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Background Lung cancer has been the leading cause of American deaths from cancer. Although Medicare started covering lung cancer screening (LCS) with low-dose computed tomography (LDCT) in 2015, the uptake of LDCT-LCS remains low. This study examines the changes in adherence to provider referrals for LDCT-LCS and the factors at patient, provider, and health system levels that influence the completion rate of LDCT-LCS orders before and during the COVID-19 pandemic.Methods Our study examined electronic health record data (December 2013 - December 2020) from a large, community-based clinical healthcare delivery system in California. We plotted monthly trends in the frequency of LDCT-LCS orders and completion rate and compared the annual LDCT-LCS completion rate between LCS-eligible and LCS-ineligible groups. We then explored multilevel factors associated with the completion of LDCT-LCS orders using hierarchical generalized linear models.Results There was an increase in LDCT-LCS orders (N = 12,469) from 2013 to 2019, followed by a sharp decline in March 2020 due to the onset of the COVID-19 pandemic. Thereafter, LDCT-LCS orders slowly increased again in June 2020. The completion rate of LDCT-LCS increased from 0% in December 2013 to approximately 70% in 2018–2019 but declined to 50–60% in 2020 during the pandemic. Ineligible patients had lower completion rates of LDCT-LCS. Patients who were new to the healthcare system, Black, received the LDCT-LCS order in the first few years after Medicare coverage (2016 or 2017), during the pandemic, had major comorbidities, and smoked less than 30 pack-years were less likely to complete an order. Patients were more likely to complete LDCT-LCS orders if they were younger, received the LDCT-LCS order from a physician (vs. nonphysician provider), from family medicine or other specialties (vs. internal medicine), or saw a provider with more experience in LDCT-LCS.Conclusions The beginning of the COVID-19 pandemic largely decreased the volume of LDCT-LCS orders, but rates have since been slowing recovering. Future interventions to improve lung cancer screening should consider doing more targeted outreach to new patients and Black patients as well as providing additional education to nonphysician practitioners and those providers with lower rates of LDCT-LCS referral orders.

Purpose To assess the impact of Lean primary care redesigns on the amount of time that physicians spent working each day. Methods This observational study was based on 92 million time-stamped Epic® EHR access logs captured among 317 primary care physicians in a large ambulatory care delivery system. Seventeen clinic facilities housing 46 primary care departments were included for study. We conducted interrupted time series analysis to monitor changes in physician work patterns over 6 years. Key measures included total daily work time; time spent on “desktop medicine” outside the exam room; time spent with patients during office visits; time still working after clinic, i.e., after seeing the last patient each day; and remote work time. Results The amount of time that physicians spent on desktop EHR activities throughout the day, including after clinic hours, decreased by 10.9% (95% CI: −22.2, −2.03) and 8.3% (95% CI: −13.8, −2.12), respectively, during the first year of Lean implementation. Total daily work hours among physicians, which included both desktop activity and time in office visits, decreased by 20% (95% CI: −29.2, −9.60) by the third year of Lean implementation. Conclusions These findings suggest that Lean redesign may be associated with time savings for primary care physicians. However, since this was an observational analysis, further study is warranted (e.g., randomized trial) —to determine the impact of Lean interventions on physician work experiences.

Multi-cancer gene panels for hereditary cancer syndromes (hereditary cancer panels, HCPs) are widely available, and some laboratories have programs that limit patients' out-of-pocket (OOP) cost share. However, little is known about practices by cancer genetic counselors for discussing and ordering an HCP and how insurance reimbursement and patient out-of-pocket share impact these practices. We conducted a survey of cancer genetic counselors based in the United States through the National Society of Genetic Counselors to assess the impact of reimbursement and patient OOP share on ordering of an HCP and hereditary cancer genetic counseling. Data analyses were conducted using chi-square and t tests. We received 135 responses (16% response rate). We found that the vast majority of respondents (94%, 127/135) ordered an HCP for patients rather than single-gene tests to assess hereditary cancer predisposition. Two-thirds of respondents reported that their institution had no protocol related to discussing HCPs with patients. Most respondents (84%, 114/135) indicated clinical indications and patients' requests as important in selecting and ordering HCPs, while 42%, 57/135, considered reimbursement and patient OOP share factors important. We found statistically significant differences in reporting of insurance as a frequently used payment method for HCPs and in-person genetic counseling (84% versus 59%, respectively, p 0.0001). Perceived patient willingness to pay more than $100 was significantly higher for HCPs than for genetic counseling(41% versus 22%, respectively, p 0.01). In sum, genetic counselors' widespread selection and ordering of HCPs is driven more by clinical indications and patient preferences than payment considerations. Respondents perceived that testing is more often reimbursed by insurance than genetic counseling, and patients are more willing to pay for an HCP than for genetic counseling. Policy efforts should address this incongruence in reimbursement and patient OOP share. Patient-centered communication should educate patients on the benefit of genetic counseling.

ObjectiveTo examine the effect of Lean primary care redesigns on patient satisfaction with care and timeliness of care received.Data/settingWe used patient surveys and time-stamped electronic health record (EHR) data in a large ambulatory care system.DesignLean-based changes to clinical spaces and care team workflows were implemented in one pilot site and then scaled to all primary care departments across the system. Redesigns included standardizing equipment and patient education materials in examination rooms, streamlining call management functions, co-locating physician and medical assistant dyads in a shared workspace, and creating new care team workflows. We used a non-randomized stepped-wedge study design and segmented regression with interrupted time series analysis to examine Lean impacts on patient outcomes.Data collectionWe analyzed patient satisfaction ratings and wait times as documented by the EHR. These longitudinal data were collected for 317 physician-led teams in 46 primary care departments from January 2011 to December 2016.Principal findingsAfter implementation of Lean redesigns, patients reported a 44.8 percent increase in satisfaction with the adequacy of time spent with care providers during office visits (P&nbsp

