Skip to main content
Translational Behavioral Medicine logoLink to Translational Behavioral Medicine
. 2023 Mar 20;13(8):539–550. doi: 10.1093/tbm/ibac122

Implementation planning for equitable tobacco treatment services: a mixed methods assessment of contextual facilitators and barriers in a large comprehensive cancer center

Jennifer Tsui 1,2,, Kylie Sloan 3, Rajiv Sheth 4, Esthelle Ewusi Boisvert 5, Jorge Nieva 6,7, Anthony W Kim 8,9, Raina D Pang 10,11,12, Steve Sussman 13,14, Matthew Kirkpatrick 15,16,17
PMCID: PMC10848232  PMID: 36940412

Abstract

Tobacco use among cancer patients is associated with an increased mortality and poorer outcomes, yet two-thirds of patients continue using following diagnosis, with disproportionately higher use among racial/ethnic minority and low socioeconomic status patients. Tobacco treatment services that are effectively tailored and adapted to population characteristics and multilevel context specific to settings serving diverse patients are needed to improve tobacco cessation among cancer patients. We examined tobacco use screening and implementation needs for tobacco treatment services to inform equitable and accessible delivery within a large comprehensive cancer center in the greater Los Angeles region.

We conducted a multi-modal, mixed methods assessment using electronic medical records (EMR), and clinic stakeholder surveys and interviews (guided by the Consolidated Framework for Implementation Research).

Approximately 45% of patients (n = 11,827 of 26,030 total) had missing tobacco use history in their EMR. Several demographic characteristics (gender, age, race/ethnicity, insurance) were associated with greater missing data prevalence. In surveys (n = 32), clinic stakeholders endorsed tobacco screening and cessation services, but indicated necessary improvements for screening/referral procedures. During interviews (n = 13), providers/staff reported tobacco screening was important, but level of priority differed as well as how often and who should screen. Several barriers were noted, including patients’ language/cultural barriers, limited time during visits, lack of smoking cessation training, and insurance coverage.

While stakeholders indicated high interest in tobacco use assessment and cessation services, EMR and interview data revealed opportunities to improve tobacco use screening across patient groups. Implementing sustainable system-level tobacco cessation programs at institutions requires leadership support, staff training, on routine screening, and intervention and referral strategies that meet patients’ linguistic/cultural needs.

Keywords: Tobacco cessation, Health equity, Mixed methods, Implementation planning


Implementing sustainable tobacco cessation programs within cancer care settings will require leadership support, staff training, and strategies that meet linguistic and cultural needs of diverse patient populations.


Implications.

Practice: Equitable implementation planning can be informed by multi-modal assessments that indicate: (i) where targeted efforts are needed (screening, clinic team training) and (ii) engagement and support by inner (leadership) and outer (community partners) context stakeholders.

Policy: Employing a health equity lens at the implementation planning stage, within systems and communities, is critical to addressing the systemic barriers to tobacco use screening and referral.

Research: Research that informs multilevel approaches to optimizing implementation to achieve health equity is required at the system, provider staff, and patient levels.

BACKGROUND

Persistent cigarette smoking and other tobacco use by cancer patients is causally linked to an increased all-cause and cancer-related mortality, risk for secondary primary cancers, cancer treatment toxicity, and attenuated response to cancer treatment [1–3]. Quitting tobacco use after a cancer diagnosis can greatly reduce these negative outcomes, resulting in reduced risk of new cancers and longer post-treatment survival [4]. However, despite the known risks for smoking and the benefits of quitting, a relatively large proportion of cancer patients who smoked prior to diagnosis continue to smoke after diagnosis [5]. Thus, cancer patients need tobacco treatment; one important opportunity for delivering treatment is in the context of oncology visits, which can be “teachable moments” to encourage lifestyle changes.

Based on a 2009 survey of 58 NCI-Designated Clinical and Comprehensive Cancer Centers, tobacco use treatment was not considered a part of standard cancer care in the majority of cancer centers [6]. Efforts to implement systematic tobacco use screening and treatment significantly increased in 2017, when NCI launched the Cancer Center Cessation Initiative (C3I), a nationwide Cancer Moonshot effort to increase the reach and effectiveness of smoking cessation treatment at cancer centers using the principles and methods of implementation science. Key features of C3I include a population-level approach (i.e., every patient is assessed for tobacco use and offered treatment), a systems-based approach (i.e., using electronic health record technology to facilitate program integration and enhance long-term sustainability), and an evidence-based approach (i.e., providing a range of known effective treatment approaches including referrals to quit lines, pharmacotherapy, behavioral treatment, etc.). Prior cancer centers within C3I reported increasing patient tobacco use screening to approximately 96% and engaging approximately 25% of tobacco-using patients in an evidence-based treatment [7], which was substantially higher than the <15% typically observed in patient settings [8, 9]. Other emerging studies also indicate effective strategies require a multilevel approach, including training providers [10–14]. While effective interventions for tobacco cessation among oncology patients are available [15, 16] and health system-based tobacco cessation referral programs have been established throughout NCI cancer centers in recent years [10, 17–23], few studies to date have examined the implementation needs of routine tobacco cessation services settings with diverse patient race/ethnicity, linguistic, and social needs, where tailoring and adaptation of evidence-based programs are likely required.

Racial/ethnic minority status, low socioeconomic status (SES), and LGBTQ+ status individuals are at high-risk for tobacco use and suffer disproportionately from tobacco-related illness and death [24–26]. While rates of tobacco-related outcomes fare better in California compared to the USA as a whole, gains in tobacco-related outcomes have not been equitably distributed across population groups [27], due in part to structural and systemic inequities. Tobacco is targeted in more low SES communities, and there is greater point-of-sale marketing in neighborhoods with more Black residents [28]. Racial/ethnic minority adult tobacco users (especially Asian/Pacific Islanders and African Americans) are more likely to initiate use in young adulthood [29–34], and use remains disproportionately high among those of low SES compared to high SES [35–37]. Regarding cessation efforts, women have more difficulty maintaining long-term abstinence than men [38], and previous research indicates that a significantly smaller proportion of African Americans had quit for at least 1 year (30.4%) compared with other groups (39.8% for Asian Americans; 36.6% for Hispanics/Latinos; 42.9% for Non-Hispanic Whites) [39]. Successful implementation planning of tobacco cessation services within oncology settings serving diverse populations will require effective tailoring and adaptation to the needs of the target patient population and multilevel context [40–43]. Emerging evidence in non-oncology clinical settings suggests systematic implementation of tobacco cessation interventions is often suboptimal and exposed to a variety of multilevel barriers [44, 45]. Thus, there is a vital need to comprehensively assess the local community health system context to effectively employ a health equity lens in implementation planning for tobacco cessation services [46, 47].

Since 2017, 52 centers have participated in the NCI Cancer Center Cessation Initiative (C3I) Moonshot initiative [48]. The [BLINDED] Cancer Center joined the initiative in 2020 to build capacity and infrastructure for tobacco cessation treatment services for patients and survivors in the greater Los Angeles region. This manuscript describes a mixed methods implementation planning study that examines the feasibility, acceptability, and infrastructure requirements needed to implement a tobacco cessation program within a large comprehensive cancer center serving one of the most diverse patient populations in the country. The goal of the study is to focus on identifying the tailoring and adaptation of tobacco requirements for tobacco use screening and cessation services within this context.

