Using a validated survey called the Digital IT Maturity Survey, the team is conducting a three-wave, longitudinal, repeated measures survey in a national sample of NHs. Currently, in year 2 of recruitment and analyzing year 1 data. Methods include an examination of the relationships between NH IT Maturity and stages of maturity, and nationally-reported, publicly-available NH Quality Measures available through Nursing Home Compare over three consecutive years. Specific aims are: 1) Explore NH IT maturity using the survey and staging model during a 3-year national assessment 2) Examine if NH IT maturity is associated with CMS quality measures in a national sample of NHs over 3 years. This study includes a survey of NH IT Maturity in a nationally representative sample including 10% of NHs recruited from each state in the United States (N=1,570). Statistical analysis will be done using the software SAS v9 (SAS Institute Inc., Cary, NC, USA). Since the sampling method involves stratification by state and since the sampling weights assigned to homes will depend on the number of respondents within each state, the analysis must take the complex sampling design into account. SAS procedures including SURVEYMEANS, SURVEYFREQ, SURVEYLOGISTIC, and SURVEYREG will be used for such analyses.

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New York Presbyterian/Columbia University Irving Medical Center (NYP/CUIMC) serves a high number of racial/ethnic minority and low-income patients. In this project, we will create a data repository of all patients who have completed a universal screen in a clinical encounter for social determinants of health, including food insecurity. The scholar will handle large datasets extracted from the medical record for database creation and data visualizations. The dataset will include patient demographics, food security, and clinical outcomes. This data resource will allow the scholar to partner with researchers to examine predictors of food insecurity, clinical courses, and health outcomes among a large population of patients, including a time period prior to the COVID-19 surge in New York City. The project will be co-mentored through the members of the University-wide Food Systems Network, a novel collaboration of researchers at the Medical Center, Earth Institute, SIPA, and Teacher’s College.

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This was a 1-year prospective observational study to examine the relation between sleep and cardiometabolic risk among 506 women in the NYC area. All of the data has been collected and entered in a Redcap database, has been cleaned, and is ready for analysis.

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I am conducting studies on lifestyle behaviors, in particular diet, sleep behaviors, and circadian rest-activity rhythms in relation to cardiometabolic outcomes (hypertension, type 2 diabetes, and obesity). Sample sizes of my studies range from n=100 to n=16,000.

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Scholars would assist with Aim 1 of a new R01 working with our lab and the Health Evaluation and Analytics Laboratory at NYU Wagner.

Congenital heart defects (CHDs) are the most common and resource intensive birth defects managed in the United States (US), affecting ~40,000 births per year in the US. (1) One-year mortality for these children is >10%. It is >30% for children requiring neonatal surgery. (2) Yet there are currently limited data on long-term outcomes and health expenditures for these children. Due to marked heterogeneity in disease subtypes and treatments among CHD patients, the power of single-center studies is limited. Multi-center data are siloed in diagnostic or procedural registries or in-patient databases, or are the product of individual investigations. Administrative data may lack clinical precision, as ICD codes for this population are not based on physiology. Further, data on costs and value typically rely on cost-to-charge ratio based costs, which are highly influenced by hospital accounting.

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