cancer Network and the American Society of Clinical Oncology.29–34 Since the publication of these guidelines, there has been little published about changes in practice patterns; however, one recent study reports SLNB adoption in some areas is barely over 50%, so many patients who could benefit from the technique still do not.28

In general, the timing of adoption of an innovation by individuals within a community follows a predictable pattern, which approximates a normal distribution. At one end of the distribution are the innovators and early adopters, who precede the adoption by the majority; the laggards are the last to accept innovation.35 The cumulative adoption curve (the fraction of the community who has implemented the technique over time) therefore follows a sigmoid curve.35 Prior work suggests that the rate of technology diffusion is affected by four sets of factors: the characteristics of the innovation, the characteristics of the potential adopters, the characteristics of the environment into which it will be adopted, and social forces (Fig. 1Go).35–37


Figure 1
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  		FIG. 1. Factors affecting adoption of innovations.

 
SLNB is an ideal platform for studying decision-making factors that underlie diffusion of surgical innovations because of its recent and rapid transition from experimental to a standard of care and its wide variability in use. Additionally, SLNB truly represents a technological innovation—with new equipment, new knowledge, and new skills—that is not fully represented by other medical innovations (such as new medications). To our knowledge, no prior studies have attempted to understand what sources physicians use to learn and implement new technologies. This knowledge is important for shaping continuing medical education and quality improvement strategies that will support rapid adoption of evidence-based practices while retarding (or averting) the adoption of practices that lack adequate empirical support.

The purpose of this study was to identify decision-making factors underlying SLNB implementation and learning patterns in one community, and to determine whether personal and practice characteristics (including specialty affiliation) affected the time of adoption and learning sources.


   MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Semistructured interviews were used to understand and describe the specific factors that affected decision making and attitudes about SLNB adoption and modification.38,39

Subjects
This project was approved by the University of California–Davis institutional review board, and all subjects gave informed consent before participation. Physicians providing surgical breast cancer care within a three-county urban region (population of nearly 2 million people) were recruited. Eligible subjects were surgical oncologists who perform breast surgery and all general surgeons who perform at least two breast cases per month. A surgical oncologist was defined as a surgeon with fellowship training in oncology; at least 50% devoted to cancer care; or a member of the Society of Surgical Oncology. Hospital directories, city phone directories, and word-of-mouth referrals were used to identify all surgical practices in the three-county region. All practices were contacted by telephone to determine surgeon eligibility. Forty-four eligible surgeons were identified and asked to participate by phone or in person.

Semistructured Interviews
A semistructured interview format was used to assess surgeons’ attitudes and experiences.40 All interviews were performed in person or by telephone after informed consent was obtained. Guiding questions for the interview consisted of 14 demographic questions (e.g., age, sex, training, practice characteristics) and six open-ended questions designed to elicit surgeons’ practice patterns, comfort with SLNB, learning experiences, and attitudes and factors influencing learning and practice patterns. Each open-ended question was followed by a series of prompts to generate more detailed discussion. All interviews were audio recorded and transcribed for analysis.

Qualitative Data Analysis
Systematic coding of transcripts and data analysis were performed by standard qualitative methods.38,39,41 The project team met intermittently to discuss emerging themes and how they might be categorized. Individually, a subset of team members (K.V., D.A.P.) reviewed all transcripts; collectively, they noted the predominant and recurrent themes and developed a code book of salient categories for analysis on the basis of the data and its relevance to surgical decision making.

All transcripts were entered into a qualitative software program (Atlas.ti 4.2; Atlas.ti Scientific Software, Berlin, Germany) to facilitate data analysis, where coding criteria were systematically applied to each transcript. Ten percent of all transcripts were randomly selected for dual coding (K.V., D.A.P.) to ensure consistency in the application of coding criteria. Data segments based on definitions of coding categories were abstracted from transcripts and organized into relevant thematic groups. The software program was then used to search across categories for recurring themes in the coded data. Matrices reflecting the presence or absence of key learning sources for each individual were created and used for calculations and comparisons between groups.

