Erin E. Hahn

Use of posttreatment imaging and biomarkers in survivors of early‐stage breast cancer: Inappropriate surveillance or necessary care?

Advanced imaging and serum biomarkers are commonly used for surveillance in patients with early‐stage breast cancer, despite recommendations against this practice. Incentives to perform such low‐value testing may be less prominent in integrated health care delivery systems. The purpose of the current study was to evaluate and compare the use of these services within 2 integrated systems: Kaiser Permanente (KP) and Intermountain Healthcare (IH). The authors also sought to distinguish the indication for testing: diagnostic purposes or routine surveillance.

Use of Imaging for Staging of Early-Stage Breast Cancer in Two Integrated Health Care Systems: Adherence With a Choosing Wisely Recommendation

PURPOSE Advanced imaging is commonly used for staging of early-stage breast cancer, despite recommendations against this practice. The objective of this study was to evaluate and compare use of imaging for staging of breast cancer in two integrated health care systems, Kaiser Permanente (KP) and Intermountain Healthcare (IH). We also sought to distinguish whether imaging was routine or used for diagnostic purposes. METHODS We identified patients with stages 0 to IIB breast cancer diagnosed between 2010 and 2012. Using KP and IH electronic health records, we identified use of computed tomography, positron emission tomography, or bone scintigraphy 30 days before diagnosis to 30 days postsurgery. We performed chart abstraction on a random sample of patients who received a presurgical imaging test to identify indication. RESULTS For the sample of 10,010 patients, mean age at diagnosis was 60 years (range, 22 to 99 years); with 21% stage 0, 47% stage I, and 32% stage II. Overall, 15% of patients (n = 1,480) received at least one imaging test during the staging window, 15% at KP and 14% at IH (P = .5). Eight percent of patients received imaging before surgery, and 7% postsurgery. We found significant intraregional variation in imaging use. Chart abstraction (n = 129, 16% of patients who received presurgical imaging) revealed that 48% of presurgical imaging was diagnostic. CONCLUSION Use of imaging for staging of low-risk breast cancer was similar in both systems, and slightly lower than has been reported in the literature. Approximately half of imaging tests were ordered in response to a sign or symptom.

Using Implementation Science to Examine the Impact of Cancer Survivorship Care Plans

Rebecca Selove, Tennessee State University, Nashville, TN Sarah A. Birken, The University of North Carolina at Chapel Hill, Chapel Hill, NC Ted A. Skolarus, University of Michigan; Veterans Affairs Health Services Research and Development Center for Clinical Management Research; and Veterans Affairs Ann Arbor Healthcare System, Ann Arbor, MI Erin E. Hahn, Kaiser Permanente Southern California, Pasadena, CA Anne Sales, University of Michigan, Ann Arbor, MI Enola K. Proctor, Washington University in St Louis, St Louis, MO

Anxiety, Culture, and Expectations: Oncologist-Perceived Factors Associated With Use of Nonrecommended Serum Tumor Marker Tests for Surveillance of Early-Stage Breast Cancer

PURPOSE Breast cancer offers several opportunities for reducing use of ineffective practices based on American Society of Clinical Oncology guidelines. We assessed oncologist-perceived factors associated with use of one such practice-serum tumor markers for post-treatment breast cancer surveillance-focusing on medical oncologists with high, medium, or low test use. METHODS Using a mixed-methods design, we identified patients who had been treated for early-stage breast cancer diagnosed between January 1, 2009, and December 31, 2012, within Kaiser Permanente Southern California and calculated the number of tests ordered from January 1, 2010, to December 31, 2014. We identified oncologists with high, medium, or low use and subsequently performed semistructured interviews. We used patient satisfaction data to assess association between pattern of use and satisfaction score. RESULTS We identified 7,363 patients, with 40,114 tests ordered. High-use oncologists were defined as those ordering at least one test annually for 35% of patients or more, low-use oncologists as those ordering at least one test for 5% of patients or less; 42% of oncologists were high, 27% low, and 31% medium users. We interviewed 17 oncologists: six high, eight low, and three medium users. Factors associated with high use included: perceived patient anxiety, oncologist anxiety, belief that there was nothing else to offer, concern about satisfaction, patient competition, peer use, and system barriers. Factors associated with low use included: beliefs about consequences (eg, causes harms) and medical center culture (eg, collective decision to follow guidelines). We found no association between satisfaction score and pattern of use. CONCLUSION Barriers to deimplementation are numerous and complex. Traditional strategies of practice change alone are unlikely to be effective. Multifaceted, multilevel strategies deployed to address patient-, clinician-, and system-related barriers may be required.