METHODS

Study aim

We conducted a multi-model, mixed methods assessment [49] (concurrent QUANT + QUAL design) of contextual health system-level facilitators and barriers to systematic tobacco use screening and implementation of tobacco cessation services within the [BLINDED] Cancer Center, which serves a diverse cancer patient and survivor population in the greater Los Angeles region. The study included three components: (i) electronic medical records (EMR) assessment of routine tobacco use screening by patient sociodemographic factors; (ii) quantitative survey of oncology providers, clinic staff, and administrators on motivation and perceptions of tobacco service needs; and (iii) qualitative interviews with clinic stakeholders (providers and staff) at two oncology outpatient sites. All procedures were approved by the authorship team’s Institutional Review Board (IRB UP-20-01168).

Tobacco screening data in the EMR

We examined EMR data from all patients who had a least one visit to all [BLINDED] Cancer Center clinics between January and June 2019 (N = 26,030). All data, obtained from the Cerner-based EMR system, were de-identified and provided by the Clinical Research Informatics unit at the [BLINDED] Institute. Tobacco use history is available through the Social History section of the medical records, which includes: (i) type of tobacco product used (e.g., cigarettes, oral, hookah or pipe, vaping or e-cigarette, other type); (ii) current tobacco user status (e.g., never smoker, 4 or less a day, 5–9 a day, 10 or more a day, former smoker); (iii) age of tobacco use onset; (iv) age of successful cessation; and (v) readiness to quit.

Each patient’s smoking status was initially coded as: never smoker, former smoker, current smoker (comprised of anyone who reported any combustible cigarette use), or missing. For the purposes of this study, where the primary interest is whether smoking status was recorded in the EMR, we re-coded smoking status information as: status present (coded as “0”) versus status missing (coded as “1”). Additionally, each patient record provided data on several sociodemographic factors: race/ethnicity (coded as Asian, Black, Hispanic/Latino, White, Other), sex/gender (coded as Female, Male), age group (coded as 65 and older, younger than 65), and primary insurance as measure of socioeconomic status (coded as Private Insurance, Medicare, Medicaid/None).

Clinic survey assessing motivation and perceptions of tobacco service needs

We administered a brief self-administered online survey to assess current procedures and baseline motivation of health system stakeholders (physicians, nursing staff, administrators, other clinic staff members) to screen for tobacco use, as well as perceptions of providers’ role in providing treatment and the need for tobacco treatment as part of cancer care. A total of 45 [BLINDED] oncology providers and clinic staff were identified through staff lists, from a range of clinics (Women’s Health, [BLINDED] Ambulatory Clinic, Radiation Oncology, Other) and roles (Physician, NP/PA, RN, MA/LVN, Patient Navigator, Scheduler, Other) and contacted via email to participate in the 14-item survey. Of the 45 physicians and clinic staff recruited for the quantitative survey, 32 completed the self-administered survey on existing tobacco use screening processes and perspectives on system-level needs for tobacco cessation services (71%). Three participants were drawn at random to receive a $25 Amazon gift card.

The surveys were provided via REDCap link by email in July 2021 to all identified providers and staff. Research team members sent weekly reminders until the survey data collection window closed in October 2021. The survey included items on current tobacco use assessment practices at clinical outpatient units. Current assessment practices were measured by asking about systems put in place, frequency of, and process for assessing patients’ tobacco use, in addition to who is responsible for documenting tobacco use in the EMR and awareness of tobacco cessation referral options. The survey also included ratings (strongly disagree to strongly agree) on the importance of routinely assessing tobacco use and providing tobacco cessation options as a part of cancer care. Participants rated whether their unit is equipped for implementation of tobacco use screening and referral right now. Participants also rated the extent that clinic leadership is supportive of systematic tobacco use assessment and EMR documentation and if leadership expects the participant to advise patients on quitting.

Quantitative data analysis of EMR and survey data

. For analysis of the EMR data, we conducted logistic regression models including each demographic characteristic (gender, age, primary insurance, race) as main effect predictors, as well as all possible two-way interactions between each demographic characteristic. The primary outcome was missingness of tobacco use (smoking status) in the EMR record (status present versus status missing). Results of the logistic regression analysis are presented as odds ratios. Predicted probabilities of smoking status missingness for all main effect and interaction groups were calculated and presented for ease of interpretation. Significance was set at the p < 0.05 level. All analyses were conducted using SPSS 28.0. For the survey data, descriptive results are presented in frequencies and means.

Qualitative interviews with clinic providers and staff

We conducted one-on-one in-depth interviews with providers and staff in two oncology outpatient clinics between June 2021 and September 2021. The research team identified two physician champions, one from medical oncology and one from pulmonary/thoracic surgery, who connected the research team to clinic managers in their outpatient clinics. Managers then provided contact information of potential providers and staff for participation. One graduate-level research team member emailed clinic staff members to provide study information and ask for participation via in-person interviews, with the goal of reaching 6–8 participants per site.

Interview guides consisted of semi-structured, open-ended questions based on domains in the Consolidated Framework for Implementation Research (CFIR), including inner and outer setting factors that impact implementation of tobacco cessation services, planned referral and cessation services, and aspects of the participants’ clinic roles and perspectives on tobacco cessation needs for their patient population. In-person one-on-one interviews, with clinic staff members, within the same clinic took place on consecutive days for approximately 30 min each. Providers were interviewed virtually, via Zoom, by the same graduate-level research team member. Following all interviews, participants were asked the following demographic questions: race, ethnicity, gender, age, and length at organization. All participants received a $25 gift card upon interview completion. Audio files of all interviews were sent to an external service for transcription and then de-identified by the research team.

Qualitative data analysis.

The qualitative data analysis was guided deductively by tobacco treatment topics and CFIR framework domains covered in the interview guide as well as inductively through emergent themes. Core members of the research team, comprised of those with expertise in tobacco control, health services research, social work, and clinical psychology, met bi-weekly to discuss emergent themes and develop appropriate codes through an immersion/crystallization process. Two independent coders from the core team thoroughly read and coded all interview transcripts using the codebook. We used Miles and Huberman’s process of creating matrices to display the data for comparative analyses [50] where one team member extracted all data relevant to each code. The team continued to meet to discuss discrepant coding and modify the codebook accordingly throughout analysis period. Both coders met at the conclusion of coding to discuss major themes and finalize analysis of interviews. Measurement of coding agreement was calculated on a random subset of two interview transcripts, with average agreement of approximately 70%.

Integration of quantitative and qualitative data.

Following completion of the quantitative and qualitative data analysis, the team used a mixed methods approach to integrate the qualitative data (from interviews) with the quantitative data (survey and EMR data) to systematically compare the findings on facilitators and barriers to tobacco use screening and treatment referral across levels of context (patient factors from EMR, motivation by health system stakeholders from surveys, current clinic processes for screening from qualitative interviews) [49, 51] and then used to guide recommendations for future interventions. Qualitative and quantitative findings were merged and compared through ongoing research team meetings [52], presented in a joint display table format [53], and reported to health system/cancer center leadership and the broader research team in Spring 2022 for further interpretation and discussion of intervention tailoring and adaptation needs.