Network Analysis
Social network diagrams were created to depict connections between surgeon and key learning sources by using sociometric and graph theory principles.42 Relationships with information sources were considered directional, with information flowing to and from each surgeon and learning source. Noninterviewed surgeons mentioned as sources of information were included in the diagrams. The in-degrees (number of incoming links) for each surgeon was tabulated and compared across subgroups. In-degrees on surgeons who were not interviewed were not included in the analysis. Links between practice partners were only included if partners were specifically reported as an information source.

Statistical Analysis
Differences between groups were tested by {chi}2 test for discrete variables (presence or absence of factors) and by independent t-tests for continuous variables (age, time performing SLNB). P values were reported to provide a sense of the stability of differences and not to make statistical inferences to a larger population. For analyses of learning sources, surgeons were divided by their exposure to SLNB during training. For diffusion analyses, age was used as a marker of experience because time in practice was confounded by additional research or fellowship training obtained by specialty-trained surgeons before starting their practice. Cumulative adoption curves were generated by plotting the percentage of eligible surgeons performing SLNB (number of surgeons performing SLNB divided by the number in practice) during each calendar year. Histograms were also generated showing the number of surgeons who adopted SLNB each year, and approximated normal curves were generated and overlaid where appropriate. Stata 9.0 (StataCorp, College Station, TX) was used for statistical analyses.


   RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Forty-four eligible surgeons were identified, and 38 surgeons (86%) were interviewed between February and August 2005, including 11 surgical oncologists and 27 general surgeons. At the time of the interviews, all participants had implemented SLNB, except for one general surgeon. Six eligible general surgeons declined participation in the interview process. Semi-structured interview length averaged 20 minutes (range, 9–52 minutes). Interobserver coding reliability for the transcripts was calculated on the basis of the presence or absence of factors for each transcript ({kappa} = .97). Demographic and practice characteristics of the participants are listed in Table 2Go.


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  		TABLE 2. Demographics of study group (n = 38)
 
We examined two aspects of SLNB diffusion: timing of adoption and sources of initial learning of the technique. Timing of adoption was associated with specialty affiliation (e.g., surgical oncologist vs. general surgeon) but was not related to age. Although surgical oncologists were older than general surgeons (mean, 51 vs. 48 years, P = .02), they had used SLNB longer (6.1 vs. 3.3 years, P = .01). SLNB had been adopted by 100% of eligible surgical oncologists by 2000 at a time when it was still considered experimental (Fig. 2AGo). Surgical oncologists’ adoption of SLNB did not follow a normal distribution; rather, it was heavily skewed to early adoption, with the adopters after 2000 representing surgeons beginning a practice (Fig. 2BGo). General surgeons’ adoption followed a normal distribution (Fig. 2BGo), with few general surgeons adopting SLNB before 2000 (with new surgeons sometimes delaying their adoption several years after starting practice) and most general surgeons reporting adoption of SLNB between 2000 and 2003, after SLNB gained support as a standard of care at national meetings and publications.29–34 The overall diffusion of SLNB in our region followed a normal distribution (data not shown), with the surgical oncologists representing most early adopters. However, since the initial reports of SLNB success in breast cancer staging, it has taken over 10 years to diffuse through our community, with a single remaining nonadopter as of 2005.15–16


Figure 2
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  		FIG. 2. Adoption trends by year. (A) Cumulative adoption of sentinel lymph node biopsy (SLNB) between 1995 and 2005 (percentage of eligible surgeons performing SLNB by calendar year). X indicates entire group (N = 38); open circles indicate general surgeons (n = 27); solid triangles indicate surgical oncologists (n = 11). (B) Frequency plot of number of new adopters by year among general surgeons and surgical oncologists. General surgeons’ adoption follows the expected normal distribution (superimposed curve); surgical oncologists’ adoption is skewed toward early adopters.36

