Lab Matters Fall 2024 | Page 86

APHL 2024 POSTER ABSTRACTS

and future objectives to ensure there is a robust system in place to support national surveillance efforts .

Presenter : Samuel Abrams , samuel . abrams @ aphl . org

Establishing a Minimum Laboratory Data Set for Data Sharing with CDC

D . Mustaquim , Centers for Disease Control and Prevention

Laboratory data are an important component of public health surveillance and has a key role in emergency response , from supporting situational awareness to driving rapid public health action . The Centers for Disease Control and Prevention ( CDC ) currently uses laboratory data in many forms , but this poster focuses on data from partner laboratories ( including public health laboratories ).

In November 2022 , the CDC Advisory Committee to the Director Data and Surveillance Workgroup report recommended to “ define the minimal data necessary for core public health data sources .” The Public Health Data Strategy released in April 2023 defines laboratory data as a core data source and also lists as part of its fourth goal (“ To advance more open and interoperable public health data ”) that a minimal data element set for at least case and laboratory data should be established , in collaboration with state , territorial , local and tribal ( STLT ) partners and CDC programs . To address these recommendations and goals , the Data Policy and Standards Division at CDC is establishing a minimum data set ( MDS ) for laboratory data shared with CDC .

As national standards currently exist for laboratory data exchange ( Electronic Laboratory Reporting ( ELR ) 2.5.1 , Laboratory Results Interface ( LRI )), this effort was based on data concepts in these standards . We additionally compared with United States Core Data for Interoperability ( USCDI and USCDI +), COVID-19 reporting guidance through the CARES Act and CDC program message guides for data received at CDC . We sought consensus among CDC subject matter experts receiving laboratory data , as well as endorsements from CDC leadership and the following external partners : the Council of State and Territorial Epidemiologists ( CSTE ), the Association of Public Health Laboratories ( APHL ) and the American Clinical Laboratory Association ( ACLA ).

This poster will describe this process undertaken to develop this MDS , detailing how key data elements were identified and how support for these was obtained . We will also provide a status update for the MDS .

Presenter : Desiree Mustaquim , dwc6 @ cdc . gov

Evaluating How Well a Laboratory ’ s LIMS Meets Their Requirements

M . Akre 1 , M . Shipman 1 , M . Pentella 2 , S . Hearn 3 , E . Hopkins 4 , J Michael Consulting 1 , University of Iowa 2 , Oregon State Public Health Laboratory 3 , Virginia Division of Consolidated Laboratory Services 4

Evaluating how well a laboratory ’ s laboratory information management system ( LIMS ) meets their requirements is a valuable exercise to determine a long-term informatics strategy . Is the LIMS supporting regulatory compliance , instrument integration and supporting laboratorians to meet long-term goals ? Implementation of a new LIMS is a resource-intensive process for which a laboratory must have a clear justification and plan . A full LIMS evaluation provides the tools a laboratory needs to fully understand their current state , clarify the ideal state , identify gaps between the current state and modernization goals and craft a prioritized plan for addressing those gaps . Several public health laboratories have recently completed a LIMS evaluation which was used to determine plans for long-term use of their current LIMS . Laboratories used the evaluation results to support the replacement of their LIMS or prioritize changes to their current system . Methods : Using a systematized set of tools including surveys , interviews and direct observation , each lab captured their current state , compared this to their ideal state and documented gaps . These gaps were categorized and prioritized to use as a basis for improvements to their current system or a LIMS replacement effort . Results : For laboratories who chose to pursue a LIMS replacement , these artifacts were used to justify the change to a new system and were used to create scripts and evaluation criteria for vendors during a proposal evaluation . Laboratories who chose to stay with their current system used these artifacts to prioritize and scope improvements to the system to better meet the needs of their users . Conclusion : The process of LIMS evaluation is a useful process for any laboratory to assess how well their current system supports their laboratory ’ s mission . By using a data-driven assessment , this evaluation can bolster the laboratory ’ s ability to determine their informatics strategy including both LIMS replacement and improvements to their current system .

Presenter : Tim Longo , tlongo @ jmichael-consulting . com

Improving Data Quality Through LIMS and Vital Statistics Data

J . Vasquez , Ruvos

From September 2021-2023 , Ruvos partnered with the Department of Health in Florida and the Bureau of Public Health Laboratories ( BPHL ) Newborn Screening program in order to improve the quality of critical data used across these teams . Data from the laboratory information management system ( LIMS ) database and the Florida Vital Stats ( FVS ) database were matched and discrepancies were identified in prioritized data fields , resulting in the development and implementation of the Florida NBS and Vital Stats Data Matching Application .

The initial analysis found that there were multiple data quality check points to improve the quality of data being entered into the LIMS system as part of the lab ordering process . These quality checks were 100 % manual , required the use of disparate systems and databases and involved multiple steps and layers to data correction . The processes that were developed through the Florida NBS and Vital Stats Data Matching Application help to ensure that missing data is entered and that data from the specimen card match what is entered into the LIMS system . The program also identified the need to validate data in the specimen card and the LIMS by matching with an external system like vital stats ; and to alert / flag when data entered is incorrect or does not match the external system .

The following project implementation goals were set :

• Match 100 % of births in LIMS with birth records in FVS to identify any discrepancies in prioritized fields : ( Birth date and time / MRN – medical record number / Mother ’ s address / Birth hospital )