Faculty Bibliography

Statement of Problem Or Question (One Sentence): Can a home visit complex care management program successfully identify and engage high risk patients in a FQHC? Objectives of Program/Intervention (No More Than Three Objectives): 1. Identify patients at an FQHC who are at risk for preventable hospitalization 2. Enroll and engage patients in a home visit based complex care management program. Description of Program/Intervention, Including Organizational Context (E.G. Inpatient Vs. Outpatient, Practice or Community Characteristics): The Primary Care Plus program (PCP+) is a home visit based program established to address the needs of patients at risk for preventable hospitalizations within the Family Health Centers at NYU Langone. The program staff-a physician, a nurse practitioner, a social worker and 2 community health workers-coordinate as a team to identify and address the biopsychosocial needs of high risk patients. A key intervention is the home visit lead by a physician or nurse practitioner to perform the medical assessment, medication reconciliation, and identification of both medical and social impediments to optimal health. The program is not intended to replace the patient's primary care provider, but to function as an addition to the patient's care team, identifying and mitigating risk drivers, and handing off to the primary team and care management resources once the risk drivers have been addressed. Patients are referred into the program by either their primary care doctors or care management. The program is restricted to those patients who have a continuity relationship in the Federally Qualified Health Center, and who are identified as being at risk for a preventable hospitalization. Latitude is given to the referral source in how patients are identified; guidance is given to focus on patients with a history of preventable hospitalizations (as defined by PQI) or patients with advanced disease and potential palliative care needs. Measures of Success (Discuss Qualitative And/Or Quantitative Metrics Which Will Be Used To Evaluate Program/Intervention): The primary measure of success is patient engagement. Patient engagement is defined by both consent to the program and successful home visit by the medical provider. Other outcome metrics are patient characteristics, number of emergency department visits and number of inpatient hospitalizations in the 12 months before program enrollment. Findings To Date (It Is Not Sufficient To State Findings Will Be Discussed): Since program inception in August 2018 through December 31, 2018, 75 patients have been identified by care management or primary care providers as potential candidates for the program and who met criteria as defined above. Of the 75 patients, 6 (8%) declined the program, and another 10 (13.3%) could not be found. The remaining 59 patients were seen at home and assessed. Total engagement was 78.7%. Patients identified represent a cohort of patients with an average of 2.0 inpatient admissions and 3.2 emergency department visits in the preceding 12 months prior to enrollment. Key Lessons For Dissemination (What Can Others Take Away For Implementation To Their Practice Or Community?): Identification of a high-risk patient population in a federally qualified health center and referral into a home visit based care management program is associated with high acceptance and engagement. Future study will determine if patients enrolled in the program have an impact on risk drivers and preventable hospitalizations