Early palliative care (PC) for individuals with advanced cancer improves patient and family outcomes and experience. However, it is unknown when, why, and how in an outpatient setting individuals with stage IV cancer are referred to PC. At a large multi-specialty group in the USA with outpatient PC implemented beginning in 2011, clinical records were used to identify adults diagnosed with stage IV cancer after January 1, 2012 and deceased by December 31, 2017 and their PC referrals and hospice use. In-depth interviews were also conducted with 25 members of medical oncology, gynecological oncology, and PC teams and thematically analyzed. A total of 705 individuals were diagnosed and died between 2012 and 2017: of these, 332 (47%) were referred to PC, with 48.5% referred early (within 60 days of diagnosis). Among referred patients, 79% received hospice care, versus 55% among patients not referred. Oncologists varied dramatically in their rates of referral to PC. Interviews revealed four referral pathways: early referrals, referrals without active anti-cancer treatment, problem-based referrals, and late referrals (when stopping treatment). Participants described PC’s benefits as enhancing pain/symptom management, advance care planning, transitions to hospice, end-of-life experiences, a larger team, and more flexible patient care. Challenges reported included variation in oncologist practices, patient fears and misconceptions, and access to PC teams. We found high rates of use and appreciation of PC. However, interviews revealed that exclusively focusing on rates of referrals may obscure how referrals vary in timing, reason for referral, and usefulness to patients, families, and clinical teams.

Many studies have assessed the factors associated with overall video visit use during the COVID-19 pandemic, but little is known about who is most likely to continue to use video visits and why. The authors combined a survey with electronic health record data to identify factors affecting the continued use of video visit. In August 2020, a stratified random sample of 20,000 active patients from a large health care system were invited to complete an email survey on health care seeking preferences during the COVID. Weighted logistic regression models were applied, adjusting for sampling frame and response bias, to identify factors associated with video visit experience, and separately for preference of continued use of video visits. Actual video visit utilization was also estimated within 12 months after the survey. Three thousand three hundred fifty-one (17.2%) patients completed the survey. Of these, 1208 (36%) reported having at least 1 video visit in the past, lowest for African American (33%) and highest for Hispanic (41%). Of these, 38% would prefer a video visit in the future. The strongest predictors of future video visit use were comfort using video interactions (odds ratio [OR] = 5.30, 95% confidence interval [95% CI]: 3.57-7.85) and satisfaction with the overall quality (OR = 3.94, 95% CI: 2.66-5.86). Interestingly, despite a significantly higher satisfaction for Hispanic (40%-55%) and African American (40%-50%) compared with Asian (29%-39%), Hispanic (OR = 0.46, 95% CI: 0.12-0.88) and African American (OR = 0.54, 95% CI: 0.16-0.90) were less likely to prefer a future video visit. Disparity exists in the use of video visit. The association between patient satisfaction and continued video visit varies by race/ethnicity, which may change the future long-term video visit use among race/ethnicity groups.

Background: Real-world evidence (RWE) studies for surveillance patterns following lung cancer (LC) diagnosis can inform optimizing recommendations on surveillance and practice. One major obstacle in RWE studies for LC surveillance is the lack of radiologic imaging indication for surveillance vs. other reasons (e.g., symptoms). To enable RWE studies for surveillance to detect second primary lung cancer among LC survivors, we developed a hybrid modelling approach that integrates structured data from electronic health records (EHRs) with natural language processing (NLP) from radiology reports for abstracting computed tomography (CT) imaging indications in LC survivors. Methods: We manually reviewed and abstracted CT imaging indications, i.e., surveillance vs. others (e.g., symptoms and metastatic disease follow-up) to create a gold standard from 200 randomly selected radiology reports among 1,952 LC patients (i) who were diagnosed in 2000-2017 at Stanford Health Care (SHC) and (ii) survived ≧5 years after the diagnosis. We abstracted medically relevant key-phrases using the part-of-speech grammar and PageRank algorithms. Hierarchical clustering identified context-specific key-phrase clusters as follows: “surveillance”, “stable”, “nodule”, “symptom”, and “metastasis”. The text-based radiology reports were vectorized to generate NLP features using phrase occurrence frequencies. The structured variables from EHRs included: (i) diagnosis of lung diseases or chest symptoms in previous 6 months, (ii) ordering provider-type (oncology vs. others [e.g. emergency and internal medicine]), and (iii) time from previous CT (≧6 months). A hybrid model was then fitted using logistic regression including both structured and NLP features and validated using a 10-fold cross-validation. The model’s performance was compared to those solely based on NLP or structured data. Results: The dataset of 200 radiology reports included 141 LC survivors (49% White, 72% adenocarcinoma). The proposed hybrid model showed high discrimination (AUC: 0.92), outperforming those based solely on NLP (AUC: 0.88) or structured data (AUC: 0.87). The proposed model demonstrated higher sensitivity (SN: 0.73) and specificity (SP: 0.96) versus those solely based on NLP (SN: 0.53; SP: 0.96) or structured data (SN: 0.53; SP: 0.90). The hybrid model showed that the following variables were positively associated with a higher likelihood that the given CT imaging indication is “surveillance”: (i) a longer time interval (≧6 months) from the previous CT (odds ratio [OR]: 4.63; p=0.01) and key-phrases of (ii) “nodule” (OR: 1.55; p=0.004) and (iii) “stable” (OR: 1.37; p=0.03). On the other hand, the following were negatively associated with the likelihood of surveillance: the key-phrases of “symptom” (OR: 0.17; p=0.02) and “metastasis” (OR: 0.26; p=0.02). Conclusion: A hybrid modeling approach combining text-based NLP and structured EHRs has the potential for abstracting CT imaging indications for LC surveillance. Future directions include validation using other EHR systems and extension using larger data. Citation Format: Aparajita Khan, Julie Wu, Eunji Choi, Anna Graber-Naidich, Solomon Henry, Heather A. Wakelee, Allison W. Kurian, Su-Ying Liang, Ann Leung, Curtis Langlotz, Leah M. Backhus, Summer S. Han. A hybrid modelling approach for abstracting CT imaging indications by integrating natural language processing from radiology reports with structured data from electronic health records. [abstract]. In: Proceedings of the AACR Special Conference: Precision Prevention, Early Detection, and Interception of Cancer; 2022 Nov 17-19; Austin, TX. Philadelphia (PA): AACR; Can Prev Res 2023;16(1 Suppl): Abstract nr P068.

