Intra-database validation of case-identifying algorithms using reconstituted electronic health records from healthcare claims data

BMC Medical Research Methodology

Bruno Brochet¹  Marine Gross-Goupil²  Marc Debouverie³  Olivier Heinzlef⁴  Sylvestre Le Moulec⁵  Michel Soulié⁶  Mathieu Roumiguié⁶  Stéphanie Lamarque⁷  Pauline Bosco-Levy⁷  Régis Lassalle⁷  Séverine Lignot⁷  Patrick Blin⁷  Abdelilah Abouelfath⁷  Pauline Diez⁷  Nicholas Moore⁷  Nicolas H. Thurin⁷  Jérémy Jové⁷  Magali Rouyer⁷  Cécile Droz-Perroteau⁷  Emmanuelle Bignon⁷  Elisabeth Maillart⁸  Céline Louapre⁹  Francis Guillemin^1,10 

[1] CRC SEP, Neurology Department, CHU de Bordeaux, Bordeaux, France;INSERM U1215, Neurocentre Magendie, Univ. Bordeaux, Bordeaux, France;Department of Medical Oncology, Hôpital Saint André, CHU de Bordeaux, Bordeaux, France;Department of Neurology, CHRU de Nancy, Nancy, France;Université de Lorraine, EA 4360 APEMAC, Nancy, France;Department of Neurology, Hôpital CHI de Poissy/Saint-Germain-en-Laye, Paris, France;Department of Oncology, Clinique Marzet, Pau, France;Department of Urology, University Hospital of Rangueil, CHU de Toulouse, Toulouse, France;INSERM CIC-P1401, Bordeaux PharmacoEpi, Univ. Bordeaux, Bordeaux, France;Neurology Department, Hôpital de la Pitié Salpêtrière, APHP, Paris, France;Sorbonne Université, Institut du cerveau, ICM, Hôpital de la Pitié Salpêtrière, INSERM UMR S 1127, CNRS UMR 7225, Paris, France;Neurology Department, Hôpital de la Pitié Salpêtrière, APHP, Paris, France;Université de Lorraine, EA 4360 APEMAC, Nancy, France;INSERM CIC 1433 Epidémiologie Clinique, CHRU de Nancy, Nancy, France;

关键词: Validation study;    Case-identifying algorithm;    Claims database;    Reconstituted electronic health record;    Multiple sclerosis;    Prostate Cancer;    Positive predictive value;    Negative predictive value;   

DOI  :  10.1186/s12874-021-01285-y

来源: Springer

【 摘 要 】

BackgroundDiagnosis performances of case-identifying algorithms developed in healthcare database are usually assessed by comparing identified cases with an external data source. When this is not feasible, intra-database validation can present an appropriate alternative.ObjectivesTo illustrate through two practical examples how to perform intra-database validations of case-identifying algorithms using reconstituted Electronic Health Records (rEHRs).MethodsPatients with 1) multiple sclerosis (MS) relapses and 2) metastatic castration-resistant prostate cancer (mCRPC) were identified in the French nationwide healthcare database (SNDS) using two case-identifying algorithms. A validation study was then conducted to estimate diagnostic performances of these algorithms through the calculation of their positive predictive value (PPV) and negative predictive value (NPV). To that end, anonymized rEHRs were generated based on the overall information captured in the SNDS over time (e.g. procedure, hospital stays, drug dispensing, medical visits) for a random selection of patients identified as cases or non-cases according to the predefined algorithms. For each disease, an independent validation committee reviewed the rEHRs of 100 cases and 100 non-cases in order to adjudicate on the status of the selected patients (true case/ true non-case), blinded with respect to the result of the corresponding algorithm.ResultsAlgorithm for relapses identification in MS showed a 95% PPV and 100% NPV. Algorithm for mCRPC identification showed a 97% PPV and 99% NPV.ConclusionThe use of rEHRs to conduct an intra-database validation appears to be a valuable tool to estimate the performances of a case-identifying algorithm and assess its validity, in the absence of alternative.

【 授权许可】

CC BY