Comorbidity Profiles and Their Effect on Treatment Selection and Survival among Patients with Lung Cancer

Rationale: Prior work has shown that the comorbidity burden is high among patients with lung cancer, but patterns of comorbid conditions have not been systematically identified. Objectives: We aimed to identify distinct comorbidity profiles in a large sample of patients with lung cancer and to examine the effect of comorbidity profiles on treatment and survival. Methods: In this retrospective cohort study, we used latent class analysis to identify comorbidity profiles (or classes) in a population‐based sample of 6,662 patients with bronchogenic carcinoma diagnosed between 2008 and 2013. We included specific comorbid conditions from the Charlson comorbidity index. We used Cox proportional hazards analysis to examine the effect of comorbidity class on survival. Results: The mean age of the patients was 70 years, and 50% were female, 34% were nonwhite, and 17% were never‐smokers. Most patients had stage III (21%) or IV (53%) disease. Over half (51%) had at least one comorbid condition, whereas 18% had at least four comorbidities. Latent class analysis identified five distinct comorbidity classes. Classes were defined by progressively greater Charlson comorbidity index scores and were further distinguished by the presence or absence of specific types of vascular disease and diabetes. Comorbidity class was independently associated with treatment selection (P < 0.001) and survival (P < 0.0001), especially among patients with stages 0‐II disease (P < 0.0001). Conclusions: Patients with lung cancer can be described by distinct comorbidity profiles that are independent predictors of treatment and survival. These profiles provide a more nuanced understanding of how comorbidities cluster within patients with lung cancer and how they can be applied for descriptive purposes or in research.

Integrating qualitative research methods into care improvement efforts within a learning health system: addressing antibiotic overuse

BackgroundDespite reports advocating for integration of research into healthcare delivery, scant literature exists describing how this can be accomplished. Examples highlighting application of qualitative research methods embedded into a healthcare system are particularly needed. This article describes the process and value of embedding qualitative research as the second phase of an explanatory, sequential, mixed methods study to improve antibiotic stewardship for acute sinusitis.MethodsPurposive sampling of providers for in-depth interviews improved understanding of unwarranted antibiotic prescribing and elicited stakeholder recommendations for improvement. Qualitative data collection, transcription and constant comparative analyses occurred iteratively.ResultsEmerging themes and sub-themes identified primary drivers of unwarranted antibiotic prescribing patterns and recommendations for improving practice. These findings informed the design of a health system intervention to improve antibiotic stewardship for acute sinusitis. Core components of the intervention are also described.ConclusionQualitative research can be effectively applied in learning healthcare systems to elucidate quantitative results and inform improvement efforts.

Understanding Comorbidity Profiles and Their Effect on Treatment and Survival in Patients With Colorectal Cancer

