Faculty Bibliography

BACKGROUND:Digital diabetes prevention programs (dDPPs) are effective behavior change tools to prevent disease progression in patients at risk for diabetes. At present, these programs are poorly integrated into existing health information technology infrastructure and clinical workflows, resulting in barriers to provider-level knowledge of, interaction with, and support of patients who use dDPPs. Tools that can facilitate patient-provider interaction around dDPPs may contribute to improved patient engagement and adherence to these programs and improved health outcomes. OBJECTIVE:This study aims to use a rigorous, user-centered design (UCD) methodology to develop a theory-driven system that supports patient engagement with dDPPs and their primary care providers with their care. METHODS:at 6 and 12 months. Secondary outcomes will be patient engagement (use and activity) in the dDPP. The mediator variables (self-efficacy, digital health literacy, and patient-provider relationship) will be measured. RESULTS:The project was initiated in 2018 and funded in September 2019. Enrollment and data collection for phase 1 began in September 2019 under an Institutional Review Board quality improvement waiver granted in July 2019. As of December 2020, 27 patients have been enrolled and first results are expected to be submitted for publication in early 2021. The study received Institutional Review Board approval for phases 2 and 3 in December 2020, and phase 2 enrollment is expected to begin in early 2021. CONCLUSIONS:Our findings will provide guidance for the design and development of technology to integrate dDPP platforms into existing clinical workflows. This will facilitate patient engagement in digital behavior change interventions and provider engagement in patients' use of dDPPs. Integrated clinical tools that can facilitate patient-provider interaction around dDPPs may contribute to improved patient adherence to these programs and improved health outcomes by addressing barriers faced by both patients and providers. Further evaluation with pilot testing and a clinical trial will assess the effectiveness and implementation of these tools. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT04049500; https://clinicaltrials.gov/ct2/show/NCT04049500. INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)/UNASSIGNED:DERR1-10.2196/26750.

BACKGROUND:The transformation of health care during COVID-19, with the rapid expansion of telemedicine visits, presents new challenges to chronic care and preventive health providers. Clinical decision support (CDS) is critically important to chronic care providers, and CDS malfunction is common during times of change. It is essential to regularly reassess an organization's ambulatory CDS program to maintain care quality. This is especially true after an immense change, like the COVID-19 telemedicine expansion. OBJECTIVE:Our objective is to reassess the ambulatory CDS program at a large academic medical center in light of telemedicine's expansion in response to the COVID-19 pandemic. METHODS:Our clinical informatics team devised a practical framework for an intrapandemic ambulatory CDS assessment focused on the impact of the telemedicine expansion. This assessment began with a quantitative analysis comparing CDS alert performance in the context of in-person and telemedicine visits. Board-certified physician informaticists then completed a formal workflow review of alerts with inferior performance in telemedicine visits. Informaticists then reported on themes and optimization opportunities through the existing CDS governance structure. RESULTS:Our assessment revealed that 10 of our top 40 alerts by volume were not firing as expected in telemedicine visits. In 3 of the top 5 alerts, providers were significantly less likely to take action in telemedicine when compared to office visits. Cumulatively, alerts in telemedicine encounters had an action taken rate of 5.3% (3257/64,938) compared to 8.3% (19,427/233,636) for office visits. Observations from a clinical informaticist workflow review included the following: (1) Telemedicine visits have different workflows than office visits. Some alerts developed for the office were not appearing at the optimal time in the telemedicine workflow. (2) Missing clinical data is a common reason for the decreased alert firing seen in telemedicine visits. (3) Remote patient monitoring and patient-reported clinical data entered through the portal could replace data collection usually completed in the office by a medical assistant or registered nurse. CONCLUSIONS:In a large academic medical center at the pandemic epicenter, an intrapandemic ambulatory CDS assessment revealed clinically significant CDS malfunctions that highlight the importance of reassessing ambulatory CDS performance after the telemedicine expansion.

