Caring for Patients Seeking Asylum: Early Data From the Safety Net System in New York City.

Context: Over 200 000 people seeking asylum have arrived in New York City from 2022 to 2024.

Program: As the safety net hospital system for our city, New York City (NYC) Health + Hospitals (H + H) has taken the lead in caring for newly arrived asylum seekers. We used electronic medical record data to gain early insights into utilization and needs among these patients.

Developing a Model to Predict High Health Care Utilization Among Patients in a New York City Safety Net System.

Background: Health care facilities use predictive models to identify patients at risk of high future health care utilization who may benefit from tailored interventions. Previous predictive models that have focused solely on inpatient readmission risk, relied on commercial insurance claims data, or failed to incorporate social determinants of health may not be generalizable to safety net hospital populations. To address these limitations, we developed a payer-agnostic risk model for patients receiving care at the largest US safety net hospital system.

Social distancing and mask-wearing could avoid recurrent stay-at-home restrictions during COVID-19 respiratory pandemic in New York City.

Stay-at-home restrictions such as closure of non-essential businesses were effective at reducing SARS-CoV-2 transmission in New York City (NYC) in the spring of 2020. Relaxation of these restrictions was desirable for resuming economic and social activities, but could only occur in conjunction with measures to mitigate the expected resurgence of new infections, in particular social distancing and mask-wearing. We projected the impact of individuals' adherence to social distancing and mask-wearing on the duration, frequency, and recurrence of stay-at-home restrictions in NYC.

Surge and Mortality in ICUs in New York City's Public Healthcare System.

Objectives: To evaluate the impact of ICU surge on mortality and to explore clinical and sociodemographic predictors of mortality.

Design: Retrospective cohort analysis.

Setting: NYC Health + Hospitals ICUs.

Generalizability of Indicators from the New York City Macroscope Electronic Health Record Surveillance System to Systems Based on Other EHR Platforms.

Introduction: The New York City (NYC) Macroscope is an electronic health record (EHR) surveillance system based on a distributed network of primary care records from the Hub Population Health System. In a previous 3-part series published in , we reported the validity of health indicators from the NYC Macroscope; however, questions remained regarding their generalizability to other EHR surveillance systems.

Methods: We abstracted primary care chart data from more than 20 EHR software systems for 142 participants of the 2013-14 NYC Health and Nutrition Examination Survey who did not contribute data to the NYC Macroscope.

Can Electronic Health Records Be Used for Population Health Surveillance? Validating Population Health Metrics Against Established Survey Data.

Introduction: Electronic health records (EHRs) offer potential for population health surveillance but EHR-based surveillance measures require validation prior to use. We assessed the validity of obesity, smoking, depression, and influenza vaccination indicators from a new EHR surveillance system, the New York City (NYC) Macroscope. This report is the second in a 3-part series describing the development and validation of the NYC Macroscope.

Monitoring Prevalence, Treatment, and Control of Metabolic Conditions in New York City Adults Using 2013 Primary Care Electronic Health Records: A Surveillance Validation Study.

Introduction: Electronic health records (EHRs) can potentially extend chronic disease surveillance, but few EHR-based initiatives tracking population-based metrics have been validated for accuracy. We designed a new EHR-based population health surveillance system for New York City (NYC) known as NYC Macroscope. This report is the third in a 3-part series describing the development and validation of that system.

Design of the New York City Macroscope: Innovations in Population Health Surveillance Using Electronic Health Records.

Introduction: Electronic health records (EHRs) have the potential to offer real-time, inexpensive standardized health data about chronic health conditions. Despite rapid expansion, EHR data evaluations for chronic disease surveillance have been limited. We present design and methods for the New York City (NYC) Macroscope, an EHR-based chronic disease surveillance system.

Characterizing Adults Receiving Primary Medical Care in New York City: Implications for Using Electronic Health Records for Chronic Disease Surveillance.

Introduction: Electronic health records (EHRs) from primary care providers can be used for chronic disease surveillance; however, EHR-based prevalence estimates may be biased toward people who seek care. This study sought to describe the characteristics of an in-care population and compare them with those of a not-in-care population to inform interpretation of EHR data.

Methods: We used data from the 2013-2014 New York City Health and Nutrition Examination Survey (NYC HANES), considered the gold standard for estimating disease prevalence, and the 2013 Community Health Survey, and classified participants as in care or not in care, on the basis of their report of seeing a health care provider in the previous year.

The state of population health surveillance using electronic health records: a narrative review.

Electronic health records (EHRs) are transforming the practice of clinical medicine, but the extent to which they are being harnessed to advance public health goals remains uncertain. Data extracted from integrated EHR networks offer the potential for almost real-time determination of the health status of populations in care, for targeting interventions to vulnerable populations, and for monitoring the impact of such initiatives over time. This is especially true in ambulatory care settings, which are uniquely suited for monitoring population health indicators including risk factors and disease management indicators associated with chronic diseases.

Evaluating the 2010 New York State HIV testing law in NYC ambulatory practices using electronic health records.

Introduction: In 2010, the New York State Legislature made it mandatory to offer an HIV test to people aged 13-64 years receiving hospital or primary care services, with limited exceptions. In this study, we used data from New York City practices to evaluate the impact of the law on HIV testing rates in ambulatory care.

Methods: We collected quarterly testing data from the electronic health records of 218 practices.

Assessing capacity and disease burden in a virtual network of New York City primary care providers following Hurricane Sandy.

Urban contexts introduce unique challenges that must be addressed to ensure that areas of high population density can function when disasters occur. The ability to generate useful data to guide decision-making is critical in this context. Widespread adoption of electronic health record (EHR) systems in recent years has created electronic data sources and networks that may play an important role in public health surveillance efforts, including in post-disaster situations.