The Experts below are selected from a list of 252 Experts worldwide ranked by ideXlab platform
Michel Dumontier - One of the best experts on this subject based on the ideXlab platform.
-
overlap in drug disease associations between clinical practice guidelines and drug Structured Product label indications
Journal of Biomedical Semantics, 2016Co-Authors: Tiffany I. Leung, Michel DumontierAbstract:Background Clinical practice guidelines (CPGs) recommend pharmacologic treatments for clinical conditions, and drug Structured Product labels (SPLs) summarize approved treatment indications. Both resources are intended to promote evidence-based medical practices and guide clinicians’ prescribing decisions. However, it is unclear how well CPG recommendations about pharmacologic therapies match SPL indications for recommended drugs. In this study, we perform text mining of CPG summaries to examine drug-disease associations in CPG recommendations and in SPL treatment indications for 15 common chronic conditions.
-
Comparing Drug-Disease Associations in Clinical Practice Guideline Recommendations and Drug Product Label Indications
Studies in Health Technology and Informatics, 2015Co-Authors: Tiffany I. Leung, Michel DumontierAbstract:Clinical practice guidelines (CPGs) and Structured Product labels (SPLs) are both intended to promote evidence-based medical practices and guide clinicians' prescribing decisions. However, it is unclear how well CPG recommendations about pharmacologic therapies for certain diseases match SPL indications for recommended drugs. In this study, we use publicly available data and text mining methods to examine drug-disease associations in CPG recommendations and SPL treatment indications for 15 common chronic conditions. Preliminary results suggest that there is a mismatch between guideline-recommended pharmacologic therapies and SPL indications. Conflicting or inconsistent recommendations and indications may complicate clinical decision making and implementation or measurement of best practices.
Dina Demnerfushman - One of the best experts on this subject based on the ideXlab platform.
-
a dataset of 200 Structured Product labels annotated for adverse drug reactions
Scientific Data, 2018Co-Authors: Dina Demnerfushman, Sonya E Shooshan, Laritza Rodriguez, Alan R Aronson, Francois Michel Lang, Willie J Rogers, Kirk Roberts, Joseph M TonningAbstract:Adverse drug reactions (ADRs), unintended and sometimes dangerous effects that a drug may have, are one of the leading causes of morbidity and mortality during medical care. To date, there is no Structured machine-readable authoritative source of known ADRs. The United States Food and Drug Administration (FDA) partnered with the National Library of Medicine to create a pilot dataset containing standardised information about known adverse reactions for 200 FDA-approved drugs. The Structured Product Labels (SPLs), the documents FDA uses to exchange information about drugs and other Products, were manually annotated for adverse reactions at the mention level to facilitate development and evaluation of text mining tools for extraction of ADRs from all SPLs. The ADRs were then normalised to the Unified Medical Language System (UMLS) and to the Medical Dictionary for Regulatory Activities (MedDRA). We present the curation process and the structure of the publicly available database SPL-ADR-200db containing 5,098 distinct ADRs. The database is available at https://bionlp.nlm.nih.gov/tac2017adversereactions/ ; the code for preparing and validating the data is available at https://github.com/lhncbc/fda-ars . Machine-accessible metadata file describing the reported data (ISA-Tab format)
-
coreference resolution for Structured drug Product labels
Meeting of the Association for Computational Linguistics, 2014Co-Authors: Halil Kilicoglu, Dina DemnerfushmanAbstract:FDA drug package inserts provide comprehensive and authoritative information about drugs. DailyMed database is a repository of Structured Product labels extracted from these package inserts. Most salient information about drugs remains in free text portions of these labels. Extracting information from these portions can improve the safety and quality of drug prescription. In this paper, we present a study that focuses on resolution of coreferential information from drug labels contained in DailyMed. We generalized and expanded an existing rule-based coreference resolution module for this purpose. Enhancements include resolution of set/instance anaphora, recognition of appositive constructions and wider use of UMLS semantic knowledge. We obtained an improvement of 40% over the baseline with unweighted average F1-measure using B-CUBED, MUC, and CEAF metrics. The results underscore the importance of set/instance anaphora and appositive constructions in this type of text and point out the shortcomings in coreference annotation in the dataset.
Gunther Schadow - One of the best experts on this subject based on the ideXlab platform.
