Dataset Information

Validity of Diagnostic Codes for Acute Stroke in Administrative Databases: A Systematic Review.

ABSTRACT:

Objective

To conduct a systematic review of studies reporting on the validity of International Classification of Diseases (ICD) codes for identifying stroke in administrative data.

Methods

MEDLINE and EMBASE were searched (inception to February 2015) for studies: (a) Using administrative data to identify stroke; or (b) Evaluating the validity of stroke codes in administrative data; and (c) Reporting validation statistics (sensitivity, specificity, positive predictive value (PPV), negative predictive value (NPV), or Kappa scores) for stroke, or data sufficient for their calculation. Additional articles were located by hand search (up to February 2015) of original papers. Studies solely evaluating codes for transient ischaemic attack were excluded. Data were extracted by two independent reviewers; article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool.

Results

Seventy-seven studies published from 1976-2015 were included. The sensitivity of ICD-9 430-438/ICD-10 I60-I69 for any cerebrovascular disease was ? 82% in most [? 50%] studies, and specificity and NPV were both ? 95%. The PPV of these codes for any cerebrovascular disease was ? 81% in most studies, while the PPV specifically for acute stroke was ? 68%. In at least 50% of studies, PPVs were ? 93% for subarachnoid haemorrhage (ICD-9 430/ICD-10 I60), 89% for intracerebral haemorrhage (ICD-9 431/ICD-10 I61), and 82% for ischaemic stroke (ICD-9 434/ICD-10 I63 or ICD-9 434&436). For in-hospital deaths, sensitivity was 55%. For cerebrovascular disease or acute stroke as a cause-of-death on death certificates, sensitivity was ? 71% in most studies while PPV was ? 87%.

Conclusions

While most cases of prevalent cerebrovascular disease can be detected using 430-438/I60-I69 collectively, acute stroke must be defined using more specific codes. Most in-hospital deaths and death certificates with stroke as a cause-of-death correspond to true stroke deaths. Linking vital statistics and hospitalization data may improve the ascertainment of fatal stroke.

SUBMITTER: McCormick N

PROVIDER: S-EPMC4546158 | biostudies-literature | 2015

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Validity of Diagnostic Codes for Acute Stroke in Administrative Databases: A Systematic Review.

McCormick Natalie N Bhole Vidula V Lacaille Diane D Avina-Zubieta J Antonio JA

PloS one 20150820 8

<h4>Objective</h4>To conduct a systematic review of studies reporting on the validity of International Classification of Diseases (ICD) codes for identifying stroke in administrative data.<h4>Methods</h4>MEDLINE and EMBASE were searched (inception to February 2015) for studies: (a) Using administrative data to identify stroke; or (b) Evaluating the validity of stroke codes in administrative data; and (c) Reporting validation statistics (sensitivity, specificity, positive predictive value (PPV), ...[more]

PMID: 26292280

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Project description:Breast, lung and colorectal cancers constitute the most common cancers worldwide and their epidemiology, related health outcomes and quality indicators can be studied using administrative healthcare databases. To constitute a reliable source for research, administrative healthcare databases need to be validated. The aim of this protocol is to perform the first systematic review of studies reporting the validation of International Classification of Diseases 9th and 10th revision codes to identify breast, lung and colorectal cancer diagnoses in administrative healthcare databases.This review protocol has been developed according to the Preferred Reporting Items for Systematic Reviews and Meta-Analyses Protocol (PRISMA-P) 2015 statement. We will search the following databases: MEDLINE, EMBASE, Web of Science and the Cochrane Library, using appropriate search strategies. We will include validation studies that used administrative data to identify breast, lung and colorectal cancer diagnoses or studies that evaluated the validity of breast, lung and colorectal cancer codes in administrative data. The following inclusion criteria will be used: (1) the presence of a reference standard case definition for the disease of interest; (2) the presence of at least one test measure (eg, sensitivity, positive predictive values, etc) and (3) the use of data source from an administrative database. Pairs of reviewers will independently abstract data using standardised forms and will assess quality using a checklist based on the Standards for Reporting of Diagnostic accuracy (STARD) criteria.Ethics approval is not required. We will submit results of this study to a peer-reviewed journal for publication. The results will serve as a guide to identify appropriate case definitions and algorithms of breast, lung and colorectal cancers for researchers involved in validating administrative healthcare databases as well as for outcome research on these conditions that used administrative healthcare databases.CRD42015026881.

