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Purpose: The purpose of this paper is to provide guidance on the evaluation of data linkage quality through the development of a checklist for reporting key elements of the linkage process., Methods: Responding to a call for manuscripts from the International Society for Pharmacoepidemiology (ISPE), a working group including international representation from the academic, industry, and contract research, and regulatory sectors was formed to develop a checklist for evaluation of data linkage performance and reporting data linkage specifically for pharmacoepidemiologic research. This checklist expands on the reporting of studies conducted using observational routinely collected health data specific to pharmacoepidemiology (RECORD-PE) guidelines., Results: A key aspect of data linkage evaluation for pharmacoepidemiology is to articulate how a linkage process was performed and its accuracy in terms of validation and verification of the resulting linked data. This study generates a checklist, which covers domains including data sources, linkage variables, linkage methods, linkage results, and linkage evaluation. For each domain, specific recommendations provide a clear and transparent assessment of the linkage process., Conclusions: Linking data sources can help to enrich analytic databases to more accurately define study populations, enable adjustment for confounding, and improve the capture of health outcomes. Clear and transparent reporting of data linkage processes will help to increase confidence in the evidence generated from these data by allowing researchers and end users to critically assess the potential for bias owing to the data linkage process., (© 2019 John Wiley & Sons, Ltd.)

Purpose: Long-acting beta agonists (LABAs) when used without concomitant inhaled corticosteroids (ICS) increase the risk of asthma-related deaths, but the effect on asthma-related death of LABA used in combination with ICS therapy is unknown. To address this question, we explored the feasibility of conducting an observational study using multiple US health care data sources., Methods: Retrospective cohort study to evaluate the likelihood of getting an upper 95% confidence limit ≤1.4 for the asthma mortality rate ratio and ≤0.40 per 10 000 person-years for the mortality rate difference, assuming no effect of new use of combined LABA + ICS (versus non-LABA maintenance therapy) on asthma mortality. Ten research institutions executed centrally distributed analytic code based on a standard protocol using an extracted (2000-2010) persistent asthma cohort (asthma diagnosis and ≥4 asthma medications in 12 months). Pooled results were analyzed by the coordinating center. Asthma deaths were ascertained by linkage with the National Death Index., Results: In a cohort of 994 627 persistent asthma patients (2.4 million person-years; 278 asthma deaths), probabilities of the upper 95% confidence limit for effect estimates being less than targeted values, assuming a null relation, were about 0.05. Modifications in cohort and exposure definitions increased exposed person-time and outcome events, but study size remained insufficient to attain study goals., Conclusions: Even with 10 data sources and a 10-year study period, the rarity of asthma deaths among patients using certain medications made it infeasible to study the association between combined LABA + ICS and asthma mortality with our targeted level of study precision. Copyright © 2016 John Wiley & Sons, Ltd., (Copyright © 2016 John Wiley & Sons, Ltd.)

Purpose: Our aim was to identify individuals with Churg-Strauss syndrome (CSS) among asthma drug users, based on patterns of diagnostic and procedural codes (termed 'algorithms') contained in automated claims data., Methods: A retrospective study was conducted among patients who had been dispensed asthma drugs at three HMOs. Individuals who received > or =3 dispensings of an asthma drug during any consecutive 12-month period beginning 1 January 1994 through 20 June 2000 were identified. Information on patient age, gender, enrollment status, asthma drugs dispensed, inpatient and outpatient diagnoses and procedures were obtained from the HMO automated databases. Twelve combinations of diagnostic and billing codes ('algorithms') were developed using the claims data to identify potential cases of CSS. Chart reviews blinded to drug exposure were performed using a standardized abstraction form. A rheumatologist reviewed abstracted information on all subjects, and those who met two or more American College of Rheumatology (ACR) criteria for CSS were further reviewed by two clinical experts. Cases were classified as unlikely, possible, or probable/definite CSS. Each clinical expert independently rated the cases; disagreements were resolved by consensus., Results: A total of 185 604 patients who had been dispensed asthma drugs were identified. Three hundred fifty subjects were selected for chart review, and 15 were classified as having 'probable/definite' CSS. The algorithms that were most successful in identifying patients with CSS were as follows: (1) two or more codes for vasculitis (13 confirmed cases from 129 reviewed; positive predictive value 10%); (2) codes for both vasculitis and neurologic symptoms (6 confirmed cases from 15 reviewed; positive predictive value 40%) and (3) codes for both eosinophilia and vasculitis (4 confirmed cases from 5 reviewed; positive predictive value 80%)., Conclusion: Automated claims data can be used to identify patients with CSS. This approach can facilitate better epidemiologic study of the risk factors for the condition., (2003 John Wiley & Sons, Ltd.)