RESULTS

Tobacco use history missingness in the EMR social history form

Approximately, 45% of patients (n = 11,827) with at least one cancer center visit between January and June 2019 had missing tobacco use information (i.e., there was no tobacco use history documented in the Social History form). Logistic regression results revealed tobacco use missingness was associated with several demographic characteristics, including main effects of age and insurance status, as well as several interactions between demographic characteristics (Table 1). For example, there were overall differences in predicted probabilities of missing tobacco use data as function of primary insurance (Table 2). Patients with Medicaid/no insurance were more likely to have missing data relative to those with private insurance (61.6% vs. 44.0%). The significant insurance × race interaction indicated that the gap between Medicaid/No insurance and Private insurance differed by race. While the gap between Medicaid/No insurance and Private Insurance was 9.1% for White patients, the gap was 24.2% for Asian patients, and 28.1% for Black patients. Similarly, there was a significant insurance × gender interaction, indicating that Female patients had a larger insurance-related data missingness gap (19.5%) compared to Male patients (13.5%). There was also a significant race × gender interaction, indicating that the data missingness gap between men and women differed by race. That is, while the gap between White men and women was relatively small (0.2%), there was a substantial gender gap for Asian patients (i.e., 12.3% greater predicted probability for women) and for Black patients (i.e., 6.8% greater predicted probability for men).

Table 1.

Logistic regression results (presented as odds ratios) of smoking history data missingness as a function of gender, age, primary insurance, and race/ethnicity

Odds of missing data
N OR (95% CI) p
Gender
 Male (reference) 12,024 1.00
 Female 14,002 0.92 (0.78, 1.07) 0.28
Age
 65 and older (reference) 12,082 1.00
 Younger than 65 13,948 1.48 (1.28, 1.71) <0.001
 Primary insurance
 Private insurance (reference) 12,034 1.00
 Medicare 11,400 0.84 (0.73, 0.97) 0.02
 Medicaid/none 1,631 1.55 (1.08, 2.24) 0.02
Race/ethnicity
 White (reference) 10,795 1.00
 Asian 3,639 1.06 (0.82, 1.37) 0.67
 Black 1,068 0.86 (0.60, 1.25) 0.43
 Hispanic/Latino 5,147 0.80 (0.64, 1.00) 0.50
 Other 5,381 2.08 (1.66, 2.60) <0.001
Gender × age
 Female, Younger than 65 0.83 (0.71, 0.96) 0.02
Gender × primary insurance
 Female, Medicare 1.22 (1.04, 1.42) 0.01
 Female, Medicaid/none 1.41 (1.14, 1.75) <0.01
Gender × race/ethnicity
 Female, Asian 1.66 (1.42, 1.95) <0.001
 Female, Black 0.74 (0.57, 0.98) 0.03
 Female, Hispanic/Latino 0.96 (0.83, 1.11) 0.53
 Female, Other 1.18 (1.02, 1.35) 0.02
Age × primary insurance
 Younger than 65, Medicare 0.55 (0.47, 0.65) <0.001
 Younger than 65, Medicaid/None 0.63 (0.45, 0.87) 0.01
Age × Race/Ethnicity
 Younger than 65, Asian 0.79 (0.62, 1.02) 0.07
 Younger than 65, Black 1.09 (0.77, 1.55) 0.63
 Younger than 65, Hispanic/Latino 1.28 (1.04, 1.58) 0.02
 Younger than 65, Other 0.88 (0.71, 1.10) 0.27
Primary insurance × race/ethnicity
 Medicare, Asian 1.22 (0.95, 1.57) 0.13
 Medicare, Black 1.17 (0.82, 1.66) 0.40
 Medicare, Hispanic/Latino 1.01 (0.81, 1.25) 0.94
 Medicare, Other 0.96 (0.77, 1.20) 0.71
 Medicaid/None, Asian 1.92 (1.31, 2.83) <0.001
 Medicaid/None, Black 2.20 (1.30, 3.73) <0.01
 Medicaid/None, Hispanic/Latino 1.32 (0.99, 1.76) 0.06
 Medicaid/None, Other 1.09 (0.80, 1.49) 0.58

Table 2.

Predicted Probabilities of data missingness for tobacco use in EMR

Main effect Two-way interactions
Gender Age Primary insurance
Male Female 65 and older Younger than 65 Private Medicare Medicaid/none
Gender
 Male 46.7
 Female 48.3
Age
 65 and older 48.2 46.3 50.1
 Younger than 65 46.8 47.2 46.5
Primary insurance
 Private insurance 44.0 45.4 42.7 40.6 47.5
 Medicare 36.9 35.8 38.0 40.4 33.4
 Medicaid/no insurance 61.6 58.9 64.2 63.5 59.6
Race/ethnicity
 White 41.3 41.4 41.2 41.8 40.7 41.1 32.5 50.2
 Asian 52.6 46.5 58.8 56.1 49.2 45.9 41.9 70.1
 Black 43.0 46.4 39.6 42.5 43.5 35.2 30.5 63.3
 Hispanic/Latino 40.8 41.4 40.1 38.5 43.1 38.3 30.0 54.1
 Other 59.9 58.0 61.8 62.1 57.7 59.7 49.6 70.3

Note: Bolded cells indicate significant associations in the logistic regression

Clinic survey assessing motivation and perceptions of tobacco service needs

Survey respondents (n = 32) were mostly providers (physicians, NPs) (n = 9) and clinic staff (RN/MA/LVN) (n = 13) and majority worked in Women’s Health, Dermatology, and Ambulatory clinics. Overall, results indicate that health system stakeholders agreed that it is important to routinely assess patient’s tobacco use (84% agree or strongly agree) and provide tobacco cessation services as part of cancer care (80% agree or strongly agree). However, more than one-third (38%) reported not having or not knowing whether a current system is in place to assess patient’s tobacco use within the clinic settings and more than half (52%) strongly disagreed or disagreed that their unit was equipped to implement tobacco screening and referral services currently. Importantly, more than one-third of participants did not agree that there was support for or expectations by clinic leadership for routine tobacco use screening and documentation.

Qualitative interviews with providers and clinic staff

Thirteen participants completed in-depth interviews (Table 3) from two purposively sampled oncology outpatient clinics, including 4 providers (physicians, PAs) and 9 clinic staff (RN/LVN/LPN, clinic manager, patient care assistant, nurse specialist). Three-fourths of the interview participants were female and half of the respondents (50%) had been working at [BLINDED] for more than 5 years. About one-third identified as Hispanic or Latino/a and half (50%) identified as White. Themes from interviews are presented and organized by CFIR domains: inner setting, outer setting, intervention characteristics, and characteristics of individuals, and compared and integrated with quantitative findings described above in Table 4.

Table 3.

Characteristics of participants from qualitative interviews (N = 13)a

Demographic characteristics N %
Total 13 100
Clinic role
 Physician 2 15.4
 PA 2 15.4
 RN 3 23.1
 LVN/LPN 3 23.1
 Other/Unknown 3 23.1
Self-reported race
 Asian American/Pacific Islander 3 23.1
 Middle Eastern 1 7.7
 White 6 46.2
 Unknown 3 23.1
Ethnicity
 Hispanic or Latino/a 4 30.8
Non-Hispanic or Latino/a/Unknown 9 69.3
Gender
 Female/feminine 9 69.3
 Male/masculine 3 23.1
 Other/unknown 1 7.7
Age (years)
 18–29 1 8.3
 30–39 2 16.7
 40–49 2 16.7
 50–59 6 50.0
 60+ 1 7.7
Length at organization (years) 12
 <1 1 (8.3)
 1–5 5 (41.7)
 5–10 5 (41.7)
 >10 1 (8.3)

aMissing demographics from one participant who declined to respond.