Statement of Problem Or Question (One Sentence): As healthcare delivery shifts to the value based paradigm how do you educate primary care providers on medication adherence metrics while performing a meaningful educational experience? Objectives of Program/Intervention (No More Than Three Objectives): 1.Educate Internal Medicine residents in a Primary Care residency program on NCQA HEDIS measures regarding medication adherence metrics 2.Work with a clinically integrated network (CIN) pharmacy team on identifying patients who have not refilled their medications, and how to engage patient medication adherence Description of Program/Intervention, Including Organizational Context (E.G. Inpatient Vs. Outpatient, Practice or Community Characteristics): The Family Health Centers (FHC) at NYU Langone is a network of 8 Federally Qualified Health Centers in Brooklyn New York. Primary care residents, working with the NYU CIN pharmacy team, collaborated on telephonic outreach to engage patients identified by payor contracts as nonadherent on medication refills. After initial training, which included education on how the Proportion of Days Covered (PDC) rate is a quantitative metric used to measure quality of care and scripted exercise on telephonic patient engagement, residents were tasked with identifiying challenges on medication refill as well as intervening when appropriate. At the end of the intervention period a resident focus group was conducted to determine the educational value in this quality initiative. Measures of Success (Discuss Qualitative And/Or Quantitative Metrics Which Will Be Used To Evaluate Program/Intervention): Primary endpoint was increased PDC rates based on payor data for patients who are diagnosed with either having diabetes (non gestational), hypertension or dyslipidemia. A post intervention focus group and semantical content analysis was performed regarding educational value from this exercise. Findings To Date (It Is Not Sufficient To State Findings Will Be Discussed): In a 6-month period 523 unique patients were engaged with 899 outreaches completed. 1061 barriers were identified. The top 3 patient identified barriers were: patients unaware they had not filled the prescription (31.05%), lack of clearly identified reason for non adherence (20.23%), and patients did not feel committed to taking the prescribed medication (14.97%). When comparing PDC rates from the previous year, this intervention saw a 7% increase in aggregate PDC rates for those who were prescribed medications and having diabetes. Regarding post intervention focus groups with residents, semantic content analysis revealed the highest affinity for positive descriptors in the domains of educational value, need to expand education to resident providers, and continued interest in future quality projects with the pharmacy team. Key Lessons For Dissemination (What Can Others Take Away For Implementation To Their Practice Or Community?): Key take home lessons in this intervention is that telephonic pharmacy adherence outreach has a positive impact on maintaining PDC rate compliance, particularly in patients with managed Medicare plans. On educational value, further development is needed in resident curriculum regarding medication adherence and reconciliation in the ambulatory setting. Lastly residents working with pharmacy teams find value in addressing medication adherence barriers and may impact best practices in provider prescribing habits when engaging patients

Background: Sodium bicarbonate therapy (SBT) has a variety of ED indications but its use is controversial. Some authors recommend SBT for drug overdoses involving salicylates and sodium channel antagonists such as tricyclics (TCA). Due to its effect on serum potassium, we hypothesized that SBT may prolong the QTc and increase risk for adverse cardiovascular events (ACVE). Our purpose was to evaluate SBT dose and duration in ED patients with drug overdose for an association with ACVE.
Method(s): We prospectively analyzed consecutive ED patients with acute drug overdose who were given SBT at two urban teaching hospitals from 2015-present. Data included SBT indication, dose, duration, and QTc (initial/peak from computer generated Bazett correction) during hospital stay. We used median values to dichotomize total dose (high/low) and total duration (long/short) of SBT. Patients were prospectively followed to hospital discharge for the occurrence of the primary outcome: ACVE and/or mortality. The previously validated definition of ACVE was used for in-hospital occurrence of any of these: ventricular dysrhythmia, myocardial infarction, shock requiring vasopressors, and cardiac arrest. Severe QTc prolongation was defined using the validated cutoff >=500ms. Ventricular dysrhythmias were adjudicated by a blinded cardiologist.
Result(s): Indications for SBT in 30 patients analyzed were: salicylism (5), sodium channel antagonist (6 TCA, 5 other), wide QRS in absence of known drug (9), acidosis or cardiac arrest (3), and unknown (2). After SBT, severe QTc prolongation occurred in 6 (20%), ACVE in 17 (57%), and 6 (20%) died. There was a significant association between severe QTc prolongation in-hospital for both high dose and long duration groups (p<0.05 for both). There was a significant correlation between both SBT dose (83% high, 38% low, p < .05) and SBT duration (100% long, 25% short, p < .05) with the primary outcome.
Conclusion(s): ED patients with acute drug overdose receiving SBT had very high rates of mortality and ACVE, which were strongly associated with higher dose and longer duration of SBT. Severity of overdose was a limitation to interpretation as a potential confounder. Overall, these results are consistent with the hypothesis that SBT prolongs the QTc and increases risk for ACVE, validating previous safety concerns regarding the administration of SBT for drug overdose

