Skip to main content

Informatics

Description

Health care information is a fundamental source of data for biosurveillance, yet configuring EHRs to report relevant data to health departments is technically challenging, labor intensive, and often requires custom solutions for each installation. Public health agencies wishing to deliver alerts to clinicians also must engage in an endless array of one-off systems integrations. Despite a $48B investment in HIT, and meaningful use criteria requiring reporting to biosurveillance systems, most vendor electronic health records are architected monolithically, making modification difficult for hospitals and physician practices. An alternative approach is to reimagine EHRs as iPhone-like platforms supporting substitutable apps-based functionality. Substitutability is the capability inherent in a system of replacing one application with another of similar functionality.

Objective

To enable public health departments to develop “apps” to run on electronic health records (EHRs) for (1) biosurveillance and case reporting and (2) delivering alerts to the point of care. We describe a novel health information technology platform with substitutable apps constructed around core services enabling EHRs to function as iPhone-like platforms.

Submitted by uysz on
Description

INDICATOR is a multi-stream open source platform for biosurveillance and outbreak detection, currently focused on Champaign County in Illinois[1]. It has been in production since 2008 and is currently receiving data from emergency departments, patient advisory nurse call center, outpatient convenient care clinic, school absenteeism, animal control, and weather sources. Long term scalability was however compromised during the 2009 H1N1 influenza pandemic as immediate public health needs took priority over our systematic development plan. With the impending addition of veterinary clinic data and recognizing that the health of a community also depends on animal and environmental factors, we decided to revisit the INDICATOR architecture and redesign it to be a more holistic and scalable system. We also decided to revisit the data submission format, keeping in line with the philosophy of making opportunistic secondary use of as much data about the health of a community that we can obtain.

Objective

To redesign INDICATOR for One Health, establish a common data format, and provide for long term scalability.

Submitted by uysz on
Description

Researchers have demonstrated benefits to identifying and developing interventions for patients that frequently seek healthcare services in the ED. The New Yorker Magazine, recently published an article titled The Hot Spotters, summarizing work being done in the United States to lower medical costs by giving the neediest patients better healthcare (1). In Camden, NJ, Physician Jeffrey Brenner closed his regular practice to focus on Hot Spotter patients (directing resources and brainpower to help their improvement) and measured a 40% reduction in hospital inpatient and ED visits and a 56% medical cost reduction for the first 36 Hot Spotters. A 2008 NH Office of Medicaid Business and Policy (OMBP) outpatient Medicaid ED frequency visit study was conducted, which cited that frequent ED users were more likely to have higher costs and rates of illness or disease than all Medicaid members (2). It was noted that increased prevention and wellness could reduce frequent ED use and increase cost savings (5% of the NH Medicaid population contributed to approximately 38% of ED costs). The NH Division of Public Health Services initiated a pilot project to examine NH Emergency Department (ED) surveillance data to identify high utilizer patients and realize improved health benefits and medical cost reductions.

Objective:

To develop a manageable surveillance methodology to detect Emergency Department (ED) patients with the highest healthcare utilization, and monitor their targeted treatment improvement and medical health cost reductions over time for overall improvements in statewide health.

 

Submitted by Magou on
Description

Fusion Analytics is the data integration system developed by the Fusion Cell at the U.S. Department of Health and Human Services (HHS), Office of the Assistant Secretary for Preparedness and Response (ASPR). Fusion Analytics meaningfully augments traditional public and population health surveillance reporting by providing webbased data analysis and visualization tools.

Objective

The objective of this demonstration is to show conference attendees how they can integrate, analyze, and visualize diverse data type data from across a variety of systems by leveraging an off-the-shelf enterprise business intelligence (EBI) solution to support decisionmaking in disasters.

Submitted by teresa.hamby@d… on
Description

Pertussis (i.e., whooping cough) is on the rise in the US. To implement effective prevention and treatment strategies, it is critical to conduct timely contact tracing and evaluate people who may have come into contact with an infected person. We describe a collaborative effort between epidemiologists and public health informaticists at the Utah Department of Health (UDOH) to determine the feasibility and value of a network-analytic approach to pertussis outbreak management and contact tracing.

Objective: 

To determine the feasibility and value of a social network analysis tool to support pertussis outbreak management and contact tracing in the state of Utah.

