Disease diagnostic coding to facilitate evidence-based medicine: current and future perspectives

Abstract

Technologic advances in information management have rapidly changed laboratory testing and the practice of veterinary medicine. Timely and strategic sampling, same-day assays, and 24-h access to laboratory results allow for rapid implementation of intervention and treatment protocols. Although agent detection and monitoring systems have progressed, and wider tracking of diseases across veterinary diagnostic laboratories exists, such as by the National Animal Health Laboratory Network (NAHLN), the distinction between detection of agent and manifestation of disease is critical to improved disease management. The implementation of a consistent, intuitive, and useful disease diagnosis coding system, specific for veterinary medicine and applicable to multiple animal species within and between veterinary diagnostic laboratories, is the first phase of disease data aggregation. Feedback loops for continuous improvement that could aggregate existing clinical and laboratory databases to improve the value and applications of diagnostic processes and clinical interventions, with interactive capabilities between clinicians and diagnosticians, and that differentiate disease causation from mere agent detection, remain incomplete. Creating an interface that allows aggregation of existing data from clinicians, including final diagnosis, interventions, or treatments applied, and measures of outcomes, is the second phase. Prototypes for stakeholder cooperation, collaboration, and beta testing of this vision are in development and becoming a reality. We focus here on how such a system is being developed and utilized at the Iowa State University Veterinary Diagnostic Laboratory to facilitate evidence-based medicine and utilize diagnostic coding for continuous improvement of animal health and welfare.

Use of smartphone messaging applications to increase diagnostic efficiency in veterinary diagnostic laboratories

“…veterinarians. This approach may not apply to countries that have a broad network of VDLs (Derscheid et al 2021, Trevisan et al 2021. However, in countries with large territorial areas of animal production but do not have a sufficiently broad network of VDLs, the search for alternatives that facilitate access to these VDLs is feasible to increase the diagnosis of cattle diseases.…”

Utilizing productivity and health breeding-to-market information along with disease diagnostic data to identify pig mortality risk factors in a U.S. swine production system

“…The ISU VDL disease diagnostic coding system (Dx Code) is used to succinctly summarize pathologic process(s) and etiology(s) found in submissions of tissues from diseased pigs, used to describe diagnostic alignment between pathogens detected and lesions observed in tissues submitted for diagnostic evaluation. These codes are organized in terms of body system affected/insult type/predominant lesions(s) detected/confirmed or highly likely specific agent(s), and provide a precise etiological diagnosis when data aligns ( 8 ). One or more DX codes are assigned per case depending on these evaluations.…”

Detection and disease diagnosis trends (2017–2022) for Streptococcus suis, Glaesserella parasuis, Mycoplasma hyorhinis, Actinobacillus suis and Mycoplasma hyosynoviae at Iowa State University Veterinary Diagnostic Laboratory

“…A diagnostic case (the unit of analysis) consists of the specimens and associated information provided by the submitting veterinarian for the investigation of a disease event on one swine farm, as well as the test results and diagnostic interpretation provided by the diagnostician. This information is stored in a customized Laboratory Information Management System (LIMS) on a standardized disease diagnosis coding system [ 20 ].…”

“…For disease diagnosis, a pathological evaluation is conducted by ISU VDL diagnosticians, and diagnostic codes (DxCodes) are assigned to the case based on the interpretation of the clinical history, diagnostic testing, and pathological changes. Derscheid et al [ 20 ] highlights that disease diagnostic codes are a summarization of the case and they then serve as a proxy for querying data for stakeholder support, surveillance, and benchmarking of animal diseases in their herds. Briefly, the DxCodes included in this study were related to body system, insult, lesion, and etiology.…”