Background: Current guidelines for diabetes screening start at age 45, but disparities in certain subgroups exist and poor diabetic outcomes are known to cluster in specific neighborhoods. The objective of this study was to quantify disparities in the age distribution of patients with type 2 diabetes by sex, race/ethnicity, and geographic location. We also studied how patient age relates to diabetes-related hospital use and development of diabetic complications.
Method(s): Using all-payer hospital claims data, we performed a cross-sectional analysis of patients with type 2 diabetes. Our study included patients in New York City as identified by geocoded home address. Patients aged 10 to 100 years old were identified as having type 2 diabetes based on diagnosis codes from emergency claims data from 2011-2015. Our main measures included the estimated prevalence of type 2 diabetes at each year of life, the age distribution of patients as stratified by decade, and the comparison of patient age in geographic hotspots of frequent diabetes-related hospital use and diabetic complications.
Result(s): We identified 576,306 unique patients diagnosed with type 2 diabetes, which represented over half of all cases in New York City. Minority subgroups were on average 5.5 to 8.4 years younger than non-Hispanic White patients. Males with type 2 diabetes were 2.6 years younger than females. At 45 years of age, the estimated prevalence of type 2 diabetes was 10.9% among Black patients compared to 5.2% among White patients. In our geospatial analyses, patients with type 2 diabetes were on average 5.9 years younger in hotspots of diabetes-related emergency department use and inpatient hospitalizations. The average age of patients with type 2 diabetes was 1.5 to 2.2 years younger in hotspots of microvascular diabetic complications.
Conclusion(s): We identified profound disparities in the age of patients with type 2 diabetes among minorities and in neighborhoods with poor health outcomes. The younger age of these patients may be due to earlier onset of diabetes and/or earlier death from diabetes-related complications. Our findings demonstrate the need for geographically targeted interventions that promote earlier diagnosis and better glycemic control to reduce disparities in diabetes burden. [Figure Presented] Age Distribution of Patients with Type 2 Diabetes by Race and Ethnicity

Background: Discharge to skilled nursing facilities (SNF) is common in patients with heart failure (HF). The goal of a SNF stay is to improve functional status to allow patients to return home safely. However, the second transition from SNF to home may also be risky. Here, we examine the association between receipt of home health care (HHC) and readmission risk among patients discharged from SNF to home following HF hospitalization.
Method(s): We examined all Medicare fee-for-service beneficiaries 65 and older admitted 2012-2015 with a HF diagnosis discharged to SNF then subsequently discharged home. The primary outcome was unplanned read-mission within 30 days of SNF to home discharge, using CMS's HF read-mission methodology. We plotted time to readmission with Kaplan-Meier curves and compared these groups with a log-rank test. Then, we compared time to readmission using an adjusted Cox model; this model included a frailty term to account for correlation of patient outcome by SNF.
Result(s): There were 67,585 HF hospitalizations discharged to SNF and subsequently discharged home; 13,257 (19.6%) were discharged with HHC, 54,328 (80.4%) without. Patients discharged home from SNF with HHC had lower 30-day readmission rates than patients discharged without HHC (22.8% vs 24.5%, p< 0.0001). Kaplan-Meier curves demonstrated that patients discharged home from SNF with HHC have a longer unadjusted time to readmission. Of those readmitted within 30 days, median time to readmission for those discharged home from SNF with HHC was 11 days and 9 days for those discharged home without HHC (p< 0.0001). After risk-adjustment, patients discharged home with HHC still had a lower hazard of 30-day readmission.
Conclusion(s): Patients who received HHC were less likely to be readmitted within 30 days compared to those discharged home without HHC. This is unexpected as patients discharged with HHC likely have more functional impairments and therefore at higher readmission risk. Since patients requiring a SNF stay after hospital discharge may have additional needs, they may be especially likely to benefit from restorative therapy through HHC; however only about 20% received such services