BACKGROUND Behavioral economics–based techniques have been an increasingly utilized method in health care to influence behavior change by modifying language in patient communication (through choice architecture and the framing of words). Patient portals are a key tool for facilitating patient engagement in their health, and interventions deployed via patient portals have been effective in improving utilization of preventive health services. OBJECTIVE We examined the impacts of behavioral economics–based nudge health maintenance reminders on appointment scheduling through a patient portal and appointment completion for 2 preventive services: Medicare wellness visits and Pap smear. METHODS We conducted a retrospective observational study using electronic health record data from an integrated health care system in Northern California. Nudge health maintenance reminders with behavioral economics–based language were implemented for all sites in November 2017 for Medicare wellness visits and for selected sites in February 2018 for Pap smears. We analyzed 125,369 health maintenance reminders for Medicare wellness visits, and 585,358 health maintenance reminders for Pap smear sent between January 2017 and February 2020. The primary outcomes were rate of appointments scheduled through the patient portal and appointment completion rate. We compared the outcomes between those who received the new, behavioral economics–based health maintenance reminders (the nudge group) and those who received the original, standard health maintenance reminders (the control group). We used segmented regression with interrupted time series to assess the immediate and gradual effect of the nudge for Medicare wellness visits, and we used logistic regression to assess the association of nudge health maintenance reminders, adjusting for the propensity to receive a nudge health maintenance reminder, for Pap smear. RESULTS The rates of appointments scheduled through the patient portal were higher for nudge health maintenance reminder recipients than those for control health maintenance reminder recipients (Medicare wellness visits—nudge: 12,537/96,839, 13.0%; control: 2,769/28,530, 9.7%, PPPP=.30). There was a marginally gradual effect of nudge on number of appointments scheduled through the patient portal for the overall Medicare wellness visits sample (at a monthly rate of 0.26%, P=.09), and a significant gradual effect among scheduled appointments (at a monthly rate of 0.46%, P=.04). For Pap smear, nudge health maintenance reminders were positively associated with number of appointments scheduled through the patient portal (overall sample: propensity adjusted odds ratio [OR] 1.62; 95% CI 1.50-1.74; among scheduled appointments: propensity adjusted OR 1.61, 95% CI 1.47-1.76) and with appointment completion (propensity adjusted OR 1.07; 1.04-1.10). CONCLUSIONS Nudges, a behavioral economics–based approach to providing health maintenance reminders, imcreased the number of appointments scheduled through the patient portal for Medicare wellness visits and Pap smear. Our study demonstrates that a simple approach—framing and modifying language in an electronic message—can have a significant and long-term impact on patient engagement and access to care.

PURPOSE: Optimal cancer care requires patient self-management and coordinated timing and sequence of interdependent care. These are challenging, especially in safety-net settings treating underserved populations. We evaluated the 4R Oncology model (4R) of patient-facing care planning for impact on self-management and delivery of interdependent care at safety-net and non–safety-net institutions. METHODS: Ten institutions (five safety-net and five non–safety-net) evaluated the 4R intervention from 2017 to 2020 with patients with stage 0-III breast cancer. Data on self-management and care delivery were collected via surveys and compared between the intervention cohort and the historical cohort (diagnosed before 4R launch). 4R usefulness was assessed within the intervention cohort. RESULTS: Survey response rate was 63% (422/670) in intervention and 47% (466/992) in historical cohort. 4R usefulness was reported by 79.9% of patients receiving 4R and was higher for patients in safety-net than in non–safety-net centers (87.6%, 74.2%, P = .001). The intervention cohort measured significantly higher than historical cohort in five of seven self-management metrics, including clarity of care timing and sequence (71.3%, 55%, P < .001) and ability to manage care (78.9%, 72.1%, P = .02). Referrals to interdependent care were significantly higher in the intervention than in the historical cohort along all six metrics, including primary care consult (33.9%, 27.7%, P = .045) and flu vaccination (38.6%, 27.9%, P = .001). Referral completions were significantly higher in four of six metrics. For safety-net patients, improvements in most self-management and care delivery metrics were similar or higher than for non–safety-net patients, even after controlling for all other variables. CONCLUSION: 4R Oncology was useful to patients and significantly improved self-management and delivery of interdependent care, but gaps remain. Model enhancements and further evaluations are needed for broad adoption. Patients in safety-net settings benefited from 4R at similar or higher rates than non–safety-net patients, indicating that 4R may reduce care disparities.

BACKGROUND: Many primary care practices have adopted Lean techniques to reduce the amount of time spent completing routine tasks. Few studies have evaluated both immediate and sustained impacts of Lean to improve this aspect of primary care work efficiency. OBJECTIVE: To examine 3-year impacts of Lean implementation on the amount of time taken for physicians to complete common clinical tasks. DESIGN: Non-randomized stepped wedge with segmented regression and interrupted time series analysis (January 2011–December 2016). PARTICIPANTS: A total of 317 physician-led teams in 46 primary care departments in a large ambulatory care delivery system. INTERVENTION: Lean redesign was initiated in one pilot site followed by system-wide spread across all primary care departments. Redesigns included standardization of exam room equipment and supplies, streamlining of call management processes, care team co-location, and team management of the electronic inbox. MEASURES: Time-stamped EHR tracking of physicians’ completion time for 4 common tasks: (1) office visit documentation and closure of patient charts; (2) telephone call resolution; (3) prescription refill renewal; and (4) response to electronic patient messages. RESULTS: After Lean implementation, we found decreases in the amount of time to complete: office visit documentation (− 29.2% [95% CI: − 44.2, − 10.1]), telephone resolution (− 22.2% [95% CI: − 38.1, − 2.27]), and renewal of prescription refills (− 2.96% per month [95% CI: − 4.21, − 1.78]). These decreases were sustained over several years. Response time to electronic patient messages did not change significantly. CONCLUSIONS: Lean redesigns led to improvements in timely completion of 3 out of 4 common clinical tasks. Our findings support the use of Lean techniques to engage teams in routine aspects of patient care. More research is warranted to understand the mechanisms by which Lean promotes quality improvement and effectiveness of care team workflows.

