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Surveillance

The utility of specific sources of data for surveillance, and the quality of those data, are an ingoing issue in public health(1). Syndromic surveillance is typically conducted as a secondary use of data collected as part of routine clinical practice, and as such the data can be of high quality for the clinical use but of lower quality for the purpose of surveillance. A major data quality issue with surveillance data is that of timeliness. Data used in surveillance typically arrive as a periodic process, inherently creating a delay in the availability of the data for surveillance purposes. Surveillance data are often collected from multiple sources, each with their own processes and delays, creating a situation where the data available for surveillance are accrued piecemeal.

Objective

This abstract discusses the quality issues identified in using Distribute. From 2006 to 2012, the ISDS ran Distribute (2), a surveillance system for monitoring influenza like illness (ILI) and gastroenteritis (GI) ED visits on a nationwide basis. This system collected counts for ILI, GI and total ED visits, aggregated to the level of jurisdiction. The primary data quality issue faced with the Distribute system was that of timeliness due to accrual lag; variable delays in the receipt of surveillance data from sources by jurisdictions together with variable delays in the reporting of aggregate data from jurisdictions to Distribute resulted in data which accrued over time(3).

Submitted by knowledge_repo… on

In response to major epidemic and pandemic outbreaks, WHO-AFRO and its Member States have adopted the Integrated Disease Surveillance and Response (IDSR) strategy to address International Health Regulations (2005) as well as individual Member State’s national disease control objectives. Significant progress has been made scaling-up capacity for disease surveillance and response using the IDSR guidelines, including implementation of IHR, the WHO African Region has experienced many challenges in designing, developing and implementing electronic surveillance systems. Over the past decade or more, many local and international stakeholders have independently pursued solutions for electronic surveillance and reporting in African countries. This has resulted in multiple systems of varying effectiveness and minimum interoperability due, in part, to limited agreement among stakeholders on data collecting and reporting standards. This complicated situation prevents most African countries from reaping the full benefits of having electronic systems to help detect, report, and respond to endemic, emerging and priority disease threats.

Objective

We report on the development of the African Surveillance Informatics Governing Board (ASIGB) as a conceptual strategy for strengthening eSurveillance in the African Region.

Submitted by knowledge_repo… on

Infectious disease surveillance is important for disease control as well as to inform prevention and treatment [1]. While influenza surveillance data coverage and quality has improved significantly in recent years due to resource investments and advances in information technology, the need remains for improvements in data dissemination to the wider community.

Objective

This paper describes a review of modes and styles of the online dissemination of national influenza surveillance data.

Referenced File
Submitted by elamb on

A Quest Diagnostics Incorporated – CDC collaboration in 2000  pioneered  exploration  of  test  ordering data to enhance infectious diseasessurveillance1. This  year’s  unexpected shortage of vaccine and reports of human illness caused by avian influenza  A  (H5N1)  in  Asia2  heightened concern about  influenza and focused attention on moving toward more complete, real time surveillance. We extended our previous collaboration to explore the use of  the Quest Diagnostics Corporate Informatics Data Warehouse (QIDW) as a tool for surveillance of influenza.

Objective

To explore the potential of a large commercial data warehouse for influenza surveillance.

Referenced File
Submitted by elamb on

The  ability  to  accurately  predict  influenza  infection  by  symptoms  and  local  epidemiology  prior  to  lab  confirmation  warrants  further  study  and  is  particular  concern as the threat of pandemic flu heightens.  Antiviral drugs are effective when given within 48 hours of  symptom  onset,  but  this  usually  precludes  culture  confirmation. Further,  rapid  tests  can  be  clinically  helpful   but   lack   the   sensitivity   of   viral   culture. Hence,  ILI  symptoms  are  a  potentially  important  covariate  in  the  early  diagnosis  of  flu. However,  gaps  remain  in  several  areas  of  flu  symptom  research,  including  knowledge  of  potential  differences  between  symptoms  of  Influenza  A  and  of  Influenza  B  [1]. Therefore,  an  examination  of  symptoms  generally  associated  with  Influenza  infection  was  begun,  as  well  as  an  examination  of  symptoms  specifically  associated with Flu A and Flu B. An additional focus in  this  study  was  to  evaluate  the  performance  of  the  current  ILI  case  definition  used  by  the  DoD  flu  program.  This definition is useful to identify individuals who  are  likely  to  be  infected  with  influenza,  as  the  ability  to  capture  and  characterize  novel  strains  of  influenza is an important component to this program. Better yields of influenza mean less time and money spent processing negative specimens.

Objective

This study describes clinical symptoms reported in conjunction with influenza, non-influenza respiratory viruses, and negative viral cultures from the Department of Defense (DoD) Global Influenza Surveillance Program; influenza-like illness (ILI) case questionnaires were linked to corresponding laboratory specimen results for the 2005-06 influenza season for analysis.

