Dataset Information

Validity of ICD-9 and ICD-10 codes used to identify acute liver injury: A study in three European data sources.

ABSTRACT: PURPOSE:Validating cases of acute liver injury (ALI) in health care data sources is challenging. Previous validation studies reported low positive predictive values (PPVs). METHODS:Case validation was undertaken in a study conducted from 2009 to 2014 assessing the risk of ALI in antidepressants users in databases in Spain (EpiChron and SIDIAP) and the Danish National Health Registers. Three ALI definitions were evaluated: primary (specific hospital discharge codes), secondary (specific and nonspecific hospital discharge codes), and tertiary (specific and nonspecific hospital and outpatient codes). The validation included review of patient profiles (EpiChron and SIDIAP) and of clinical data from medical records (EpiChron and Denmark). ALI cases were confirmed when liver enzyme values met a definition by an international working group. RESULTS:Overall PPVs (95% CIs) for the study ALI definitions were, for the primary ALI definition, 84% (60%-97%) (EpiChron), 60% (26%-88%) (SIDIAP), and 74% (60%-85%) (Denmark); for the secondary ALI definition, 65% (45%-81%) (EpiChron), 40% (19%-64%) (SIDIAP), and 70% (64%-77%) (Denmark); and for the tertiary ALI definition, 25% (18%-34%) (EpiChron), 8% (7%-9%) (SIDIAP), and 47% (42%-52%) (Denmark). The overall PPVs were higher for specific than for nonspecific codes and for hospital discharge than for outpatient codes. The nonspecific code "unspecified jaundice" had high PPVs in Denmark. CONCLUSIONS:PPVs obtained apply to patients using antidepressants without preexisting liver disease or ALI risk factors. To maximize validity, studies on ALI should prioritize hospital specific discharge codes and should include hospital codes for unspecified jaundice. Case validation is required when ALI outpatient cases are considered.

SUBMITTER: Forns J

PROVIDER: S-EPMC6618105 | biostudies-literature | 2019 Jul

REPOSITORIES: biostudies-literature

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Validity of ICD-9 and ICD-10 codes used to identify acute liver injury: A study in three European data sources.

Forns Joan J Cainzos-Achirica Miguel M Hellfritzsch Maja M Morros Rosa R Poblador-Plou Beatriz B Hallas Jesper J Giner-Soriano Maria M Prados-Torres Alexandra A Pottegård Anton A Cortés Jordi J Castellsagué Jordi J Jacquot Emmanuelle E Deltour Nicolas N Perez-Gutthann Susana S Pladevall Manel M

Pharmacoepidemiology and drug safety 20190606 7

<h4>Purpose</h4>Validating cases of acute liver injury (ALI) in health care data sources is challenging. Previous validation studies reported low positive predictive values (PPVs).<h4>Methods</h4>Case validation was undertaken in a study conducted from 2009 to 2014 assessing the risk of ALI in antidepressants users in databases in Spain (EpiChron and SIDIAP) and the Danish National Health Registers. Three ALI definitions were evaluated: primary (specific hospital discharge codes), secondary (spe ...[more]

