Local Health Departments

When a reportable condition is identified, clinicians and laboratories are required to report the case to public health authorities. These case reports help public health officials to make informed decisions and implement appropriate control measures to prevent the spread of disease. Incomplete or delayed case reports can result in new occurrences of disease that could have been prevented. To improve the disease reporting and surveillance processes, the Utah Department of Health is collaborating with Intermountain Healthcare and the University of Utah to electronically transmit case reports from healthcare facilities to public health entities using Health Level Seven v2.5, SNOMED CT, and LOINC. As part of the Utah Center of Excellence in Public Health Informatics, we conducted an observation study in 2009 to identify metrics to evaluate the impact of electronic systems. We collected baseline data in 2009 and in this paper we describe preliminary results from a follow-up study conducted in 2010.

Objective

This paper describes a comparison study conducted to identify quality of reportable disease case reports received at Salt Lake Valley health department in 2009 and 2010.

Syndromic surveillance data have been widely shown to be useful to large health departments. Use at smaller local health departments (LHDs) has rarely been described, and the effectiveness of various methods of delivering syndromic surveillance data and information to smaller health departments is unknown. Syndromic surveillance data and information in North Carolina are available to all local public health staff by several routes. This report characterizes LHD access to syndromic surveillance data and information and their use for key public health purposes.

Objective

To characterize use of syndromic surveillance information for key public health functions at the local health department level, and to make recommendations to facilitate use of syndromic surveillance data for these functions.

Public health disease surveillance is defined as the ongoing systematic collection, analysis and interpretation of health data for use in the planning, implementation and evaluation of public health, with the overarching goal of providing information to government and the public to improve public health actions and guidance. Since the 1950s, the goals and objectives of disease surveillance have remained consistent. However, the systems and processes have changed dramatically due to advances in information and communication technology, and the availability of electronic health data. At the intersection of public health, national security and health information technology emerged the practice of syndromic surveillance.

Objective

Review of the origins and evolution of the field of syndromic surveillance. Compare the goals and objectives of public health surveillance and syndromic surveillance in particular. Assess the science and practice of syndromic surveillance in the context of public health and national security priorities. Evaluate syndromic surveillance in practice, using case studies from the perspective of a local public health department.

Public Health departments are increasingly called upon to be innovative in quality service delivery under a dwindling resource climate as highlighted in several publications of the Institute of Medicine. Collaboration with other entities in the delivery of core public health services has emerged as a recurring theme. One model of this collaboration is an academic health department: a formal affiliation between a health professions school and a local health department. Initially targeted at workforce development, this model of collaboration has since yielded dividends in other core public health service areas including community assessment, program evaluation, community-based participatory research and data analysis.

The Duval County Health Department (DCHD), Florida, presents a unique community-centered model of the academic health department. Prominence in local informatics infrastructure capacity building and hosting a CDC-CSTE applied public health informatics fellowship (APHIF) in the Institute for Public Health Informatics and Research (IPHIR) in partnership with the Center for Health Equity Research, University of Florida & Shands medical center are direct dividends of this collaborative model.

Objective

Highlight one academic health department’s unique approach to optimizing collaborative opportunities for capacity development and document the implications for chronic disease surveillance and population health.

A decade ago, the primary objective of syndromic surveillance was bioterrorism and outbreak early event detection (EED. Syndromic systems for EED focused on rapid, automated data collection, processing and statistical anomaly detection of indicators of potential bioterrorism or outbreak events. The paradigm presented a clear and testable surveillance objective: the early detection of outbreaks or events of public health concern. Limited success in practice and limited rigorous evaluation, however, led to the conclusion that syndromic surveillance could not reliably or accurately achieve EED objectives. At the federal level, the primary rationale for syndromic surveillance shifted away from bioterrorism EED, and towards allhazards biosurveillance and SA. The shift from EED to SA occurred without a clear evaluation of EED objectives, and without a clear definition of the scope or meaning of SA in practice. Since public health SA has not been clearly defined in terms of operational surveillance objectives, statistical or epidemiological methods, or measurable outcomes and metrics, the use of syndromic surveillance to achieve SA cannot be evaluated.

Objective

Review concept of situation awareness (SA) as it relates to public health surveillance, epidemiology and preparedness. Outline hierarchical levels and organizational criteria for SA. Initiate consensus building process aimed at developing a working definition and measurable outcomes and metrics for SA as they relate to syndromic surveillance practice and evaluation.

Syndromic surveillance systems offer richer understanding of population health. However, because of their complexity, they are less used at small public health agencies, such as many local health departments (LHDs). The evolution of these systems has included modifying user interfaces for more efficient and effective use at the local level. The North Carolina Preparedness and Emergency Response Research Center previously evaluated use of syndromic surveillance information at LHDs in North Carolina. Since this time, both the NC DETECT system and distribution of syndromic surveillance information by the state public health agency have changed. This work describes use following these changes.

Objective

Our objective was to describe changes in use following syndromic surveillance system modifications and assess the effectiveness of these modifications.

 

LHDs are operating in a changing data environment. As household telephone use declines, national surveys are not sampling large enough populations to report representative local health statistics. As a result, reliable indicators from surveys such as the Behavioral Risk Factors Surveillance Survey (BRFSS) are becoming scarce. Soon, these indicators may not be sufficient for county assessments. NC DETECT primarily uses data from emergency departments, the Carolinas Poison Center, and the Pre-hospital Medical Information System (PreMIS) to identify outbreaks and facilitate emergency response. However, while built to aggregate “real-time” data, NC DETECT also provides a source for rich, long-term indicators. The challenge for LHDs is that they may not have the knowledge, training, or technical assistance needed to fully utilize NC DETECT services. This project capitalizes on available human, organizational, and technical resources to increase LHD situational awareness and to demonstrate the usefulness of both “real-time” surveillance data as aggregate indicators of county health, and of low-cost prototyping using Excel’s more advanced Business Intelligence (BI) features.

Objective

This project aims to fill a growing county-level health data gap through the development of a low-cost, Excel-based surveillance tool. This prototype utilizes emergency department data (ED) collected by NC DETECT, a state-wide syndromic surveillance system, in order to visualize, monitor, and compare annual local health indicators for use in local decision making. In this way, the project aims to increase noncommunicable disease surveillance capacity and improve situational awareness within North Carolina local health departments (LHDs).