Stoto Michael

Infectious disease surveillance is a process, the product of which reflects both real illness and public awareness of the disease (Figure 1). According to our previous research studies [1,2], decisions made by patients, healthcare providers, and public health professionals about seeking and providing healthcare and about reporting cases to health authorities are all influenced by the information environment, which changes constantly. Biases are therefore imbedded in each surveillance systems, and need to be assessed to provide better situational awareness for decision-making.

Objective

Our goal is to develop a statistical framework to characterize influenza surveillance systems and their sensitivity to information environment.

For syndromic and related public health surveillance systems to be effective, state and local health departments and the Centers for Disease Control and Prevention (CDC) need access to a variety of types of health data. Since the development and implementation of syndromic surveillance systems in recent years, health departments have gained varied levels of access to personal health information for inclusion in these systems. A variety of federal, state, and local laws enable, restrict, and otherwise infl uence the sharing of health information between health care providers and public health agencies for surveillance, as well as research, purposes. Some health care providers have expressed reluctance or refused to provide identifi able data for syndromic surveillance to health departments (1), citing state privacy laws or the Health Insurance Portability and Accountability Act of 1996 (HIPAA) Privacy Rule (2). Although the HIPAA Privacy Rule permits health care providers to disclose protected health information without patients’ consent to public health agencies for authorized purposes, it does not supersede state laws that provide greater protection of individual privacy (2,3). The use of individuals’ health information for syndromic surveillance poses challenging questions regarding the interpretation and future development of ethical and legal standards for public health practice and research. While the practice of syndromic surveillance extends the longstanding tradition of public health surveillance as an essential element of public health practice (4), it raises in a new light equally longstanding questions about governments’ authority to collect and use health information (5). As the practice of syndromic surveillance evolves, it is in the national interest to clarify the conditions under which health information can be shared, the ways that privacy and confi dentiality can be protected, and the ways that local, state, and federal public health agencies can legally, ethically, and effectively exercise their respective responsibilities to detect, monitor, and respond to public health threats.

 

For syndromic and related surveillance systems to be effective public health tools, state and local health departments and CDC need access to a variety of types of health data.  However, since the development and implementation of syndromic surveillance systems began in recent years, experience in gaining access to personal health data has been mixed.  Although some have argued that the HIPAA Privacy Rule permits data owners to disclose protected health information to public health authorities, covered entities have cited HIPAA in refusing to provide data to researchers and health departments.  In addition to HIPAA, a variety of federal, state, and local public health laws enable, restrict, and otherwise influence the ability to share data for public health surveillance purposes.  Concerns about protecting proprietary data also influence data sharing for public health purposes.  It is in the national interest to clarify the conditions under which data can be shared, balancing privacy and confidentiality with the ability of public health agencies at all levels of jurisdiction to access information needed to protect the public from disease.  As the practice of syndromic surveillance evolves, it is equally important to assure that data are collected and used ethically as well as legally. The methods and uses of syndromic surveillance pose challenging questions regarding the interpretation and future development of ethical and legal standards for public health practice and research. The discussion will not be confined to the legal and ethical issues surrounding the release of data but will also address these issues as they concern the subsequent transmission, storage, replication, and display of health data by local, state, and federal public health users, including how the information is used for both early event detection and situational awareness functions. 

Objective

The International Society for Disease Surveillance will convene a group of experts to: (1) share experience with privacy, confidentiality, and other legal and ethical issues in syndromic surveillance; (2) clarify the research, practice, legal, and ethical issues that enable and restrict data sharing; and (3) identify approaches to overcoming barriers in a way that protects privacy and confidentiality while maximizing the usefulness of syndromic and related surveillance systems.

Immediately following September 11, 2001, the District of Columbia Department of Health began a syndromic surveillance program based on emergency room (ER) visits. ER logs are faxed on a daily basis to the health department, where health department staff code them on the basis of chief complaint, recording the number of patients in each of the following syndromic categories: death, sepsis, rash, respiratory complaints, gastrointestinal complaints, unspecified infection, neurological, or other complaints. These data are analyzed daily and when a syndromic category shows an unusually high occurrence, a patient chart review is initiated to determine if the irregularity is a real threat. 

A time series analysis of the data from this system has shown that with the application of a variety of detection algorithms, the syndromic surveillance data does well in identifying the onset of the flu season. In addition, simulation studies using the same data have shown that over a range of simulated outbreak types, the univariate and multivariate CUSUM algorithms performed more effectively than other algorithms. The multivariate CUSUM was preferred to the univariate CUSUM for some but not all outbreak types.

Objective

This paper evaluates an ER syndromic surveillance system based on simulation studies and comparisons with other surveillance systems.

Syndromic surveillance aims to decrease the time to detection of an outbreak compared to traditional surveillance methods. Emergency department (ED) syndromic surveillance systems vary in their methodology and complexity and are usually based on presenting chief complaints. Prior work in ED-based syndromic surveillance has shown conflicting results on agreement between chief complaint and discharge diagnosis, which may be syndrome-dependent. The use of ED discharge diagnosis may improve surveillance validity if it can be done in a timely fashion.

Objective 

The purpose of this study is to characterize the relationship of emergency department chief complaint and final primary ICD-9 diagnosis assigned at the time of emergency department disposition for patients with symptoms and/or ICD-9 codes associated with influenza like illness (ILI) using an electronic medical record.