Associated Professor of Public Service, NYU Wagner; Professor of Medicine and Population Health, NYU Langone School of Medicine
Marc N. Gourevitch, MD., MPH, is Professor and founding Chair of the Department of Population Health at the NYU School of Medicine. The focus of Dr. Gourevitch's work is on developing approaches that leverage both healthcare delivery and policy- and community-level -level interventions to advance the health of populations. Dr. Gourevitch is co-Director of the Community Engagement and Population Health Research Core of the Clinical and Translational Science Institute that bridges NYU and the NYC Health and Hospitals Corporation, and leads NYU's participation in the NYC Clinical Data Research Network funded by PCORI. His research interests center on health service utilization and clinical epidemiology among drug users and other underserved populations; integrating pharmacologic treatments for opioid and alcohol dependence into primary care; and strategies for bridging academic research with applied challenges faced by health care delivery systems and public sector initiatives. From 2004-2012, Dr. Gourevitch served as Director of NYU’s Division of General Internal Medicine. Dr. Gourevitch holds joint appointments in the Departments of Medicine and of Psychiatry as well as at NYU’s Robert F. Wagner Graduate School of Public Service. A graduate of Harvard College and Harvard Medical School, he trained in primary care/internal medicine at NYU and Bellevue and received his Master’s of Public Health with a concentration in epidemiology from the Mailman School of Public Health.
Limited investigations have been conducted on syndemics and HIV continuum of care outcomes. Using baseline data from a multi-site, randomized controlled study of HIV-positive injection drug users (n = 1,052), we examined whether psychosocial factors co-occurred, and whether these factors were additively associated with behavioral and HIV continuum of care outcomes. Experiencing one type of psychosocial problem was significantly (p < 0.05) associated with an increased odds of experiencing another type of problem. Persons with 3 or more psychosocial problems were significantly more likely to report sexual and injection risk behaviors and were less likely to be adherent to HIV medications. Persons with 4 or more problems were less likely to be virally suppressed. Reporting any problems was associated with not currently taking HIV medications. Our findings highlight the association of syndemics not only with risk behaviors, but also with outcomes related to the continuum of care for HIV-positive persons.
Objective: The purpose of this study was to evaluate the association of physician continuity of care with length of stay, likelihood of weekend discharge, in-hospital mortality and 30-day readmission.
Design: A cohort study of hospitalized medical patients. The primary exposure was the weekend usual provider continuity (UPC) over the initial weekend of care. This metric was adapted from an outpatient continuity of care index. Regression models were developed to determine the association between UPC and outcomes.
Setting: An academic medical center.
Main: outcome measure Length of stay which was calculated as the number of days from the first Saturday of the hospitalization to the day of discharge.
Results: Of the 3391 patients included in this study, the prevalence of low, moderate and high UPC for the initial weekend of hospitalization was 58.7, 22.3 and 19.1%, respectively. When compared with low continuity of care, both moderate and high continuity of care were associated with reduced length of stay, with adjusted rate ratios of 0.92 (95% CI 0.86–1.00) and 0.64 (95% CI 0.53–0.76), respectively. High continuity of care was associated with likelihood of weekend discharge (adjusted odds ratio 2.84, 95% CI 2.11–3.83) but was not significantly associated with mortality (adjusted odds ratio 0.72, 95% CI 0.29–1.80) or readmission (adjusted odds ratio 0.88, 95% CI 0.68–1.14) when compared with low continuity of care.
Conclusions: Increased weekend continuity of care is associated with reduced length of stay. Improvement in weekend cross-coverage and patient handoffs may be useful to improve clinical outcomes.