 
To explore the social network underlying diffusion of SLNB among surgeons, two network diagrams were created (data not shown): surgeon-surgeon interactions and timing of SLNB adoption; and surgeon interactions with key learning sources. In these networks, surgical oncologists and the university training program were key intermediaries between general surgeons and national specialty center (e.g., a nationally recognized center such as M. D. Anderson Cancer Center, Memorial Sloan-Kettering Cancer Center, H. Lee Moffitt Cancer Center and Research Institute, John Wayne Cancer Institute). Seventy-six percent of surgeons in our community (n = 29) received training or information directly from a specialty center, either directly or through an early adopter; three-quarters of surgeons in our community have access to and obtained educational information from a national specialty center. Furthermore, two-thirds of the information sources reported by surgeons were outside of the community (e.g., meetings or courses, literature, specialty centers, distant residency programs). Peer interactions accounted for less than one-quarter of the information sources, and a prior residency training program accounted for just 10%.

Mean and median number of sources used by individual surgeons was two, with a range of one to four. The learning sources used by surgeons are listed in Table 3Go.


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  		TABLE 3. Sources of learning for sentinel lymph node biopsy adoption based on exposure during training
 
Forty-eight percent of surgeons in group practice cited three or more learning sources, compared with only 20% of solo practitioners. Literature was the only source of learning for three practitioners (8%). Most general surgeons (55%) used three or more learning resources; conversely, surgical oncologists rarely cited three or more resources (18%, P = .04). There was no difference in the distribution of learning resources between surgical oncologists and general surgeons (data not shown). The university training program served as a key source of learning for 10 of 12 young (<45 years old) general surgeons in the community.


   DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
The results of this study suggest that learning new surgical approaches to breast cancer care involves multiple sources, and that almost all surgeons use two or more sources when learning a new surgical technique for breast cancer care. Surgeons early in their practice rely heavily on exposure during residency as their primary information source, with a minority seeking additional sources, even when they delay adoption of new surgical techniques for several years after being in practice. Interestingly, specialty affiliation (but not age) predicted timing of learning and adoption of SLNB, with surgical oncologists (who were slightly older) representing the early adopters.

Our study has three major limitations: small sample size, regional selection of the sample group, and potential self-reporting bias. Although the sample size is small, 85% of surgeons in our region participated in this study, representing every hospital and practice type. This is an excellent response rate given both the type of study (interviews) and study subjects (practicing surgeons). Although the practice patterns and timing of adoption of the six surgeons who did not participate cannot be easily assessed, all were performing SLNB for breast cancer by the time of our study. Because our sample is small and geographically limited, further research into learning patterns and social networking in larger and more diverse communities is needed to confirm and expand these results in the broader community. Although timing of SLNB adoption was obtained through physician self-report, we are confident of the veracity of these reports because surgeons had access to patient records during the interview and could refer to their records when necessary. Furthermore, most surgeons reported the exact timing immediately and with confidence, often naming the first patient they performed the procedure on, or referring to a temporally related event (e.g., a partner joining the practice or a specific national meeting they attended). We did not verify the competence of surgeons performing the technique, and only a handful of surgeons (the early adopters) reported performing a series of concomitant ALNDs to verify their results.43,44

The diffusion of SLNB through our community as a whole was rapid, and in keeping with theories of diffusion, it followed the expected normal distribution. However, different cohorts were seen to have their own adoption curves, and the adoption of SLNB by surgical oncologists in our area did not follow a normal distribution. In fact, the surgical oncologists were the early adopters in the overall diffusion curve of SLNB through our community, and their adoption was approximately 3 years earlier than their nonspecialty counterparts. Although the initial adopters in our community were involved in large clinical trials, all of the surgical oncologists had embraced SLNB by 2000—well before the technique had gained wide support as an acceptable standard of care. In this instance, published standards lagged behind the community standards for our specialists. Earlier adoption of SLNB by surgical oncologists may reflect earlier exposure, different social pressures, a desire to provide unique and competitive services, or personality differences among specialists (e.g., greater openness to change or greater comfort with new technologies in general), but our data cannot distinguish between these hypotheses, which are not mutually exclusive. Exposure to SLNB for melanoma and substantial supportive data expanding the technique for use in breast cancer may have been available to surgical oncologists sooner than to general surgeons (at meetings, in specialty publications, and in fellowship training), although we did not specifically examine this variable. Furthermore, incorporation of SLNB for breast cancer in surgical oncology fellowship training likely occurred before incorporation in general surgical training, although exact years of for comparison are not available. The success of SLNB among specialists may have lead to its later consideration and support for use in general surgical practice.

