388 research outputs found
PRM252 A Practical Guide To Adding Patient Heterogeneity Into Phase Iii Trials: Results from Imi Getreal Wp2
Identifying and visualizing variability in object-oriented variability-rich systems
International audienceIn many variability-intensive systems, variability is implemented in code units provided by a host language, such as classes or functions, which do not align well with the domain features. Annotating or creating an orthogonal decomposition of code in terms of features implies extra effort, as well as massive and cumbersome refactoring activities. In this paper, we introduce an approach for identifying and visualizing the variability implementation places within the main decomposition structure of object-oriented code assets in a single variability-rich system. First, we propose to use symmetry, as a common property of some main implementation techniques, such as inheritance or overloading, to identify uniformly these places. We study symmetry in different constructs (e.g., classes), techniques (e.g., subtyping, overloading) and design patterns (e.g., strategy, factory), and we also show how we can use such symmetries to find variation points with variants. We then report on the implementation and application of a toolchain, symfinder, which automatically identifies and visualizes places with symmetry. The publicly available application to several large open-source systems shows that symfinder can help in characterizing code bases that are variability-rich or not, as well as in discerning zones of interest w.r.t. variability
Comparing comorbidity measures for predicting mortality and hospitalization in three population-based cohorts
<p>Abstract</p> <p>Background</p> <p>Multiple comorbidity measures have been developed for risk-adjustment in studies using administrative data, but it is unclear which measure is optimal for specific outcomes and if the measures are equally valid in different populations. This research examined the predictive performance of five comorbidity measures in three population-based cohorts.</p> <p>Methods</p> <p>Administrative data from the province of Saskatchewan, Canada, were used to create the cohorts. The general population cohort included all Saskatchewan residents 20+ years, the diabetes cohort included individuals 20+ years with a diabetes diagnosis in hospital and/or physician data, and the osteoporosis cohort included individuals 50+ years with diagnosed or treated osteoporosis. Five comorbidity measures based on health services utilization, number of different diagnoses, and prescription drugs over one year were defined. Predictive performance was assessed for death and hospitalization outcomes using measures of discrimination (<it>c</it>-statistic) and calibration (Brier score) for multiple logistic regression models.</p> <p>Results</p> <p>The comorbidity measures with optimal performance were the same in the general population (<it>n </it>= 662,423), diabetes (<it>n </it>= 41,925), and osteoporosis (<it>n </it>= 28,068) cohorts. For mortality, the Elixhauser index resulted in the highest <it>c</it>-statistic and lowest Brier score, followed by the Charlson index. For hospitalization, the number of diagnoses had the best predictive performance. Consistent results were obtained when we restricted attention to the population 65+ years in each cohort.</p> <p>Conclusions</p> <p>The optimal comorbidity measure depends on the health outcome and not on the disease characteristics of the study population.</p
Changes in Drug Utilization during a Gap in Insurance Coverage: An Examination of the Medicare Part D Coverage Gap
Jennifer Polinski and colleagues estimated the effect of the "coverage gap" during which US Medicare beneficiaries are fully responsible for drug costs and found that the gap was associated with a doubling in discontinuing essential medications
Undertreatment of osteoporosis in the oldest old? A nationwide study of over 700,000 older people
The reporting of studies conducted using observational routinely collected health data statement for pharmacoepidemiology (RECORD-PE).
In pharmacoepidemiology, routinely
collected data from electronic health
records (including primary care
databases, registries, and
administrative healthcare claims) are a
resource for research evaluating the
real world effectiveness and safety of
medicines. Currently available
guidelines for the reporting of research
using non-randomised, routinely
collected data—specifically the
REporting of studies Conducted using
Observational Routinely collected
health Data (RECORD) and the
Strengthening the Reporting of
OBservational studies in Epidemiology
(STROBE) statements—do not
capture the complexity of
pharmacoepidemiological research.
We have therefore extended the
RECORD statement to include
reporting guidelines specific to
pharmacoepidemiological research
(RECORD-PE). This article includes the
RECORD-PE checklist (also available on
www.record-statement.org) and
explains each checklist item with
examples of good reporting. We
anticipate that increasing use of the
RECORD-PE guidelines by researchers
and endorsement and adherence by
journal editors will improve the
standards of reporting of
pharmacoepidemiological research
undertaken using routinely collected
data. This improved transparency will
benefit the research community,
patient care, and ultimately improve
public health
Annotation analysis for testing drug safety signals using unstructured clinical notes
BackgroundThe electronic surveillance for adverse drug events is largely based upon the analysis of coded data from reporting systems. Yet, the vast majority of electronic health data lies embedded within the free text of clinical notes and is not gathered into centralized repositories. With the increasing access to large volumes of electronic medical data-in particular the clinical notes-it may be possible to computationally encode and to test drug safety signals in an active manner.ResultsWe describe the application of simple annotation tools on clinical text and the mining of the resulting annotations to compute the risk of getting a myocardial infarction for patients with rheumatoid arthritis that take Vioxx. Our analysis clearly reveals elevated risks for myocardial infarction in rheumatoid arthritis patients taking Vioxx (odds ratio 2.06) before 2005.ConclusionsOur results show that it is possible to apply annotation analysis methods for testing hypotheses about drug safety using electronic medical records
Drug retention and safety of TNF inhibitors in elderly patients with rheumatoid arthritis
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