The time required to conduct drug and alcohol screening has been a major barrier to its implementation in mainstream healthcare settings. Because patient self-administered tools are potentially more efficient, we translated the Alcohol, Smoking and Substance Involvement Screening Test (ASSIST) into an audio guided computer assisted self interview (ACASI) format. This study reports on the test–retest reliability of the ACASI ASSIST in an adult primary care population. Adult primary care patients completed the ACASI ASSIST, in English or Spanish, twice within a 1–4 week period. Among the 101 participants, there were no significant differences between test administrations in detecting moderate to high risk use for tobacco, alcohol, or any other drug class. Substance risk scores from the two administrations had excellent concordance (90–98%) and high correlation (ICC 0.90–0.97) for tobacco, alcohol, and drugs. The ACASI ASSIST has good test–retest reliability, and warrants additional study to evaluate its validity for detecting unhealthy substance use.
The New York City Clinical Data Research Network (NYC-CDRN), funded by the Patient-Centered Outcomes Research Institute (PCORI), brings together 22 organizations including seven independent health systems to enable patient-centered clinical research, support a national network, and facilitate learning healthcare systems. The NYC-CDRN includes a robust, collaborative governance and organizational infrastructure, which takes advantage of its participants' experience, expertise, and history of collaboration. The technical design will employ an information model to document and manage the collection and transformation of clinical data, local institutional staging areas to transform and validate data, a centralized data processing facility to aggregate and share data, and use of common standards and tools. We strive to ensure that our project is patient-centered; nurtures collaboration among all stakeholders; develops scalable solutions facilitating growth and connections; chooses simple, elegant solutions wherever possible; and explores ways to streamline the administrative and regulatory approval process across sites.
Optimizing the health of populations, whether defined as persons receiving care from a health care delivery system or more broadly as persons in a region, is emerging as a core focus in the era of health care reform. To achieve this goal requires an approach in which preventive care is valued and “nonmedical” determinants of patients’ health are engaged. For large, multimission systems such as academic medical centers, navigating the evolution to a population-oriented paradigm across the domains of patient care, education, and research poses real challenges but also offers tremendous opportunities, as important objectives across each mission begin to align with external trends and incentives. In clinical care, opportunities exist to improve capacity for assuming risk, optimize community benefit, and make innovative use of advances in health information technology. Education must equip the next generation of leaders to understand and address population-level goals in addition to patient-level needs. And the prospects for research to define strategies for measuring and optimizing the health of populations have never been stronger. A remarkable convergence of trends has created compelling opportunities for academic medical centers to advance their core goals by endorsing and committing to advancing the health of populations.
Background: With rising rates of prescription drug abuse and associated overdose deaths, there is great interest in having accurate and efficient screening tools that identify nonmedical use of prescription drugs in health care settings. The authors sought to gain a better understanding of how patients interpret questions about misuse of prescription drugs, with the goal of improving the accuracy and acceptability of instruments intended for use in primary care.
Methods: A total of 27 English-speaking adult patients were recruited from an urban safety net primary care clinic to complete a cognitive interview about a 4-item screening questionnaire for tobacco, alcohol, illicit drugs, and misuse of prescription drugs. Detailed field notes were analyzed for overall comprehension of the screening items on illicit drug use and prescription drug misuse, the accuracy with which participants classified drugs into these categories, and whether the screening response correctly captured the participant's substance use behavior.
Results: Based on initial responses to the screening items, 6 (22%) participants screened positive for past-year prescription drug misuse, and 8 (30%) for illicit drug use. The majority (26/27) of participants correctly interpreted the item on illicit drug use, and appropriately classified drugs in this category. Eleven (41%) participants had errors in their understanding of the prescription drug misuse item. The most common error was classifying use of medications without abuse potential as nonmedical use. All cases of misunderstanding the prescription drug misuse item occurred among participants who screened negative for illicit drug use.
Conclusions: The results suggest that terminology used to describe misuse of prescription medications may be misunderstood by many primary care patients, particularly those who do not use illicit drugs. Failure to improve upon the language used to describe prescription drug misuse in screening questionnaires intended for use in medical settings could potentially lead to high rates of false-positive results.
Objective: Previous studies have suggested that weekend hospital care is inferior to weekday care and that this difference may be related to diminished care intensity. The purpose of this study was to determine whether a metric for measuring intensity of hospital care based on use of the electronic health record was associated with patient-level outcomes.
