Faculty Bibliography

OBJECTIVES/OBJECTIVE:Guidelines recommend that smokers participate in four or more counseling sessions when trying to quit, but smokers rarely engage in multiple sessions. The "decoy effect" is a cognitive bias that can cause consumer preferences for a "target" product to change when presented with a similar but inferior product (a "decoy"). This study tested the use of a decoy to guide smokers' selection of a target number of counseling sessions. During an online survey, adult tobacco users (N = 93) were randomized to one of two groups that determined the answer choices they saw in response to a question assessing their interest in multi-session cessation counseling. Group A choose between two sessions or a "target" of five sessions. Group B was given a third "decoy" option of seven sessions. Binary logistic regression was used to compare groups on the proportion of participants selecting the "target." RESULTS:Among 90 participants with complete data, a decoy effect was not found. There was no significant difference between groups in the proportion of participants selecting the target of five sessions (47% in Group B vs. 53% in Group A; aOR = 0.76, 95%CI 0.48-1.19). Trial Registration This study was retrospectively registered at clinicaltrials.gov on December 13, 2019 (NCT04200157).

OBJECTIVE:HealthyHearts NYC was a stepped wedge randomized control trial that tested the effectiveness of practice facilitation on the adoption of cardiovascular disease guidelines in small primary care practices. The objective of this study was to identify was to identify attributes of small practices that signaled they would perform well in a practice facilitation intervention implementation. METHODS:A mixed methods multiple-case study design was used. Six small practices were selected representing 3 variations in meeting the practice-level benchmark of >70% of hypertensive patients having controlled blood pressure. Inductive and deductive approaches were used to identify themes and assign case ratings. Cross-case rating comparison was used to identify attributes of high performing practices. RESULTS:Our first key finding is that the high-performing and improved practices in our study looked and acted similarly during the intervention implementation. The second key finding is that 3 attributes emerged in our analysis of determinants of high performance in small practices: (1) advanced use of the EHR; (2) dedicated resources and commitment to quality improvement; and (3) actively engaged lead clinician and office manager. CONCLUSIONS:These attributes may be important determinants of high performance, indicating not only a small practice's capability to engage in an intervention but possibly also its readiness to change. We recommend developing tools to assess readiness to change, specifically for small primary care practices, which may help external agents, like practice facilitators, better translate intervention implementations to context.

Few studies have examined factors that facilitate recruitment of small independent practices (SIPs) (<5 full-time clinicians) to participate in research and methods for optimizing retention. The authors analyzed qualitative data (eg, recruiter's field notes and diary entries, provider interviews) to identify barriers and facilitators encountered in recruiting and retaining 257 practices in HealthyHearts New York City (NYC). This study was a stepped-wedge randomized controlled trial that took place 2015 through 2018 across 5 boroughs in NYC. Three main factors facilitated rapid recruitment: (1) a prior well-established relationship with the local health department, (2) alignment of project goals with practice priorities, and (3) providing appropriate monetary incentives. Retention was facilitated through similar mechanisms and an ongoing multifaceted communication strategy. This article identifies specific strategies that enhance recruitment of SIPs and fills gaps in knowledge about factors that influence retention in the context of a design that requires waiting to receive the intervention.

Introduction: The use of electronic cigarettes (e-cigarettes) in smokers with mental health conditions (MHC) is not well understood. Aims: This study aims to compare e-cigarette users and non-users among veteran smokers with MHC to characterize differences in smoking behavior, motivation to quit, psychological distress, primary psychiatric diagnosis, and other factors. Methods: Baseline survey data were used from a randomized smoking cessation trial enrolling smokers with MHC from four Veterans Health Administration hospitals. Participants were categorized as current, former (having ever tried an e-cigarette), or never e-cigarette users. Pearson's chi2 and

INTRODUCTION/BACKGROUND:Smoking disproportionately affects individuals with psychiatric diagnoses. Providers can play a role in reducing tobacco-related morbidity among people with a psychiatric diagnosis by routinely screening and treating all patients for tobacco use. This study seeks to identify rates of tobacco screening, counseling, and medication orders during outpatient visits with adults who have a psychiatric diagnosis. METHODS:Data from the 2012-2015 National Ambulatory Medical Care Survey were examined to calculate the proportion of visits with people who have a psychiatric diagnosis that included tobacco screening, counseling, or smoking-cessation medications. Logistic regression was used to identify patient and visit factors associated with tobacco screening and treatment. All analyses were conducted in 2018. RESULTS:Seventy-two percent of visits included tobacco screening, 23% of visits with tobacco users included cessation counseling, and 4% of visits with tobacco users included a cessation medication order. Visits were more likely to include tobacco screening if they were for a nonpsychiatric condition, were >30 minutes, or were with a primary care physician (p<0.05). Visits were less likely to include tobacco screening if they were with a black, non-Hispanic patient or patient with Medicaid (p<0.05). Visits were more likely to include cessation counseling if they were for a nonpsychiatric condition (p<0.05), and were less likely to include counseling if they were with a Hispanic or self-pay patient (p<0.05). CONCLUSIONS:There is still room for improvement in providing equitable treatment for people with psychiatric conditions for smoking, particularly in nonprimary settings.

