Faculty Bibliography

INTRODUCTION/BACKGROUND:The impact of remote patient monitoring (RPM) for hypertension (HTN) on cardiovascular health (CVH) remains ill-defined. This study characterized the association between a RPM, team-based HTN intervention and CVH markers. METHODS:This retrospective, single-arm cohort study included patients with uncontrolled HTN enrolled February 2022-July 2024 in the ALTA trial (clinicaltrials.gov NCT03713515) at five safety-net practices. The ALTA intervention involves RPM supported by a virtual clinic including a nurse practitioner (NP), registered nurse, and community health worker. Demographics, ALTA utilization, and CVH markers (blood pressure [BP], lipids, glycemic indicators, body mass index [BMI], and smoking) at baseline and 12 months were collected. Five markers were scored (0=poor, 1=intermediate, 2=ideal) and summed into a CVH score. The primary endpoint was the 12-month CVH score change in patients with baseline score ≤7. Secondary endpoints included individual non-BP marker changes in patients with baseline derangements. RESULTS:Among 568 patients (mean age: 56 years), most were female, non-Hispanic Black, and English-speaking. NP visits were more common among females (p=0.04); no other demographics predicted ALTA utilization. The CVH score improved from 4.5 to 5.2 (n=196, p<0.001), independent of ALTA utilization. Total cholesterol (n=86, p<0.001), LDL (n=128, p<0.001), and triglycerides (n=51, p=0.004) improved. Hemoglobin A1c (n=195) dropped among patients with ≥1 NP visit (p=0.02). Fasting glucose (n=135) and BMI (n=289) decreased in the highest tertile of NP visits (p=0.03) and RPM (p=0.02), respectively. 4 of 27 patients quit smoking. CONCLUSIONS:RPM with team-based support was associated with CVH improvements. Benefits may depend on intervention utilization.

The underlying drivers and outcomes of social determinants of health are dynamically complex, making it difficult to design effective responses. This complexity has inspired a growing number of calls to move beyond mechanistic thinking and use systems science to engage directly with complexity and highlight opportunities for methodological innovation to enhance translation of insight into real world action. This case study describes a methodological innovation combining community-based system dynamics and design thinking to understand multi-level complexity of a public health challenge: optimizing the design of a community-clinical linkage in Brooklyn, New York. In-depth description of the case illustrates methods integration and resulting insights and recommendations. Results from the case demonstrate that integrating methods generates insight at multiple levels, including connecting holistic system understanding to individual experiences of system structure and operationalizing and translating insights into action. Combining community-based system dynamics and design thinking holds value for intervention planning, strategic implementation, and sustaining change.

OBJECTIVE/UNASSIGNED:To examine the transition to telemental health within the behavioral health program of a large federally qualified health center, The Family Health Centers at NYU Langone, in the 3 months following the onset of the COVID-19 pandemic-specifically impacts on show rates and access to care. METHODS/UNASSIGNED:Demographic and clinical information for all scheduled visits was collected for two time periods: the telemental health period, March 16, 2020-July 16, 2020 (46,878 visits, 5,183 patients), and a comparison period, March 15, 2019-July 16, 2019 (47,335 visits, 5,190 patients). Data collected included modality, appointments scheduled/completed/cancelled/no-showed, age, gender, race, language, and diagnosis. Generalized estimating equations with a compound symmetry correlation structure and logit link were used for analysis. RESULTS/UNASSIGNED:= 0.01), which was eliminated by implementation of telemental health. CONCLUSIONS/UNASSIGNED:This study supports the use telemental health to increase access for all patients, including those from under-represented, lower socioeconomic status backgrounds.

PURPOSE/UNASSIGNED:We aimed to determine whether implementation of clinical decision support (CDS) tool integrated into the electronic health record of a multisite academic medical center increased the proportion of patients with AUA "high-risk" microscopic hematuria (MH) who receive guideline concordant evaluations. MATERIALS AND METHODS/UNASSIGNED:We conducted a two-arm cluster randomized quality improvement project in which 202 ambulatory sites from a large health system were randomized to either have their physicians receive at time of test results an automated CDS alert for patients with "high-risk" MH with associated recommendations for imaging and cystoscopy (intervention) or usual care (control). Primary outcome was met if a patient underwent both imaging and cystoscopy within 180 days from MH result. Secondary outcomes assessed individual completion of imaging, cystoscopy, or placement of imaging orders. RESULTS/UNASSIGNED:= .09). CONCLUSIONS/UNASSIGNED:Implementing an electronic health record-integrated CDS tool to promote evaluation of patients with high-risk MH did not lead to improvements in patient completion of a full guideline-concordant evaluation. The development of an algorithm to trigger a CDS alert was demonstrated to be feasible and effective. Further multilevel assessment of barriers to evaluation is necessary to continue to improve the approach to evaluating high-risk patients with MH.

