The existing New York State Department of Health emergency department syndromic surveillance system has used patientâs chief complaint (CC) for assigning to six syndrome categories (Respiratory, Fever, Gastrointestinal, Neurological, Rash, Asthma). The sensitivity and specificity of the CC computer algorithms that assign CC to syndrome categories are determined by using chart review as the criterion standard. These analyses are used to refine the algorithm and to evaluate the effect of changes in the syndrome definitions. However, the chart review (CR) method is labor intensive and expensive. Using an automated ICD9 code-based assignment as a surrogate for chart review could offer a significant cost reduction in this process and allow us to survey a much larger sample of visits.
Chang Hwa-Gan
To evaluate four algorithms with varying baseline periods and adjustment for day of week for anomaly detection in syndromic surveillance data.
The final rules released by the Centers for Medicare and Medicaid Services specified the initial criteria for eligible hospitals to qualify for an incentive payment by demonstrating meaningful use of certified Electronic Health Record (EHR) technology. Syndromic surveillance reporting is one of three public health objectives that eligible hospitals can choose for stage 1. The PHIN messaging guide for syndromic surveillance was published for hospitals to construct emergency department data using Admit Discharge Transfer (ADT) messages, with the minimum dataset that is standard among hospitals and public health agencies. Currently New York hospitals are reporting emergency department (ED) visit data to the NY syndromic surveillance (SS) system. Patient chief complaint data are monitored for trends of illness at the community level in order to detect possible outbreaks and situational awareness.
Objective:
To evaluate the readiness and timeliness of ED data submitted by hospitals following PHIN syndromic surveillance messaging guide and to evaluate the availability of minimum data elements. To validate the accuracy and completeness of data from ADT messages compared with data currently reported to the NY syndromic surveillance system.
Early detection of heroin overdose clusters is important in the current battle against the opioid crisis to effectively implement prevention and control measures. The New York State syndromic surveillance system collects hospital emergency department (ED) visit data, including visit time, chief complaint, and patient zip code. This data can be used to timely identify potential heroin overdose outbreaks by detecting spatial-temporal case clusters with scan statistic.
Objective:
To utilize syndromic surveillance data timely detecting herion overdose outbreaks in the community.
EDCC data provides an opportunity for capturing the early mental health impact of disaster events at the community level, and to track their impact over time. However, while rapid mental health assessment can facilitate a better understanding of the acute post-disaster period and aid early identification of persons at long-term risk,1 determining how wide a net to effectively capture the critical range of mental health sub-categories has not yet been clearly defined. This project creates a comprehensive set of mental health sub-category keywords, and applies them to evaluate short- and long-term trends in postHurricane Sandy mental health outcomes in New York State.
Objective
To define mental health keywords using daily hospital emergency department chief complaint (EDCC) data during and after Hurricane Sandy 2) To track short- and long-term trends in mental health EDCCs. 3) To compare mental health EDCCs in affected counties to the rest of the New York State population.
All positive laboratory tests of reportable conditions on persons residing in New York State (NYS) are mandated to be sent to the NYS Department of Health (NYSDOH) via ECLRS. NYS, excluding New York City (NYC), receives over 100,000 ECLRS messages on general communicable diseases (CD) and hepatitis (HEP), not including Lyme disease and Influenza, annually. Although ECLRS is integrated with CDESS, the local health departments (LHD) need to review each lab report for proper initiation of a case investigation. Once the investigation is created, the LHD may need supportive evidence to create a reportable case or may dismiss it if evidence does not support the case definition.
Our goal is to follow all ECLRS records from official retrieval by the LHD through CDESS case creation, to ensure all cases are reported and are done so in a timely manner. Cases for diseases that are nationally notifiable are sent to CDC the following week for publication in the Morbidity and Mortality Weekly Report. Timely reporting to CDC allows for more accurate description of disease occurrence, which is essential for public health planning and response.