Background: Patients with colorectal cancer (CRC) commonly present at an older age with multiple comorbid conditions and complex care needs at the time of diagnosis. Clusters of comorbid conditions, or profiles, have not been systematically identified in this patient population. This study aimed to identify clinically distinct comorbidity profiles in a large sample of patients with CRC from an integrated healthcare system, and to examine the effect of comorbidity profiles on treatment and survival. Methods: In this retrospective cohort study, we used latent class analysis (LCA) to identify comorbidity profiles in a sample of 7,803 patients with CRC diagnosed between 2008 and 2013. We identified treatment received from electronic health records and used Cox proportional hazards analysis to examine the effect of comorbidity class on survival. We also examined the effect of comorbidity profile on receipt of guideline-recommended treatment. Results: Median age at diagnosis was 66 years, 52% of patients were male, and 48% were nonwhite. A plurality had stage 0-I disease (42%), with 22% stage II, 22% stage III, and 14% stage IV. More than half (59%) had ≤1 comorbid condition, whereas 19% had ≥4 comorbidities. LCA identified 4 distinct comorbidity classes. Classes were distinguished by the presence or absence of vascular and/or respiratory disease and diabetes with complications, as well as progressively greater Charlson comorbidity index scores. Comorbidity class was independently associated with treatment selection (P<.001) and survival (P<.001). Conclusions: Patients with CRC can be described by 4 distinct comorbidity profiles that are independent predictors of treatment and survival. These results provide insight into how comorbidities cluster within patients with CRC. This work represents a shift away from simple counting of comorbid conditions and toward a more nuanced understanding of how comorbidities cluster within groups of patients with CRC.

Survivorship care plans: are randomized controlled trials assessing outcomes that are relevant to stakeholders?

PurposeThe purpose of this study was to compare outcomes assessed in extant randomized controlled trials (RCTs) to outcomes that stakeholders expect from survivorship care plans (SCPs). To facilitate the transition from active treatment to follow-up care for the 15.5 million US cancer survivors, many organizations require SCP use. However, results of several RCTs of SCPs’ effectiveness have been null, possibly because they have evaluated outcomes on which SCPs should be expected to have limited influence. Stakeholders (e.g., survivors, oncologists) may expect outcomes that differ from RCTs’ outcomes.MethodsWe identified RCTs’ outcomes using a PubMed literature review. We identified outcomes that stakeholders expect from SCPs using semistructured interviews with stakeholders in three healthcare systems in the USA and Canada. Finally, we mapped RCTs’ outcomes onto stakeholder-identified outcomes.ResultsRCT outcomes did not fully address outcomes that stakeholders expected from SCPs, and RCTs assessed outcomes that stakeholders did not expect from SCPs. RCTs often assessed outcomes only from survivors’ perspectives.ConclusionsRCTs of SCPs’ effectiveness have not assessed outcomes that stakeholders expect. To better understand SCPs’ effectiveness, future RCTs should assess outcomes of SCP use that are relevant from the perspective of multiple stakeholders.Implications for Cancer SurvivorsSCPs’ effectiveness may be optimized when used with an eye toward outcomes that stakeholders expect from SCPs. For survivors, this means using SCPs as a map to guide them with respect to what kind of follow-up care they should seek, when they should seek it, and from whom they should seek it.

Surveillance Imaging in Patients with Resected Non–Small Cell Lung Cancer: Too Much, Not Enough, or Just Right?

