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Notifiable Condition Reporting

Standard vocabulary facilitates the routing and filtering of laboratory data to various public health programs. In 2008, Council of State and Territorial Epidemiologists (CSTE) developed 67 Technical Implementation Guides (TIGs) that accompany each condition and contain standard codes for NNC reporting. Those TIGs were reviewed by a public health subject matter expert panel (SMEP), in May 2010, consisting of members of the CDC CSTE Laboratory and PHIN Vocabulary and Messaging Communities of Practice Program, and representatives from the Regenstrief Institute and the International Health Terminology Standards Development Organization.

Objective

Electronic laboratory reporting (ELR) has a key role in public health case reporting and case notification. This paper will discuss the current status, problems, and solutions in a vocabulary support of nationally notifiable conditions (NNC) reporting.

Referenced File
Submitted by Magou on

The Duval County Health Department (DCHD) serves a community of over one million people in Jacksonville, FL, USA. Each year, DCHD Epidemiology Program reports an average of 1133 (4-year average) notifiable diseases and conditions (NDC) with the exception of STD/HIV, TB, and viral hepatitis. Within Duval County, emergency medical care is provided by eight local hospitals, including one pediatric facility and a level-1 trauma center. These facilities contribute syndromic surveillance (SS) chief complaint (CC) data to the Electronic Surveillance System for Early Notification of Community-based Epidemics of Florida.

Historically, evaluations of SS systems have used ICD-9 diagnoses as the gold standard to determine predictive values. However, limited studies have surveyed reports of NDC to identify related emergency department (ED) visits and subsequent CC-based syndrome categorization. These data may provide public health investigators insight into health seeking behaviors, interpretation of SS signals, and prevalence of NDC within ED data.

 

Objective

This paper characterizes ED utilization among individuals diagnosed and reported with NDC. Furthermore, it evaluates the subsequent assignment of SS syndromes based on the patient’s CC during their ED visit.

Referenced File
Submitted by hparton on

The Electronic Surveillance System for the Early Notification of Community-based Epidemics (ESSENCE) obtains electronic data from 153 Veterans Affairs (VA) Medical Centers plus outpatient clinics in all 50 states, American Samoa, Guam, Philippines, Puerto Rico, and U.S. Virgin Islands. Currently, there is no centralized VA reporting requirement for nationally notifiable infectious conditions detected in VA facilities. Surveillance and reporting of cases to local public health authorities are performed manually by VA Infection Preventionists and other clinicians. In this analysis, we examined positive predictive value of ICD-9-CM diagnosis codes in VA ESSENCE to determine the utility of this system in electronic detection of reportable conditions in VA.

 

Objective

To determine the utility of ICD-9-CM diagnosis codes in the VA ESSENCE for detection and public health surveillance of nationally notifiable infectious conditions in veteran patients.

Referenced File
Submitted by hparton on

Nationally, vaccine safety is monitored through several systems including Vaccine Adverse Event Reporting System (VAERS), a passive reporting system designed to detect potential vaccine safety concerns. Healthcare providers are encouraged to report adverse events after vaccination to VAERS, whether or not they believe that the vaccine caused the adverse event. The 2009 Pandemic H1N1 influenza vaccine became available in the United States in October 2009. By January 2010, Center for Disease Control and Prevention (Atlanta, GA, USA) estimated that 61 million persons across the United States had received the vaccine. As of January 2010, an estimated 28% of the North Carolina population greater than or equal to six months of age had been vaccinated against 2009 H1N1.

 

Objective

The objectives of this study were: (1) to compare trends in vaccine adverse events identified through emergency department (ED) diagnosis codes and reports from the VAERS, and (2) to determine whether 2009 H1N1 vaccine adverse events identified through VAERS could also be identified using ED diagnosis codes.

Referenced File
Submitted by hparton on

Reporting notifiable conditions to public health authorities by health-care providers and laboratories is fundamental to the prevention, control, and monitoring of population-based disease. To successfully develop community centered health, public health strives to understand and to manage the diseases in its community. Public health surveillance systems provide the mechanisms for public health professionals to ascertain the true disease burden of the population in their community. The information

necessary to determine the disease burden is primarily found in the data generated during clinical care processes.

