gms | German Medical Science

67. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS), 13. Jahreskongress der Technologie- und Methodenplattform für die vernetzte medizinische Forschung e. V. (TMF)

21.08. - 25.08.2022, online

Comparing Voluntary LOINC Mappings for the SHIP-4 Medical Laboratory Data Dictionary Before and After Domain Expert Review

Meeting Abstract

  • Esther Inau - Department of Medical Informatics, University Medicine Greifswald, Greifswald, Germany
  • Dörte Radke - Department of Study of Health in Pomerania, University Medicine Greifswald, Greifswald, Germany
  • Susanne Westphal - Department of Study of Health in Pomerania, University Medicine Greifswald, Greifswald, Germany
  • Atinkut Alamirrew Zeleke - Department of Medical Informatics, University Medicine Greifswald, Greifswald, Germany
  • Dagmar Waltemath - Department of Medical Informatics, University Medicine Greifswald, Greifswald, Germany

Deutsche Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie. 67. Jahrestagung der Deutschen Gesellschaft für Medizinische Informatik, Biometrie und Epidemiologie e. V. (GMDS), 13. Jahreskongress der Technologie- und Methodenplattform für die vernetzte medizinische Forschung e.V. (TMF). sine loco [digital], 21.-25.08.2022. Düsseldorf: German Medical Science GMS Publishing House; 2022. DocAbstr. 155

doi: 10.3205/22gmds058, urn:nbn:de:0183-22gmds0584

Veröffentlicht: 19. August 2022

© 2022 Inau et al.
Dieser Artikel ist ein Open-Access-Artikel und steht unter den Lizenzbedingungen der Creative Commons Attribution 4.0 License (Namensnennung). Lizenz-Angaben siehe http://creativecommons.org/licenses/by/4.0/.


Gliederung

Text

Introduction: The Logical Observation Identifiers Names and Codes (LOINC) is a reference terminology used for sharing laboratory data across laboratory systems internationally [1]. The adoption of LOINC has seen great improvement since its inception and it is now a legal requirement that clinical laboratories must fulfill in the United States. With this work we attempt to increase the value of data collected in the Study of Health in Pomerania (SHIP) by annotating the SHIP-4 human-readable laboratory metadata with LOINC codes [2], [3], [4].

Methods: The domain experts preprocessed the SHIP-4 metadata. An expert curator then manually mapped the human-readable institutional codes to LOINC codes (version 2.71). The annotated LOINC metadata was afterwards revised by SHIP domain experts. Following the methodology employed by Lin et al. [5], [6], common characteristics of unmapped institutional codes were documented to gain insight to why some institutional codes had not successfully been mapped to LOINC codes.

Results: We compare the number of institutional codes successfully mapped to LOINC prior to consultation with the SHIP domain experts against the number of codes successfully mapped after consultation. Reasons for unsuccessful annotation include incomplete information where the institutional code does not encompass the required LOINC parts such as “LAB: lipase (µkatal/l)” and lack of LOINC codes that sufficiently code for some institutional codes such as “GFR (CAPA) (ml/min/1,73qm)”. There are also some institutional codes that are unique to the internal processes within the SHIP laboratory and therefore do not require annotations such as “LAB: PTT // prefix for PTT_Z”. Other unsuccessfully mapped institutional codes include those that are not method-specific such as “LAB: fibrinogen (g/l)”.). The revision of annotated codes is ongoing on an iterative basis in consultation with the SHIP domain experts. As of now 10.26% of the SHIP-4 metadata has been successfully annotated.

Discussion: In conducting this work we came to resonate with the sentiment that manual annotation of institutional medical laboratory data to LOINC codes is a time-consuming clerical burden [7], [8]. We have described our experiences and the effort needed to define coverage of SHIP-4 laboratory metadata which may influence the decision to employ LOINC to annotate institutional laboratory (meta)data on a larger scale. We clearly need to train data owners to annotate institutional (meta)data and incentivize them for the same. We also need sufficient preprocessing of metadata to provide correct labels while eliminating noisy labels brought about by imperfect labeling.

Conclusion: This work is a preliminary step towards achieving data interoperability, automatic extraction and FAIRness [9]. It shows the importance of collaboration between the standards experts and the domain experts in the mapping process to avoid work duplication, reduce errors in mapping and save on time and labor in the long term. It also informs the audience on the importance of sufficient (meta)data preprocessing. We anticipate that the provision of curated metadata will improve the value of the SHIP-4 medical laboratory (meta)data, inform the annotation process of the rest of the SHIP medical laboratory metadata and be a valuable contribution to the LOINC community at large.

The authors declare that they have no competing interests.

The authors declare that an ethics committee vote is not required.


References

1.
Nikiema JN, Mougin F, Jouhet V. Building a Graph Representation of LOINC\u174 ? to Facilitate its Alignment to French Terminologies. AMIA Annu Symp Proc AMIA Symp. 2020;2020:933–42.
2.
Ewert R, Ittermann T, Bollmann T, Spielhagen T, Dörr M, Schäper C, et al. Pneumologisch relevante Daten aus der Study of Health in Pomerania (SHIP) – eine Übersicht zu den Kohorten, Methoden und ersten Ergebnissen. Pneumologie. 2017 Jan 23;71(01):17–35.
3.
Semler SC. LOINC: Origin, development of and perspectives for medical research and biobanking – 20 years on the way to implementation in Germany. J Lab Med. 2019 Dec 18;43(6):359–82.
4.
Volzke H, Alte D, Schmidt CO, Radke D, Lorbeer R, Friedrich N, et al. Cohort Profile: The Study of Health in Pomerania. Int J Epidemiol. 2011 Apr 1;40(2):294–307.
5.
Braunstein ML. Health Informatics on FHIR: How HL7’s API is Transforming Healthcare. 2022.
6.
Lin MC, Vreeman DJ, McDonald CJ, Huff SM. A Characterization of Local LOINC Mapping for Laboratory Tests in Three Large Institutions. Methods Inf Med. 2011;50(02):105–14.
7.
Uchegbu C, Jing X. The potentialadoption benefits and challenges of LOINC codes in a laboratory department: a case study. Health Inf Sci Syst. 2017 Dec;5(1):6.
8.
Wei Q, Franklin A, Cohen T, Xu H. Clinical text annotation - what factors are associated with the cost of time? AMIA Annu Symp Proc AMIA Symp. 2018;2018:1552–60.
9.
Inau ET, Sack J, Waltemath D, Zeleke AA. Initiatives, Concepts, and Implementation Practices of FAIR (Findable, Accessible, Interoperable, and Reusable) Data Principles in Health Data Stewardship Practice: Protocol for a Scoping Review. JMIR Res Protoc. 2021 Feb 2;10(2):e22505.