Dataset Information

Claims Data Studies of Direct Oral Anticoagulants Can Achieve Balance in Important Clinical Parameters Only Observable in Electronic Health Records.

ABSTRACT: Claims databases provide information on the effects of direct oral anticoagulants (DOACs) as used in routine care but may not contain important data on clinical characteristics, which may be captured in electronic health records (EHRs). Within a US claims database, we identified patients initiating a DOAC or warfarin between October 2010 and December 2014. Propensity score (PS) matching, 1:1, was used to balance 78 claims-defined baseline characteristics. We evaluated whether balance was achieved in patient characteristics immeasurable in the claims data study by evaluating the balance in clinical information (using absolute standardized differences (aSDs)) from linked EHR data. From a claims data cohort study of 140,187 patients, 5,935 (4.2%) were linked to EHR data. After PS matching, almost all EHR-defined patient characteristics were well balanced (aSD < 0.1). A new user active comparator design with 1:1 PS matching on many patient characteristics improved balance on clinical risk factors observed in EHRs but not in claims data.

SUBMITTER: Huybrechts KF

PROVIDER: S-EPMC6422763 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Claims Data Studies of Direct Oral Anticoagulants Can Achieve Balance in Important Clinical Parameters Only Observable in Electronic Health Records.

Huybrechts Krista F KF Gopalakrishnan Chandrasekar C Franklin Jessica M JM Zint Kristina K Franca Lionel Riou LR Bartels Dorothee B DB Landon Joan J Schneeweiss Sebastian S

Clinical pharmacology and therapeutics 20181111 4

Claims databases provide information on the effects of direct oral anticoagulants (DOACs) as used in routine care but may not contain important data on clinical characteristics, which may be captured in electronic health records (EHRs). Within a US claims database, we identified patients initiating a DOAC or warfarin between October 2010 and December 2014. Propensity score (PS) matching, 1:1, was used to balance 78 claims-defined baseline characteristics. We evaluated whether balance was achieve ...[more]

PMID: 30341980

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Project description:AIM:To evaluate the extent to which balance in unmeasured characteristics of patients with type 2 diabetes (T2DM) was achieved in claims data, by comparing against more detailed information from linked electronic health records (EHR) data. METHODS:Within a large US commercial insurance database and using a cohort design, we identified patients with T2DM initiating linagliptin or a comparator agent within class (ie, another dipeptidyl peptidase-4 inhibitor) or outside class (ie, pioglitazone or a sulphonylurea) between May 2011 and December 2012. We focused on comparators used at a similar stage of diabetes to linagliptin. For each comparison, 1:1 propensity score (PS) matching was used to balance >100 baseline claims-based characteristics, including proxies of diabetes severity and duration. Additional clinical data from EHR were available for a subset of patients. We assessed representativeness of the claims-EHR-linked subset, evaluated the balance of claims- and EHR-based covariates before and after PS-matching via standardized differences (SDs), and quantified the potential bias associated with observed imbalances. RESULTS:From a claims-based study population of 166 613 patients with T2DM, 7219 (4.3%) patients were linked to their EHR data. Claims-based characteristics in the EHR-linked and EHR-unlinked patients were similar (SD < 0.1), confirming the representativeness of the EHR-linked subset. The balance of claims-based and EHR-based patient characteristics appeared to be reasonable before PS-matching and generally improved in the PS-matched population, to be SD < 0.1 for most patient characteristics and SD < 0.2 for select laboratory results and body mass index categories, which was not large enough to cause meaningful confounding. CONCLUSION:In the context of pharmacoepidemiological research on diabetes therapy, choosing appropriate comparison groups paired with a new-user design and 1:1 PS matching on many proxies of diabetes severity and duration improves balance in covariates typically unmeasured in administrative claims datasets, to the extent that residual confounding is unlikely.

Dataset Information

Claims Data Studies of Direct Oral Anticoagulants Can Achieve Balance in Important Clinical Parameters Only Observable in Electronic Health Records.

Publications

Claims Data Studies of Direct Oral Anticoagulants Can Achieve Balance in Important Clinical Parameters Only Observable in Electronic Health Records.

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