An Evaluation of Electronic Laboratory Data Quality and a Health Information Exchange

Electronic laboratory reporting (ELR) was demonstrated just over a decade ago to be an effective method to improve the timeliness of reporting as well as the number of reports submitted to public health agencies. The quality of data (inc. completeness) in information systems across all industries and organizations is often poor, and anecdotal reports in the surveillance literature suggest that ELR may not improve the completeness of the data in the submitted reports.

 

Objective 

May 02, 2019

An information visualization approach to improving data quality

The Public Health - Seattle & King County syndromic surveillance system has been collecting emergency department (ED) data since 1999. These data include hospital name, age, sex, zip code, chief complaint, diagnoses (when available), disposition, and a patient and visit key. Data are collected for 19 of 20 King County EDs, for visits that occurred the previous day.

May 02, 2019

Visualizing Data Quality: Tools and Views

Distribute is a national emergency department syndromic surveillance project developed by the International Society for Disease Surveillance for influenza-like-illness (ILI) that integrates data from existing state and local public health department surveillance systems. The Distribute project provides graphic comparisons of both ILI-related clinical visits across jurisdictions and a national picture of ILI. Unlike other surveillance systems, Distribute is designed to work solely with summarized (aggregated) data which cannot be traced back to the un-aggregated 'raw' data.

May 02, 2019

How good is your data?

Distribute is a national emergency department syndromic surveillance project developed by the International Society for Disease Surveillance (ISDS) for influenza-like-illness (ILI) that integrates data from existing state and local public health department surveillance systems. The Distribute is a national emergency department syndromic surveillance project developed by the International Society for Disease Surveillance (ISDS) for influenza-like-illness (ILI) that integrates data from existing state and local public health department surveillance systems.

May 02, 2019

Data Collection, Management and Surveillance: Using Smartphones in Smart Ways

This presentation will focus on health managment information systems (HMIS) and surveillance activities in resource limited settings. The presenters will discuss how systems could be enhanced using smart phones or other innovative technologies and provide examples of ongoing applications in the field.

Panelists

Marion McNabb, MPH, DrPh Candidate, Program Manager, DGAP, Center for Global Health and Development, Boston University School of Public Health

October 19, 2017

Data quality in federated disease surveillance: using variability as an indicator of quality

Most, if not all, disease surveillance systems are federated in the sense that hospitals, doctors’ offices, pharmacies are the source of most surveillance data. Although a health department may request or mandate that these organizations report data, we are not aware of any requirements about the method of data collection or audits or other measures of quality control.

June 14, 2019

Description of the quality of public health case reports received at a local health department and potential impact on workflow

When a reportable condition is identified, clinicians and laboratories are required to report the case to public health authorities. These case reports help public health officials to make informed decisions and implement appropriate control measures to prevent the spread of disease. Incomplete or delayed case reports can result in new occurrences of disease that could have been prevented.

June 14, 2019

Meaningful use and public health surveillance: to travel fast or far?

There is an ancient African proverb that states, ‘If you want to travel fast, travel alone; if you want to travel far, travel together.’ This paper examines the issue of whether public health can and should ‘go it alone’ in efforts for creating linkages between clinical care systems and the public health sector, as part of meaningful use requirements. ‘Going it alone’ in this circumstances refers to whether public health should seek to require data flows, through meaningful use requirements, that meet its work flow needs but do not add value to clinical work flows.

June 18, 2019

Impact of alternate diagnoses on the accuracy of influenza-like illness case definition used for H1N1 screening in the emergency department

In June 2009, the CDC defined a confirmed case of H1N1 as a person with an ILI and laboratory confirmed novel influenza A H1N1 virus infection. ILI is defined by the CDC as fever and cough and/or sore throat, in the absence of a known cause other than influenza. ILI cases are usually reported without accounting for alternate diagnoses (that is, pneumonia). Therefore, evaluation is needed to determine the impact of alternate diagnoses on the accuracy of the ILI case definition.

Objective

June 18, 2019

Assessing address data quality for public health surveillance in Montreal

In Montreal, notifiable diseases are reported to the Public Health Department (PHD). Of 44, 250 disease notifications received in 2009, up to 25% had potential address errors. These can be introduced during transcription, handwriting interpretation and typing at various stages of the process, from patients, labs and/or physicians, and at the PHD. Reports received by the PHD are entered manually (initial entry) into a database. The archive personnel attempts to correct omissions by calling reporting laboratories or physicians.

June 18, 2019

Pages

Contact Us

NSSP Community of Practice

Email: syndromic@cste.org

 

This website is supported by Cooperative Agreement # 6NU38OT000297-02-01 Strengthening Public Health Systems and Services through National Partnerships to Improve and Protect the Nation's Health between the Centers for Disease Control and Prevention (CDC) and the Council of State and Territorial Epidemiologists. Its contents are solely the responsibility of the authors and do not necessarily represent the official views of CDC. CDC is not responsible for Section 508 compliance (accessibility) on private websites.

Site created by Fusani Applications