Project description:ObjectiveHeart failure (HF) is an important covariate and outcome in studies of elderly populations and cardiovascular disease cohorts, among others. Administrative data is increasingly being used for long-term clinical research in these populations. We aimed to conduct the first systematic review and meta-analysis of studies reporting on the validity of diagnostic codes for identifying HF in administrative data.MethodsMEDLINE and EMBASE were searched (inception to November 2010) for studies: (a) Using administrative data to identify HF; or (b) Evaluating the validity of HF codes in administrative data; and (c) Reporting validation statistics (sensitivity, specificity, positive predictive value [PPV], negative predictive value, or Kappa scores) for HF, or data sufficient for their calculation. Additional articles were located by hand search (up to February 2011) of original papers. Data were extracted by two independent reviewers; article quality was assessed using the Quality Assessment of Diagnostic Accuracy Studies tool. Using a random-effects model, pooled sensitivity and specificity values were produced, along with estimates of the positive (LR+) and negative (LR-) likelihood ratios, and diagnostic odds ratios (DOR = LR+/LR-) of HF codes.ResultsNineteen studies published from 1999-2009 were included in the qualitative review. Specificity was ≥95% in all studies and PPV was ≥87% in the majority, but sensitivity was lower (≥69% in ≥50% of studies). In a meta-analysis of the 11 studies reporting sensitivity and specificity values, the pooled sensitivity was 75.3% (95% CI: 74.7-75.9) and specificity was 96.8% (95% CI: 96.8-96.9). The pooled LR+ was 51.9 (20.5-131.6), the LR- was 0.27 (0.20-0.37), and the DOR was 186.5 (96.8-359.2).ConclusionsWhile most HF diagnoses in administrative databases do correspond to true HF cases, about one-quarter of HF cases are not captured. The use of broader search parameters, along with laboratory and prescription medication data, may help identify more cases.

Project description:BACKGROUND:Validation of administrative databases for cerebrovascular diseases is crucial for epidemiological, outcome, and health services research. The aim of this study was to validate ICD-9 codes for hemorrhagic or ischemic stroke in administrative databases, to use them for a comprehensive assessment of the burden of disease in terms of major outcomes, such as mortality, hospital readmissions, and use of healthcare resources. METHODS:We considered the hospital discharge abstract database of the Umbria Region (890,000 residents). Source population was represented by patients aged >18 discharged from hospital with a diagnosis of hemorrhagic or ischemic stroke between 2012 and 2014 using ICD-9-CM codes in primary position. We randomly selected and reviewed medical charts of cases and non-cases from hospitals. For case ascertainment we considered symptoms and instrumental tests reported in the medical charts. Diagnostic accuracy measures were computed using 2x2 tables. RESULTS:We reviewed 767 medical charts for cases and 78 charts for non-cases. Diagnostic accuracy measures were: subarachnoid hemorrhage: sensitivity (SE) 100% (95% CI: 97%-100%), specificity (SP) 96% (90-99), positive predictive value (PPV) 98% (93-100), negative predictive value (NPV) 100% (95-100); intracerebral hemorrhage: SE 100% (97-100), SP 98% (91-100), PPV 98% (94-100), NPV 100% (95-100); other and unspecified intracranial hemorrhage: SE 100% (97-100), SP 96% (90-99), PPV 98% (93-100), NPV 100% (95-100); ischemic stroke due to occlusion and stenosis of precerebral arteries: SE 99% (94-100), SP 66 (57-75), PPV 70% (61-77), NPV 99% (93-100); occlusion of cerebral arteries: SE 100% (97-100), SP 87% (78-93), PPV 91% (84-95), NPV 100% (95-100); acute, but ill-defined, cerebrovascular disease: SE 100% (97-100), SP 78% (69-86), PPV % 83 (75-89), NPV 100% (95-100). CONCLUSIONS:Case ascertainment for both ischemic and hemorrhagic stroke showed good or high levels of accuracy within the regional healthcare databases in Umbria. This database can confidently be employed for epidemiological, outcome, and health services research related to any type of stroke.

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Dataset Information

Validity of Diagnostic Codes for Acute Stroke in Administrative Databases: A Systematic Review.

Objective

Methods

Results

Conclusions

Publications

Validity of Diagnostic Codes for Acute Stroke in Administrative Databases: A Systematic Review.

Similar Datasets

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