132 research outputs found
Literature Review
Each issue of Value-Based Purchasing will provide a summary of recent articles from the published VBP literature. In this issue, we spotlight several recent publications regarding pay-for-performance programs and financial incentives for quality care
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Innovative research methods for studying treatments for rare diseases: methodological review
Objective: To examine methods for generating evidence on health outcomes in patients with rare diseases. Design: Methodological review of existing literature. Setting: PubMed, Embase, and Academic Search Premier searched for articles describing innovative approaches to randomized trial design and analysis methods and methods for conducting observational research in patients with rare diseases. Main outcome measures We assessed information related to the proposed methods, the specific rare disease being studied, and outcomes from the application of the methods. We summarize methods with respect to their advantages in studying health outcomes in rare diseases and provide examples of their application. Results: We identified 46 articles that proposed or described methods for studying patient health outcomes in rare diseases. Articles covered a wide range of rare diseases and most (72%) were published in 2008 or later. We identified 16 research strategies for studying rare disease. Innovative clinical trial methods minimize sample size requirements (n=4) and maximize the proportion of patients who receive active treatment (n=2), strategies crucial to studying small populations of patients with limited treatment choices. No studies describing unique methods for conducting observational studies in patients with rare diseases were identified. Conclusions: Though numerous studies apply unique clinical trial designs and considerations to assess patient health outcomes in rare diseases, less attention has been paid to innovative methods for studying rare diseases using observational data
Dimension reduction and shrinkage methods for high dimensional disease risk scores in historical data
Abstract Background Multivariable confounder adjustment in comparative studies of newly marketed drugs can be limited by small numbers of exposed patients and even fewer outcomes. Disease risk scores (DRSs) developed in historical comparator drug users before the new drug entered the market may improve adjustment. However, in a high dimensional data setting, empirical selection of hundreds of potential confounders and modeling of DRS even in the historical cohort can lead to over-fitting and reduced predictive performance in the study cohort. We propose the use of combinations of dimension reduction and shrinkage methods to overcome this problem, and compared the performances of these modeling strategies for implementing high dimensional (hd) DRSs from historical data in two empirical study examples of newly marketed drugs versus comparator drugs after the new drugs’ market entry—dabigatran versus warfarin for the outcome of major hemorrhagic events and cyclooxygenase-2 inhibitor (coxibs) versus nonselective non-steroidal anti-inflammatory drugs (nsNSAIDs) for gastrointestinal bleeds. Results Historical hdDRSs that included predefined and empirical outcome predictors with dimension reduction (principal component analysis; PCA) and shrinkage (lasso and ridge regression) approaches had higher c-statistics (0.66 for the PCA model, 0.64 for the PCA + ridge and 0.65 for the PCA + lasso models in the warfarin users) than an unreduced model (c-statistic, 0.54) in the dabigatran example. The odds ratio (OR) from PCA + lasso hdDRS-stratification [OR, 0.64; 95 % confidence interval (CI) 0.46–0.90] was closer to the benchmark estimate (0.93) from a randomized trial than the model without empirical predictors (OR, 0.58; 95 % CI 0.41–0.81). In the coxibs example, c-statistics of the hdDRSs in the nsNSAID initiators were 0.66 for the PCA model, 0.67 for the PCA + ridge model, and 0.67 for the PCA + lasso model; these were higher than for the unreduced model (c-statistic, 0.45), and comparable to the demographics + risk score model (c-statistic, 0.67). Conclusions hdDRSs using historical data with dimension reduction and shrinkage was feasible, and improved confounding adjustment in two studies of newly marketed medications
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Primary care clinicians’ perceptions about antibiotic prescribing for acute bronchitis: a qualitative study
