INFORMATICS
Expanding Electronic Laboratory Reporting Beyond COVID-19
By Patina Zarcone , MPH , director , Datapult ; Millie Malai , MPH , technical project manager , Datapult ; Victor Lee , MD , vice president , Clinical Informatics , Clinical Architecture ; Lois Harry , MD , clinical content analyst , Clinical Architecture ; and Brian Garrett , product manager , Datapult
Centralized ELR , Datapult ’ s COVID-19 electronic laboratory reporting service , is built on the AIMS platform and was used throughout the pandemic to report millions of test results to public health . The network of connections established between AIMS and surveillance systems can continue to be used for ELR beyond COVID-19 ; however , this expansion is challenging . For the expanded service ( called Expanded ELR ) to achieve its goal of reducing reporting burden , it must account for each jurisdiction ’ s ELR rules with a one-to-many connection . Datapult , together with Clinical Architecture , is undertaking the work of developing Expanded ELR for this rule-driven , tailored reporting .
Building an Expandable Logic
A modular framework was developed to “ build ” each jurisdiction ’ s ELR rules . These modules allow for uniform “ reportability factors ” ( e . g ., antibody , antigen , nucleic acid ) and “ reportability flavors ” ( e . g ., resulted , positive , negative ) to be combined in any permutation to adhere to each jurisdiction ’ s published rules . To do this , ELR criteria across all jurisdictions were reviewed and decomposed into these modular units of meaning .
Figure 1 . Snippet of ELR Modules
Question
How can one algorithm be built to use for variable jurisdictional reporting criteria ?
How can a data format be applied such that it can be consumed by any jurisdiction ?
If ELR information was not very detailed , could the rules be interpreted uniformly ?
The Challenge to Expanding and Centralized ELR : Variability
Variability was the challenge to creating a system that housed every jurisdiction ’ s ELR rules . Each jurisdiction documents differently their criteria , the detail in that documentation , and the types of test / results that are reportable . For a successful ELR service , questions needed to be resolved .
A Case for Centralizing ELR Criteria
A typical use case may be that a laboratory operates in one locale . There is only one set of reporting rules to understand and one connection that needs to be made . However , if the laboratory is a reference laboratory or national network of sub-laboratories , then multiple different connections would need to be made , with a parallel number of different rule sets and data requirements . The management of this variability posed our greatest challenge .
There are two straight-forward changes that can help significantly decrease the variability to improve timely and highquality public health reporting data .
1 . A common ELR criteria template – jurisdictional reporting criteria for ELR had to be inferred from a list of conditions . Harmonization of
Resolution
Decompose the requirements into modules that can be combined for each jurisdiction ’ s rules — in one algorithm
Create a uniform HL7 v . 2.5.1 output that refl ects all non-negotiables from each jurisdiction
Utilize assumptions and reconcile directly with each jurisdiction
laboratory-specific reporting rules could further distinguish between case reporting and laboratory reporting requirements .
2 . Making the rules easier to find – it was a challenge to find the right documentation . ELR rules for all jurisdictions in one place and in one uniform template would simplify requirement gathering .
Public Health Filling Public Health Gaps
The distances between “ non-traditional ” public health data partners , public health laboratories , public health agencies and healthcare providers is narrowing , and as it does , the disconnects and misalignment are thrust into everyone ’ s view .
Expanded ELR directly serves public health agencies ’ infectious disease surveillance programs . It singularly demonstrates the power of public health to build solutions and fill gaps that have existed in the shadows . It links the data pathways out of testing laboratories into epidemiologists . It highlights the wide variation in published reporting requirements across the country . It seeks to reconcile the variability of acceptable data standards . It is a much-needed step , and in the right direction . g
30 LAB MATTERS Fall 2023
PublicHealthLabs @ APHL APHL . org