Referenced File
Submitted by elamb on

The IBBS is part of the Indonesian MoH HIV Surveillance System, which include Serological Surveillance, Behavioral Surveillance, Reproductive Tract Infection Survey, and monthly HIV/AIDS facilitybased (hospitals, HCs, VCT Sites) monthly reports. The IBBS 2011 was conducted in 11 provinces (22 districts/municipalities) encompassing eight Most At Risk Populations (MARPs) – injection drug users, transsexuals, men who have sex with men, youths, inmates, mobile men, direct female sex workers (FSWs), and indirect FSWs. Data of 442 direct FSWs of the Jayapura Municipality and Jayawijaya District (Papua Province) showed that 406 (91.85%) have sex with partners who did not use condoms. Of these 406 FSWs 60 (14.78%) were HIV positive and 231 (56.89%) were STD positive.

 

Objective

To analyze the Integrated Behavioral & Biological Surveillance (IBBS) 2011 data for designing a condom utilization program.

Submitted by teresa.hamby@d… on

Hospital emergency departments in Cook and surrounding counties currently send data to the Cook County Department of Public Health (CCDPH) instance of ESSENCE on CCDPH servers. The cloud instance of ESSENCE has been enhanced to receive and export all meaningful use data elements in the meaningful use format. The NATO summit provided the opportunity for a demonstration project to assess the ability of an Amazon GovCloud instance of ESSENCE to ingest and process meaningful use data, and to export meaningful use surveillance data to the Cook County Locker in BioSense 2.0.

Objective

In May 2012, thousands of protesters, descended on Chicago during the NATO Summit to voice their concern about social and economic inequality. Given the increased numbers of international and domestic visitors to the Windy City and the tension surrounding protesting during the summit, increased monitoring for health events within the city and Chicago metropolitan region was advised. This project represents the first use of cloud technology to support monitoring for a high profile event.

Submitted by uysz on

Data consisting of counts or indicators aggregated from multiple sources pose particular problems for data quality monitoring when the users of the aggregate data are blind to the individual sources. This arises when agencies wish to share data but for privacy or contractual reasons are only able to share data at an aggregate level. If the aggregators of the data are unable to guarantee the quality of either the sources of the data or the aggregation process then the quality of the aggregate data may be compromised. This situation arose in the Distribute surveillance system (1). Distribute was a national emergency department syndromic surveillance project developed by the International Society for Disease Surveillance for influenza-like-illness (ILI) that integrated data from existing state and local public health department surveillance systems, and operated from 2006 until mid 2012. Distribute was designed to work solely with aggregated data, with sites providing data aggregated from sources within their jurisdiction, and for which detailed information on the un-aggregated ‘raw’ data was unavailable. Previous work (2) on Distribute data quality identified several issues caused in part by the nature of the system: transient problems due to inconsistent uploads, problems associated with transient or long-term changes in the source make up of the reporting sites and lack of data timeliness due to individual site data accruing over time rather than in batch. Data timeliness was addressed using prediction intervals to assess the reliability of the partially accrued data (3). The types of data quality issues present in the Distribute data are likely to appear to some extent in any aggregate data surveillance system where direct control over the quality of the source data is not possible.

Objective

In this work we present methods for detecting both transient and long-term changes in the source data makeup.

 

Submitted by uysz on

INDICATOR is a multi-stream open source platform for biosurveillance and outbreak detection, currently focused on Champaign County in Illinois[1]. It has been in production since 2008 and is currently receiving data from emergency departments, patient advisory nurse call center, outpatient convenient care clinic, school absenteeism, animal control, and weather sources. Long term scalability was however compromised during the 2009 H1N1 influenza pandemic as immediate public health needs took priority over our systematic development plan. With the impending addition of veterinary clinic data and recognizing that the health of a community also depends on animal and environmental factors, we decided to revisit the INDICATOR architecture and redesign it to be a more holistic and scalable system. We also decided to revisit the data submission format, keeping in line with the philosophy of making opportunistic secondary use of as much data about the health of a community that we can obtain.

Objective

To redesign INDICATOR for One Health, establish a common data format, and provide for long term scalability.

Submitted by uysz on

Researchers have demonstrated benefits to identifying and developing interventions for patients that frequently seek healthcare services in the ED. The New Yorker Magazine, recently published an article titled The Hot Spotters, summarizing work being done in the United States to lower medical costs by giving the neediest patients better healthcare (1). In Camden, NJ, Physician Jeffrey Brenner closed his regular practice to focus on Hot Spotter patients (directing resources and brainpower to help their improvement) and measured a 40% reduction in hospital inpatient and ED visits and a 56% medical cost reduction for the first 36 Hot Spotters. A 2008 NH Office of Medicaid Business and Policy (OMBP) outpatient Medicaid ED frequency visit study was conducted, which cited that frequent ED users were more likely to have higher costs and rates of illness or disease than all Medicaid members (2). It was noted that increased prevention and wellness could reduce frequent ED use and increase cost savings (5% of the NH Medicaid population contributed to approximately 38% of ED costs). The NH Division of Public Health Services initiated a pilot project to examine NH Emergency Department (ED) surveillance data to identify high utilizer patients and realize improved health benefits and medical cost reductions.

Objective:

To develop a manageable surveillance methodology to detect Emergency Department (ED) patients with the highest healthcare utilization, and monitor their targeted treatment improvement and medical health cost reductions over time for overall improvements in statewide health.

 

Submitted by Magou on
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