Data Quality

Since 2009, Houston Health Department (HHD) uses an electronic disease surveillance system (Maven) to receive ELRs from reporting facilities in the Houston jurisdiction. Currently, two large hospital systems, a blood bank, two large commercial labs, and two public health labs are sending ELRs to Maven. The overall percentage of disease reports received via ELR was over 50%. We hypothesize that the implementation of ELR has improved the timeliness and completeness of disease surveillance.

Objective

Review 5 years of surveillance data post electronic lab reporting (ELR) implementation and 8 years of data prior to ELR, to evaluate timeliness and completeness of disease surveillance.

In South Korea, the NNDSS is organized at three levels: local, provincial, and central. At the local level, physicians report the cased to the Public Health Center (PHC) and PHC conduct control measures. At the provincial level, the PHC reports the cases to the Department of Health (DOH) of the province and DOH obliged to report the cases to the Korea Centers for Disease Control and Prevention (KCDC) and feedback of the surveillance data to PHC and physicians. At the central level, the Disease Web Statistics System (http://is.cdc.go.kr/ dstat/index.jsp) provides real-time data on 54 national notifiable infectious diseases.

Although there are variations according to the disease and surveillance step, the KNNDSS generally functions well in terms of timeliness and Yu et al. reported that 89.7% of mumps, one of the most incident contagious disease in South Korea, reported in 15 days after the physician’s notification. To improve the timeliness of feedback at the provincial level, we explored the KNNDSS data and suggested an evidence based duration for publication of the weekly reports, in consideration of reducing the publication schedule.

Objective

This study will explore the timeliness of the Korean National Notifiable Disease Surveillance System (KNNDSS) at provincial Level, and suggest a reasonable duration for publication the weekly reports to improve timely feedback of infectious disease surveillance data to physicians and community.

Zika virus disease and Zika virus congenital infection are nationally notifiable conditions that became prominent recently as a growing number of travel-associated infections have been identified in the United States. The Centers for Disease Control and Prevention (CDC) have dedicated significant time and effort on determining and addressing the risks and impact of Zika on pregnant women and their babies who are most vulnerable to the disease. CDC relies on two sources of information, reported voluntarily by healthcare providers, to monitor Zika virus disease: ArboNET and the newly established U.S. Zika Pregnancy Registry. A study by IMS Health compared U.S.trends of the Zika virus disease in general and pregnant women with Zika virus disease in particular observed in an IMS healthcare claims database and the CDC ArboNET and the newly established U.S. ZikaPregnancy Registry.

Objective

Demonstrate the value of consolidated claims data from community healthcare providers in Zika Virus Disease surveillance at local level.

CPC provides the 24/7/365 poison hotline for the entire state of North Carolina and currently handles approximately 80,000 calls per year. CPC consultation services that assist callers with poison exposure, diagnosis, optimal patient management, therapy, and patient disposition guidance remain indispensable to the public and health care providers. Poison control center data have been used for years in syndromic surveillance practice as a reliable data source for early event detection. This information has been useful for a variety of public health issues, including environmental exposures, foodborne diseases, overdoses, medication errors, drug identification, drug abuse trends and other information needs. The North Carolina Department of Health and Human Services started formal integration of CPC information into surveillance activities in 2004. CPC call data are uploaded in real time (hourly), 24/7/365, to the NC DETECT state database.

Objective

To describe Carolinas Poison Control Center (CPC) calls data collected in the NC DETECT syndromic surveillance system.

Details about the ONC 2015 Edition certification criteria for Syndromic Surveillance and the related NIST Test Suite were explained previously. We now provide an overview and key information regarding updates to the Test Suite and how it is designed to be used.

Objective

The NIST Syndromic Surveillance Test Suite for 2015 Edition ONC certification testing was published in February 2016. Key information related to the purpose, development, and use of this conformance test tool is provided via snapshots on a poster.