OBJECTIVE:Through the coronavirus disease 2019 (COVID-19) pandemic, telemedicine became a necessary entry point into the process of diagnosis, triage and treatment. Racial and ethnic disparities in health care have been well documented in COVID-19 with respect to risk of infection and in-hospital outcomes once admitted, and here we assess disparities in those who access healthcare via telemedicine for COVID-19 . MATERIALS AND METHODS/METHODS:Electronic health record data of patients at New York University Langone Health between March 19th and April 30, 2020 were used to conduct descriptive and multilevel regression analyses with respect to visit type (telemedicine or in-person), suspected COVID diagnosis and COVID test results. RESULTS:Controlling for individual and community-level attributes, Black patients had 0.6 times the adjusted odds (95%CI:0.58-0.63) of accessing care through telemedicine compared to white patients, though they are increasingly accessing telemedicine for urgent care, driven by a younger and female population. COVID diagnoses were significantly more likely for Black versus white telemedicine patients. DISCUSSION/CONCLUSIONS:There are disparities for Black patients accessing telemedicine, however increased uptake by young, female Black patients. Mean income and decreased mean household size of Zip code were also significantly related to telemedicine use. CONCLUSION/CONCLUSIONS:Telemedicine access disparities reflect those in in-person healthcare access. Roots of disparate use are complex and reflect individual, community, and structural factors, including their intersection; many of which are due to systemic racism. Evidence regarding disparities that manifest through telemedicine can be used to inform tool design and systemic efforts to promote digital health equity.

STATEMENT OF PROBLEM OR QUESTION (ONE SENTENCE): In the transition away from traditional doctors' offices, how can we optimize shared multi-use clinical spaces to serve clinicians' needs LEARNING OBJECTIVES 1: Identify ways in which a practice that relies upon shared clinical spaces can remain familiar and effective for clinical work. LEARNING OBJECTIVES 2: Determine how might technology help clinicians develop a sense of belonging, professional pride, and patient rapport in multi-use spaces by allowing them to display personal information and patient education materials related to their practice. DESCRIPTION OF PROGRAM/INTERVENTION, INCLUDING ORGANIZATIONAL CONTEXT (E.G. INPATIENT VS. OUTPATIENT, PRACTICE OR COMMUNITY CHARACTERISTICS): The traditional doctor's office is being rapidly replaced by multi-use clinical environments that combine exam rooms with shared touchdown spaces, promoting efficient use of space & team-based care approach while utilizing network technologies. While potentially efficient & lower-cost, there's a need to assess the impact of these configurations on clinician workflows, professional identity & explore opportunities to improve their build and aesthetics. We conducted need assessment interviews with 9 clinicians, health technologists, 2 operational leaders, shadowed 3 clinicians & conducted 4 site visits across various clinical practices. We then issued a 10-question survey and conducted 2 HCD workshops with 12 clinicians to understand the new conditions of clinical work, their impact on clinicians' professional & personal identity, practice habits, to identify areas for potential optimization to improve clinical workflow & experience. Workshops were divided in three phases: explore, ideate and create. MEASURES OF SUCCESS (DISCUSS QUALITATIVE AND/OR QUANTITATIVEMETRICSWHICHWILL BE USEDTOEVALUATE PROGRAM/INTERVENTION): We report qualitative success metrics used to evaluate the results of the HCD workshops: 1. Understanding of what shared multi-use work spaces mean to participating clinicians. 2. Identified needs, potential concerns and pain points of clinicians and stakeholders. 3. Group generation of potential solutions without bias towards feasibility. 4. Described solutions using quick prototyping tools. FINDINGS TO DATE (IT IS NOT SUFFICIENT TO STATE FINDINGS WILL BE DISCUSSED): Clinicians identified the lack of customization and capability for sharing information about their areas of expertise and tailored patient education materials as the most significant problem, and had privacy concerns about sharing personal information on a digital display. Potential solutions include customizable content display controlled by patients that fosters engagement, exploring education materials, patient testimonials, information about the care team and wait time as well as patient-specific information, such as labs and imaging. KEY LESSONS FOR DISSEMINATION (WHAT CAN OTHERS TAKE AWAY FOR IMPLEMENTATION TO THEIR PRACTICE OR COMMUNITY): The use of the HCD principles helped us better understand the challenges of multi-use spaces for clinicians, and identify potential technology solutions for data sharing, patient education, personalization, and efficiencies. It is crucial to design these spaces and choose appropriate technology solutions that will help reduce patients' anxiety by ensuring privacy, comfort, thorough understanding of care plans and boost collaborative care decision making between clinicians and patients