Table 4.

Key findings/recommendations for intervention, based on CFIR domains, qualitative, and quantitative data

CFIR domain Qualitative interview data Quantitative survey and EMR data Intervention recommendations
Inner setting Agreement across providers/staff that routine tobacco use screening is important, but unclear perceived roles and responsibilities of who should collect the information. (Theme 1)
Many providers/staff believed provider/staff training or education would improve routine tobacco use screening in their clinic setting. (Theme 2)
SURVEY:
•84% agree or strongly agree “it is important to routinely assess patient’s tobacco use.”
•80% agree or strongly agree “providing tobacco cessation services is part of cancer care.”
•35% did not agree “there was support for or expectations by clinic leadership for routine tobacco use screening and documentation.”
Training staff and other team members on evidence-based tobacco screening strategies that are feasible within oncology clinic settings.
Outer setting Patients’ cultural acceptance in discussing tobacco use and English language proficiency were reported barriers. (Theme 3)
Patients’ social needs were cited barriers to accessing tobacco cessation service. (Theme 4)
EMR:
•Among Asian patients, there was 12.3% greater predicted probability of data missingness for women compared to men.
•Among Black patients, there was 28.1% greater data missingness for uninsured compared to privately insured patients.
•Close to half of patients are Hispanic, Black, Asian, or other race and ethnicity.
Engagement with community members and policy partners to identify community needs and appropriate strategies.
Providing screening and tobacco cessation materials in multiple languages.
Intervention characteristics Consistent workflows and system-wide policy could improve tobacco use screening and referral. (Theme 5)
Increasing providers/staff awareness of available tobacco cessation services within the system. (Theme 6)
Input and partnership with community stakeholders and patient advocates can inform optimal adaptation needs of existing evidence-based programs to fit the current context. (Theme 3)
SURVEY:
•38% reported not having or not knowing whether “a current system is in place to assess patient’s tobacco use within the clinic settings.”
•52% strongly disagreed or disagreed that “their unit was equipped to implement tobacco screening and referral services currently.”
Increasing awareness among providers and clinic staff that the Cancer Center has existing resources for tobacco treatment.
Facilitate established workflows and protocols for screening and referral.
Characteristics of individuals Providers/staff had limited awareness of smoking cessation guidelines for cancer patients. (Theme 7)
Providers/staff indicated established workflows and responsibilities for tobacco use screening and cessation referral would improve their comfortability in tobacco use discussions with patients. (Theme 8)
SURVEY:
•50% of participants have worked at cancer center for less than 5 years.
Emphasizing during intervention training that smoking cessation is part of NCCN guidelines
Providing information about how tobacco cessation will improve treatment of all cancers and prevent secondary cancers

Inner setting

Two themes emerged for inner setting, or context within the clinic, that inform the need to clearly delineate roles and responsibilities within clinic teams and provide education to team members to optimize routine tobacco use screening and cessation referral.

Theme 1: providers/clinic staff agreed routine tobacco use screening among cancer patients is important, but were unclear about roles and responsibilities

Clinic team members recognized the importance of systematic and routine tobacco use screening. Some providers and staff described how important their role is in assessing tobacco use and supporting patients without support/resources for quitting. Defined workflows for assessment of tobacco use after the first patient encounter were lacking in both clinics. Some providers further recognized their role in the lack of a routine screening process:

“…I think I could do a better job of reassessing, especially postoperatively…I can definitely do a better job of checking in on patients…” (PA, Clinic 2).

Most providers were aware of the need for follow-up with patients to reassess tobacco use. Overall, providers and staff responses illustrated how there was agreement on the need to routinely assess tobacco use among patients but workflow and designated roles across clinic team members were not clear.

Theme 2: most providers/clinic staff believed provider/staff training or education would improve routine tobacco use screening in their clinic setting

In both clinics, providers and staff were asked for what they believed would improve routine screening of tobacco use and were prompted with examples of leadership support, incentives, designated staff time, and staff training or education. Most providers and staff reported a desire for training/education: “…I [want to] know how to successfully—be more convincing, I guess, about what I [want to] share and educate my patients on” (PA, Clinic 2). Providers and staff also shared why clinic staff need more guidance in how to discuss tobacco use with patients: “…I don’t think the nurses know how to engage in a conversation about smoking cessation … they don’t go through the six A’s of smoking cessation. I don’t think [it] comes natural…” (Nurse Specialist, Clinic 1).

Providers expressed wanting to be impactful in their discussions about tobacco use and cessation with patients and showed an openness to learning more, further highlighting the need for additional training and education. Providers and staff described wanting to know the purpose of routine screening and have a clearer workflow in their clinics. Providers and staff also reported a need for additional training in how to use the EMR to document screening.

Outer setting

Two themes for outer setting, or clinic’s external environment, became apparent that highlight the need to address barriers to tobacco use screening and referral and access to cessation services relating to culture, English language proficiency, and social needs of patients.

Theme 3: patients’ cultural acceptance in discussing tobacco use and English language proficiency were reported barriers to address in tobacco screening and referral

Clinic staff and providers discussed barriers to tobacco use assessment and access to cessation treatment for racial/ethnic minority groups (e.g., Armenian, Chinese, Korean, and Hispanic/Latino/a). English language proficiency and cultural differences were factors noted as impacting patients’ comfortability in discussing tobacco use and normalization of smoking behaviors leading some patients to downplay their usage. Providers and staff shared challenges of utilizing a translation service during appointments, and also noted potential barriers to providing linguistically accessible tobacco cessation services to meet patients’ needs. One provider highlighted the impact of provider-patient cultural concordance on receptivity to cessation counseling and need to recognize community-specific, culturally tailored messaging:

I think someone [physician]… who’s Persian sees a Persian patient, understands the context of Persian culture, he can relate to them and perhaps frame it in a way for them to better appreciate the significance of smoking cessation. (Physician, Clinic 2)

Theme 4: patients’ social needs were cited barriers to accessing cessation services

Clinic staff and providers named financial hardship, including type of health insurance, as well as transportation to and from healthcare services, as barriers to accessing tobacco cessation treatment for racial/ethnic minority patients:

Insurance is the big one. Transportation, jobs, just daily life. But I would say the insurance is probably the big one…And finances. Some people just can’t afford [it]. (RN, Clinic 1)

One clinic staff member elaborated on issues related to health insurance and access to treatment specifically for patients with public health insurance: “…when it comes to the smoking cessation stuff, they [public insurance] don’t provide that too often...” (LVN, Clinic 2). Providers and staff stressed the importance of tobacco cessation treatment for low-income patients and older adults with Medicaid (Medi-Cal) and/or Medicare insurance, and discussed the complexity of barriers due to cost and transportation limiting access to treatment. Overall, social needs of racial/ethnic minority and low-income patients emerged as perceived barriers to accessing cessation treatment.

Intervention characteristics

Two themes pertaining to intervention characteristics, or attributes of routine screening and referral, were noted that emphasize the importance of setting up clear clinic workflows for tobacco use screening and referral and making staff aware of available cessation services.