Background: A relatively high proportion of Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females with lung cancer have never smoked. We used an integrative data approach to assemble a large-scale cohort to study lung cancer risk among AANHPIs by smoking status with attention to representation of specific AANHPI ethnic groups. Methods: We leveraged electronic health records (EHRs) from two healthcare systems—Sutter Health in northern California and Kaiser Permanente Hawai'i—that have high representation of AANHPI populations. We linked EHR data on lung cancer risk factors (i.e., smoking, lung diseases, infections, reproductive factors, and body size) to data on incident lung cancer diagnoses from statewide population-based cancer registries of California and Hawai'i for the period between 2000 and 2013. Geocoded address data were linked to data on neighborhood contextual factors and regional air pollutants. Results: The dataset comprises over 2.2 million adult females and males of any race/ethnicity. Over 250,000 are AANHPI females (19.6% of the female study population). Smoking status is available for over 95% of individuals. The dataset includes 7,274 lung cancer cases, including 613 cases among AANHPI females. Prevalence of never-smoking status varied greatly among AANHPI females with incident lung cancer, from 85.7% among Asian Indian to 14.4% among Native Hawaiian females. Conclusion: We have developed a large, multilevel dataset particularly well-suited to conduct prospective studies of lung cancer risk among AANHPI females who never smoked. Impact: The integrative data approach is an effective way to conduct cancer research assessing multilevel factors on cancer outcomes among small populations.

OBJECTIVES To assess quality, cost, physician productivity, and patient experience for 2 primary care physician (PCP) practice styles: the focused, who typically address only the patient's acute problem, versus the max-packers, who typically address additional conditions also. STUDY DESIGN Retrospective observational study using administrative data, electronic health record (EHR) data, and patient surveys. Data represent 285 PCPs (779 PCP-years) in a large, multispecialty group practice during 2011, 2012, and 2013. METHODS PCPs were ranked each year by their number of additional conditions addressed during acute care visits. The top one-third (max-packers) addressed 25.4% more "other problems" than expected, while focused PCPs (bottom one-third) addressed 20.3% fewer than expected. Outcomes were resource use, clinical quality metrics, patient-reported experience, physician time using the EHR, and physician productivity. All measures were risk-adjusted to account for patient mix. T tests were used to compare measures. RESULTS Relative to a focused pattern of care, max-packing was associated with 3.4% lower overall resource use, consistently better scores for the available clinical quality metrics, and comparable patient experience (except for worse wait time ratings). Patients of focused PCPs used 7.3% more specialist services, in terms of costs, than patients of max-packers ($1218 vs $1136; P

Background: For Asian American, Native Hawaiian and Pacific Islander (AANHPI) females, lung cancer is one of the most common cancers and the leading cause of cancer death. More than half of lung cancers among AANHPI females occur among never-smokers, but incidence rates of lung cancer according to smoking status have not been available. Purpose: With a large, integrated dataset of electronic health record data from two healthcare systems—Sutter Health in Northern California and Kaiser Permanente Hawai'i—linked to state cancer registry data on incident lung cancer diagnoses 2000-2013, we describe incidence of lung cancer according to smoking status among females across detailed race and ethnicity. Methods: We calculated age-adjusted incidence rates for lung cancer according to smoking status and detailed race and ethnicity among females, focusing on AANHPI ethnic groups, and assessed relative incidence across racial and ethnic groups. The study population included N=1,222,694 females (n=244,147 AANHPI), n=3,297 (n=535) of whom were diagnosed with lung cancer. We examined relative incidence across group defined by detailed race and ethnicity. We also provided incidence of lung cancer among AANHPI males who never smoked in a supplement. Results: Among AANHPI female groups, proportions of lung cancers among never-smokers ranged from 25% among Native Hawaiian to 80% among Chinese females. Incidence of lung cancer among never-smoking AANHPI females as an aggregate was 17.1 per 100,000 (95% CI: 14.9, 19.4), but rates varied widely across ethnic groups. Never-smoking Chinese females had the highest rate (22.8; 95% CI: 17.3, 29.1). Except for Japanese females, incidence among every never-smoking AANHPI female ethnic group was higher than that of all never-smoking females combined. Never-smoking AANHPI males also have higher incidence of lung cancer compared to other groups defined by race and ethnicity. Conclusions: The integrative data analysis approach offers great advantages over traditional cancer cohorts, but it does require substantial time and effort to assure data confidentiality, integrity, and transparency to provide robust results. However, with convergence epidemiology—in this case leveraging needed expertise in data science and analysis to answer an epidemiology question—it is also a valuable approach to study disparate cancer outcomes among small populations. Illustrating this, our study is the first to document high rates of lung cancer among never-smoking AANHPI ethnic groups, dispels the myth that AANHPI females are at overall reduced risk of lung cancer, and demonstrates the need to disaggregate this highly diverse population. Results should inform lung cancer prevention strategies among AANHPI populations. Citation Format: MIndy C. DeRouen, Alison J. Canchola, Caroline A. Thompson, Anqi Jin, Sixiang Nie, Carmen Wong, Daphne Lichtensztajn, Laura Allen, Manali I. Patel, Yihe G. Daida, Harold S. Luft, Salma Shariff-Marco, Peggy Reynolds, Heather A. Wakelee, Su-Ying Liang, Beth E. Waitzfelder, Iona Cheng, Scarlett L. Gomez. Applying a data integrative and convergence epidemiology approach to study multilevel risk factors for cancer in distinct AANHPI populations [abstract]. In: Proceedings of the AACR Virtual Conference: 14th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2021 Oct 6-8. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2022;31(1 Suppl):Abstract nr IA-21.