 

Objective

This poster will present a predictive model to describe the actual number of confirmed cases for an outbreak (H1N1) based on the current number of confirmed cases reported to public health. The model describes the methods used to calculate the number of cases expected in a community based on the lag time in the diagnosis and reporting of these cases to public health departments.

Referenced File
Submitted by hparton on

New York State has implemented a statewide Electronic Clinical Laboratory Reporting System (ECLRS) to which laboratories can electronically submit test results for reportable conditions. The Communicable Disease Electronic Surveillance System (CDESS) was used by 57 Local Health Departments (LHDs) to transfer ECLRS information and initiate investigations. Currently over 98% of licensed clinical labs are reporting via ECLRS. Positive laboratory test results are required to confirm over 80% of communicable diseases and they are often the first indication of a disease. Early detection of disease outbreaks is important for timely implementation of disease prevention and control measures. The space-time permutation scan statistic only requires disease counts, event date and disease location, which are collected from ECLRS and can be used to detect potential disease outbreaks by identifying spatial-temporal lab report clusters.

Objective

This abstract explains how the space-time permutation scan statistic only requires disease counts, event date and disease location, which are collected from ECLRS and can be used to detect potential disease outbreaks by identifying spatial-temporal lab report clusters.

Submitted by knowledge_repo… on

The importance transmitting clinical information to public health for disease surveillance is well-documented. Conventional reporting processes require health care providers to complete paper-based notifiable condition reports which are transmitted by fax and mail to public health agencies. These processes result in incomplete reports, inconsistencies in reporting frequencies among different diseases and reporting delays as well as time-consuming follow-up by public health to get needed information. One strategy to address these issues is to electronically pre-populate report forms with available clinical, lab and patient data to streamline reporting workflows, increase data completeness and, ultimately, provide access to more timely and accurate surveillance data for public health organizations. Prior to implementing an intervention that includes using pre-populated forms, we conducted interviews in clinical and public health settings to identify the barriers and facilitators to adopting and utilizing the forms and their potential impact on workflow and perceived burden. These interviews are a component of a larger mixed methods evaluation that will triangulate pre- and post-intervention quantitative data quality measures with qualitative results.

Objective

Introduction of new health information technologies can produce unanticipated consequences on existing user behaviors, workflow, etc. Prior to implementing a public health reporting intervention, we conducted a series of interviews regarding workflow and perceptions of task burden with respect to notifiable condition reporting.

Submitted by knowledge_repo… on

Clinician reporting of notifiable diseases has historically been slow, labor intensive, and incomplete. Manual and electronic laboratory reporting (ELR) systems have increased the timeliness, efficiency, and completeness of notifiable disease reporting but cannot provide full demographic information about patients, integrate an array of pertinent lab tests to yield a diagnosis, describe patient signs and symptoms, pregnancy status, treatment rendered, or differentiate a new diagnosis or from follow-up of a known old diagnosis. Electronic medical record (EMR) systems are a promising resource to combine the timeliness and completeness of ELR systems with the clinical perspective of clinician initiated reporting. We describe an operational system that detects and reports patients with notifiable diseases to the state health department using EMR data.

 

Objective

To leverage EMR systems to improve the timeliness, completeness, and clinical detail of notifiable disease reporting.

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Submitted by elamb on

Professor Hripcsak rightly points out some of the challenges inherent in disseminating and sustaining robust information systems to automate the detection and reporting of notifiable diseases using data from electronic medical records (EMR). New York City'™s experience with automated tuberculosis identification and notification is a salient reminder that sophisticated technology alone is not enough to ensure broad adoption of automated electronic reporting systems. Substantial resources and ongoing active support by a wide range of public health stakeholders are also essential ingredients. We have attempted to engineer the Electronic medical record Support for Public health (ESP) system to make it suitable for widespread adoption but the ultimate success of this endeavour will depend upon sustained collaboration between many parties including commercial EMR vendors, clinical administrators, state health departments, the Centers for Disease Control and Prevention (CDC), the Council of State and Territorial Epidemiologists (CSTE), and others.

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Submitted by elamb on
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