Methods: We performed a cohort study of hospitalizations at an academic medical center. Intensity of care was defined as the hourly number of provider accessions of the electronic health record, termed “electronic health record interactions.” Hospitalizations were categorized on the basis of the mean difference in electronic health record interactions between the first Friday and the first Saturday of hospitalization. We used regression models to determine the association of these categories with patient outcomes after adjusting for covariates.
Results: Electronic health record interactions decreased from Friday to Saturday in 77% of the 9051 hospitalizations included in the study. Compared with hospitalizations with no change in Friday to Saturday electronic health record interactions, the relative lengths of stay for hospitalizations with a small, moderate, and large decrease in electronic health record interactions were 1.05 (95% confidence interval [CI], 1.00-1.10), 1.11 (95% CI, 1.05-1.17), and 1.25 (95% CI, 1.15-1.35), respectively. Although a large decrease in electronic health record interactions was associated with in-hospital mortality, these findings were not significant after risk adjustment (odds ratio 1.74, 95% CI, 0.93-3.25).
Conclusions: Intensity of inpatient care, measured by electronic health record interactions, significantly diminished from Friday to Saturday, and this decrease was associated with length of stay. Hospitals should consider monitoring and correcting temporal fluctuations in care intensity.
Background: The New York University– New York City Health and Hospitals Corporation (NYU-HHC) Clinical and Translational Science Institute (CTSI) used a community-based participatory research (CBPR) and consensus-building approach among its community advisory board (CAB) and steering committee (SC) members to formulate research priorities to foster shared research collaborations.
Methods: The Delphi technique is a methodology used to generate consensus from diverse perspectives and organizational agendas through a multi-method, iterative approach to collecting data. A series of on-line surveys was conducted with CAB members to identify health and research priorities from the community perspective. Subsequently, CAB and SC members were brought together and the snow card approach was utilized to narrow to two priority areas for shared research collaborations.
Results: Cardiovascular disease (CVD)/obesity and mental health were identified as health disparity areas for shared research collaborations within a social determinants framework. In response, two workgroups were formed with leadership provided by three co-chairs representing the three constituents of the NYU-HHC CTSI: NYU faculty, HHC providers, and community leaders.
Conclusions: The Delphi approach fostered ownership and engagement with community partners because it was an iterative process that required stakeholders’ input into decision making. The snow card technique allowed for organizing of a large number of discrete ideas. Results have helped to inform the overall CTSI research agenda by defining action steps, and setting an organizing framework to tackle two health disparity areas. The process helped ensure that NYUHHC CTSI research and community engagement strategies are congruent with community priorities.
Background: Hospital care on weekends has been associated with reduced quality and poor clinical outcomes, suggesting that decreases in overall intensity of care may have important clinical effects. We describe a new measure of hospital intensity of care based on utilization of the electronic health record (EHR).
Methods: We measured global intensity of care at our academic medical center by monitoring the use of the EHR in 2011. Our primary measure, termed EHR interactions, was the number of accessions of a patient's electronic record by a clinician, adjusted for hospital census, per unit of time. Our secondary measure was percent of total available central processing unit (CPU) power used to access EHR servers at a given time.
Results: EHR interactions were lower on weekend days as compared to weekdays at every hour (P < 0.0001), and the daytime peak in intensity noted each weekday was blunted on weekends. The relative rate and 95% confidence interval (CI) of census-adjusted record accessions per patient on weekdays compared with weekends were: 1.76 (95% CI: 1.74-1.77), 1.52 (95% CI: 1.50-1.55), and 1.14 (95% CI: 1.12-1.17) for day, morning/evening, and night hours, respectively. Percent CPU usage correlated closely with EHR interactions (r = 0.90).
Conclusions: EHR usage is a valid and easily reproducible measure of intensity of care in the hospital. Using this measure we identified large, hour-specific differences between weekend and weekday intensity. EHR interactions may serve as a useful measure for tracking and improving temporal variations in care that are common, and potentially deleterious, in hospital systems.