Electronic case reporting (eCR) is defined as the fully or semiautomated generation and electronic transmission of reportable disease case reports from an electronic health record (EHR) system to public health authorities, replacing the historically paper-based process. ECR has been reported to increase the number, accuracy, completeness and timeliness of surveillance case reports. Chicago Department of Public Health (CDPH) collaborated with Alliance of Chicago (AOC) to develop an application to generate electronic provider reports (ePR) for chlamydia (CT) and gonorrhea (GC) cases from the EHR system managed by AOC and send ePR records to the Illinois National Electronic Disease Surveillance System (I-NEDSS). This application was tested in the EHR database of Health Center A in AOC’s network. It is essential to ensure ePR data are accurate, so that public health receives correct information to take actions if needed. Therefore, evaluation is needed to assess ePR records data quality.

Objective

To describe the evaluation process to assess data quality during development of an electronic case report application, and to describe the evaluation results

In spite of the noted benefits of syndromic surveillance, and more than a decade after it started gaining support, the primary use for syndromic surveillance appears to be largely for seasonal and jurisdictional disease monitoring, event response and situational awareness as opposed to its intended purpose of early event detection. Research assessing the user characteristics and standards applied at local public health agencies (LPHA’s) for syndromic surveillance are scarce, and in national surveys epidemiologists frequently tend to utilize their own syndromic surveillance systems as opposed to a national system such as Biosense. While the National Syndromic Surveillance Program (NSSP) has addressed many operational concerns from stakeholders, and is in the process of providing access to the cloud based Biosense platform-along with ESSENCE as a key tool, there is still a paucity of research that exists as to what can be done to improve the utilization of syndromic surveillance systems for its primary purpose of early event detection.

Objective

A mixed methods study is being conducted on the statewide Early Notification of Community Based Epidemics (ESSENCE) system in Missouri to identify factors that can improve the timeliness and identification of outbreaks. This research will provide stakeholders with guidance on how best to implement and improve ESSENCE usage statewide, and by sharing this research input can be solicited on the utility of the applied framework as well as future implications from this body of work.

As a participant in the National Syndromic Surveillance Program (NSSP), the Massachusetts Department of Public Health (MDPH) has worked closely with our statewide Health Information Exchange (HIE) and National Syndromic Surveillance Program (NSSP) technical staff to collect and transmit emergency department (ED) data from eligible hospitals (EHs) to the NSSP. Our goal is to ensure complete and accurate data using a multi-step process beginning with pre-production data and continuing after EHs are sending live data to production.

Objective

To develop a detailed data validation strategy for facilities sending emergency department data to the Massachusetts Syndromic Surveillance program and to evaluate the validation strategy by comparing data quality metrics before and after implementation of the strategy.

Nearly all of the myriad activities (or use cases) in clinical and public health (e.g., patient care, surveillance, community health assessment, policy) involve generating, collecting, storing, analyzing, or sharing data about individual patients or populations. Effective clinical and public health practice in the twenty-first century requires access to data from an increasing array of information systems, including but not limited to electronic health records. However, the quality of data in electronic health record systems can be poor or “unfit for use.” Therefore measuring and monitoring data quality is an essential activity for clinical and public health professionals as well as researchers. 

Objective

To extend an open source platform for measuring the quality of electronic health data by adding functions useful for syndromic surveillance 

Syndromic surveillance is an alternative type of public health surveillance which utilizes pre-diagnostic data sources to detect outbreaks earlier than conventional (laboratory) surveillance and monitor the progression of illnesses in populations. These systems are often noted for their ability to detect a wider range of cases in under- reported illnesses, utilize existing data sources, and alert public health authorities of emerging crises. In addition, they are highly versatile and can be applied to a wide range of illnesses (communicable and non-communicable) and environmental conditions. As a result, their implementation in public health practice is expanding rapidly. This scoping review aimed to identify all existing literature detailing the necessary components in the defining, creating, implementing, and evaluating stages of human infectious disease syndromic surveillance systems.