Faculty Bibliography

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

BACKGROUND:Insulin titration is typically done face-to-face with a clinician; however, this can be a burden for patients due to logistical issues associated with in-person clinical care. The Mobile Insulin Titration Intervention (MITI) used basic cell phone technology including text messages and phone calls to help patients with diabetes find their optimal basal insulin dose (OID). OBJECTIVE:To evaluate sociodemographic and clinical correlates of reaching OID, text message response rate, and days needed to reach OID. METHODS:Primary care providers referred patients to MITI and nurses delivered the program. Three multivariable regression models quantified relationships between various correlates and primary outcomes. RESULTS:The sample included 113 patients from 2 ambulatory clinics, with a mean age of 50 years (SD = 10), 45% female, 79% Hispanic, 43% unemployed, and 46% uninsured. In regression models, baseline fasting blood glucose (FBG) was negatively associated with odds of reaching OID and 100% text responses, and positively associated with days to reach OID, p < .05). CONCLUSIONS:Patients with higher baseline FBG levels were less successful across outcomes and may need additional supports in future mHealth diabetes programs. PRACTICAL IMPLICATIONS/CONCLUSIONS:Basic cell phone technology can be used to adjust patients' insulin remotely, thereby reducing logistical barriers to care.

Objectives: Tobacco use may be related to financial strain in people with depression. This study explored the relationship among tobacco expenditures, financial distress, and smoking-induced deprivation (SID) in smokers with and without depression. Methods: Adult tobacco users in the United States (N = 234) completed a survey assessing depression (PHQ-8≥10), sociodemographics, tobacco use and spending, financial satisfaction and distress, and SID. Regression models controlling for income compared outcomes between participants with (N = 96) and without (N = 138) depression. Results: Participants with depression were 4 times more likely to report SID (32% vs 8%, p = .00). Smokers with depression had lower financial satisfaction, greater worry about being able to meet monthly living expenses, higher frequency of being unable to afford a leisure activity, higher frequency living paycheck to paycheck, and lower confidence in finding money for an emergency (p < .01). In smokers with depression, higher tobacco expenditures were independently associated with greater odds of SID and higher levels of financial distress (p < .01). Conclusions: About one-third of smokers with depression forego essentials to pay for tobacco. Tobacco interventions may alleviate financial strain in people with depression.

Background/UNASSIGNED:Tobacco spending may exacerbate financial hardship in low-income populations by using funds that could go toward essentials. This study examined post-quit spending plans among low-income smokers and whether financial hardship was positively associated with motivation to quit in the sample. Methods/UNASSIGNED:= 410). Linear regression was used to examine the relationship between financial distress, food insecurity, smoking-induced deprivation (SID) and motivation to quit (measured on a 0-10 scale). We performed summative content analyses of open-ended survey questions to identify the most common plans among participants with and without SID for how to use their tobacco money after quitting. Results/UNASSIGNED:The top three spending plans among participants with and without SID were travel, clothing and savings. There were three needs-based spending plans unique to a small number of participants with SID: housing, health care and education. Conclusions/UNASSIGNED:Financial distress and food insecurity did not enhance overall motivation to quit, while smokers with SID were less motivated to quit. Most low-income smokers, including those with SID, did not plan to use their tobacco money on household essentials after quitting.

Background/UNASSIGNED:Many tobacco dependent cancer survivors continue to smoke after diagnosis and treatment. This study investigated the extent to which hospital-based cancer registries could be used to identify smokers in order to offer them assistance in quitting. The concordance of tobacco use coded in the registry was compared with tobacco use as coded in the accompanying Electronic Health Records (EHRs). Methods/UNASSIGNED:We gathered data from three hospital-based cancer registries in New York City during June 2014 to December 2016. For each patient identified as a current combustible tobacco user in the cancer registries, we abstracted tobacco use data from their EHR to independently code and corroborate smoking status. We calculated the proportion of current smokers, former smokers, and never smokers as indicated in the EHR for the hospitals, cancer site, cancer stage, and sex. We used a logistic regression model to estimate the log odds of the registry-based smoking status correctly predicting the EHR-based smoking status. Results/UNASSIGNED:Agreement in current smoking status between the registry-based smoking status and the EHR-based smoking status was 65%, 71%, and 90% at the three participating hospitals. Logistic regression results indicated that agreement in smoking status between the registry and the EHRs varied by hospital, cancer type, and stage, but not by age and sex. Conclusions/UNASSIGNED:The utility of using tobacco use data in cancer registries for population-based tobacco treatment interventions is dependent on multiple factors including accurate entry into EHR systems, updated data, and consistent smoking status definitions and registry coding protocols. Our study found that accuracy varied across the three hospitals and may not be able to inform interventions at these hospitals at this time. Several changes may be needed to improve the coding of tobacco use status in EHRs and registries.