Background: Clinicians prescribe antibiotics to over 65% of adults with acute bronchitis despite guidelines stating that antibiotics are not indicated. Methods: To identify and understand primary care clinician perceptions about antibiotic prescribing for acute bronchitis, we conducted semi-structured interviews with 13 primary care clinicians in Boston, Massachusetts and used thematic content analysis. Results: All the participants agreed with guidelines that antibiotics are not indicated for acute bronchitis and felt that clinicians other than themselves were responsible for overprescribing. Barriers to guideline adherence included 6 themes: (1) perceived patient demand, which was the main barrier, although some clinicians perceived a recent decrease; (2) lack of accountability for antibiotic prescribing; (3) saving time and money; (4) other clinicians’ misconceptions about acute bronchitis; (5) diagnostic uncertainty; and (6) clinician dissatisfaction in failing to meet patient expectations. Strategies to decrease inappropriate antibiotic prescribing included 5 themes: (1) patient educational materials; (2) quality reporting; (3) clinical decision support; (4) use of an over-the-counter prescription pad; and (5) pre-visit triage and education by nurses to prevent visits. Conclusions: Clinicians continued to cite patient demand as the main reason for antibiotic prescribing for acute bronchitis, though some clinicians perceived a recent decrease. Clinicians felt that other clinicians were responsible for inappropriate antibiotic prescribing and that better pre-visit triage by nurses could prevent visits and change patients’ expectations. Electronic supplementary material The online version of this article (doi:10.1186/s12875-014-0194-5) contains supplementary material, which is available to authorized users
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Effect of smoking on comparative efficacy of antiplatelet agents: systematic review, meta-analysis, and indirect comparison
Objective: To evaluate whether smoking status is associated with the efficacy of antiplatelet treatment in the prevention of cardiovascular events. Design: Systematic review, meta-analysis, and indirect comparisons. Data sources Medline (1966 to present) and Embase (1974 to present), with supplementary searches in databases of abstracts from major cardiology conferences, the Cumulative Index to Nursing and Allied Health (CINAHL) and the CAB Abstracts databases, and Google Scholar. Study selection Randomized trials of clopidogrel, prasugrel, or ticagrelor that examined clinical outcomes among subgroups of smokers and nonsmokers. Data extraction Two authors independently extracted all data, including information on the patient populations included in the trials, treatment types and doses, definitions of clinical outcomes and duration of follow-up, definitions of smoking subgroups and number of patients in each group, and effect estimates and 95% confidence intervals for each smoking status subgroup. Results: Of nine eligible randomized trials, one investigated clopidogrel compared with aspirin, four investigated clopidogrel plus aspirin compared with aspirin alone, and one investigated double dose compared with standard dose clopidogrel; these trials include 74 489 patients, of whom 21 717 (29%) were smokers. Among smokers, patients randomized to clopidogrel experienced a 25% reduction in the primary composite clinical outcome of cardiovascular death, myocardial infarction, and stroke compared with patients in the control groups (relative risk 0.75, 95% confidence interval 0.67 to 0.83). In nonsmokers, however, clopidogrel produced just an 8% reduction in the composite outcome (0.92, 0.87 to 0.98). Two studies investigated prasugrel plus aspirin compared with clopidogrel plus aspirin, and one study investigated ticagrelor plus aspirin compared with clopidogrel plus aspirin. In smokers, the relative risk was 0.71 (0.61 to 0.82) for prasugrel compared with clopidogrel and 0.83 (0.68 to 1.00) for ticagrelor compared with clopidogrel. Corresponding relative risks were 0.92 (0.83 to 1.01) and 0.89 (0.79 to 1.00) among nonsmokers. Conclusions: In randomized clinical trials of antiplatelet drugs, the reported clinical benefit of clopidogrel in reducing cardiovascular death, myocardial infarction, and stroke was seen primarily in smokers, with little benefit in nonsmokers
Beta-blocker initiation and adherence after hospitalization for acute myocardial infarction.