Theme 5: workflow for tobacco use screening varied across clinic settings

While some providers and clinic staff could describe current tobacco use screening processes for patient visits, many could not specify who on the clinic team was a part of the workflow and few mentioned a routine screening process. Responses also varied for how often tobacco use screening occurred during patient visits and what current protocols were for screening. While some staff thought screening was everyone’s job, some providers did not report a formal tobacco use screening process for who was to screen and when. One provider described screening falling to PAs: “…PAs are integral to our practice, and they know to ask about the smoking history…they end up by default screening” (Physician, Clinic 2). Despite having a designated EMR form for ascertaining tobacco use status, roles and agreed upon workflow for tobacco use screening, and identifying patients for referral to tobacco cessation services, were not established across clinics.

Theme 6: few providers/clinic staff were aware of available tobacco cessation services

Providers and clinic staff exhibited some knowledge of tobacco cessation services offered within the cancer center. However, most providers and staff lacked information about the services that were currently offered so many did not refer patients to cessation treatment services already available in their health system. Providers and staff expressed interest in receiving updated and accessible information on cessation services where they could refer patients, which was also discussed when they reported wanting additional training and education to improve screening. Some providers and staff did offer medication as an option for cessation treatment to patients, and some would refer patients to existing programs in primary care or social work:

…we will refer them back to their PCP to discuss the different options…we’ve actually given patients the tobacco cessation, like the patch. That’s pretty much all I know that we would give. I don’t know of any programs … (LVN, Clinic 2)

Characteristics of individuals

Two themes related to characteristics of individuals (team members in the clinic) point to opportunities for training to increase awareness of smoking cessation guidelines specific to cancer patients, and improve comfort discussing tobacco through clearly delineated workflows.

Theme 7: providers/staff were less aware of cessation guidelines for cancer patients

Clinic staff and providers displayed a lack of knowledge about specific guidelines for smoking cessation for cancer patients, such as guidelines from the National Comprehensive Cancer Network. Additionally, providers expressed limited knowledge about the specifics of guidelines for cancer patients: “Only to the extent for lung cancer. That’s it. Even then, I still always need a refresher course…” (Physician, Clinic 2). Overall, providers and staff in both clinics indicated a willingness to learn more about guidelines for smoking cessation for cancer patients, further highlighting the need for additional education and training.

Theme 8: providers/staff indicated established workflows and responsibilities for screening and referral would improve comfortability in discussions with patients

Providers and staff mostly viewed their interactions as positive with patient smokers, yet the level of interaction with patients about tobacco use varied. Few providers or staff were both screening and discussing tobacco use with patients. Some would screen for tobacco use but not discuss use, or some would not screen but did discuss use. One provider described interactions with their patients who refused to quit smoking: “…when they tell me ‘Hell, no.’ They’ll say that in a general good-natured way, and I won’t usually push too far beyond that…” (Physician, Clinic 1). Another provider did report pushing patients to discuss their usage in order to promote cessation, based on the strength of the patient–provider relationship.

A few of the providers and staff described negative interactions with patient smokers and also reported limiting discussions due to discomfort: “Some patients I know not to ask [about tobacco use] …I don’t push too much because the patients don’t like us to…they told me, ‘I’m going to do it,’ and that’s it” (LPN, Clinic 1). The core concerns, however, did not appear to be providers and staff feeling uncomfortable when bringing up tobacco, rather that there was no formal process in place for how to screen and when or how to discuss use in either clinic.

DISCUSSION

This multi-modal assessment of current tobacco use screening informs several opportunities for establishing capacity and infrastructure to best optimize the implementation of tobacco cessation services across contexts serving diverse populations. First, we observed opportunities for improvement in documentation of tobacco use status in patients’ EMR records (only 55% of patients had any smoking status/tobacco use information), and targeted efforts in equitable documentation of tobacco use among patients by gender, race/ethnicity, insurance, and age, which may include provider and clinic team trainings and in-language support services to address patients’ linguistic, cultural, and social needs. While we observed no data missingness differences between women and men, or among race/ethnicity groups, there were several interactions between gender, race/ethnicity, and insurance status that provide insight into how demographic-based discrepancies might be addressed by a clinic-level intervention to improve tobacco use screening and documentation. For example, the finding that there was a substantial gender gap for Asian patients (i.e., 12.3% greater predicted probability of data missingness for women) may indicate that clinic staff have a cognitive bias towards believing that Asian women patients are unlikely to smoke. In addition, insurance gaps among Asian and Black patients (24.2% greater data missingness for uninsured Asian patients and 28.1% for uninsured Black patients) may indicate an institutional bias against patients with relatively few financial resources, which may be exacerbated by persistent implicit racial biases. Use of evidence-based interventions tailored to specific communities could emphasize both quick and efficient tobacco screening strategies, as well as referral to low- to no-cost, effective tobacco treatment resources (e.g., the state quitline). Implementing an equitable tobacco cessation program for cancer patients in a diverse setting, such as the one in this study, will require equitable identification of patient need and referral access to cessation programs.

Second, our study also highlights the importance of addressing cultural and social needs of patients, particularly in settings serving patients from diverse cultural, linguistic, and socioeconomic backgrounds. Language and cultural backgrounds of diverse patient populations may impact provider and staff abilities to successfully screen for tobacco use or communicate the importance of tobacco cessation. Our findings indicate that provider and staff training on recommended guidelines for tobacco cessation among cancer patients is needed, which will likely require adaptations to account for a range of communication strategies, appropriateness of messaging to patients, and addressing community-specific barriers and stigmas, in order to serve patients from multiple racial/ethnic, cultural, and linguistic communities. These adaptations can be optimally developed with outer context stakeholders, including cancer center community advisory boards and community partners, to ensure program fit and sustainability. Tobacco cessation services will need to provide equitable options based on health literacy, transportation, appointment times, and cost/insurance coverage to better serve all patient groups. Settings with patients from diverse cultural backgrounds, languages, and social norms around smoking will require targeted messaging and tobacco cessation counseling that meets the unique needs of communities. Addressing health-related social needs within health care settings has gained focus in recent years and screening for social needs and social risk may be an important consideration when designing implementation of system-level programs that would benefit the most vulnerable, high-risk patient groups [54–58]. In the context of tobacco cessation, potential adaptations to address diverse patient needs can build upon work previous work described in NCI Evidence-Based Cancer Control Programs, such as manualized advice for clinicians on how to build rapport and conduct functional tobacco screening with diverse populations [59], and culturally tailored booklets to educate patients on cessation strategies [60].

Third, prior studies have observed system-level implementation of tobacco cessation programs for cancer patients will entails low-cost, efficient systems that take advantage of EMR tobacco use history to identify all patients who smoke without the need for time-consuming manual referrals [61, 62]. While there was consensus across stakeholders that providing tobacco cessation services is important, findings from the EMR analysis and the qualitative interviews indicate potential to examine and refine clinic workflows, designated roles and responsibilities, and improve awareness and training for tobacco use screening and referral. These findings align with prior studies on implementation of tobacco cessation programs that indicate addressing systemic and organizational barriers are necessary for longer term adoption and maintenance [45, 63]. Several strategies have been previously documented as system- or provider-level interventions that can result in improved tobacco cessation outcomes, including identifying system leadership support, having physician champions engage with peers within the system, implementing standards of care and other system policies, providing incentives for practice change, delivering provider and staff trainings to improve systematic tobacco use screening and referrals, covering dedicated staff to provide tobacco cessation services, and use of EMR to monitor and provide feedback to clinic teams [64–66]. Thus, our findings are consistent with the need to use multiple implementation strategies within the system, across providers, clinic staff, and clinic sites, to maximize routine use of screening and treatment services in diverse patient populations.