PURPOSE/OBJECTIVE:Small independent primary care practices (SIPs) often lack the resources to implement system changes. HealthyHearts NYC, funded through the EvidenceNOW initiative of the Agency for Healthcare Research and Quality, studied the effectiveness of practice facilitation to improve cardiovascular disease- related care in 257 SIPs. We sought to understand SIP clinicians' perspectives on the benefits of practice facilitation. METHODS:We conducted in-depth interviews with 19 SIP clinicians enrolled in HealthyHearts NYC. Interviews were transcribed and coded using deductive and inductive approaches. To understand whether the perceived benefits of practice facilitation differ based on the availability of internal staff for quality improvement (QI), we compared themes pertaining to benefits between practices with 3 or fewer office staff vs more than 3 office staff. RESULTS:Clinicians perceived 2 main benefits of practice facilitation. First, facilitators served as a connection to the external health care environment for SIPs, often through teaching and information sharing. Second, facilitators provided electronic health record (EHR)/data expertise, often by teaching functionality and completing technical assistance and tasks. SIPs with more than 3 office staff felt that facilitators provided benefits primarily through teaching, whereas SIPs with 3 or fewer staff felt that facilitators also provided hands-on support. At the intersections of these benefits, there emerged 3 central practice facilitation benefits: (1) creating awareness of quality gaps, (2) connecting practices to information, resources, and strategies, and (3) optimizing the EHR for QI goals. CONCLUSIONS:SIP clinicians perceived practice facilitation to be an important resource for connecting their practice to the external health care environment and resources, and helping their practice build QI capacity through teaching, hands-on support, and EHR-driven solutions.

BACKGROUND:In 2016, a short message service text messaging intervention to titrate insulin in patients with uncontrolled type 2 diabetes was implemented at two health care facilities in New York City. OBJECTIVE:This study aimed to conduct a qualitative evaluation assessing barriers to and the facilitators of the implementation of the Mobile Insulin Titration Intervention (MITI) program into usual care. METHODS:We conducted in-depth interviews with 36 patients enrolled in the MITI program and the staff involved in MITI (n=19) in the two health care systems. Interviews were transcribed and iteratively coded by two study investigators, both inductively and deductively using a codebook guided by the Consolidated Framework for Implementation Research. RESULTS:Multiple facilitator themes emerged: (1) MITI had strong relative advantages to in-person titration, including its convenience and time-saving design, (2) the free cost of MITI was important to the patients, (3) MITI was easy to use and the patients were confident in their ability to use it, (4) MITI was compatible with the patients' home routines and clinic workflow, (5) the patients and staff perceived MITI to have value beyond insulin titration by reminding and motivating the patients to engage in healthy behaviors and providing a source of patient support, and (6) implementation in clinics was made easy by having a strong implementation climate, communication networks to spread information about MITI, and a strong program champion. The barriers identified included the following: (1) language limitations, (2) initial nurse concerns about the scope of practice changes required to deliver MITI, (3) initial provider knowledge gaps about the program, and (4) provider perceptions that MITI might not be appropriate for some patients (eg, older or not tech-savvy). There was also a theme that emerged during the patient and staff interviews of an unmet need for long-term additional diabetes management support among this population, specifically diet, nutrition, and exercise support. CONCLUSIONS:The patients and staff were overwhelmingly supportive of MITI and believed that it had many benefits and that it was compatible with the clinic workflow and patients' lives. Initial implementation efforts should address staff training and nurse concerns. Future research should explore options for integrating additional diabetes support for patients.

Background: Smoking rates are two times higher among people living in poverty. Low-income smokers face unique barriers to cessation, including high levels of financial distress. Reducing financial distress may improve cessation rates in this vulnerable population. Moreover, cessation of tobacco spending may further alleviate financial distress by freeing-up funds that could go toward essentials (e.g., food). We examined the efficacy of a program that integrates financial management coaching into smoking cessation coaching for low-income smokers.
Method(s): We recruited 359 smokers living below 200% of the federal poverty level in New York City and randomized them 1: 1 to receive up to 9 sessions of integrated financial management-smoking cessation coaching or usual care. The financial coaching aimed to help participants move from spending on cigarettes to spending on household essentials, and to help participants access financial resources. Participants completed surveys at baseline, 2 and 6 months to assess smoking and financial outcomes and treatment satisfaction.
Result(s): Intervention patients were more likely to have made a quit attempt by 6 months than Control participants (81% vs. 66%, p=.03). Abstinence was significantly higher for the Intervention group at 2 months (23% vs 9%, p=.01) and 6 months (30% vs. 10%, p<.005). At 6 months, Intervention participants were less likely to report high levels of stress about their general finances (44% vs. 66% Control, p=.01), high levels of worry about meeting monthly expenses (56% vs 73% Control, p=.01), or high dissatisfaction with their present financial situation (63% vs 75% Control, p<.05). Intervention participants were also less likely to report frequently living paycheck to paycheck (71% vs 88% Control, p=.01) or frequently being unable to afford leisure activities (51% vs 70% Control, p<.05). There was no group difference in the level of confidence in being able to pay for a $ 1,000 financial emergency (71% low confidence for both). Among the 71% of Intervention participants who began counseling, 85% reported being very satisfied with the integrated counseling. Fifty-one percent reported that the number of counseling sessions they received was " just right," while 36% reported that the number was " too few." Out of the participants who quit smoking, 100% reported that quitting smoking helped them financially and 58% described achieving one or more of their post-quit financial goals.
Conclusion(s): Integrating financial coaching into our smoking cessation program was feasible and produced significantly higher abstinence rates and reductions in financial distress than usual care. Participants were highly satisfied with the integrated program and felt it helped them financially. Our integrated program can serve as model for addressing the unique needs of low-income smokers