BACKGROUND:Intensive glycemic control is of unclear benefit and carries increased risk for older adults with diabetes. The American Geriatrics Society's (AGS) Choosing Wisely (CW) guideline promotes less aggressive glycemic targets and reduction in pharmacologic therapy for older adults with type II diabetes. Meanwhile, behavioral economic (BE) approaches offer promise in influencing hard-to-change behavior, and previous studies have shown the benefits of using electronic health record (EHR) technology to encourage guideline adherence. OBJECTIVE:This study aimed to develop and pilot test an intervention that leverages BE with EHR technology to promote appropriate diabetes management in older adults. DESIGN/METHODS:A pilot study within the New York University Langone Health (NYULH) EHR and Epic system to deliver BE-inspired nudges at five NYULH clinics at varying time points from July 12, 2018, through October 31, 2019. PARTICIPANTS/METHODS:Clinicians across five practices in the NYULH system whose patients were older adults (age 76 and older) with type II diabetes. INTERVENTIONS/METHODS:A BE-EHR module comprising six nudges was developed through a series of design workshops, interviews, user-testing sessions, and clinic visits. BE principles utilized in the nudges include framing, social norming, accountable justification, defaults, affirmation, and gamification. MAIN MEASURES/METHODS:Patient-level CW compliance. KEY RESULTS/RESULTS:CW compliance increased 5.1% from a 16-week interval at baseline to a 16-week interval post intervention. From February 14 to June 5, 2018 (prior to the first nudge launch in Vanguard clinics), CW compliance for 1278 patients was mean (95% CI)-16.1% (14.1%, 18.1%). From July 3 to October 22, 2019 (after BE-EHR module launch at all five clinics), CW compliance for 680 patients was 21.2% (18.1%, 24.3%). CONCLUSIONS:The BE-EHR module shows promise for promoting the AGS CW guideline and improving diabetes management in older adults. A randomized controlled trial will commence to test the effectiveness of the intervention across 66 NYULH clinics. NIH TRIAL REGISTRY NUMBER/UNASSIGNED:NCT03409523.

BACKGROUND:Clinical decision support (CDS) is a promising tool for reducing antibiotic prescribing for acute respiratory infections (ARIs). OBJECTIVE:To assess the impact of previously effective CDS on antibiotic-prescribing rates for ARIs when adapted and implemented in diverse primary care settings. DESIGN/METHODS:Cluster randomized clinical trial (RCT) implementing a CDS tool designed to guide evidence-based evaluation and treatment of streptococcal pharyngitis and pneumonia. SETTING/METHODS:Two large academic health system primary care networks with a mix of providers. PARTICIPANTS/METHODS:All primary care practices within each health system were invited. All providers within participating clinic were considered a participant. Practices were randomized selection to a control or intervention group. INTERVENTIONS/METHODS:Intervention practice providers had access to an integrated clinical prediction rule (iCPR) system designed to determine the risk of bacterial infection from reason for visit of sore throat, cough, or upper respiratory infection and guide evidence-based evaluation and treatment. MAIN OUTCOME(S)/UNASSIGNED:Change in overall antibiotic prescription rates. MEASURE(S)/UNASSIGNED:Frequency, rates, and type of antibiotics prescribed in intervention and controls groups. RESULTS:33 primary care practices participated with 541 providers and 100,573 patient visits. Intervention providers completed the tool in 6.9% of eligible visits. Antibiotics were prescribed in 35% and 36% of intervention and control visits, respectively, showing no statistically significant difference. There were also no differences in rates of orders for rapid streptococcal tests (RR, 0.94; P = 0.11) or chest X-rays (RR, 1.01; P = 0.999) between groups. CONCLUSIONS:The iCPR tool was not effective in reducing antibiotic prescription rates for upper respiratory infections in diverse primary care settings. This has implications for the generalizability of CDS tools as they are adapted to heterogeneous clinical contexts. TRIAL REGISTRATION/BACKGROUND:Clinicaltrials.gov (NCT02534987). Registered August 26, 2015 at https://clinicaltrials.gov.