 

Submitted by Magou on
Description

In this panel, the presenters will discuss their perspective in responding to Hurricanes Harvey and Irma. Hurricane Harvey made landfall on August 25th and over the course of 4 days dropped approximately 27 trillion gallons of water on Texas and Louisiana. The flooding that ensued was unprecedented and forced over 13,000 people into shelters. These individuals needed to have their basic needs -food, shelter, clothing, sanitation- met as well as their physical and mental health needs. The George R Brown Conference Center (GRB) and NRG Stadium Center were set up as mega-shelters to house shelterees. Hurricane Irma made landfall on September 10th in the Florida Keys as a Category 4 Hurricane. The Hurricane caused 72 deaths and forced thousands of people into shelters. These weather events created novel challenges for local response efforts. Decision makers needed timely and actionable data, including surveillance data.

Objective:

In this panel, attendees will learn about how disaster surveillance was conducted in response to Hurricanes Irma and Harvey, as well as the role of CDC at the federal level in supporting local response efforts. By hearing and discussing the challenges faced and solutions identified, attendees will be better able to respond in the event of a low-frequency/high-consequence disaster occurring within their jurisdiction.

Submitted by elamb on
Description

Environmental Public Health Zoonotic Disease surveillance includes veternary, environmental, and vector data. Surveillance systems within each sector may appear disparate from each other, although they are actually complimentaly and closely allied. Consolidating and integrating data in to one application can be challenging, but there are commonalities shared by all. The goal of the One Health Integrated Data Sysytem is to standardize data collection, streamline data entry, and integrate these sectors in to one application.

Objective:

Integrate and streamline the collection and analysis of environmental, veterinary, and vector zoonotic data using a One Health approach to data system development.

Submitted by elamb on
Description

BioSense 2.0 protects the health of the American people by providing timely insight into the health of communities, regions, and the nation by offering a variety of features to improve data collection, standardization, storage, analysis, and collaboration. BioSense 2.0 is the result of a partnership between the Centers for Disease Control and Prevention (CDC) and the public health community to track the health and well-being of communities across the country. In 2010, the BioSense Program began a redesign effort to improve features such as centralized data mining and addressing concerns that the system could not meet its original objective to provide early warning or detect local outbreaks.

Objective

To familiarize public health practitioners with the BioSense 2.0 application and its use in all hazard surveillance.

 

Submitted by Magou on
Description

With increasing availability of syndromic meaningful use data, new approaches to disease surveillance utilizing linkages to other data systems are possible. Expanded communicable disease information may be valuable during outbreaks or other public health emergencies. San Diego County is experiencing a significant and protracted hepatitis A outbreak. The disease has been transmitted person-to-person through close contact or through a fecally-contaminated environment, and has been primarily affecting homeless people and injection and non-injection illicit drug users. As of August 31, 2017, there were nearly 400 cases with 15 deaths. Approximately, 70% of the cases were hospitalized. This is one of the nation’s largest hepatitis A outbreaks since the introduction of the hepatitis A vaccine in 1995. Additional cases are expected over the next twelve months. The population affected by this outbreak presents some challenges for outbreak response. It is often a difficult population to reach. In addition, many have multiple comorbidities and often have health care seeking behaviors that differ from the general population. Using the medical record number (MRN) to link hepatitis A disease cases from the communicable disease registry to syndromic HL7 messages for emergency department visits and hospitalizations enabled the identification of additional hospital encounters the cases may have had before, during, or following their hepatitis A disease incident. This allowed an exploration of the ways in which this unique population interacted with the health care system in the context of a communicable disease outbreak. This presentation will highlight the steps to link information across surveillance systems, the results, the challenges, and the benefits of linked information to public health departments.

Objective:

To describe how the County of San Diego linked information from a communicable disease registry and syndromic surveillance system to further describe cases associated with a large hepatitis A outbreak. Specifically, to detail the linkage process which resulted in a longitudinal understanding of individuals’ hospital visits before, during, and after the reported hepatitis A incident.

Submitted by elamb on
Description

Public health is at a precipice of increasing demand for the consumption and analysis of large amounts of disparate data, the centralization of local and state IT offices, and the compartmentalization of programmatic technology solutions. Public health informatics needs differ across programmatic areas, but may have commonalities across jurisdictions. Initial development of the PHCP was launched with the goal of providing a shared infrastructure for state and local jurisdictions enabling the development of interoperable systems and distributed analytical methods with common sources of data. The PHCP is being designed to leverage recent successes with cloud-based technology in public health.

Success of the PHCP is dependent on the involvement of state and local public health jurisdictions in the transparent development and future direction of the platform. Equally critical to success is the selection of appropriate technology, consideration of various governance structures, and full understanding of the legal implications of a shared platform model.

Objective

To update the public health practice community on the continuing development of the Public Health Community Platform (PHCP).

Submitted by teresa.hamby@d… on