Background: There is tremendous potential to leverage the value gained from integrating electronic health records (EHR) and population-based cancer registry data for research. Registries provide diagnosis details, tumor characteristics, and treatment summaries, while EHRs contain rich clinical detail. A carefully conducted cancer registry linkage may also be used to improve the internal and external validity of inferences made from EHR-based studies. Methods: We linked the EHRs of a large, multispecialty, mixed-payer health care system with the statewide cancer registry and assessed the validity of our linked population. For internal validity, we identify patients that might be “missed” in a linkage, threatening the internal validity of an EHR study population. For generalizability, we compared linked cases with all other cancer patients in the 22-county EHR catchment region. Results: From an EHR population of 4.5 million, we identified 306,554 patients with cancer, 26% of the catchment region patients with cancer; 22.7% of linked patients were diagnosed with cancer after they migrated away from our health care system highlighting an advantage of system-wide linkage. We observed demographic differences between EHR patients and non-EHR patients in the surrounding region and demonstrated use of selection probabilities with model-based standardization to improve generalizability. Conclusions: Our experiences set the foundation to encourage and inform researchers interested in working with EHRs for cancer research as well as provide context for leveraging linkages to assess and improve validity and generalizability. Impact: Researchers conducting linkages may benefit from considering one or more of these approaches to establish and evaluate the validity of their EHR-based populations. See all articles in this CEBP Focus section, “Modernizing Population Science.”

Early palliative care (PC) for individuals with advanced cancer improves patient and family outcomes and experience. However, it is unknown when, why, and how in an outpatient setting individuals with stage IV cancer are referred to PC.At a large multi-specialty group in the USA with outpatient PC implemented beginning in 2011, clinical records were used to identify adults diagnosed with stage IV cancer after January 1, 2012 and deceased by December 31, 2017 and their PC referrals and hospice use. In-depth interviews were also conducted with 25 members of medical oncology, gynecological oncology, and PC teams and thematically analyzed.A total of 705 individuals were diagnosed and died between 2012 and 2017: of these, 332 (47%) were referred to PC, with 48.5% referred early (within 60 days of diagnosis). Among referred patients, 79% received hospice care, versus 55% among patients not referred. Oncologists varied dramatically in their rates of referral to PC. Interviews revealed four referral pathways: early referrals, referrals without active anti-cancer treatment, problem-based referrals, and late referrals (when stopping treatment). Participants described PC's benefits as enhancing pain/symptom management, advance care planning, transitions to hospice, end-of-life experiences, a larger team, and more flexible patient care. Challenges reported included variation in oncologist practices, patient fears and misconceptions, and access to PC teams.We found high rates of use and appreciation of PC. However, interviews revealed that exclusively focusing on rates of referrals may obscure how referrals vary in timing, reason for referral, and usefulness to patients, families, and clinical teams.

OBJECTIVES: To examine the temporal trajectory of insurance coverage for next-generation tumor sequencing (sequencing) by private US payers, describe the characteristics of coverage adopters and nonadopters, and explore adoption trends relative to the Centers for Medicare and Medicaid Services’ National Coverage Determination (CMS NCD) for sequencing. METHODS: We identified payers with positive coverage (adopters) or negative coverage (nonadopters) of sequencing on or before April 1, 2019, and abstracted their characteristics including size, membership in the BlueCross BlueShield Association, and whether they used a third-party policy. Using descriptive statistics, payer characteristics were compared between adopters and nonadopters and between pre-NCD and post-NCD adopters. An adoption timeline was constructed. RESULTS: Sixty-nine payers had a sequencing policy. Positive coverage started November 30, 2015, with 1 payer and increased to 33 (48%) as of April 1, 2019. Adopters were less likely to be BlueCross BlueShield members (P < .05) and more likely to use a third-party policy (P < .001). Fifty-eight percent of adopters were small payers. Among adopters, 52% initiated coverage pre-NCD over a 25-month period and 48% post-NCD over 17 months. CONCLUSIONS: We found an increase, but continued variability, in coverage over 3.5 years. Temporal analyses revealed important trends: the possible contribution of the CMS NCD to a faster pace of coverage adoption, the interdependence in coverage timing among BlueCross BlueShield members, the impact of using a third-party policy on coverage timing, and the importance of small payers in early adoption. Our study is a step toward systematic temporal research of coverage for precision medicine, which will inform policy and affordability assessments.

Context: In existence for nearly 25 years, the Healthcare Systems Research Network (HCSRN) is an established and sustainable network of health care systems that serves as a “real world” laboratory to enable the integration of research findings into practice. The objective of this paper is to demonstrate how the HCSRN serves as an ideal environment for studying dissemination and implementation of evidence-based practices into health care systems through the example of developing a multi-site study on the implementation of evidence-based precision medicine practices.Case description: The “Implementing Universal Lynch Syndrome Screening (IMPULSS)” study (NIH R01CA211723) involves seven HCSRN health care systems and two external health care systems. The IMPULSS study will describe and explain organizational variability around Lynch syndrome (LS) screening to identify which factors in different organizational contexts are important for successful implementation of LS screening programs and will create a toolkit to facilitate organizational decision making around implementation and improvement of precision medicine programs in health care systems.Major Themes: The strengths of the HCSRN that facilitate D&I research include: 1) a culture of collaboration, 2) standardization of data and processes across systems, and 3) researchers embedded in diverse health care systems. We describe how these strengths contributed to developing the IMPULSS study.Conclusion: Given the importance of conducting research in real world settings to improve patient outcomes, the unique strengths of the HCSRN are of vital importance. The IMPULSS study is one case example of how the strengths of the HCSRN make it an excellent environment for research on implementing evidence-based precision medicine practices in health care systems.