Finally, providers and staff in our study indicated the need for increased training to clarify the roles and responsibilities of clinic team members within their workflow to facilitate routine implementation of tobacco screening and service provision for cancer patients. The American Society of Clinical Oncology referenced the need for internal champions to achieve system-wide adoption and implementation of tobacco cessation programs. Having physician or other system-level champions will be important for buy-in across stakeholder groups within a large health system setting, as evidenced in prior studies [67]. Furthermore, establishing roles and responsibilities across departments and within clinic teams for tobacco use screening and referral, as well as having dedicated staff to identify and follow-up with patients who need tobacco treatment services, and system-level informatics and data support for monitoring feedback and uptake of treatment services, will lead to overall system improvements. Ongoing assessment of EMR data for tobacco screening and data missingness will also identify specific targets for equitable uptake.

While our study provides a comprehensive assessment of existing capacity and implementation needs for system-level tobacco cessation services in an oncology setting, some limitations should be noted. First, tobacco use history items are not mandated and enforced to be completed during a patient visit, introducing the possibility that even if tobacco use was assessed during the clinic visit, patient’s tobacco use history may not be stored in their EMR, or may be stored outside of the Social History (e.g., in a free-text clinic note) thus making this information inaccessible to data queries. In addition, prior studies have documented underreporting of tobacco use among cancer patients. Second, our EMR assessment of tobacco use status was based on 2019 data. More recent data may have differing patterns due to disruptions from the COVID-19 pandemic which disproportionately impacted racial/ethnic minority and low-income groups. Furthermore, due to limitations of the EMR data set, we could not examine the reason(s) for visits or patients’ medical histories, and rather just examined whether tobacco use status was present for any patient. Thus, we could not take into account severity of disease or other factors that may impede tobacco use screening. Third, health insurance status of patients and other insurance-based factors were noted as potential barriers to routine tobacco use screening and treatment referral. Managed care penetration and tobacco treatment coverage in the study region may be different from other regions in the USA. Finally, participants in our survey and qualitative interviews may not be representative of all clinic stakeholders as we interviewed clinic team members from only two outpatient settings within a large health system. While we iteratively assessed the qualitative data for thematic saturation, our qualitative data relied on a small sample from two clinics. Nonetheless, our qualitative interviews were purposively sampled from two different outpatient settings and we aimed to compare responses across clinics and within sites.

CONCLUSIONS

Opportunities for implementation of health system-wide sustainable tobacco cessation programs include leadership support for change, clinic staff training on brief, low-burden screening, as well as intervention and referral strategies that meet the needs of diverse patients. Employing a health equity lens at the implementation planning stage is critical to addressing the systemic barriers to tobacco use screening and referral and multiple stages (i.e., EMR documentation, training of providers and staff, perceived and determined roles and responsibilities). Thus, in this assessment, equitable implementation planning can be informed by multi-modal assessments that indicate: (i) where targeted efforts are needed (screening, clinic team training) and (ii) engagement and support by inner (leadership) and outer context stakeholders (community partners). It is critical to ensure equity with implementation to avoid worsening disparities [68, 69]. Our findings indicate that multilevel approaches to optimizing implementation to achieve health equity is required at the system, provider staff, and patient levels.

ACKNOWLEDGEMENTS

The authors thank the USC Norris Comprehensive Cancer Center Data Science Core (David Birtwell) and the USC Keck School of Medicine (Neil Bahroos) for informatics support. The authors also thank the support and guidance of the tobacco treatment team at the USC Chan Division of Occupational Science and Occupational Therapy.

Contributor Information

Jennifer Tsui, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA.

Kylie Sloan, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Rajiv Sheth, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Esthelle Ewusi Boisvert, Department of Psychology, University of Southern California, Los Angeles, CA, USA.

Jorge Nieva, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA; Department of Medicine, Division of Oncology, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Anthony W Kim, Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA; Department of Surgery, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA.

Raina D Pang, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA; Department of Psychology, University of Southern California, Los Angeles, CA, USA.

Steve Sussman, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA.

Matthew Kirkpatrick, Department of Population and Public Health Sciences, Keck School of Medicine, University of Southern California, Los Angeles, CA, USA; Norris Comprehensive Cancer Center, University of Southern California, Los Angeles, CA, USA; Department of Psychology, University of Southern California, Los Angeles, CA, USA.

FUNDING

This work was funded by a supplement to the USC Norris Comprehensive Cancer Center CCSG grant (5P30CA014089-45l; PI: Caryn Lerman).

COMPLIANCE WITH ETHICAL STANDARDS

Conflicts of interest: The authors declare that they have no conflicts of interest.

Human rights: All procedures were approved by the authorship team’s Institutional Review Board (IRB UP-20-01168).

Informed consent: Informed consent of participants was waived. All data were de-identified.

Welfare of Animals: This article does not contain any studies with animals.

TRANSPARENCY STATEMENTS

Study registration: This study was not formally registered.

Analytic plan registration: The analysis plan was not formally pre-registered.

Availability of data: De-identified data from this study will be made available by emailing the corresponding author.

Availability of analytic code: Analytic code used in this study may be available by emailing the corresponding author.

Availability of materials: Materials used to conduct this study are not publicly available.

