Feasibility and accuracy of linking a heart failure registry to the national claims database using indirect identifiers.


Journal

Archives of cardiovascular diseases
ISSN: 1875-2128
Titre abrégé: Arch Cardiovasc Dis
Pays: Netherlands
ID NLM: 101465655

Informations de publication

Date de publication:
Jan 2023
Historique:
received: 05 09 2022
revised: 02 11 2022
accepted: 03 11 2022
pubmed: 23 12 2022
medline: 9 2 2023
entrez: 22 12 2022
Statut: ppublish

Résumé

Heart failure (HF) registries include rich data on patient inclusion characteristics, but follow-up information is often incomplete. Medicoadministrative databases may provide less clinical information than registries, e.g. on left ventricular ejection fraction (LVEF), but long-term data are exhaustive and reliable. The combination of the two types of database is therefore appealing, but the feasibility and accuracy of such linking are largely unexplored. To assess the feasibility and accuracy of linking an HF registry (FRESH; FREnch Survey on Heart Failure) with the French National Healthcare System database (SNDS). A probabilistic algorithm was developed to link and match patient data included in the FRESH HF registry with anonymized records from the SNDS, which include: hospitalizations and diagnostic codes; all care-related reimbursements by national health system; and deaths. Consistency was assessed between deaths recorded in the registry and in the SNDS. A comparison between the two databases was carried out on several identifiable clinical characteristics (history of HF hospitalization, diabetes, atrial fibrillation, chronic bronchopneumopathy, severe renal failure and stroke) and on events during 1-year follow-up after inclusion. Of 2719 patients included in the FRESH registry (1049 during decompensation; 1670 during outpatient follow-up), 1885 could be matched with a high accuracy of 94.3% for deaths. Mortality curves were superimposable, including curves according to type of HF and LVEF. The rates of missing data in the FRESH registry were 2.3-8.4% for clinical characteristics and 17.5% for hospitalizations during follow-up. The discrepancy rate for clinical characteristics was 3-13%. Hospitalization rates were significantly higher in the SNDS than in the registry cohort. The anonymous matching of an HF research cohort with a national health database is feasible, with a significant proportion of patients being accurately matched, and facilitates combination of clinical data and a reduced rate of losses to follow-up.

Sections du résumé

BACKGROUND BACKGROUND
Heart failure (HF) registries include rich data on patient inclusion characteristics, but follow-up information is often incomplete. Medicoadministrative databases may provide less clinical information than registries, e.g. on left ventricular ejection fraction (LVEF), but long-term data are exhaustive and reliable. The combination of the two types of database is therefore appealing, but the feasibility and accuracy of such linking are largely unexplored.
AIMS OBJECTIVE
To assess the feasibility and accuracy of linking an HF registry (FRESH; FREnch Survey on Heart Failure) with the French National Healthcare System database (SNDS).
METHODS METHODS
A probabilistic algorithm was developed to link and match patient data included in the FRESH HF registry with anonymized records from the SNDS, which include: hospitalizations and diagnostic codes; all care-related reimbursements by national health system; and deaths. Consistency was assessed between deaths recorded in the registry and in the SNDS. A comparison between the two databases was carried out on several identifiable clinical characteristics (history of HF hospitalization, diabetes, atrial fibrillation, chronic bronchopneumopathy, severe renal failure and stroke) and on events during 1-year follow-up after inclusion.
RESULTS RESULTS
Of 2719 patients included in the FRESH registry (1049 during decompensation; 1670 during outpatient follow-up), 1885 could be matched with a high accuracy of 94.3% for deaths. Mortality curves were superimposable, including curves according to type of HF and LVEF. The rates of missing data in the FRESH registry were 2.3-8.4% for clinical characteristics and 17.5% for hospitalizations during follow-up. The discrepancy rate for clinical characteristics was 3-13%. Hospitalization rates were significantly higher in the SNDS than in the registry cohort.
CONCLUSIONS CONCLUSIONS
The anonymous matching of an HF research cohort with a national health database is feasible, with a significant proportion of patients being accurately matched, and facilitates combination of clinical data and a reduced rate of losses to follow-up.

Identifiants

pubmed: 36549971
pii: S1875-2136(22)00228-5
doi: 10.1016/j.acvd.2022.11.002
pii:
doi:

Types de publication

Journal Article

Langues

eng

Sous-ensembles de citation

IM

Pagination

18-24

Informations de copyright

Copyright © 2022 Elsevier Masson SAS. All rights reserved.

Auteurs

Damien Logeart (D)

Paris Cité University, Hôpital Lariboisière, AP-HP, 75010 Paris, France. Electronic address: damien.logeart@aphp.fr.

Thibaud Damy (T)

Hôpital Henri-Mondor, AP-HP, 94000 Créteil, France.

Maxime Doublet (M)

Clinityx, 75008 Paris, France.

Muriel Salvat (M)

Hôpital Michallon, 38700 La Tronche, France.

Christophe Tribouilloy (C)

University Hospital Amiens, 80000 Amiens, France.

Fabrice Bauer (F)

University Hospital Rouen, 76000 Rouen, France.

Jean-Christophe Eicher (JC)

University Hospital Dijon, 21000 Dijon, France.

François Picard (F)

University Hospital Bordeaux, 33000 Bordeaux, France.

Gérald Roul (G)

University Hospital Strasbourg, 67000 Strasbourg, France.

Jean-Noël Trochu (JN)

University Hospital Nantes, 44000 Nantes, France.

Pascal De Groote (P)

University Hospital Lille, 59000 Lille, France.

Nicolas Bihry (N)

Saint-Joseph and Saint-Luc Hospital, 69007 Lyon, France.

Emmanuelle Berthelot (E)

Hôpital Kremlin Bicêtre, AP-HP, 94270 Le Kremlin-Bicêtre, France.

Guillaume Jondeau (G)

Hôpital Bichat, AP-HP, 75018 Paris, France.

Marie-France Seronde (MF)

University Hospital Besançon, 25000 Besançon, France.

François Roubille (F)

University Hospital Montpellier, 34295 Montpellier, France.

Richard Isnard (R)

Hôpital Pitié-Salpétrière, AP-HP, 75013 Paris, France.

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Classifications MeSH