Lung cancer remains the leading cause of cancer death for both men and women in the United States, with about 1 out of 4 cancer deaths being due to lung cancer (1). Thankfully, due to advances in detection and treatment, the 5-year relative survival rate is increasing over time, and lung cancer mortality has been falling, on average, 2.2% per year over the past decade (2). There are approximately half a million lung cancer survivors living in the United States today (1). In addition, the adoption of lung cancer screening in high-risk individuals may increase the frequency of localized lung cancer, potentially leading to a substantial increase in the number of survivors of long-term lung cancer. Thus, developing evidence and clinical programs to deliver high-quality, evidence-based surveillance care for patients with lung cancer is of critical importance to ensure optimal patient experience and outcomes. There is considerable debate over the optimal frequency, timing, and modalities for post-treatment surveillance of patients with lung cancer treated with curative intent (3–5). Lacking data from prospective, randomized control trials, professional societies and others have relied on retrospective observational data to craft guidelines for surveillance care of surgically resected patients with lung cancer. For example, guidelines from the American College of Chest Physicians (ACCP) make a weak (conditional) recommendation in favor of computed tomography (CT) scanning every 6 months in the first 2 years after treatment, and annual scanning thereafter, for patients with non–small cell lung cancer (NSCLC) treated with curative intent (6). The ACCP guidelines are explicit about the lack of well-designed, prospective research studies on surveillance strategies for these patients and the associated potential for confounding and selection bias. Accordingly, the guidelines include recommendations for patient–provider discussion of surveillance preferences, and highlight the need for further research in this area. Given the uncertainty around surveillance of patients with NSCLC lung cancer treated with curative intent, what is the current state of surveillance care for these patients? In this issue of AnnalsATS, Sharma and colleagues (pp. 1559–1567) describe patterns of surveillance imaging for patients with NSCLC treated with surgical resection in the United States using Surveillance, Epidemiology, and End Results (SEER)-Medicare linked data (7). The authors examined use of chest radiography, chest CT, and positron emission tomography (PET) between 1992 and 2005. In the 5 years after surgical resection, the vast majority of patients underwent at least one imaging test during each year of the 5-year surveillance period. A surprising number of patients had chest radiography, the most common imaging service in this cohort, ranging from 91% of patients who received at least one in the first year after treatment to 84% in the fifth year. The use of chest CT ranged from 41% of patients in the first year to 7% in the fifth year, and use of PET was uncommon, ranging from 5% in the first year to 4% in the fifth. Overall, the findings indicate that use of chest CT and PET rose rapidly from 1992 to 2005, which echoes findings from other population-based studies on imaging patterns (8). The authors found that use of imaging had discernable peaks at 6and 12-month intervals, suggesting that many of these services are, in fact, being used for surveillance purposes, rather than for the evaluation of patient-reported symptoms or clinical signs found on physical exam. In addition, the authors categorized imaging services as either for surveillance or evaluation, with evaluation defined as: (1) scans performed during hospitalization; or (2) scans performed within 30 days of a chest radiograph. The odds of receiving a surveillance CT or PET scan were found to increase every year, based on year of diagnosis (odds ratio, 1.32; 95% confidence interval, 1.29–1.36). The sensitivity and specificity of this method is not perfect, as, for example, a chest CT may be ordered to evaluate a symptom or sign without an initial chest radiograph. However, this is a reasonable approach to determining clinical indication in a large, de-identified dataset where chart review is not possible. It is not surprising that the highest rates of imaging were found in the years immediately after treatment. Recurrence rates for patients with NSCLC patients range from 30–75%, depending on stage (9). Patients and clinicians are likely to want to do everything they can to identify and treat recurrence and new primary disease. Risk-averse clinicians may perceive a significant benefit to more aggressive imaging during the first 2 years after

Developing innovative models of care for cancer survivors: use of implementation science to guide evaluation of appropriateness and feasibility

PurposeLimited understanding of factors affecting uptake and outcomes of different cancer survivorship care models hampers implementation of best practices. We conducted a formative evaluation of stakeholder-perceived acceptability and feasibility of an embedded primary care provider (PCP) survivorship care model.MethodsWe identified clinical, operational, and patient stakeholders within Kaiser Permanente Southern California and conducted semi-structured interviews. Analyses were guided by the Consolidated Framework for Implementation Research (CFIR), an integrated framework from the field of implementation science. Deductive thematic categories were derived a priori from CFIR domains; thematic sub-categories were developed inductively.ResultsWe interviewed 12 stakeholders; multiple themes were identified. Acceptability: oncologists and operational leaders perceived that the model was an acceptable solution to issues of capacity and efficiency with the potential to improve quality; however, several oncologists perceived negative consequences including “[loss of] the joy of medicine.” Patients were less enthusiastic, fearing the introduction of “[someone] who doesn’t know me.” Feasibility: confidence was high that this model can succeed, although there was concern about finding the right PCP and investment in training and staff support. Culture/climate: numerous system-level facilitators were identified, including encouragement of innovation and familiarity with developing new models.ConclusionsFormative evaluation is a critical pre-implementation process. Acceptability and feasibility for this model were high among oncologists and operational leaders but patients were ambivalent. Keys to successful implementation include training and support of engaged PCPs and a patient transition plan introduced early in the care trajectory.