Background Although organizational context can affect the implementation of quality initiatives, we know less about the influence of contextual conditions on quality outcomes. We examined organizational features of primary care clinics that achieved greatest performance improvements after implementing Lean redesigns. Methods We used operational data and baseline (ie, pre-Lean implementation) surveys of 1333 physicians and staff in 43 primary care clinics located across a large ambulatory care system. Segmented regression with interrupted time series analysis was used to identify clinics with highest improvements in workflow efficiency, physician productivity, and patient satisfaction following Lean redesign. We conducted independent-samples t tests to identify contextual features of clinics that showed greatest improvements in performance outcomes. Results Clinics with highest increases in efficiency had most prior experience with quality improvement, compared with all other clinics. Efficiency gains were also found in clinics reporting highest levels of burnout and work stress prior to redesign. Highest improvements in physician productivity were associated with a history of change, staff participation, and leadership support for redesigns. Greatest improvements in patient satisfaction occurred in least stressful environments with highest levels of teamwork, staff engagement/efficacy, and leadership support. Conclusions Our findings encourage careful evaluation of clinic characteristics and capacity to effectively implement redesigns. Such evaluations may help leaders select interventions most appropriate for certain clinics, while identifying others that may need extra support with implementing change.

Objectives: To determine the racial disparities in oncology visits of racial minorities before and after COVID-19. Methods: Data were obtained from the electronic health records, a multi-specialty healthcare system serving a racially/ethnically diverse patient population in northern California. The study cohort included patients who had at least one oncology visit from January 2019 to August 2020. We examined the trends in the volume of oncology office visits and adoption of video visits during the ongoing COVID-19 pandemic period. Chi-square test and multivariate logistic regression were performed to examine variability in use of video visits by specific patient characteristics (sex, age, race/ethnicity and language barrier). Results: Of 63,903 cancer patients (median age: 66; 68% female), Whites, Blacks, Hispanics, Asians and others composed of 64.8%, 3.5%, 9.2%, 11.7% and 10.8% of our study cohort. Over the 20 month study period, the drop in in-person visits began in March and peaked in April 2020. Compared to the year 2019, the office visits decreased by -16.6%, -55.9%, and -50.9% in March, April, and May of 2020. Although there was a trend towards increased office visits in June (-21.9% compared to 2019), this again decreased to -35% in July 2020. The proportion of visits conducted by video began at 16.6% in the first week after California's shelter-in-place order in March, peaked at a high rate of 43.4% in April, and remained at a rate of 33.8% in August. We focused on variability by specific patient subgroups when telemedicine was offered and used prevalently during early pandemic in April. Based on age, the younger cohorts, 18-50 and 51-64 year olds, were more likely to utilize video visit at 50.6%, and 50.6% compared to only 38.0% and 36.7% of the older groups (65-75 and 76+ years old, p Conclusions: Overall office visits have decreased significantly during the COVID-19 pandemic. Older patients, Black patients, Hispanic patients, and patients who required interpreting services were less likely to be treated through video visits. Future studies are needed to better understand the barriers to telemedicine care.

e18806 Background: There has been a significant decline in office visits and cancer screening interventions such as mammograms and colonoscopies during the COVID-19 pandemic. The aim of this study is to analyze treatment patterns and to identify if there was also a delay in time to treatment for breast and colorectal cancers diagnosed during the pandemic. Methods: We utilized a dataset linking the institutional tumor registry and electronic health records from a large ambulatory group practice in Northern California. We analyzed data from 1,047 patients with newly diagnosed breast and colorectal cancers between 1/2019 and 8/2020 who received care at Sutter Health-Palo Alto Medical Foundation until 12/2020. We performed a T-test to examine whether patterns of treatment status (surgery vs chemotherapy vs neither) and time-to-treatment are different in pre-COVID vs pandemic eras. Results: The proportion of patients who did not receive surgery or chemotherapy during the pandemic was significantly higher, compared to the pre-COVID era (34.5% vs. 13.0%, p < 0.01). Among the breast and colorectal cancer patients who received care, the time to initial treatment did not significantly vary in the pre-COVID (median 34 days, mean 36.8 days) era as compared to during the pandemic (median 30 days, mean 32.2 days) (p = 0.15). There was no difference when accounting for surgery (p = 0.15) vs chemotherapy (p = 0.52) as the initial treatment modality. A statistically significant difference was seen amongst the 888 breast cancer cases identified during the study period, but the mean time to treatment during the pandemic (31 days) was actually shorter than the mean time to treatment identified prior to the pandemic (38 days). This difference in breast cancer time to treatment was mainly driven by a statistically shorter time to surgery (p = 0.04) in the pandemic era with no statistically significant difference in time to chemotherapy following a breast cancer diagnosis in the pandemic era as compared to the pre-COVID era (p = 0.99). Conclusions: There was a significant difference in the number of patients who did not receive surgery or chemotherapy during the pandemic for newly diagnosed breast and colorectal cancers. However, amongst those patients who did receive treatment, there were no significant delays observed in time to initial treatment, regardless of treatment modality.[Table: see text]

10594 Background: The accessibility of cancer hereditary syndrome testing has increased, and the cost has declined significantly in the past few years. We conducted a national, quantitative survey of genetic counselors (GCs) to assess their perspectives on what influences hereditary cancer genetic testing decisions and practices, with a focus on cost. This survey was funded by NIH, conducted by UCSF TRANSPERS, and supported by the National Society of Genetic Counselors (NSGC). Methods: The survey was developed through literature review, expert interviews, and a pilot. Sent to the NSGC Cancer Special Interest Group via email. Chi-square tests were used to examine variability. Results: The survey response rate was 56% (202/363). Multiple hereditary cancer syndrome tests are discussed often/always by 86% of genetic counselors (GCs). The existence of an institutional protocol on multiple hereditary cancer syndrome testing was reported by 35.4% of GCs. When asked about GC counseling encounters, GCs report insurance rarely/never pays for: 25.2% pre-test in-person, 39.7% for pre-test tele-genetics, 35.4% post-test in-person, and 52.9% post-test tele-genetics. GCs rated clinical factors higher than cost as influencing decision for multiple hereditary syndrome cancer testing (table); the total cost of the test was least important. These patterns were similar across the GCs institution types and years in practice. Conclusions: We found consistent use of multiple hereditary cancer syndrome tests, with less focus on cost, out-of-pocket, and insurance coverage and more of a focus on clinical indicators. GCs reported challenges with reimbursement for GC counseling encounters. The shift toward more genetic counseling encounters via tele-genetics necessitates evaluation of insurance reimbursement.[Table: see text]