REFERENCES

  • 1. Arnold  M, Liu  L, Kenter  GG, Creutzberg  CL, Coebergh  JW, Soerjomataram  I.  Second primary cancers in survivors of cervical cancer in the Netherlands: implications for prevention and surveillance. Radiother Oncol.  2014;111(3):374–381. [DOI] [PubMed] [Google Scholar]
  • 2. Office of the Surgeon General. The Health Consequences of Smoking—50 Years of Progress: A Report of the Surgeon General. Atlanta, GA: US Department of Health and Human Services, Citeseer; 2014. [Google Scholar]
  • 3. Waggoner  SE, Darcy  KM, Fuhrman  B, et al. Association between cigarette smoking and prognosis in locally advanced cervical carcinoma treated with chemoradiation: a gynecologic oncology group study. Gynecol Oncol.  2006;103(3):853–858. [DOI] [PubMed] [Google Scholar]
  • 4. Gritz  ER, Toll  BA, Warren  GW.  Tobacco use in the oncology setting: advancing clinical practice and research. Cancer Epidemiol Biomarkers Prev.  2014;23(1):3–9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 5. Chang  EHE, Braith  A, Hitsman  B, Schnoll  RA.  Treating nicotine dependence and preventing smoking relapse in cancer patients. Expert Review of Quality of Life in Cancer Care. 2017;2(1):23–39. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 6. Croyle  RT, Morgan  GD, Fiore  MC.  Addressing a core gap in cancer care—the NCI moonshot program to help oncology patients stop smoking. N Engl J Med.  2019;380(6):512–515. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 7. D’Angelo  H, Rolland  B, Adsit  R, et al. Tobacco treatment program implementation at NCI cancer centers: progress of the NCI Cancer moonshot-funded Cancer center cessation initiative. Cancer Prev Res.  2019;12(11):735–740. [DOI] [PubMed] [Google Scholar]
  • 8. Boyle  RG, Solberg  LI, Fiore  MC.  Electronic medical records to increase the clinical treatment of tobacco dependence: a systematic review. Am J Prev Med.  2010;39(6):S77–S82. [DOI] [PubMed] [Google Scholar]
  • 9. Fiore  M, Adsit  R, Zehner  M, et al. An electronic health record–based interoperable eReferral system to enhance smoking quitline treatment in primary care. J Am Med Inform Assoc.  2019;26(8-9):778–786. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 10. Rodgers-Melnick  SN, Hooper  MW.  Implementation of tobacco cessation services at a comprehensive cancer center: a qualitative study of oncology providers’ perceptions and practices. Support Care Cancer.  2021;29(5):2465–2474. [DOI] [PubMed] [Google Scholar]
  • 11. Khodadadi  AB, Carroll  W, Lee  EL, Hansen  B, Scarinci  IC.  It takes two to tango: patients’ and providers’ perspectives in tobacco cessation and head/neck cancer. Oncologist. 2021;26(9):761–770. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 12. Chase  W, Zurmehly  J, Amaya  M, Browning  KK.  Implementation of a smoking cessation e-Learning education program for oncology clinic healthcare providers: evaluation with implications for evidence-based practice. Worldviews Evid Based Nurs.  2020;17(6):476–482. [DOI] [PubMed] [Google Scholar]
  • 13. Sheffer  CE, Stein  JS, Petrucci  C, et al. Tobacco dependence treatment in oncology: initial patient clinical characteristics and outcomes from roswell park comprehensive cancer center. Int J Environ Res Public Health.  2020;17(11):3907. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 14. Matulewicz  RS, Bassett  JC, Kwan  L, Sherman  SE, McCarthy  WJ, Saigal  CS, Gore  JL.  Using a multilevel implementation strategy to facilitate the screening and treatment of tobacco use in the outpatient urology clinic: a prospective hybrid type I study. Cancer.  2022;128(6):1184–1193. [DOI] [PubMed] [Google Scholar]
  • 15. Cinciripini  PM, Karam-Hage  M, Kypriotakis  G, et al. Association of a comprehensive smoking cessation program with smoking abstinence among patients with cancer. JAMA Netw Open.  2019;2(9):e1912251. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 16. Fiore  MC, D’Angelo  H, Baker  T.  Effective cessation treatment for patients with cancer who smoke-the fourth pillar of cancer care. JAMA Netw Open.  2019;2(9):e1912264. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 17. Gali  K, Pike  B, Kendra  MS, et al. Integration of tobacco treatment services into cancer care at Stanford. Int J Environ Res Public Health.  2020;17(6):2101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 18. Gali  K, Prochaska  JJ.  Treating tobacco use in cancer survivors. In: Schapira  L, ed. Essentials of Cancer Survivorship: A Guide for Medical Professionals. Boca Raton, FL: CRC Press; 2021:1–247. [Google Scholar]
  • 19. Gummerson  SP, Lowe  JT, Taylor  KL, Lobo  T, Jensen  RE.  The characteristics of patients who quit smoking in the year following a cancer diagnosis. J Cancer Surviv.  2021;16(1):111–118. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 20. Jenssen  BP, Leone  F, Evers-Casey  S, Beidas  R, Schnoll  R.  Building systems to address tobacco use in oncology: early benefits and opportunities from the cancer center cessation initiative. J Natl Compr Canc Netw.  2019;17(6):638–643. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 21. Salloum  RG, D’Angelo  H, Theis  RP, et al. Mixed-methods economic evaluation of the implementation of tobacco treatment programs in National Cancer Institute-designated cancer centers. Implement Sci Commun.  2021;2(1):1–12. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 22. Simmons  VN, Sutton  SK, Meltzer  LR, et al. Preventing smoking relapse in patients with cancer: a randomized controlled trial. Cancer.  2020;126(23):5165–5172. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 23. Tong  EK, Wolf  T, Cooke  DT, Fairman  N, Chen  MS.  The emergence of a sustainable tobacco treatment program across the cancer care continuum: a systems approach for implementation at the University of California Davis comprehensive cancer center. Int J Environ Res Public Health.  2020;17(9):3241. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 24. Allen  AM, Oncken  C, Hatsukami  D.  Women and smoking: the effect of gender on the epidemiology, health effects, and cessation of smoking. Curr Addic Rep.  2014;1(1):53–60. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 25. Fagan  P, King  G, Lawrence  D, et al. Eliminating tobacco-related health disparities: directions for future research. Am J Public Health.  2004;94(2):211–217. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 26.Office of the Surgeon General. Tobacco Use Among United States Racial/ethnic Minority Groups. U.S. Department of Health and Human Services; 1998. [Google Scholar]
  • 27. Sakuma  KK, Pierce  JP, Fagan  P, et al. Racial/ethnic disparities across indicators of cigarette smoking in the era of increased tobacco control, 1992-2019. Nicotine Tob Res.  2021;23(6):909–919. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 28. Lee  JG, Henriksen  L, Rose  SW, Moreland-Russell  S, Ribisl  KM.  A systematic review of neighborhood disparities in point-of-sale tobacco marketing. Am J Public Health.  2015;105(9):e8–e18. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 29. Biener  L, Albers  AB.  Young adults: vulnerable new targets of tobacco marketing. Am J Public Health.  2004;94(2):326–330. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 30. Freedman  KS, Nelson  NM, Feldman  LL.  Smoking initiation among young adults in the United States and Canada, 1998-2010: a systematic review. Prev Chronic Dis.  2012; 9:E05. [PMC free article] [PubMed] [Google Scholar]
  • 31. Kiefe  CI, Williams  OD, Lewis  CE, Allison  JJ, Sekar  P, Wagenknecht  LE.  Ten-year changes in smoking among young adults: are racial differences explained by socioeconomic factors in the CARDIA study? Am J Public Health.  2001;91(2):213–238. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 32. Trinidad  DR, Gilpin  EA, Lee  L, Pierce  JP.  Has there been a delay in the age of regular smoking onset among African Americans? Ann Behav Med.  2004;28(3):152–157. [DOI] [PubMed] [Google Scholar]
  • 33. Trinidad  DR, Gilpin  EA, Lee  L, Pierce  JP.  Do the majority of Asian-American and African-American smokers start as adults? Am J Prev Med.  2004;26(2):156–158. [DOI] [PubMed] [Google Scholar]
  • 34. Watson  JM, Scarinci  IC, Klesges  RC, et al. Relationships among smoking status, ethnicity, socioeconomic indicators, and lifestyle variables in a biracial sample of women. Prev Med.  2003;37(2):138–147. [DOI] [PubMed] [Google Scholar]
  • 35. Control CD and Prevention. Current cigarette smoking prevalence among working adults—United States, 2004-2010. MMWR Morb Mortal Wkly Rep.  2011;60(38):1305–1309. [PubMed] [Google Scholar]
