Determination of the relative economic impact of different molecular-based laboratory algorithms for respiratory viral pathogen detection, including Pandemic (H1N1), using a secure web based platform

<p>Abstract</p> <p>Background</p> <p>During period of crisis, laboratory planners may be faced with a need to make operational and clinical decisions in the face of limited information. To avoid this dilemma, our laboratory utilizes a secure web based platform, Data Integration for Alberta Laboratories (DIAL) to make near real-time decisions.</p> <p>This manuscript utilizes the data collected by DIAL as well as laboratory test cost modeling to identify the relative economic impact of four proposed scenarios of testing for Pandemic H1N1 (2009) and other respiratory viral pathogens.</p> <p>Methods</p> <p>Historical data was collected from the two waves of the pandemic using DIAL. Four proposed molecular testing scenarios were generated: A) Luminex respiratory virus panel (RVP) first with/without US centers for Disease Control Influenza A Matrix gene assay (CDC-M), B) CDC-M first with/without RVP, C) RVP only, and D) CDC-M only. Relative cost estimates of different testing algorithm were generated from a review of historical costs in the lab and were based on 2009 Canadian dollars.</p> <p>Results</p> <p>Scenarios A and B had similar costs when the rate of influenza A was low (< 10%) with higher relative cost in Scenario A with increasing incidence. Scenario A provided more information about mixed respiratory virus infection as compared with Scenario B.</p> <p>Conclusions</p> <p>No one approach is applicable to all conditions. Testing costs will vary depending on the test volume, prevalence of influenza A strains, as well as other circulating viruses and a more costly algorithm involving a combination of different tests may be chosen to ensure that tests results are returned to the clinician in a quicker manner. Costing should not be the only consideration for determination of laboratory algorithms.</p

DIAL: A Platform for real-time Laboratory Surveillance

Laboratory information systems fulfill many of the requirements for individual result management within a public health laboratory. However, access to the systems by data users, timely data extraction, integration, and data analysis are difficult tasks. These difficulties are further complicated by often having multiple laboratory results for specific analytes or related analytes per specimen tested as part of complex laboratory algorithms requiring specialized expertise for result interpretation. We describe DIAL, (Data Integration for Alberta Laboratories), a platform allowing laboratory data to be extracted, interpreted, collated and analyzed in near real-time using secure web based technology, which is adapted from CNPHI’s Canadian Early Warning System (CEWS) technology. The development of DIAL represents a major technical advancement in the public health information management domain, building capacity for laboratory based surveillance

Rubella immunity among pregnant women in a Canadian provincial screening program

BACKGROUND: There are limited recent data on rubella immunity in women of childbearing age in Canada. In the present paper, the proportion of rubella seroreactivity and redundant testing (testing of women previously seropositive when tested by the same physician) in the Alberta prenatal rubella screening program were studied

DIAL: A Platform for real-time Laboratory Surveillance

Laboratory information systems may fulfill many of the requirements for individual result management within a public health laboratory but typically system access by data users, timely data extraction, integration and analysis is difficult. This is further complicated by often having multiple laboratory results for specific analytes or related analytes per specimen tested as part of complex laboratory algorithms requiring specialized expertise for result interpretation. We describe DIAL, (Data Integration for Alberta Laboratories), a platform allowing laboratory data to be extracted, interpreted, collated and analyzed in near real-time using secure web based technology, which is adapted from CNPHI`s Canadian Early Warning System (CEWS) technology. The development of DIAL represents a major technical advancement in the public health information management domain, building capacity for laboratory based surveillance