Background: There is tremendous potential to leverage the value from electronic health records (EHRs) and population-based cancer registry data by integrating them to study the cancer continuum from screening to diagnosis and treatment. Registries provide detailed diagnosis and tumor characteristics and initial treatment summaries (even across health care systems), while EHRs contain rich clinical detail such as medical histories and preventive screenings. Moreover, to the extent that EHR systems may be comparable across health care systems, pooling EHRs from multiple health care systems can enhance the generalizability of findings. Furthermore, there is the potential to integrate neighborhood or environmental data based on geocoding patient addresses for research focusing on multilevel exposures. With patient populations frequently in the millions, the opportunities for highly powered scientific discovery are nearly unparalleled. However, the logistical complexity, cost, and possibility for systematic error to hamper findings may be considerable. Recently, we linked the EHRs of a large, multispecialty health care delivery system with the California cancer registry (CCR) and established two retrospective cohort studies. We will describe the process undertaken, some challenges and lessons learned, and the resulting cohort populations. Methods: Using a probabilistic linkage process, we combined Sutter Health EHR data with the CCR to identify incident cancer cases occurring among the EHR population. We then established two retrospective cohorts each with 13 years of follow-up time and distinct scientific objectives. The mammogram cohort is designed to study patterns of screening utilization and breast cancer-related outcomes. The lung cancer cohort will elucidate risk factors for lung cancer in never-smokers, an uncommon diagnosis that has not been successfully studied in other data sources due to lack of smoking status and/or small sample sizes. Results: From an adult EHR population of 4.5 million, we identified 306,554 unique cancers diagnosed between 2000 and 2013. Linkage efforts, including multiple institutional approvals, took 18 months to complete. We compared the identified cases with the rest of the CCR patients in the Sutter Health catchment region to evaluate external validity. Inclusion/exclusion criteria resulted in a mammogram cohort of 516,419 screened women, 11,222 of whom were diagnosed with breast cancer, and a lung cancer cohort with 1.3 million male and female never-smokers, 1,143 of whom were diagnosed with lung cancer. For the latter, we also undertook patient address geocoding and linkage with neighborhood and environmental data. Multiple imputation and sensitivity analysis will be used to explore the impact of missing EHR data, a common issue in such studies. Conclusions: Our experiences set the foundation to encourage and inform researchers interested in working with EHRs for cancer research as well as provide context for improvement and scalability. This abstract is also being presented as Poster A27. Citation Format: Caroline A. Thompson, Mindy DeRouen, Su-Ying Liang, Anqi Jin, Harold S. Luft, Daphne Lichtensztajn, Salma Shariff-Marco, Iona Cheng, Scarlett L. Gomez. Linking electronic health records with cancer registry data for epidemiology and health services research: Challenges and opportunities [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr PR08.

Background: For Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females, lung cancer is one of the most common cancers and the leading cause of cancer death. More than half of AANHPI female lung cancers occur in never-smokers, and contributing risk factors among never-smokers remain largely unknown. Until now, there was no single sufficiently large data source to document lung cancer incidence rates by smoking status and sex among specific AANHPI ethnic groups, which is central to understanding and reducing the burden of this disease in this population. We assembled a large-scale cohort to quantify the burden of lung cancer by smoking status among single- and multiethnic AANHPI groups, with an emphasis on identifying the underlying factors driving lung cancer risk among never-smoking AANHPI females. Methods: Assembly of the cohort involved (1) harmonizing and pooling electronic health record (EHR) data on known and putative lung cancer risk factors from two large health systems (i.e., Northern California Sutter Health system and Kaiser Permanente Hawaii (KPH)), (2) linking EHR data from Sutter and KPH with tumor and diagnosis data from the California Cancer Registry and Hawaii Tumor Registry, respectively, (3) geocoding and linking the Sutter portion of the cohort to regional air pollutant data and data on specific neighborhood contextual factors from the California Neighborhoods Data System, and (4) developing neighborhood contextual variables to enhance the geocoded data for KPH cohort members. Incidence rates stratified by sex, detailed race/ethnicity, smoking status, and lung cancer histology have been calculated; as well as incidence rate ratios by race/ethnicity. Results: The cohort comprises over 2.3 million individuals (250,000 AANHPI females) followed up to 15 years for incident lung cancer. It includes over 6,000 incident lung cancer cases, of which 558 are AANHPI females. Among AANHPI female groups, proportions of lung cancers among never-smokers range from 31% among Native Hawaiian to 88% among Chinese females. Incidence rates of never-smoking lung cancer are highest among Native Hawaiian females (AAIR, 28.7) and Asian females reporting multiple races/ethnicities (AAIR, 27.8). Conclusions: We have assembled a large, integrated dataset well suited to study multilevel risk of lung cancer that will serve as a critical evidence base to inform screening, research, and public health priorities, especially among AANHPI females. Ongoing work will include longitudinal analyses of lung cancer risk among never-smoking AANHPI females, including absolute risk modeling, examining six exposure domains representing known and putative lung cancer risk factors. This abstract is also being presented as Poster A104. Citation Format: Mindy C. DeRouen, Caroline Thompson, Alison J. Canchola, Anqi Jin, Siaxing Nie, Jennifer Jain, Salma Shariff-Marco, Daphne Y. Lichetensztajn, Yihe Daida, Carmen Wong, Yuqing Li, Manali I. Patel, Heather A. Wakelee, Su-Ying Liang, Beth E. Waitzfelder, Iona Cheng, Scarlett L. Gomez. Lung cancer incidence and risk factors in never-smoking Asian American, Native Hawaiian, and Pacific Islander women: A multilevel dataset of electronic health record, cancer registry, and environmental data [abstract]. In: Proceedings of the Twelfth AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2019 Sep 20-23; San Francisco, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl_2):Abstract nr PR07.