  • 36. Garrett  BE, Dube  SR, Babb  S, McAfee  T.  Addressing the social determinants of health to reduce tobacco-related disparities. Nicotine Tob Res.  2015;17(8):892–897. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 37. Garrett  BE, Dube  SR, Winder  C, Caraballo  RS, Centers for Disease Control Prevention. Cigarette smoking—United States, 2006–2008 and 2009–2010. MMWR Suppl.  2013;62(3):81–84. [PubMed] [Google Scholar]
  • 38. Smith  PH, Bessette  AJ, Weinberger  AH, Sheffer  CE, McKee  SA.  Sex/gender differences in smoking cessation: a review. Prev Med.  2016;92:135–140. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 39. Trinidad  DR, Pérez-Stable  EJ, White  MM, Emery  SL, Messer  K.  A nationwide analysis of US racial/ethnic disparities in smoking behaviors, smoking cessation, and cessation-related factors. Am J Public Health.  2011;101(4):699–706. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 40. Powell  BJ, Beidas  RS, Lewis  CC, Aarons  GA, McMillen  JC, Proctor  EK, Mandell  DS.  Methods to improve the selection and tailoring of implementation strategies. J Behav Health Serv Res.  2017;44(2):177–194. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 41. Vinson  CA.  Using concept mapping to develop a conceptual framework for creating virtual communities of practice to translate cancer research into practice. Prev Chronic Dis.  2014;11:E68. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 42. Waltz  TJ, Powell  BJ, Matthieu  MM, et al. Use of concept mapping to characterize relationships among implementation strategies and assess their feasibility and importance: results from the Expert Recommendations for Implementing Change (ERIC) study. Implement Sci.  2015;10:109. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 43. Windsor  LC.  Using concept mapping in community-based participatory research: a mixed methods approach. J Mix Methods Res.  2013;7(3):274–293. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 44. Andres  A, Castellano  Y, Fu  M, et al. Exploring individual and contextual factors contributing to tobacco cessation intervention implementation. Addict Behav.  2019;88:163–168. [DOI] [PubMed] [Google Scholar]
  • 45. Rojewski  AM, Bailey  SR, Bernstein  SL, et al. Considering systemic barriers to treating tobacco use in clinical settings in the United States. Nicotine Tob Res.  2019;21(11):1453–1461. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 46. Brownson  RC, Kumanyika  SK, Kreuter  MW, Haire-Joshu  D.  Implementation science should give higher priority to health equity. Implement Sci.  2021;16(1):28. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 47. Woodward  EN, Singh  RS, Ndebele-Ngwenya  P, Castillo  AM, Dickson  KS, Kirchner  JE.  A more practical guide to incorporating health equity domains in implementation determinant frameworks. Implement Sci Commun.  2021;2(1):61. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 48.Cancer Center Cessation Initiative Implementation Science Working Group. Implementation science to improve tobacco cessation services in oncology care. J Natl Compr Canc Netw.  2021;19(Suppl_1):S12–S15. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 49. Aarons  GA, Fettes  DL, Sommerfeld  DH, Palinkas  LA.  Mixed methods for implementation research: application to evidence-based practice implementation and staff turnover in community-based organizations providing child welfare services. Child Maltreat.  2012;17(1):67–79. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 50. Miles  MB, Huberman  AM, Saldaña  J.  Qualitative Data Analysis: A Methods Sourcebook. 3rd ed. London: Sage Publications; 2014. [Google Scholar]
  • 51. Fetters  MD, Curry  LA, Creswell  JW.  Achieving integration in mixed methods designs-principles and practices. Health Serv Res.  2013;48(6 Pt 2):2134–2156. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 52. Crabtree  BF, Miller  WL.  Doing Qualitative Research in Primary Care: Multiple Strategies. 2nd ed. Newbury Park, CA: Sage Publications; 1999. [Google Scholar]
  • 53. Guetterman  TC, Fetters  MD, Creswell  JW.  Integrating quantitative and qualitative results in health science mixed methods research through joint displays. Ann Fam Med.  2015;13(6):554–561. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 54. Addressing Social Risks in Cancer Care Delivery. Virtual Workshop. N.C.I.D.o.C.C.a.P. Sciences, Editor. 2021. Available at: https://events.cancer.gov/hdrp/ncisocialrisksmeeting. [Google Scholar]
  • 55. Integrating Social Care into the Delivery of Health Care: Moving Upstream to Improve the Nation’s Health. National Academies of Sciences, Engineering, and Medicine; Health and Medicine Division; Board on Health Care Services; Committee on Integrating Social Needs Care into the Delivery of Health Care to Improve the Nation’s Health, Editor. Washington, DC: National Academies Press; 2019. [PubMed] [Google Scholar]
  • 56. Tsui  J, Yang  A, Anuforo  B, et al. Health related social needs among chinese american primary care patients during the COVID-19 pandemic: implications for cancer screening and primary care. Front Public Health.  2021;9:674035. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 57. Sundar, KR.  Universal screening for social needs in a primary care clinic: a quality improvement approach using the your current life situation survey. Perm J, 2018. 22:18–89. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 58. Billioux  A, Verlander  K, Anthony  S, Alley  D.  Standardized Screening for Health-Related Social Needs in Clinical Settings: The Accountable Health Communities Screening Tool. National Academy of Medicine, 2017:1–19. Available at: NAM.edu/Perspectives. [Google Scholar]
  • 59. Dornelas  EA, Magnavita  J, Beazoglou  T, et al. Efficacy and cost-effectiveness of a clinic-based counseling intervention tested in an ethnically diverse sample of pregnant smokers. Patient Educ Couns.  2006;64(1–3):342–349. [DOI] [PubMed] [Google Scholar]
  • 60. Hodge  FS, Casken  J.  Characteristics of American Indian women cigarette smokers: prevalence and cessation status. Health Care Women Int.  1999;20(5):455–469. [DOI] [PubMed] [Google Scholar]
  • 61. Karn  S, Fernandez  A, Grossberg  LA, et al. Systematically improving tobacco cessation patient services through electronic medical record integration. Health Promot Pract.  2016;17(4):482–489. [DOI] [PubMed] [Google Scholar]
  • 62. D’Angelo  H, Hohl  SD, Rolland  B, et al. Reach and effectiveness of the NCI Cancer moonshot-funded Cancer Center Cessation Initiative. Translational Behavioral Medicine.  2022;12(5):688–692. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 63. D’Angelo  H, Ramsey  AT, Rolland  B, et al. Pragmatic Application of the RE-AIM framework to evaluate the implementation of tobacco cessation programs within NCI-designated cancer centers. Front Public Health.  2020;8:221. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 64. Thomas  D, Abramson  MJ, Bonevski  B, George  J.  System change interventions for smoking cessation. Cochrane Database Syst Rev.  2017;2(2):CD010742. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 65.Office of the Surgeon General. Smoking Cessation: A Report of the Surgeon General. 2020. Available at: https://www.hhs.gov/surgeongeneral/index.html. Accessibility verified December 14, 2022.
  • 66. Ugalde  A, White  V, Rankin  NM, et al. How can hospitals change practice to better implement smoking cessation interventions? A systematic review. CA Cancer J Clin.  2022;72(3):266–286. [DOI] [PubMed] [Google Scholar]
  • 67. Hohl  SD, Bird  JE, Nguyen  CVT, et al. Operationalizing leadership and clinician buy-in to implement evidence-based tobacco treatment programs in routine oncology care: a mixed-method study of the U.S. cancer center cessation initiative. Curr Oncol.  2022;29(4):2406–2421. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 68. Woodward  EN, Matthieu  MM, Uchendu  US, Rogal  S, Kirchner  JE.  The health equity implementation framework: proposal and preliminary study of hepatitis C virus treatment. Implement Sci.  2019;14(1):26. [DOI] [PMC free article] [PubMed] [Google Scholar]
  • 69. Baumann  AA, Cabassa  LJ.  Reframing implementation science to address inequities in healthcare delivery. BMC Health Serv Res.  2020;20(1):190. [DOI] [PMC free article] [PubMed] [Google Scholar]

Articles from Translational Behavioral Medicine are provided here courtesy of Oxford University Press

RESOURCES