Using pharmacy data to identify those with chronic conditions in Emilia Romagna, Italy

Maio, Vittorio; Yuen, Elaine J.; Rabinowitz, Carol; Louis, Daniel Z.; Jimbo, Masahito; Donatini, Andrea; Mall, Sabine; Taroni, Francesco

doi:10.1258/135581905774414259

Cited by 70 publications

(69 citation statements)

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“…We found that the largest proportions of persons suffered from pain, rheumatologic conditions and cardiovascular diseases, including hypertension. These findings are in line with previous studies in Italy estimating prevalence of chronic diseases showing highest rates in cardiovascular diseases and rheumatologic conditions [12,13]. On the other hand, our results are different from the Dutch estimates based on the PCG-model showing a low prevalence rate in rheumatologic conditions [19].…”

Section: Discussionsupporting

confidence: 73%

Identifying patients with chronic conditions using pharmacy data in Switzerland: an updated mapping approach to the classification of medications

et al. 2013

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BackgroundQuantifying population health is important for public health policy. Since national disease registers recording clinical diagnoses are often not available, pharmacy data were frequently used to identify chronic conditions (CCs) in populations. However, most approaches mapping prescribed drugs to CCs are outdated and unambiguous. The aim of this study was to provide an improved and updated mapping approach to the classification of medications. Furthermore, we aimed to give an overview of the proportions of patients with CCs in Switzerland using this new mapping approach.MethodsThe database included medical and pharmacy claims data (2011) from patients aged 18 years or older. Based on prescription drug data and using the Anatomical Therapeutic Chemical (ATC) classification system, patients with CCs were identified by a medical expert review. Proportions of patients with CCs were calculated by sex and age groups. We constructed multiple logistic regression models to assess the association between patient characteristics and having a CC, as well as between risk factors (diabetes, hyperlipidemia) for cardiovascular diseases (CVD) and CVD as one of the most prevalent CCs.ResultsA total of 22 CCs were identified. In 2011, 62% of the 932′612 subjects enrolled have been prescribed a drug for the treatment of at least one CC. Rheumatologic conditions, CVD and pain were the most frequent CCs. 29% of the persons had CVD, 10% both CVD and hyperlipidemia, 4% CVD and diabetes, and 2% suffered from all of the three conditions. The regression model showed that diabetes and hyperlipidemia were strongly associated with CVD.ConclusionsUsing pharmacy claims data, we developed an updated and improved approach for a feasible and efficient measure of patients’ chronic disease status. Pharmacy drug data may be a valuable source for measuring population’s burden of disease, when clinical data are missing. This approach may contribute to health policy debates about health services sources and risk adjustment modelling.

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Section: Discussionsupporting

confidence: 73%

Identifying patients with chronic conditions using pharmacy data in Switzerland: an updated mapping approach to the classification of medications

et al. 2013

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“…Comorbidities were ascertained from non-cardiac hospital admissions with primary diagnoses for other conditions that may increase mortality risk [18]. We also used the Chronic Condition Drug Group (CCDG), a prescription drug-based comorbidity index [19]. CCDGs were developed in the same RER database and have been applied in other published studies [14,15,20].…”

Section: Covariatesmentioning

confidence: 99%

Beta-blocker initiation and adherence after hospitalization for acute myocardial infarction

Maio

Marino

Robeson

et al. 2011

European Journal of Cardiovascular Prevention & Rehabilitat

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Aims: We sought to: (1) estimate the proportion of patients who initiated beta-blocker therapy after acute myocardial infarction (AMI) in Regione Emilia-Romagna (RER); (2) examine predictors of post-AMI beta-blocker initiation; and (3) assess adherence to such therapy. Methods and Results: Using healthcare claims data covering all of RER, we identified a cohort of 24,367 patients with a hospitalization for AMI between 2004 and 2007, who were discharged from the hospital alive and without contraindications to beta-blocker therapy. We estimated the proportion of eligible patients with at least one prescription for a beta-blocker following discharge and performed a multivariable logistic regression analysis to identify independent predictors of post-AMI beta-blocker initiation. We computed the proportion of days covered (PCD) as a measure of medication adherence at 6 and 12 months post-discharge. Following discharge, 16,383 (67%) cohort members initiated beta-blocker therapy. Independent predictors of beta-blocker initiation included age and receipt of invasive procedures during hospitalization, such as coronary artery bypass graft surgery (odds ratio [OR], 2.37; 95% confidence interval [CI], 2.00–2.81), percutaneous transluminal coronary angioplasty (OR, 1.42; 95% CI, 1.31–1.54), and cardiac catheterization (OR, 1.21; 95% CI, 1.11–1.32). Among initiators, adherence to beta-blocker treatment at 6 and 12 months was low and decreased in each study year. Conclusion: Overall, use of and adherence to post-AMI beta-blocker therapy was suboptimal in RER between 2004 and 2007. Older patients and those with indicators of frailty were less likely to initiate therapy. The proportion of patients adherent at 6 and 12 months decreased over time.

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“…As a result, there are multiple data features that could potentially be used for case ascertainment. For example, osteoporosis drug treatments have been proposed for case ascertainment in pharmacy databases [10,21].…”

Section: What Is New?mentioning

confidence: 99%

Using multiple data features improved the validity of osteoporosis case ascertainment from administrative databases

Lix

Yogendran

Leslie

et al. 2008

Journal of Clinical Epidemiology

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Using pharmacy data to identify those with chronic conditions in Emilia Romagna, Italy

Cited by 70 publications

References 0 publications

Identifying patients with chronic conditions using pharmacy data in Switzerland: an updated mapping approach to the classification of medications

Identifying patients with chronic conditions using pharmacy data in Switzerland: an updated mapping approach to the classification of medications

Beta-blocker initiation and adherence after hospitalization for acute myocardial infarction

Using multiple data features improved the validity of osteoporosis case ascertainment from administrative databases

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