Evidence map›Paper›PMID 28154835›Full record

ArticleEGEMS (Washington, DC)2016

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

Remle Newton-Dame, Katharine H McVeigh, Lauren Schreibstein, Sharon Perlman, Elizabeth Lurie-Moroni, Laura Jacobson, Carolyn Greene, Elisabeth Snell, Lorna E Thorpe

Abstract read
In one paragraph

Article in EGEMS (Washington, DC), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 32 papers, 4 of them syntheses that pooled it.

0numbers the graph read from it
0cells of the map it votes in
32citing papers in PubMed, 4 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

32 citing papers in PubMed, 4 syntheses or guidelines pooled it.

  1. Pooled it
  2. Electronic health record data quality assessment and tools: a systematic review.Journal of the American Medical Informatics Association : JAMIA · 2023
    Pooled it
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  7. Blood Pressure in Young Adults in Iowa.Journal of clinical hypertension (Greenwich, Conn.) · 2025
    Observational
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Remle Newton-DameFormerly New York City Department of Health and Mental Hygiene.
Katharine H McVeighNew York City Department of Health and Mental Hygiene.
Lauren SchreibsteinFormerly New York City Department of Health and Mental Hygiene.
Sharon PerlmanNew York City Department of Health and Mental Hygiene.
Elizabeth Lurie-MoroniFormerly New York City Department of Health and Mental Hygiene.
Laura JacobsonFormerly New York City Department of Health and Mental Hygiene.
Carolyn GreeneFormerly New York City Department of Health and Mental Hygiene.
Elisabeth SnellFormerly New York City Department of Health and Mental Hygiene.
Lorna E ThorpeNYU School of Medicine Department of Population Health.

Funding

New York University, City University of New York Health Promotion & Prevention ReU48DP005008 · DP · NEW YORK UNIVERSITY SCHOOL OF MEDICINE · PI THORPE, LORNA, TRINH-SHEVRIN, CHAU · 2014 to 2018
$6.9M
PPHF-13 NY CITY DEPARTMENT OF HEALTH & MENTAL HYGIENE 2011-2012 ENVIRONMENTAL PUBU38EH000939 · EH · NEW YORK CITY HEALTH/MENTAL HYGIENE · PI MCKELVEY, WENDY · 2011 to 2015
$4.8M
NCCDPHP CDC HHS U48 DP005008NCEH CDC HHS U38 EH000939
6 · The paper itself

Abstract

introductionElectronic 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. This methods report is the first in a three part series describing the development and validation of the NYC Macroscope. This report describes in detail the infrastructure underlying the NYC Macroscope; indicator definitions; design decisions that were made to maximize data quality; characteristics of the population sampled; completeness of data collected; and lessons learned from doing this work. The second report describes the methods used to evaluate the validity and robustness of NYC Macroscope prevalence estimates; presents validation results for estimates of obesity, smoking, depression and influenza vaccination; and discusses the implications of our findings for NYC and for other jurisdictions embarking on similar work. The third report applies the same validation methods to metabolic outcomes, including the prevalence, treatment and control of diabetes, hypertension and hyperlipidemia.

methodsWe designed the NYC Macroscope for comparison to a local "gold standard," the 2013-14 NYC Health and Nutrition Examination Survey, and the telephonic 2013 Community Health Survey. NYC Macroscope indicators covered prevalence, treatment, and control of diabetes, hypertension, and hyperlipidemia; and prevalence of influenza vaccination, obesity, depression and smoking. Indicators were stratified by age, sex, and neighborhood poverty, and weighted to the in-care NYC population and limited to primary care patients. Indicator queries were distributed to a virtual network of primary care practices; 392 practices and 716,076 adult patients were retained in the final sample.

findingsThe NYC Macroscope covered 10% of primary care providers and 15% of all adult patients in NYC in 2013 (8-47% of patients by neighborhood). Data completeness varied by domain from 98% for blood pressure among patients with hypertension to 33% for depression screening. DISCUSSION: Design and validation efforts undertaken by NYC are described here to provide one potential blueprint for leveraging EHRs for population health monitoring. To replicate a model like NYC Macroscope, jurisdictions should establish buy-in; build informatics capacity; use standard, simple case defnitions; establish documentation quality thresholds; restrict to primary care providers; and weight the sample to a target population.

Indexed as

cardiovascular diseasechronic diseaseElectronic health records (EHR)population healthsurveillance

Identifiers

PMID28154835
PMCPMC5226383

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.