BACKGROUND:Despite decades of evidence demonstrating the efficacy of hypertension care delivery in reducing morbidity and mortality, a majority of hypertension cases remain uncontrolled. There is an urgent need to elucidate and address multilevel facilitators and barriers clinical staff face in delivering evidence-based hypertension care, patients face in accessing it, and clinical systems face in sustaining it. Through a rigorous pre-implementation evaluation, we aimed to identify facilitators and barriers bearing the potential to affect the planned implementation of a multilevel technology-facilitated hypertension management trial across six primary care sites in a large federally qualified health center (FQHC) in New York City. METHODS:During a dedicated pre-implementation period (3-9 months/site, 2021-2022), a capacity assessment was conducted by trained practice facilitators, including (1) online anonymous surveys (n = 124; 70.5% of eligible), (2) hypertension training analytics (n = 69; 94.5% of assigned), and (3) audio-recorded semi-structured interviews (n = 67; 48.6% of eligible) with FQHC leadership and staff. Surveys measured staff sociodemographic characteristics, adaptive reserve, evidence-based practice attitudes, and implementation leadership scores via validated scales. Training analytics, derived from end-of-course quizzes, included mean score and number attempts needed to pass. Interviews assessed staff-reported facilitators and barriers to current hypertension care delivery and uptake; following audio transcription, trained qualitative researchers employed a deductive coding approach, informed by the Consolidated Framework for Implementation Research (CFIR). RESULTS:Most survey respondents reported moderate adaptive reserve (mean = 0.7, range = 0-1), evidence-based practice attitudes (mean = 2.7, range = 0-4), and implementation leadership (mean = 2.5, range = 0-4). Most staff passed training courses on first attempt and demonstrated high scores (means > 80%). Findings from interviews identified potential facilitators and barriers to implementation; specifically, staff reported that complex barriers to hypertension care, control, and clinical communication exist; there is a recognized need to improve hypertension care; in-clinic challenges with digital tool access imposes workflow delays; and despite high patient loads, staff are motivated to provide high-quality cares. CONCLUSIONS:This study serves as one of the first to apply the CFIR to a rigorous pre-implementation evaluation within the understudied context of a FQHC and can serve as a model for similar trials seeking to identify and address contextual factors known to impact implementation success. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT03713515 , date of registration: October 19, 2018.

BACKGROUND:Early initiation of prenatal care is widely accepted to improve the health outcomes of pregnancy for both mothers and their infants. Identification of the various barriers to entry into care that patients experience may inform and improve health care provision and, in turn, improve the patient's ability to receive necessary care. AIM/OBJECTIVE:This study implements a mixed-methods approach to establish methods and procedures for identifying barriers to early entry to prenatal care in a medically-vulnerable patient population and areas for future quality improvement initiatives. METHODS:An initial chart review was conducted on obstetrics patients that initiated prenatal care after their first trimester at a large federally qualified health center in Brooklyn, NY, to determine patient-specified reasons for delay. A thematic analysis of these data was implemented in combination with both parametric and non-parametric analyses to characterize the population of interest, and to identify the primary determinants of delayed entry. RESULTS:The age of patients in the population of interest (n = 169) was bimodal, with a range of 15 - 43 years and a mean of 28 years. The mean gestational age of entry into prenatal care was 19 weeks. The chart review revealed that 8% recently moved to Brooklyn from outside of NYC or the USA. Nine percent had difficulty scheduling an initial prenatal visit within their first trimester. Teenage pregnancy accounted for 7%. Provider challenges with documentation (21%) were noted. The most common themes identified (n = 155) were the patient being in transition (21%), the pregnancy being unplanned (17%), and issues with linkage to care (15%), including no shows or patient cancellations. Patients who were late to prenatal care also differed from their peers dramatically, as they were more likely to be Spanish-speaking, to be young, and to experience a relatively long delay between pregnancy confirmation and entry into care. Moreover, the greatest determinant of delayed entry into care was patient age. CONCLUSION/CONCLUSIONS:Our study provides a process for other like clinics to identify patients who are at risk for delayed entry to prenatal care and highlight common barriers to entry. Future initiatives include the introduction of a smart data element to document reasons for delay and use of community health workers for dedicated outreach after no show appointments or patient cancellations.

The Family Health Centers at New York University Langone (FHC), a federally qualified health center network in New York City, created a novel clinical decision support (CDS) tool that alerts primary health care providers to patients"™ gaps in care and triggers a dynamic, individualized order set on the basis of unique patient factors, enabling providers to readily act on each patient"™s specific gaps in care. FHC implemented this tool in 2017, starting with 15 protocols for quality measures; as of February 2024, there are 30 such protocols. During a patient visit with a provider, when there is a gap in care, a best-practice alert (BPA) fires, which includes an order set unique to the patient and visit. The provider can bypass the alert (not open it) or acknowledge the alert (open it). The provider may review the content of the order set and accept it as is or with modifications, or they can decline its recommendations if they believe it is not appropriate or plan to address the gap in care another way during the visit. To accept the dynamic order set is the intended workflow. The authors present data from September 2019 to January 2023 totaling 171,319 patient visits with at least one open gap in care among providers in pediatrics, family medicine, and internal medicine. The rate at which providers acknowledged the BPA in the first 6 months was 45% and steadily increased. In the last 6 months of the period, providers acknowledged the BPA 78% (19,281 of 24,575) of the time. Similarly, in the first 6 months, in all encounters in which a BPA was fired, 28.8% (8,585 of 29,829) had an order placed via the dynamic order set (accepted); that rate increased to 49.7% (12,210 of 24,575) during the last 6 months. This order set completion rate is notable given that most CDS use rates are low. Gap closure was higher when providers acknowledged the alert. In an analysis of all encounters with at least one open gap, spanning 2019"“2023, 46% (48,431 of 105,371) of the time, at least one gap was closed when the alert was acknowledged compared with 33% (21,993 of 65,948) when the alert was bypassed (and the recommendations of the dynamic order set were never followed). The authors show that CDS tools can be successfully implemented in a high-volume, low-resource setting if designed with efficiency in mind, ensuring provider utilization and clinical impact through closing care gaps. CDS tools that are dynamically patient specific can help improve quality of care if they are part of a broader culture of quality improvement.