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:Early readmissions among older adults hospitalized for acute myocardial infarction (AMI) are costly and difficult to predict. Aging-related functional impairments may inform risk prediction but are unavailable in most studies. Our objective was to, therefore, develop and validate an AMI readmission risk model for older patients who considered functional impairments and was suitable for use before hospital discharge. METHODS AND RESULTS/RESULTS:SILVER-AMI (Comprehensive Evaluation of Risk in Older Adults with AMI) is a prospective cohort study of 3006 patients of age ≥75 years hospitalized with AMI at 94 US hospitals. Participants underwent in-hospital assessment of functional impairments including cognition, vision, hearing, and mobility. Other variables plausibly associated with readmissions were also collected. The outcome was all-cause readmission at 30 days. We used backward selection and Bayesian model averaging to derive (N=2004) a risk model that was subsequently validated (N=1002). Mean age was 81.5 years, 44.4% were women, and 10.5% were nonwhite. Within 30 days, 547 participants (18.2%) were readmitted. Readmitted participants were older, had more comorbidities, and had a higher prevalence of functional impairments, including activities of daily living disability (17.0% versus 13.0%; P=0.013) and impaired functional mobility (72.5% versus 53.6%; P<0.001). The final risk model included 8 variables: functional mobility, ejection fraction, chronic obstructive pulmonary disease, arrhythmia, acute kidney injury, first diastolic blood pressure, P2Y12 inhibitor use, and general health status. Functional mobility was the only functional impairment variable retained but was the strongest predictor. The model was well calibrated (Hosmer-Lemeshow P value >0.05) with moderate discrimination (C statistics: 0.65 derivation cohort and 0.63 validation cohort). Functional mobility significantly improved performance of the risk model (net reclassification improvement index =20%; P<0.001). CONCLUSIONS:In our final risk model, functional mobility, previously not included in readmission risk models, was the strongest predictor of 30-day readmission among older adults after AMI. The modest discrimination indicates that much of the variability in readmission risk among this population remains unexplained by patient-level factors. CLINICAL TRIAL REGISTRATION/BACKGROUND:URL: https://www.clinicaltrials.gov. Unique identifier: NCT01755052.

Background: Social risk factors are increasingly understood as important drivers of care utilization, including emergency department (ED) visits. As a result, new social risk screening initiatives are being implemented to direct interventions and inform care. There is limited information on patient acceptability of social risk screening in the ED. The Center for Medicare and Medicaid Innovation (CMMI) proposed a social risk screening tool for their Accountable Health Communities Model that focuses on five actionable domains. In this study, we used the CMMI tool to explore the acceptability of social risk screening to adult patients and caregivers of pediatric patients in EDs.
Method(s): A tablet-based, self-administered survey was administered to a convenience sample of adult ED patients and caregivers of pediatric patients at two adult and two pediatric academic EDs. The survey included the CMMI tool and questions on acceptability of screening. The primary acceptability measure was appropriateness of screening in the ED; a secondary outcome was comfort with including social risk data in electronic health records (EHRs). Cross-sectional data were analyzed using chi-square analyses for bivariate comparison.
Result(s): The survey was completed by 364 participants. 41% of participants screened positive for housing instability, 41% for food insecurity, 19% for transportation insecurity, 13% utilities insecurity, and 1% for interpersonal violence. 23% of respondents endorsed no social risk factors. 73% of patients felt that it was "somewhat" or "very appropriate" to conduct social risk screening in the ED. No statistically significant difference was observed in acceptability of screening between participants who endorsed one or more social risks (74% reported "somewhat" or "very appropriate" to screen) versus none (75%). 70% reported feeling "somewhat" or "completely comfortable" with screening information being included in the EHR.
Conclusion(s): In EDs caring for patients with significant social adversity, there was high patient and caregiver acceptability of social risk screening, and a high level of comfort with screening information being included in EHRs. Further investigation is needed to understand perspectives of patients who did not find social risk screening acceptable

