Validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis.

OBJECTIVE:Heart 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...

Full description

Bibliographic Details
Main Authors: Natalie McCormick, Diane Lacaille, Vidula Bhole, J Antonio Avina-Zubieta
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2014-01-01
Series:PLoS ONE
Online Access:http://europepmc.org/articles/PMC4134216?pdf=render
id doaj-8cc00584f5864b67bf428fdb836d780e
record_format Article
spelling doaj-8cc00584f5864b67bf428fdb836d780e2020-11-25T01:28:19ZengPublic Library of Science (PLoS)PLoS ONE1932-62032014-01-0198e10451910.1371/journal.pone.0104519Validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis.Natalie McCormickDiane LacailleVidula BholeJ Antonio Avina-ZubietaOBJECTIVE:Heart 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. METHODS:MEDLINE 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. RESULTS:Nineteen 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). CONCLUSIONS:While 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.http://europepmc.org/articles/PMC4134216?pdf=render
collection DOAJ
language English
format Article
sources DOAJ
author Natalie McCormick
Diane Lacaille
Vidula Bhole
J Antonio Avina-Zubieta
spellingShingle Natalie McCormick
Diane Lacaille
Vidula Bhole
J Antonio Avina-Zubieta
Validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis.
PLoS ONE
author_facet Natalie McCormick
Diane Lacaille
Vidula Bhole
J Antonio Avina-Zubieta
author_sort Natalie McCormick
title Validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis.
title_short Validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis.
title_full Validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis.
title_fullStr Validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis.
title_full_unstemmed Validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis.
title_sort validity of heart failure diagnoses in administrative databases: a systematic review and meta-analysis.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2014-01-01
description OBJECTIVE:Heart 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. METHODS:MEDLINE 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. RESULTS:Nineteen 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). CONCLUSIONS:While 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.
url http://europepmc.org/articles/PMC4134216?pdf=render
work_keys_str_mv AT nataliemccormick validityofheartfailurediagnosesinadministrativedatabasesasystematicreviewandmetaanalysis
AT dianelacaille validityofheartfailurediagnosesinadministrativedatabasesasystematicreviewandmetaanalysis
AT vidulabhole validityofheartfailurediagnosesinadministrativedatabasesasystematicreviewandmetaanalysis
AT jantonioavinazubieta validityofheartfailurediagnosesinadministrativedatabasesasystematicreviewandmetaanalysis
_version_ 1725102419990282240