Background: For Asian American, Native Hawaiian, and Pacific Islander (AANHPI) females, lung cancer is one of the most common cancers and the leading cause of cancer death. More than half of AANHPI female lung cancers occur in never-smokers, and contributing risk factors among never-smokers remain largely unknown. Until now, there was no single sufficiently-large data source to document lung cancer incidence rates by smoking status and sex among specific AANHPI ethnic groups, which is central to understanding and reducing the burden of this disease in this population. We assembled a large-scale cohort to quantify the burden of lung cancer by smoking status among single- and multiethnic AANHPI groups, with an emphasis on identifying the underlying factors driving lung cancer risk among never-smoking AANHPI females. Methods: Assembly of the cohort involved (1) harmonizing and pooling electronic health record (EHR) data on known and putative lung cancer risk factors from two large health systems (i.e., Northern California Sutter Health system and Kaiser Permanente Hawaii [KPH]); (2) linking EHR data from Sutter and KPH with tumor and diagnosis data from the California Cancer Registry and Hawaii Tumor Registry, respectively; (3) geocoding and linking the Sutter portion of the cohort to regional air pollutant data and data on specific neighborhood contextual factors from the California Neighborhoods Data System; and (4) developing neighborhood contextual variables to enhance the geocoded data for KPH cohort members. Incidence rates stratified by sex, detailed race/ethnicity, and smoking status were calculated. Results: The cohort comprises 1.8 million individuals, including 750,000 females of whom 190,000 are AANHPI females, with up to 15 years' follow-up for incident lung cancer. It includes over 24,000 incident lung cancer cases, of which 10,595 are females and over 1,500 are single- and multiethnic AANHPI females. The cohort has high representation of Asian Indian, Chinese, Japanese, Filipino, Korean, and Pacific Islander never-smoking females in addition to multiple multiethnic AANHPI ethnic groups. Ongoing analyses, including overall and histologic cell-type specific incidence rates of lung cancer by sex, race/ethnicity, and smoking status will be presented. Conclusions: We have assembled a large, integrated dataset well suited to study multilevel risk of lung cancer that will serve as a critical evidence base to inform screening, research, and public health priorities, especially among AANHPI females. Future work will include longitudinal analyses of lung cancer risk among never-smoking AANHPI females, including absolute risk modeling, examining six exposure domains representing putative lung cancer risk factors: second-hand smoke, previous lung diseases, infections, reproductive history and hormone exposure, body size, and neighborhood environmental factors, including measures of particulate matter, traffic density, neighborhood socioeconomic status, and ethnic enclave. Citation Format: Mindy C. DeRouen, Salma Shariff-Marco, Daphne Lichtensztajn, Anqi Jin, Yihe G. Daida, Alison J. Canchola, Yuqing Li, Jennifer Jain, Laura Allen, Sixiang Nie, Carmen Wong, Robert Haile, Manali Patel, Peggy Reynolds, Heather Wakelee, Hal Luft, Caroline Thompson, Su-Ying Liang, Beth E. Waitzfelder, Iona Cheng, Scarlett L. Gomez. Lung cancer incidence and risk factors in never-smoking Asian American, Native Hawaiian, and Pacific Islander women: The development of a multilevel integrated dataset of EHR, cancer registry, and environmental data [abstract]. In: Proceedings of the Eleventh AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2018 Nov 2-5; New Orleans, LA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(6 Suppl):Abstract nr IA37.

Background Systematic screening of all colorectal tumors for Lynch Syndrome (LS) has been recommended since 2009. Currently, implementation of LS screening in healthcare systems remains variable, likely because LS screening involves the complex coordination of multiple departments and individuals across the healthcare system. Our specific aims are to (1) describe variation in LS screening implementation across multiple healthcare systems; (2) identify conditions associated with both practice variation and optimal implementation; (3) determine the relative effectiveness, efficiency, and costs of different LS screening protocols by healthcare system; and (4) develop and test in a real-world setting an organizational toolkit for LS screening program implementation and improvement. This toolkit will promote effective implementation of LS screening in various complex health systems. Methods This study includes eight healthcare systems with 22 clinical sites at varied stages of implementing LS screening programs. Guided by the Consolidated Framework for Implementation Research (CFIR), we will conduct in-depth semi-structured interviews with patients and organizational stakeholders and perform economic evaluation of site-specific implementation costs. These processes will result in a comprehensive cross-case analysis of different organizational contexts. We will utilize qualitative data analysis and configurational comparative methodology to identify facilitators and barriers at the organizational level that are minimally sufficient and necessary for optimal LS screening implementation. Discussion The overarching goal of this project is to combine our data with theories and tools from implementation science to create an organizational toolkit to facilitate implementation of LS screening in various real-world settings. Our organizational toolkit will account for issues of complex coordination of care involving multiple stakeholders to enhance implementation, sustainability, and ongoing improvement of evidence-based LS screening programs. Successful implementation of such programs will ultimately reduce suffering of patients and their family members from preventable cancers, decrease waste in healthcare system costs, and inform strategies to facilitate the promise of precision medicine. Trial registration N/A Electronic supplementary material The online version of this article (10.1186/s12913-018-3636-2) contains supplementary material, which is available to authorized users.

Purpose:There is uncertainty about when personalized medicine tests provide economic value. We assessed evidence on the economic value of personalized medicine tests and gaps in the evidence base.Methods:We created a unique evidence base by linking data on published cost-utility analyses from the Tufts Cost-Effectiveness Analysis Registry with data measuring test characteristics and reflecting where value analyses may be most needed: (i) tests currently available or in advanced development, (ii) tests for drugs with Food and Drug Administration labels with genetic information, (iii) tests with demonstrated or likely clinical utility, (iv) tests for conditions with high mortality, and (v) tests for conditions with high expenditures.Results:We identified 59 cost-utility analyses studies that examined personalized medicine tests (1998-2011). A majority (72%) of the cost/quality-adjusted life year ratios indicate that testing provides better health although at higher cost, with almost half of the ratios falling below $50,000 per quality-adjusted life year gained. One-fifth of the results indicate that tests may save money.Conclusion:Many personalized medicine tests have been found to be relatively cost-effective, although fewer have been found to be cost saving, and many available or emerging medicine tests have not been evaluated. More evidence on value will be needed to inform decision making and assessment of genomic priorities. © American College of Medical Genetics and Genomics.