Background: Despite the health care sector's growing interest in systematic collection of social risk data, little is known about patient acceptability of health care-based social risk screening. Acceptability to patients and caregivers has implications for adoption, utility and sustainability. We aimed to explore acceptability of the Center for Medicare and Medicaid Innovation's (CMMI) social risk screening tool, which covers 5 actionable social domains: food, housing, utilities, and transportation security, and personal safety.
Method(s): Cross-sectional analysis of patients or caregivers of pedi-atric patients recruited from 6 primary care clinics (PCCs) and 4 emergency departments (EDs). Participants completed a tablet-based survey that included the CMMI social risk tool and questions related to both acceptability of social screening and predictors of acceptability. The primary acceptability measure was perceived appropriateness of screening in health care settings; a secondary outcome was comfort with including social risk data in electronic health records (EHRs). Multilevel mixed-effects logistic regressions were used to evaluate acceptability measures, clustering by site.
Result(s): 969 patients/caregivers completed the survey; 952 (98%) answered survey questions about acceptability. 72% of participants screened positive for at least 1 of 5 social risks. 80% of respondents reported screening was very or somewhat appropriate; 7% reported screening was very or somewhat inappropriate. 65% of participants reported being completely or somewhat comfortable with social risk data being included in EHRs; 18% reported being completely or somewhat uncomfortable. In the primary multivariable model, participants reporting higher acceptability of social risk screening had higher odds of previous social risk screening in a health care setting (aOR 1.80 [95% CI 1.31-2.47]); not endorsing prior discrimination in a health care setting (aOR 1.45 [95% CI 1.07-1.97]); being from a safety-net setting (aOR 1.85 [95% CI 1.11-3.10]); and being recruited in a PCC (aOR 2.10 [95% CI 1.01-4.32]). Participants who were more comfortable with including social risk data in EHRs had higher odds of previous social risk screening in a health care setting (aOR 1.56 [95% CI 1.17 to 2.09]). There were no associations between specific social risk domains or cumulative number of social risks with either measure of acceptability. No additional respondent-level characteristics were associated with acceptability.
Conclusion(s): Across PCC and ED settings, a majority of respondents found social risk screening acceptable. Acceptability levels did not differ across individual health care settings or level of social risks, though we identified some potentially modifiable factors associated with acceptability. High rates of acceptability support health care-based social screening implementation efforts, although future research should explore how to improve acceptability in specific patient populations and acceptability of EHR integration

Background: As research supporting potential benefits of social risk screening in health settings continues to emerge, there is little data on the patient perspective on social screening. The aim of this study is to describe the perspectives and preferences of patients and caregivers on being screened for social risks in diverse health care settings.
Method(s): As part of a larger mixed Methods multi-site study, we conducted semi-structured interviews lasting approximately 30 minutes with patients or caregivers who had completed the Center for Medicare and Medicaid Innovation (CMMI) social risk screening tool. After completion of the screening questions, 5 randomly selected respondents from each of 10 study sites were invited to participate in an interview. Interviews were conducted in English or Spanish. The interview guide asked about reactions to social risk screening and screening acceptability, preferences on screening administration, prior experiences that informed perspectives, and expectations for social assistance. Interviews were recorded, transcribed and translated. Two coders used basic thematic analysis and constant comparative Methods to identify codes, group codes into unified themes and map themes into domains of screening acceptability.
Result(s): Fifty adult patients or caregivers participated in semi-structured interviews across all study sites, which included 6 primary care clinics and 4 emergency departments. Respondents were 78% female, 36% Black, 32% Hispanic, 20% caregivers, and 71% reported having one or more social risk factor. There was broad consensus among interviewees across all clinical sites that social risk screening was acceptable. Several themes emerged: (1) respondents felt screening was the " right thing to do; " (2) respondents identified framing and compassionate approach as the most important aspects of administration; (3) respondents had insight into the connections between social risks and physical and mental health. Despite overall agreement that social risk screening is appropriate, respondents did not expect their health care team to address or resolve all of the identified issues. Interviewees felt referrals out to social services and resource sheets were adequate, and that there was benefit to the act of screening itself. Patients emphasized that screening should be done with empathy while protecting patient confidentiality.
Conclusion(s): Respondents agree that social risk screening is important, acceptable, and relevant to health. Respondents believed social risk screening would be most acceptable when implemented by a clinic staff member trained to ensure privacy and compassion. Despite published concerns about futility of social risk screening when social resources are inadequate, respondents expressed that they did not expect the health care system, and physicians in particular, to solve unmet social problems. Done appropriately, screening for social risk can build trust and strengthen relationships between patients and health care providers