Background: Tobacco remains the leading cause of preventable death and disease in the U.S. Tobacco users are at increased risk of food insecurity, and the co-occurrence of tobacco use and food insecurity may place individuals at especially high risks of poor health. The objective of this study is to identify rates and socio-demographic correlates of food-insecurity among low-income tobacco users in the New York City area.
Method(s): We used baseline survey data from a large randomized controlled trial testing a smoking cessation intervention for smokers living below 200% of the federal poverty level (FPL) to calculate the proportion of smokers experiencing food insecurity, as measured by the USDA 6-item food security model. We used bivariable and multi-variable logistic regression to identify participant factors associated with food insecurity.
Result(s): Overall, 55% of participants were food insecure, with 27% reporting very high food insecurity. Food insecurity did not significantly differ by gender, race, education, or employment status (p>.05). Marital status tended to be a protector against food insecurity. Participants who reported being separated, widowed, or divorced, were more likely to be food insecure than those who reported being married or cohabitating (AOR = 2.24, 95% CI: 1.07-4.72). Additionally, participants who reported being never married had almost three times greater odds of experiencing food insecurity than married or cohabitating participants (AOR = 2.90, 95% CI: 1.40-6.00). Participants who fell below 100% of the FPL were almost two times more likely to experience food insecurity than those with income above the FPL (AOR = 1.95, 95% CI: 1.12-3.40).
Conclusion(s): Most low-income tobacco users were experiencing food insecurity. Having been separated, divorced, widowed or never married is a significant predictor of food insecurity. Social networks and removing social isolation may be a protector against food insecurity among this unique sample of low-income NYC smokers. Future interventions which seek to alleviate food insecurity may benefit from targeting the poorest and socially isolated smokers

Background: Health equity can broadly be defined as giving people the opportunities and resources needed to maximize health regardless of socially determined circumstances. SDoH are economic and social conditions that lead to differences in health status. We practice medicine at a mission driven safety-net hospital and provide care to patients with uncontrolled type 2 IDDM. Understanding not only these patients' SDoH barriers, but also their preferences for assistance, is the first step in providing equitable help.
Method(s): We used surveys and interviews to learn about 3 themes: SDoH barriers that impacted the ability to care for one's diabetes, desirable service features of any assistance program, and the types of services patients feel are needed.
Result(s): We learned that 84% of patients had > 1 barrier to health care access, 54% were unable to pay for > 1 essential item when it was needed, 53% reported > 1 barrier in their built environment, 47% reported > 1 issue with health literacy, and 37% shared that they only saw or talked to someone that they cared about or felt close to < 2 times per week. In the process of defining SDoH barriers, we also learned about unhealthy behavior patterns: 69% of patients have inadequate fruit and vegetable consumption, 57% get no leisure-time physical activity, 48% sometimes or often miss a day of checking their blood sugar, 35% sometimes or often miss doses of their medications and 30% are unable to follow up with their doctor in the time frame they are given. Despite their obstacles, patients felt that they didn't need " help". While they did share preferences on desirable service features, they volunteered very little regarding desirable types of services. Their lack of suggestions on service features was a finding in and of itself, warranting further exploration. In the end, we gauged interest in currently available resources at our hospital and in NYC, as well as our team's ideas for potential new programs to tackle some of the unhealthy behavior patterns we learned about (see types of services below). The service features that were a priority for any assistance program were: doctor knows about the program (86%), cost (87%), program is in-person (83%), program sends reminders (74%), program is a group class (74%), program is close to home (70%). In terms of types of services, 70% of patients want to learn about Farmer's markets as a source to eat more produce, 65% want to use the pedometer program we are developing and up to 45% want to use Bellevue's new Diabetes Patient Navigator program for assistance with barriers to health care access, taking diabetes medications, and checking blood sugar.
Conclusion(s): Patients with uncontrolled type 2 IDDM at our safety-net hospital have significant SDoH barriers, multiple service feature preferences, and are interested in programs currently available and under development. Understanding patient preferences for assistance is a key step in creating solutions that provide equity for underserved patients in need