Objective
Ensure all reportable communicable disease data coming through the Electronic Clinical Laboratory Reporting System (ECLRS) is reported to the Communicable Disease Electronic Surveillance System (CDESS) in a timely and complete manner.
CO poisoning is a leading cause of mortality and morbidity in disaster and post-disaster situations, when widespread power outages most likely occur (1, 2). The NYSDOH Syndromic Surveillance System receives daily ED visit chief complaint data from 140 NYS (excluding New York City) hospitals. Daily power outage data are available from the NYS Department of Public Service (NYSDPS). These data can be used to estimate the risk of CO-EDs and provide useful information for public health situational awareness and emergency response management during disaster events.
Objective
1) To identify carbon monoxide (CO) poisoning in three most affected New York State (NYS) counties (Nassau, Suffolk, and Westchester) during and immediately after Hurricane Sandy with hospital emergency department (ED) chief complaint data reported daily to the New York State Department of Health (NYSDOH). 2) To explore the relationship between power outage and the numbers of CO-related ED visits (CO-EDs).
New York State Department of Health (NYSDOH) implemented a Communicable Disease Electronic Surveillance System (CDESS), a single and secure application used by 57 local health departments (LHDs), hospital infection control programs and NYSDOH staff to collect, integrate, analyze, and report data for infectious disease surveillance. New York State Immunization Information System (NYSIIS) is a mandated application for providers to report all vaccinations of persons < 19 years old residing in New York State (excluding New York City). Currently, LHD staff must manually search NYSIIS for vaccine preventable disease case investigations and re-enter the immunization histories into CDESS. NYSIIS has built a HL7 query functionality which can be used to automate the data exchange between NYSIIS and CDESS.
Objective
To establish the infrastructure to provide a linkage between the immunization registry and disease surveillance system using standard for data exchange.
NYS (excluding NYC) has a very robust Communicable Disease Electronic Surveillance System (CDESS). This system provides disease specific modules, as well as a tracking system for contacts, and a perinatal infant tracking system. This system provides an easy way for users to quickly download a file with all of their data.
NYS (excluding NYC) tracks, on average, 300 infants of hepatitis B surface antigen (HBsAg) positive mothers annually. CDESS provides an infant tracking module for local health departments (LHDs) to enter and monitor vaccine information, add multiple infants per mother, and track patient movement and loss to follow-up. The tool allows LHDs to analyze infants’ data by birth year cohort, with all of their current vaccination and serology information available in one record.
In 2013 and 2014, more than 13,000 cases of gonorrhea were reported to CDESS in NYS (excluding NYC). From November 2013 through May 2014, only 61% of cases were adequately treated with a regimen recommended by the Centers for Disease Control and Prevention (CDC) STD Treatment Guidelines for Gonorrhea , and 29% were missing treatment information. The CDESS system allows the LHDs to track patients who have inadequate and/or missing treatment information.
Objective
Improved methods for user analysis of communicable disease surveillance data in New York State (NYS), excluding New York City (NYC).
There were several stand-alone vector surveillance applications being used by the New York State Department of Health (NYSDOH) to support the reporting of mosquito, bird, and mammal surveillance and infection information implemented in early 2000s in response to West Nile virus. In subsequent years, the Electronic Clinical Laboratory Reporting System (ECLRS) and the Communicable Disease Electronic Surveillance System (CDESS) were developed and integrated to be used for surveillance and investigations of human infectious diseases and management of outbreaks.
An integrated vector surveillance system project was proposed to address the migration of the stand-alone vector surveillance applications into a streamlined, consolidated solution to support operational, management, and technical needs by using the national standards with the existing resources and technical environment.
Objective
To develop a mosquito surveillance module to collect mosquito information testing for West Nile, East Equine Encephalitis (EEE) and Zika viruses using national standards. To provide a common set of data for local health departments (LHDs) and state users to report and share information. To monitor the type of mosquito species that carry diseases.