Skip to main content

Gil Harold

Syndromic surveillance can provide early warning of potential public health emergencies and acute health events in a population. The sharing and aggregation of syndromic data among jurisdictions can provide more comprehensive situational awareness and improve coordination and decision-making. The BioSense 2.0 Program supports increased syndromic data-sharing among a nationwide network of local and state public health agencies. Most users of this application utilize the main web site front-door interface due to its user-friendly features for query and analysis. However, this interface currently has a limited number of analytic tools, export functions, and provides access only to binned data. The back-door interface, with access to additional data lockers containing raw and exception data, represents a potentially rich source of untapped and underutilized information. In this presentation, we discuss our ongoing development and early success of a capacity (consisting of code libraries, a parser, and an implementation guide) that allows users to tailor a program-specific, automated process for generating surveillance reports from their BioSense 2.0 data locker. The product will soon be available to members of the BioSense User Community.

Objective

The purpose of this project is to develop a capacity to facilitate implementation of a user-driven enhanced process for generating program-specific surveillance reports from BioSense 2.0 locker data.

Submitted by knowledge_repo… on

Opioid ODs have been rising globally and nationally. The death rate from ODs in the United States has increased 137% since 2000, including a 200% increase of OD deaths involving opioids1. The pilot project, a collaboration across 3 states, allowed information sharing with Syndromic surveillance (SyS) partners across jurisdictions, such as sharing a standard SyS case definition and verifying its applicability in each jurisdiction. This is a continuation of the work from an initial pilot project presented during the ISDS Opioid OD Webinar series.

Objective:

The objective is to develop a standard opioid overdose case definition that could be generalized nationally

Submitted by elamb on

Data sets from disparate sources widely vary in the number and type of factors which most hamper integrity and timeliness of the data. To maintain high quality data, data sets must be regularly assessed, particularly for those vulnerabilities that each is especially prone to due to the methods involved in collecting the data. For surveillance practitioners charged with monitoring data from multiple data sources, keeping track of the issues that each data set is susceptible to, and quickly identifying any inconsistencies or deviations from normal trends, may be a challenge. An application that can track all those issues, and trigger alerts when patterns diverge from what is expected, could help to enhance the efficiency and effectiveness of the surveillance efforts.

Objective

An interactive, point-and-click application was developed to facilitate the routine assessment of known data quality factors that compromise the integrity and timeliness of data sets used at the Marion County Public Health Department (MCPHD). The code (and associated documentation) for this application is being made available for other surveillance practitioners to adopt.

Submitted by teresa.hamby@d… on

Presenters Caleb Wiedeman and Harold Gil will describe some of the processes their organizations use to ensure the quality of data in BioSense v2.0. First, Caleb Wiedeman will review his normal routine of verifying data quality, including checking the front end of the BioSense v2.0 application for aberrations and drops in visit counts, linking front-end data to the back end using R, and using phpMyAdmin to check daily files. This portion of the presentation will focus on Tennessee’s system and the data they receive from six facilities within a single health system. 



Public health surveillance largely relies on the use of surveillance systems to facilitate the identification and investigation of epidemiologic concerns reflected in data. In order to support public health response, these systems must present relevant information, and be user-friendly, dynamic, and easily-implementable. The abundance of R tools freely-available online for data analysis and visualization presents not only opportunities but also challenges for adoption in that these tools must be integrated so as to allow a structured workflow. Many public health surveillance practitioners do not have the time available to 1) scavenge for tools, 2) align their functions so as to create a relevant set of visuals, and 3) integrate these visuals into a dashboard that allows a streamlined surveillance workflow. An openly-available, structured framework that allows simple integration of analytic capabilities packaged into readily- implementable modules would simplify the creation of relevant dashboard visuals by surveillance practitioners. 

Objective

A framework and toolbox for creating point-and-click dashboard applications (at no cost) for monitoring several facets of syndromic surveillance data were created. These tools (and associated documentation) are being made available freely online for other surveillance practitioners to adopt. 

Submitted by Magou on

To provide community input on data quality issues and enhance data quality through sharing and testing of scripts.

Summary of activities:

The Data Quality workgroup has worked to address Data Quality issues through the development, sharing and testing of scripts. The Data Quality workgroup formed a DQ EHR-Vendor Concern Subcommittee to address issues across vendors nationwide. 

Submitted by uysz on
Subscribe to Gil Harold