Global access to opioid agonist therapy and HIV/hepatitis C virus (HCV) treatment is expanding but when used concurrently, problematic pharmacokinetic and pharmacodynamic interactions may occur. Articles published from 1966 to 2012 in Medline were reviewed using the following keywords: HIV, AIDS, HIV therapy, HCV, HCV therapy, antiretroviral therapy, highly active antiretroviral therapy, drug interactions, methadone and buprenorphine. In addition, a review of abstracts from national and international meetings and conference proceedings was conducted; selected reports were reviewed as well. The metabolism of both opioid and antiretroviral therapies, description of their known interactions and clinical implications and management of these interactions were reviewed. Important pharmacokinetic and pharmacodynamic drug interactions affecting either methadone or HIV medications have been demonstrated within each class of antiretroviral agents. Drug interactions between methadone, buprenorphine and HIV medications are known and may have important clinical consequences. Clinicians must be alert to these interactions and have a basic knowledge regarding their management.
To assess the cost-effectiveness of Intervention for HIV-Seropositive injection drug users-Research and Evaluation (INSPIRE), designed to reduce risky sexual and needle-sharing behaviors in research sites in four US cities (2001-2003). Methods: We collected data on program and participant costs. We used a mathematical model to estimate the number of sex partners of injection drug users expected to become infected with human immunodeficiency virus (HIV) (with and without intervention), cost of treatment for sex partners who became infected, and the effect of infection on partners' quality-adjusted life expectancy. We determined the minimum effect that INSPIRE must have on condom use among participants for the intervention to be cost-saving (intervention cost less than savings from averted HIV infections) or cost-effective (net cost per quality-adjusted life year saved less than $50,000). Results: The intervention cost was $870 per participant. It would be cost-saving if it led to 53 percent reduction in the proportion of participants who had any unprotected sex in 1 year and cost-effective with 17 percent reduction. If behavior change lasted 3 months, the cost-effectiveness threshold was 66 percent; if 3 years, the threshold was 6 percent. Conclusions: Although cost-saving thresholds may not be achievable by the intervention, we anticipate that cost-effectiveness thresholds will be attained.
A population-based Pneumocystis carinii pneumonia (PCP) Index was developed in New York City to identify geographic areas and subpopulations at increased risk for PCP. Methods. A zip code-level PCP Index was created from AIDS surveillance and hospital discharge records and defined as (number of PCP-related hospitalizations)/(number of persons living with AIDS). Results. In 1997, there were 2262 hospitalizations for PCP among 39 740 persons living with AIDS in New York City (PCP Index = .05691). PCP Index values varied widely across neighborhoods with high AIDS prevalence (West Village = .02532 vs Central Harlem = .08696). Some neighborhoods with moderate AIDS prevalence had strikingly high rates (Staten Island = .14035; northern Manhattan = .08756). Conclusions. The PCP Index highlights communities in particular need of public health interventions to improve HIV-related service delivery.
The purpose of this study was to assess the relationship between syphilis and human immunodeficiency virus (HIV) infection in injection drug users. Methods. A 6-year prospective study of 790 injection drug users receiving methadone maintenance treatment in the Bronx, NY, was conducted. Results. Sixteen percent (4/25) of HIV-seroconverting patients, 4.8% (16/335) of prevalent HIV-seropositive patients, and 3.5% (15/430) of persistently HIV-seronegative patients were diagnosed with syphilis. Incidence rates for early syphilis (cases per 1000 person-years) were 15.9 for HIV-seroconverting patients, 8.9 for prevalent HIV-seropositive patients, and 2.9 for persistently HIV-seronegative patients. Early syphilis incidence was higher among women than men (8.4 vs 3.2 cases per 1000 person-years). Independent risks for early syphilis included multiple sex partners, HIV seroconversion, paid sex, and young age. All HIV seroconverters with syphilis were female. Conclusions. Diagnosis of syphilis in drug-using women reflects high-risk sexual activity and is associated with acquiring HIV infection. Interventions to reduce the risk of sexually acquired infections are urgently needed among female drug users.