Validation of methods to identify people with idiopathic inflammatory myopathies using hospital episode statistics.
ICD-10
epidemiology
findability
hospital episode statistics
myositis
rare diseases
Journal
Rheumatology advances in practice
ISSN: 2514-1775
Titre abrégé: Rheumatol Adv Pract
Pays: England
ID NLM: 101736676
Informations de publication
Date de publication:
2022
2022
Historique:
received:
21
07
2022
accepted:
25
10
2022
entrez:
19
12
2022
pubmed:
20
12
2022
medline:
20
12
2022
Statut:
epublish
Résumé
Hospital episode statistics (HES) are routinely recorded at every hospital admission within the National Health Service (NHS) in England. This study validates diagnostic ICD-10 codes within HES as a method of identifying cases of idiopathic inflammatory myopathies (IIMs). All inpatient admissions at one NHS Trust between 2010 and 2020 with relevant diagnostic ICD-10 codes were extracted from HES. Hospital databases were used to identify all outpatients with IIM, and electronic care records were reviewed to confirm coding accuracy. Total hospital admissions were calculated from NHS Digital reports. The sensitivity and specificity of each code and code combinations were calculated to develop an optimal algorithm. The optimal algorithm was tested in a sample of admissions at another NHS Trust. Of the 672 individuals identified by HES, 510 were confirmed to have IIM. Overall, the positive predictive value (PPV) was 76% and sensitivity 89%. Combination algorithms achieved PPVs between 89 and 94%. HES can also predict the presence of IIM-associated interstitial lung disease (ILD) with a PPV of 79% and sensitivity of 71%. The optimal algorithm excluded children (except JDM code M33.0), combined M33.0, M33.1, M33.9, M36.0, G72.4, M60.8 and M33.2, and included M60.9 only if it occurred alongside an ILD code (J84.1, J84.9 or J99.1). This produced a PPV of 88.9% and sensitivity of 84.2%. Retesting this algorithm at another NHS Trust confirmed a high PPV (94.4%). IIM ICD-10 code combinations in HES have high PPVs and sensitivities. Algorithms tested in this study could be applied across all NHS Trusts to enable robust and cost-effective whole-population research into the epidemiology of IIM.
Identifiants
pubmed: 36532317
doi: 10.1093/rap/rkac102
pii: rkac102
pmc: PMC9749128
doi:
Types de publication
Journal Article
Langues
eng
Pagination
rkac102Informations de copyright
© The Author(s) 2022. Published by Oxford University Press on behalf of the British Society for Rheumatology.
Références
Curr Rheumatol Rep. 2018 Mar 17;20(4):18
pubmed: 29550929
Ann Intern Med. 2001 Jun 19;134(12):1087-95
pubmed: 11412048
Rheumatol Adv Pract. 2018 Sep 17;2(2):rky035
pubmed: 31431976
Clin Med (Lond). 2002 Jan-Feb;2(1):34-7
pubmed: 11871636
Rheumatology (Oxford). 2021 Apr 6;60(4):1902-1909
pubmed: 33271595
Ann Rheum Dis. 2015 Aug;74(8):1551-6
pubmed: 24695011
Eur Respir Rev. 2015 Jun;24(136):216-38
pubmed: 26028634
RMD Open. 2016 Dec 26;2(2):e000342
pubmed: 28123774
J Public Health (Oxf). 2012 Mar;34(1):138-48
pubmed: 21795302
Eur J Hum Genet. 2020 Feb;28(2):165-173
pubmed: 31527858
Rheumatology (Oxford). 2015 Jan;54(1):50-63
pubmed: 25065005
N Engl J Med. 1991 Nov 21;325(21):1487-98
pubmed: 1658649
Curr Rheumatol Rep. 2013 Sep;15(9):359
pubmed: 23888366
BMJ. 2015 Oct 28;351:h5527
pubmed: 26511519
Ann Rheum Dis. 2018 Jan;77(1):40-47
pubmed: 28814428
J Rheumatol. 2011 Aug;38(8):1612-6
pubmed: 21532057