PMID: 31172633

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Project description:BACKGROUND:The phecode system was built upon the International Classification of Diseases, Ninth Revision, Clinical Modification (ICD-9-CM) for phenome-wide association studies (PheWAS) using the electronic health record (EHR). OBJECTIVE:The goal of this paper was to develop and perform an initial evaluation of maps from the International Classification of Diseases, 10th Revision (ICD-10) and the International Classification of Diseases, 10th Revision, Clinical Modification (ICD-10-CM) codes to phecodes. METHODS:We mapped ICD-10 and ICD-10-CM codes to phecodes using a number of methods and resources, such as concept relationships and explicit mappings from the Centers for Medicare & Medicaid Services, the Unified Medical Language System, Observational Health Data Sciences and Informatics, Systematized Nomenclature of Medicine-Clinical Terms, and the National Library of Medicine. We assessed the coverage of the maps in two databases: Vanderbilt University Medical Center (VUMC) using ICD-10-CM and the UK Biobank (UKBB) using ICD-10. We assessed the fidelity of the ICD-10-CM map in comparison to the gold-standard ICD-9-CM phecode map by investigating phenotype reproducibility and conducting a PheWAS. RESULTS:We mapped >75% of ICD-10 and ICD-10-CM codes to phecodes. Of the unique codes observed in the UKBB (ICD-10) and VUMC (ICD-10-CM) cohorts, >90% were mapped to phecodes. We observed 70-75% reproducibility for chronic diseases and <10% for an acute disease for phenotypes sourced from the ICD-10-CM phecode map. Using the ICD-9-CM and ICD-10-CM maps, we conducted a PheWAS with a Lipoprotein(a) genetic variant, rs10455872, which replicated two known genotype-phenotype associations with similar effect sizes: coronary atherosclerosis (ICD-9-CM: P<.001; odds ratio (OR) 1.60 [95% CI 1.43-1.80] vs ICD-10-CM: P<.001; OR 1.60 [95% CI 1.43-1.80]) and chronic ischemic heart disease (ICD-9-CM: P<.001; OR 1.56 [95% CI 1.35-1.79] vs ICD-10-CM: P<.001; OR 1.47 [95% CI 1.22-1.77]). CONCLUSIONS:This study introduces the beta versions of ICD-10 and ICD-10-CM to phecode maps that enable researchers to leverage accumulated ICD-10 and ICD-10-CM data for PheWAS in the EHR.

Project description:The study aims to identify 'missing' diagnoses amongst paediatric admissions during the UK's first national lockdown, compared with the previous 5 years. A retrospective observational cohort study of all children (0-15 years) attending for urgent care across Oxfordshire, during the first UK lockdown in 2020, compared to matched dates in 2015-2019, across two paediatric hospitals providing secondary care, including one with tertiary services. Our outcome measures were changes in numbers of patients attending and inpatient diagnoses (using ICD-10 classification) during the first 2020 lockdown, compared with the previous 5 years, were used. We found that total Emergency Department (ED) attendances (n = 4030) and hospital admissions (n = 1416) during the first UK lockdown were reduced by 56.8% and 59.4%, respectively, compared to 2015-2019 (5-year means n = 7446.8 and n = 2491.6, respectively). Proportions of patients admitted from ED and length of stay were similar across 2015-2020. ICD-10 diagnoses in lockdown of 2020 (n = 2843) versus matched 2015-2019 dates (n = 19,946) demonstrated significantly greater neoplasm diagnoses (p = 0.0123). Of diagnoses 'missing' in lockdown, 80% were categorised as infectious diseases or their sequelae and 20% were non-specific pains/aches/malaise and accidental injury/poisonings.Conclusions: Pandemic public health measures significantly altered paediatric presentations. Oxfordshire hospitals had a 58% reduction in ED attendances/inpatient admissions, with 'missing' diagnoses predominantly infection-related illnesses. These are likely driven by a combination of the following: (1) public health infection control measures successfully reducing disease transmission, (2) parents/carers keeping mild/self-limiting disease at home, and (3) pandemic-related healthcare anxieties. Prospective studies are needed to ensure referral pathways identify vulnerable children, those with social concerns, and avoid delayed presentation. What is Known: • Significant reductions of paediatric ED attendances and inpatient admissions are reported globally, throughout national and regional lockdowns for COVID-19. • Previous studies (supplemental table 5) examined only ED diagnoses or specific inpatient diagnoses during lockdown periods, demonstrating reductions of infectious diseases, accidents/injuries, and safeguarding referrals. What is New: • Using ICD-10 coding, robustly controlling for five historical years and adopting a hypothesis-independent analysis, demonstrating 80% of 'missing' inpatient diagnoses during national COVID-19 lockdown were infectious diseases or its sequelae, the remainder being non-specific aches/pains/malaise and accidental injuries/poisonings. • Greater numbers of neoplasms and other specific diagnoses were detected during lockdown, including greater documentation of co-morbidities and incidental findings.

Dataset Information

Validity of ICD-9 and ICD-10 codes used to identify acute liver injury: A study in three European data sources.

Publications

Validity of ICD-9 and ICD-10 codes used to identify acute liver injury: A study in three European data sources.

Similar Datasets

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