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Open Access Research article

Supplementing claims data with outpatient laboratory test results to improve confounding adjustment in effectiveness studies of lipid-lowering treatments

Sebastian Schneeweiss1*, Jeremy A Rassen1, Robert J Glynn1, Jessica Myers1, Gregory W Daniel2, Joseph Singer3, Daniel H Solomon1, SeoYoung Kim1, Kenneth J Rothman14, Jun Liu1 and Jerry Avorn1

Author Affiliations

1 Division of Pharmacoepidemiology and Pharmacoeconomics, Department of Medicine, Brigham and Women’s Hospital, 1 Brigham Circle, Suite 3030, Boston, 02120, MA, USA

2 The Brookings Institution, Washington, DC, USA

3 HealthCore Inc, Wilmington, DE, USA

4 RTI Health Solutions, RTP, Durham, NC, USA

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BMC Medical Research Methodology 2012, 12:180  doi:10.1186/1471-2288-12-180

Published: 26 November 2012

Abstract

Background

Adjusting for laboratory test results may result in better confounding control when added to administrative claims data in the study of treatment effects. However, missing values can arise through several mechanisms.

Methods

We studied the relationship between availability of outpatient lab test results, lab values, and patient and system characteristics in a large healthcare database using LDL, HDL, and HbA1c in a cohort of initiators of statins or Vytorin (ezetimibe & simvastatin) as examples.

Results

Among 703,484 patients 68% had at least one lab test performed in the 6 months before treatment. Performing an LDL test was negatively associated with several patient characteristics, including recent hospitalization (OR = 0.32, 95% CI: 0.29-0.34), MI (OR = 0.77, 95% CI: 0.69-0.85), or carotid revascularization (OR = 0.37, 95% CI: 0.25-0.53). Patient demographics, diagnoses, and procedures predicted well who would have a lab test performed (AUC = 0.89 to 0.93). Among those with test results available claims data explained only 14% of variation.

Conclusions

In a claims database linked with outpatient lab test results, we found that lab tests are performed selectively corresponding to current treatment guidelines. Poor ability to predict lab values and the high proportion of missingness reduces the added value of lab tests for effectiveness research in this setting.

Keywords:
Insurance claims data; Laboratory test results; Serum lipid levels; Confounding; Imputation; Pharmacoepidemiology; Lipid lowering therapy; Statin; Ezetimibe