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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Active safety monitoring of newly marketed medications in a distributed data network: application of a semi-automated monitoring system
We developed a semi-automated active monitoring system that uses sequential matched-cohort analyses to assess drug safety across a distributed network of longitudinal electronic healthcare data. In a retrospective analysis, we showed that the system would have identified cerivastatin-induced rhabdomyolysis. In this study, we evaluated whether the system would generate alerts for three drug-outcome pairs: rosuvastatin and rhabdomyolysis (known null association), rosuvastatin and diabetes mellitus, and telithromycin and hepatotoxicity (two examples for which alerting would be questionable). During >5 years of monitoring, rate differences (RDs) comparing rosuvastatin to atorvastatin were -0.1 cases of rhabdomyolysis per 1,000 person-years (95% CI, -0.4, 0.1) and -2.2 diabetes cases per 1,000 person-years (95% CI, -6.0, 1.6). The RD for hepatotoxicity comparing telithromycin to azithromycin was 0.3 cases per 1,000 person-years (95% CI, -0.5, 1.0). In a setting in which false positivity is a major concern, the system did not generate alerts for three drug-outcome pairs
The “Dry-Run” Analysis: A Method for Evaluating Risk Scores for Confounding Control
A propensity score (PS) model's ability to control confounding can be assessed by evaluating covariate balance across exposure groups after PS adjustment. The optimal strategy for evaluating a disease risk score (DRS) model's ability to control confounding is less clear. DRS models cannot be evaluated through balance checks within the full population, and they are usually assessed through prediction diagnostics and goodness-of-fit tests. A proposed alternative is the "dry-run" analysis, which divides the unexposed population into "pseudo-exposed" and "pseudo-unexposed" groups so that differences on observed covariates resemble differences between the actual exposed and unexposed populations. With no exposure effect separating the pseudo-exposed and pseudo-unexposed groups, a DRS model is evaluated by its ability to retrieve an unconfounded null estimate after adjustment in this pseudo-population. We used simulations and an empirical example to compare traditional DRS performance metrics with the dry-run validation. In simulations, the dry run often improved assessment of confounding control, compared with the C statistic and goodness-of-fit tests. In the empirical example, PS and DRS matching gave similar results and showed good performance in terms of covariate balance (PS matching) and controlling confounding in the dry-run analysis (DRS matching). The dry-run analysis may prove useful in evaluating confounding control through DRS models
Disease risk score as a confounder summary method: systematic review and recommendations: DRS AS A CONFOUNDER SUMMARY METHOD
To systematically examine trends and applications of the disease risk score (DRS) as a confounder summary method
Impact of ALLHAT publication on antihypertensive prescribing patterns in Regione Emilia-Romagna, Italy
Background and objective: Studies from the US and Canada observed changes in antihypertensive prescribing patterns in accordance with Antihypertensive and Lipid-Lowering Treatment to Prevent Heart Attack Trial (ALLHAT) study findings immediately after the study\u27s publication, but little is known about the impact of ALLHAT in Italy. The objective of this study was to examine antihypertensive prescribing patterns in Regione Emilia-Romagna (RER), Italy, following the publication of the ALLHAT main results.
Methods: We conducted a time series analysis using automated pharmacy data of approximately 4 million RER residents between 1 January 2000 and 31 December 2003. We computed monthly relative percentages of prescriptions for all antihypertensive medications and separately for all new antihypertensives defined as no recorded antihypertensive use in the previous year. A stepwise auto-regressive forecasting model based on data prior to the ALLHAT publication was used to estimate predicted relative percentages for the 12 months following the ALLHAT publication. Observed and predicted values were compared.
Results and discussion: Use of thiazide-type diuretics showed a general increasing trend over the study period, but the difference between the observed and predicted values reached statistical significance only for new prescriptions in October 2003 (3·71% vs. 2·32%; P = 0·0170). The relative percentage of new angiotensin-converting enzyme inhibitor and angiotensin receptor blocker (ACE/ARB) prescriptions was higher than predicted for the months May to August 2003 (P \u3c 0·05), but no significant differences were observed for total ACE/ARB prescriptions. Modest changes in patterns of prescribing of calcium channel blockers and α-blockers were observed.
Conclusion: We found little evidence that the ALLHAT study had an impact on antihypertensive prescribing patterns in RER in the year following their publication
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