7b - Surveillance of severe acute respiratory infections associated with SARS-CoV-2, influenza virus and RSV using ICD-10 codes: a case definition accuracy study across five European countries, 2021-2023

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Background : Surveillance of severe acute respiratory infections (SARI) using ICD-10 codes from electronic health records (EHR) lacks consensus on the optimal SARI case-defining codes. We aimed to identify codes that maximise the sensitivity (Se) and positive predictive value (PPV) for the surveillance of SARI associated with SARS-CoV-2, influenza, and respiratory syncytial virus (RSV) in Denmark, Iceland, Malta, Norway, and Spain.

Methods : We included hospitalisations in weeks 21/2021 to 39/2023, with first-three-character respiratory disease or four-character COVID-19 ICD-10 codes; and SARS-CoV-2, influenza virus or RSV tests. We assessed the Se and PPV of individual codes against laboratory confirmation and calculated the combined Se/PPV rank-sum. For each pathogen, we incrementally combined up to 10 codes based on their rank-sum, to identify code sets that maximised the Screening-Marker Index (SMI= Se*PPV): excellent (>=0.81), good (>=0.64), satisfactory (>=0.49), and poor (<0.49) utility.

Results : We included 401,215 hospitalisations. For laboratory-confirmed SARS-CoV-2; code U07.1 (B34, B97 for Denmark) yielded excellent utility in Denmark, Malta, Norway and Spain (Se>=0.88, PPV>=0.90, SMI>=0.82) and good utility in Iceland (Se: 0.97, PPV: 0.81, SMI:0.79). For influenza virus; the utility of J09, J10, J11 was excellent in Denmark, Spain and Norway (Se>=0.84, PPV>=0.97, SMI>=0.83), satisfactory in Malta (Se: 0.56, PPV: 0.93, SMI: 0.52), and poor in Iceland (Se: 0.72, PPV: 0.60, SMI:0.43). For RSV, key codes included J12, J20, J21 and J96, but utility was poor (Se: 0.35-0.91, PPV: 0.25-0.71, SMI: 0.17-0.34).

Conclusions Our findings recommend using codes U07.1, J09-J11 for identifying SARS-CoV-2 and influenza-associated SARI, and assessing the accuracy of four-character codes for RSV (e.g., J12.1). The applicability of our results may depend on surveillance systems’ characteristics, coding practices, and the epidemiology of SARI. Therefore, context-specific assessments are recommended.

Disease groups
Influenza and other respiratory viruses (except SARS-CoV-2)
Health functions
Surveillance
Keywords
Electronic Health Records,International Classification of Diseases,Data Accuracy,SARS-CoV-2,Influenza - Human,Respiratory Syncytial Virus - Human

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Surveillance systems

Authors

Author
Miguel Angel Sanchez Ruiz
Co-authors
M. Sanchez Ruiz(1), D. Marques(2), F. Lomholt(3), L. Vestergaard(4), S. Monge Corella(5), M. Lozano Álvarez(6), G. Aspelund(7), M. Thordardottir(8), A. Dziugyte(9), J. Cauchi(10), E. Seppälä(11), H. Bøås(12), T. Paulsen(13), T. Boere(14), I. Veldhuijzen(15), A. Machado(16), A. Rodrigues(17), M. Hooiveld(18), L. Alves de Sousa(19), A. Torres(20), C. Carvalho(21), B. Nunes(22)
Affiliations
(1)Epiconcept, Paris, France (2,22)Epiconcept, Paris, France (3,4)Department of Infectious Disease Epidemiology and Prevention, Statens Serum Institut, Copenhagen, Denmark (5,6)Department of Communicable Diseases, National Centre of Epidemiology, Institute of Health Carlos III, Madrid, Spain (7,8)Centre for Health Security and Communicable Disease Control, Directorate of Health, Reykjavik, Iceland (9,10)Infectious Disease Prevention and Control Unit (IDCU), Health Promotion and Disease Prevention, Msida, Malta (11,12,13)Department of Infection Control and Vaccines, Norwegian Institute of Public Health, Oslo, Norway (14,15)Centre for Infectious Disease Control, National Institute for Public Health and the Environment (RIVM), Bilthoven, The Netherlands (16,17)Epidemiology Department, National Institute of Health Doctor Ricardo Jorge, Lisboa, Portugal (18)Nivel, Utrecht, The Netherlands (19,20,21)European Centre for Disease Prevention and Control, Solna, Sweden

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