-
Structured Product labeling improves detection of drug intolerance issues
Journal of the American Medical Informatics Association, 2009Co-Authors: Gunther SchadowAbstract:Objectives: This study sought to assess the value of the Health Level 7/U.S. Food and Drug Administration Structured Product Labeling (SPL) drug knowledge representation standard and its associated terminology sources for drug-intolerance (allergy) decision support in computerized provider order entry (CPOE) systems. Design: The Regenstrief Institute CPOE drug-intolerance issue detection system and its knowledge base was compared with a method based on existing SPL label content enriched with knowledge sources used with SPL (NDF-RT/MeSH). Both methods were applied to a large set of drug-intolerance (allergy) records, drug orders, and medication dispensing records covering >50,000 patients over 30 years. Measurements: The number of drug-intolerance issues detected by both methods was counted, as well as the number of patients with issues, number of distinct drugs, and number of distinct intolerances. The difference between drug-intolerance issues detected or missed by either method was qualitatively analyzed. Results: Although <70% of terms were mapped to SPL, the new approach detected four times as many drug-intolerance issues on twice as many patients. Conclusion: The SPL-based approach is more sensitive and suggests that mapping local dictionaries to SPL, and enhancing the depth and breadth of coverage of SPL content are worth accelerating. The study also highlights specificity problems known to trouble drug-intolerance decision support and suggests how terminology and methods of recording drug intolerances could be improved.
-
Structured Product labeling improves detection of drug intolerance issues
American Medical Informatics Association Annual Symposium, 2008Co-Authors: Gunther SchadowAbstract:The HL7 Structured Product Labeling (SPL) standard1 implemented by the FDA uses the HL7 Reference Information Model (RIM)2 to represent the chemical and physical nature of medical Products and their safe and effective use. While not all of this content is available today, we enrich the 3704 available SPLs with knowledge from the SPL terminology sources, including the VA’s NDF-RT3 and MeSH. To demonstrate the value of SPL for clinical decision support, we compared the performance of drug-intolerance (allergy) issue detection using SPL with the Regenstrief Institute (RI) own CPOE system, Gopher4 and its knowledge base.
-
assessing the impact of hl7 fda Structured Product label spl content for medication knowledge management
American Medical Informatics Association Annual Symposium, 2007Co-Authors: Gunther SchadowAbstract:The amount and quality of the SPL drug knowledge which has been released so far is assessed. All published labels were loaded into a relational database and classified to create vendor-independent descriptions. While SPL labels cover only 23% of RxNorm clinical drugs, they still describe 78% of actual community pharmacy dispenses records. SPL descriptions agree well with RxNorm. SPL can be used as the primary source of drug information for e-prescribing systems once the upcoming FDA listing rule takes effect. In the interim, existing gaps can be temporarily closed with RxNorm or other sources.
Craig J. Mccann - One of the best experts on this subject based on the ideXlab platform.
-
Structured Products and the Mischief of Self-Indexing
The Journal of Index Investing, 2017Co-Authors: Geng Deng, Craig J. MccannAbstract:In the early days of Structured Products, issuers issued, underwriters underwrote, and index providers provided indexes. In the 1990s, underwriters bypassed operating companies and began issuing debt linked to operating company stocks or to stock indexes. In recent years, investment banks have gone a step further and issued Structured Products linked to proprietary indexes of stocks, commodities, currencies, and volatility, including the two VIX-derived proprietary indexes discussed herein, rather than just linking to standardized indexes from S&P and other index providers. When brokerage firms include hypothetical trading costs in their proprietary indexes—costs that are absent from third-party indexes—they render comparisons of disclosed costs at the Structured Product level uninformative. This mischief would not be possible if issuers linked to indexes provided by third-party vendors who had no interest in the payoffs from Structured Products linked to their indexes. We illustrate the problems with self-indexing Structured Products using proprietary volatility indexes from Bank of America and J.P. Morgan, although the conflicts we highlight arise equally with the proprietary indexes of other underlying assets, including commodities and currencies.
-
Ex-Post Structured Product Returns: Index Methodology and Analysis
The Journal of Investing, 2015Co-Authors: Geng Deng, Tim Dulaney, Tim Husson, Craig J. MccannAbstract:The academic and practitioner literature now includes numerous studies of the substantial issue-date mispricing of Structured Products, but there is no large-scale study of the ex post returns earned by Structured Product investors. This article augments the current literature by analyzing the ex post returns of more than 20,000 individual Structured Products issued by 13 brokerage firms since 2007. We construct our Structured-Product index and sub-indexes for reverse convertibles, single-observation reverse convertibles, tracking securities, and autocallable securities by valuing each Structured Product in our database each day. The ex post returns of U.S. Structured Products are highly correlated with the returns of large-capitalization equity markets in the aggregate, and individual Structured Products generally underperform simple alternative allocations to stocks and bonds. The observed underperformance of Structured Products is consistent with the significant issue-date underpricing documented in the literature.