By 2002 (when SLNB was gaining national support and was a common component of residency training), all general surgeons entering practice in our community initiated SLNB from the moment of their arrival. Established surgeons (who had no exposure to SLNB during training) reported learning from multiple sources, with >80% reporting learning from a colleague. Many reported learning SLNB from a younger colleague joining their practice who was trained in the technique. In addition, two-thirds of our subjects reported taking a course, and almost half cited national meetings as a learning source. This demonstrates that most surgeons are seeking information actively—physically leaving the community to gain outside information in addition to learning from their colleagues and the literature. Although traditional continuing medical education (CME) has been disparaged as having little effect on physician behavior, our data suggest that national meetings and conferences may be key learning sources that are critical to the dissemination of new techniques.45 This may be related to motivation; either surgeons had already decided to implement SLNB (for patient benefit, competitive advantage, or other reasons) and therefore actively sought training; or CME focused on skill-based procedures is more effective than knowledge-based CME. Because our interest is primarily in technology diffusion, our study questions focused on learning and implementation of the technique of SLNB, rather than accepting the scientific concept that the sentinel lymph node is an accurate staging procedure in early-stage breast cancer. We did not differentiate learning the concept as a separate event that may have predated the learning of the technical skill. Our focus on learning of a skill rather than a concept may also explain the importance of CME and colleague interactions for learning sources. Web-based resources were not mentioned by our subjects; however, this may become an important resource for future diffusion of innovations.

Age did not affect timing of adoption of new techniques—even surgeons at the end of their careers rapidly adopted SLNB. This is in contrast to data showing that increasing age and experience are associated with less adherence to newer standards of practice and greater reliance on outdated (disproven) knowledge and practices.46 The unique characteristics of SLNB (e.g., low risk for iatrogenic harm and ease of mastery) may explain its rapid adoption by surgeons of all ages. If SLNB required more technical expertise or the development of new skills, then age (and experience) might have affected overall adoption rates. Our data suggest that motivated individuals of any age will seek out information and adopt techniques, even if the sources for information acquisition are different among different age cohorts. Furthermore, our data demonstrate that most surgeons in our community accepted SLNB as an alternative to ALND (as evidenced by their learning and implementation of the technique in their practices) just before the publication of national guidelines. This finding suggests that acceptance of a new technique within the surgical community may precede published guidelines and support from national organizations.

In conclusion, age (time out of residency) may affect surgeons’ learning styles and sources of information acquisition for new breast cancer therapies, but not necessarily the rate of adoption of new techniques. This study also establishes the continued need for multiple complementary learning resources, and the importance of national meetings and courses in the dissemination of evidence-based cancer care to the community surgeon. Specialty affiliation, rather than age, seems to predict the early adopters of breast cancer innovations, and may be more important in the initial rather than the latter phases of diffusion. Therefore, specialists are important leaders (and learning sources) in their communities, and should consider education and training of their nonspecialty colleagues a part of their professional commitment to patients and the advancement of evidence-based care.


   ACKNOWLEDGMENTS
 
Presented in part at the 77th Annual Meeting of the Pacific Coast Surgical Association, February 17–20, 2006, San Francisco, CA. This research was supported by a K30 Mentored Clinical Research Training Grant from the University of California–Davis School of Medicine. We thank all of the surgeons who volunteered their time and experiences to this research.

Received for publication September 27, 2006. Accepted for publication December 18, 2006.


   REFERENCES
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 

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