Notifiable Disease

Government reporting of notifiable disease data is common and widespread, though most countries do not report in a machine-readable format. This is despite the WHO International Health Regulations stating that [e]ach State Party shall notify WHO, by the most efficient means of communication available. Data are often in the form of a file that contains text, tables and graphs summarizing weekly or monthly disease counts. This presents a problem when information is needed for more data intensive approaches to epidemiology, biosurveillance and public health. While most nations likely store incident data in a machine-readable format, governments can be hesitant to share data openly for a variety of reasons that include technical, political, economic, and motivational. A survey conducted by LANL of notifiable disease data reporting in over fifty countries identified only a few websites that report data in a machine-readable format. The majority (>70%) produce reports as PDF files on a regular basis. The bulk of the PDF reports present data in a structured tabular format, while some report in natural language or graphical charts. The structure and format of PDF reports change often; this adds to the complexity of identifying and parsing the desired data. Not all websites publish in English, and it is common to find typos and clerical errors. LANL has developed a tool, Epi Archive, to collect global notifiable disease data automatically and continuously and make it uniform and readily accessible.

Objective: Automatically collect and synthesize global notifiable disease data and make it available to humans and computers. Provide the data on the web and within the Biosurveillance Ecosystem (BSVE) as a novel data stream. These data have many applications including improving the prediction and early warning of disease events.

Chlamydia, a sexually transmitted infection which can lead to adverse reproductive health outcomes if untreated, is the most commonly reported nationally notifable disease in the United States.[1] Complete and valid demographic, geographic, and diagnosis-related data are needed to identify trends, describe populations most impacted by disease, identify inequities, and inform and evaluate prevention activities.

Objective

To assess the completeness of key variables included in Chlamydia trachomatis (chlamydia) case report data submitted to the Centers for Disease Control and Prevention (CDC) during 2012.

Completeness of public health information is essential for the accurate assessment of community health progress and disease surveillance. Yet challenges persist with respect to the level of completeness that public health agencies receive in reports submitted by health care providers. Missing and incomplete data can jeopardize information reliability and quality resulting in inaccurate disease evaluation and management (1). Additionally, incomplete data can prolong the time required for disease investigators to complete their work on a reported case. Thus, it is important to determine where the scarcity of information is coming from to recognize the characteristics of provider reporting.

Objective

To examine the completeness of data elements required for notifiable disease surveillance from official, provider-based reports submitted to a local health department.

Disease surveillance is a core public health (PH) function. To manage and adjudicate cases of suspected notifiable disease, PH workers gather data elements about persons, clinical care, and providers from various clinical sources, including providers, laboratories, among others. Current processes often yield incomplete and untimely reporting across different diseases requiring time-consuming follow-up by PH to get needed information [1,2]. To improve the completeness and timeliness of case reporting, health departments have explored accessing EHR systems, which are increasingly available. We examine whether providing PH with EHR access to gather notifiable disease case information affects data completeness.

Objective

To assess the effect of electronic health record (EHR) system access on notifiable disease case data completeness.