-
Valuation of Structured Products
The Journal of Alternative Investments, 2014Co-Authors: Geng Deng, Tim Husson, Craig J. MccannAbstract:The market for Structured Products has grown dramatically in the past decade. Their diversity and complexity have led to the development of many different valuation approaches, and it is not always clear which approach to use to value a given Product. In this article the authors discuss four approaches to valuing Structured Products: simulation of the linked financial instrument’s future values, numerical integration, decomposition, and partial differential equation approaches. As an example, the authors use all four approaches to value a common type of Structured Product, and discuss the virtues and pitfalls of each.
-
Structured Product–Based Variable Annuities: A New (and Complex) Retirement Savings Vehicle
The Journal of Retirement, 2014Co-Authors: Geng Deng, Tim Dulaney, Tim Husson, Craig J. MccannAbstract:Variable annuities, which are often marketed to investors in retirement, have become highly varied and complex investments. Recently, a new type of variable annuity has been marketed to investors in retirement and is based on Structured Product-like investments instead of the mutual fund-like investments found in traditional variable annuities. Embedding a Structured Product into a variable annuity introduces substantial complexity into an investment typically considered conservative. In this article, we describe Structured Product-based variable annuity (spVA) crediting formulas and how they differ from traditional VAs, value the embedded derivative position for a range of illustrative parameters, and calculate the fair cap levels required to fairly compensate investors for the derivative position. We also provide extensive backtests of spVA crediting formulas using our calculated cap levels, and compare the results to their underlying indexes. Our findings suggest that the complexity of spVAs can provide flexibility to the issuer by introducing new avenues for revenue generation. On the other hand, the complexity also reduces the comparability of such variable annuities to other investments in the market. These features raise questions of suitability for older American investors, whether approaching retirement or already retired.
-
Structured Product Based Variable Annuities
SSRN Electronic Journal, 2013Co-Authors: Geng Deng, Tim Dulaney, Tim Husson, Craig J. MccannAbstract:Recently, a new type of variable annuity has been marketed to investors which is based on Structured Product-like investments instead of the mutual fund-like investments found in traditional variable annuities. Embedding a Structured Product into a variable annuity introduces substantial complexity into an investment typically considered conservative. In this paper, we describe Structured Product based variable annuity (spVA) crediting formulas and how they differ from traditional VAs, value the embedded derivative position for a range of example parameters, and calculate the fair cap levels required to fairly compensate investors for the derivative position. We also provide extensive backtests of spVA crediting formulas using our calculated cap levels and compare the results to their underlying indexes. Our findings suggest that the complexity of spVAs can be used to hide fees and reduce the comparability of variable annuities to other investments in the market.
Tiffany I. Leung - One of the best experts on this subject based on the ideXlab platform.
-
overlap in drug disease associations between clinical practice guidelines and drug Structured Product label indications
Journal of Biomedical Semantics, 2016Co-Authors: Tiffany I. Leung, Michel DumontierAbstract:Background Clinical practice guidelines (CPGs) recommend pharmacologic treatments for clinical conditions, and drug Structured Product labels (SPLs) summarize approved treatment indications. Both resources are intended to promote evidence-based medical practices and guide clinicians’ prescribing decisions. However, it is unclear how well CPG recommendations about pharmacologic therapies match SPL indications for recommended drugs. In this study, we perform text mining of CPG summaries to examine drug-disease associations in CPG recommendations and in SPL treatment indications for 15 common chronic conditions.
-
Comparing Drug-Disease Associations in Clinical Practice Guideline Recommendations and Drug Product Label Indications
Studies in Health Technology and Informatics, 2015Co-Authors: Tiffany I. Leung, Michel DumontierAbstract:Clinical practice guidelines (CPGs) and Structured Product labels (SPLs) are both intended to promote evidence-based medical practices and guide clinicians' prescribing decisions. However, it is unclear how well CPG recommendations about pharmacologic therapies for certain diseases match SPL indications for recommended drugs. In this study, we use publicly available data and text mining methods to examine drug-disease associations in CPG recommendations and SPL treatment indications for 15 common chronic conditions. Preliminary results suggest that there is a mismatch between guideline-recommended pharmacologic therapies and SPL indications. Conflicting or inconsistent recommendations and indications may complicate clinical decision making and implementation or measurement of best practices.