Applications in a range of domains, including route planning and well-being, offer advice based on the social information available in prior users' aggregated activity. When designing these applications, is it better to offer: a) advice that if strictly adhered to is more likely to result in an individual successfully achieving their goal, even if fewer users will choose to adopt it? or b) advice that is likely to be adopted by a larger number of users, but which is sub-optimal with regard to any particular individual achieving their goal? We identify this dilemma, characterized as Goal-Directed vs. Adoption-Directed advice, and investigate the design questions it raises through an online experiment undertaken in four advice domains (financial investment, making healthier lifestyle choices, route planning, training for a 5k run), with three user types, and across two levels of uncertainty. We report findings that suggest a preference for advice favoring individual goal attainment over higher user adoption rates, albeit with significant variation across advice domains; and discuss their design implications.

BACKGROUND:Patient-reported outcomes (PROs) are increasingly being used in the management of type 2 diabetes (T2D) to integrate data from patients' perspective into clinical care. To date, the majority of PRO tools have lacked patient and provider involvement in their development, thus failing to meet the unique needs of end users, and lack the technical infrastructure to be integrated into the clinic workflow. OBJECTIVE:This study aims to apply a systematic, user-centered design approach to develop i-Matter (investigating a mobile health [mHealth] texting tool for embedding patient-reported data into diabetes management), a theory-driven, mobile PRO system for patients with T2D and their primary care providers. METHODS:i-Matter combines text messaging with dynamic data visualizations that can be integrated into electronic health records (EHRs) and personalized patient reports. To build i-Matter, we conducted semistructured group and individual interviews with patients with T2D and providers, a design thinking workshop to refine initial ideas and design the prototype, and user testing sessions of prototypes using a rapid-cycle design (ie, design-test-modify-retest). RESULTS:Using an iterative user-centered process resulted in the identification of 6 PRO messages that were relevant to patients and providers: medication adherence, dietary behaviors, physical activity, sleep quality, quality of life, and healthy living goals. In user testing, patients recommended improvements to the wording and timing of the PRO text messages to increase clarity and response rates. Patients also recommended including motivational text messages to help sustain engagement with the program. The personalized report was regarded as a key tool for diabetes self-management by patients and providers because it aided in the identification of longitudinal patterns in the PRO data, which increased patient awareness of their need to adopt healthier behaviors. Patients recommended adding individualized tips to the journal on how they can improve their behaviors. Providers preferred having a separate tab built into the EHR that included the personalized report and highlighted key trends in patients' PRO data over the past 3 months. CONCLUSIONS:PRO tools that capture patients' well-being and the behavioral aspects of T2D management are important to patients and providers. A clinical trial will test the efficacy of i-Matter in 282 patients with uncontrolled T2D. TRIAL REGISTRATION/BACKGROUND:ClinicalTrials.gov NCT03652389; https://clinicaltrials.gov/ct2/show/NCT03652389.

This study provides data on the feasibility and impact of video-enabled telemedicine use among patients and providers and its impact on urgent and non-urgent health care delivery from one large health system (NYU Langone Health) at the epicenter of the COVID-19 outbreak in the United States. Between March 2nd and April 14th 2020, telemedicine visits increased from 369.1 daily to 866.8 daily (135% increase) in urgent care after the system-wide expansion of virtual health visits in response to COVID-19, and from 94.7 daily to 4209.3 (4345% increase) in non-urgent care post expansion. Of all virtual visits post expansion, 56.2% and 17.6% urgent and non-urgent visits, respectively, were COVID-19-related. Telemedicine usage was highest by patients aged 20-44, particularly for urgent care. The COVID-19 pandemic has driven rapid expansion of telemedicine use for urgent care and non-urgent care visits beyond baseline periods. This reflects an important change in telemedicine that other institutions facing the COVID-19 pandemic should anticipate.