Also, anyone interested in submitted questions for this year’s F2F study-a-thon can do so here:
Team:
You've probably seen @MauraBeaton 's announcement that the next US OHDSI face-to-face will be hosted by Columbia University in New York City on May2-3. Several folks have been asking about what is planned for that 2-day event. Here's your quick answer:
We're going to do a study together!
@mvanzandt and others in the community had suggested that a good community activity would be to bring everyone together to focus on one specific common goal: to generate reliable evidence on one cli…
And here’s the list of community publications from this week:
Healthcare improvement measures in risk management and patient satisfaction.
CW Huang, U Iqbal and YJ Li,
International journal for quality in health care : journal of the International Society for Quality in Health Care , Feb 2018 01
Formalizing drug indications on the road to therapeutic intent.
SJ Nelson, TI Oprea, O Ursu, CG Bologa, A Zaveri, J Holmes, JJ Yang, SL Mathias, S Mani, MS Tuttle and M Dumontier,
Journal of the American Medical Informatics Association : JAMIA , Nov 2017 01
Therapeutic intent, the reason behind the choice of a therapy and the context in which a given approach should be used, is an important aspect of medical practice. There are unmet needs with respect to current electronic mapping of drug indications. For example, the active ingredient sildenafil has 2 distinct indications, which differ solely on dosage strength. In progressing toward a practice of precision medicine, there is a need to capture and structure therapeutic intent for computational reuse, thus enabling more sophisticated decision-support tools and a possible mechanism for computer-aided drug repurposing. The indications for drugs, such as those expressed in the Structured Product Labels approved by the US Food and Drug Administration, appears to be a tractable area for developing an application ontology of therapeutic intent.
Improvements scale-up and rapid response systems in the hospitals.
Evidence appraisal: a scoping review, conceptual framework, and research agenda.
A Goldstein, E Venker and C Weng,
Journal of the American Medical Informatics Association : JAMIA , Nov 2017 01
Critical appraisal of clinical evidence promises to help prevent, detect, and address flaws related to study importance, ethics, validity, applicability, and reporting. These research issues are of growing concern. The purpose of this scoping review is to survey the current literature on evidence appraisal to develop a conceptual framework and an informatics research agenda.We conducted an iterative literature search of Medline for discussion or research on the critical appraisal of clinical evidence. After title and abstract review, 121 articles were included in the analysis. We performed qualitative thematic analysis to describe the evidence appraisal architecture and its issues and opportunities. From this analysis, we derived a conceptual framework and an informatics research agenda.We identified 68 themes in 10 categories. This analysis revealed that the practice of evidence appraisal is quite common but is rarely subjected to documentation, organization, validation, integration, or uptake. This is related to underdeveloped tools, scant incentives, and insufficient acquisition of appraisal data and transformation of the data into usable knowledge.The gaps in acquiring appraisal data, transforming the data into actionable information and knowledge, and ensuring its dissemination and adoption can be addressed with proven informatics approaches.Evidence appraisal faces several challenges, but implementing an informatics research agenda would likely help realize the potential of evidence appraisal for improving the rigor and value of clinical evidence.
A longitudinal analysis of data quality in a large pediatric data research network.
R Khare, L Utidjian, BJ Ruth, MG Kahn, E Burrows, K Marsolo, N Patibandla, H Razzaghi, R Colvin, D Ranade, M Kitzmiller, D Eckrich and LC Bailey,
Journal of the American Medical Informatics Association : JAMIA , Nov 2017 01
PEDSnet is a clinical data research network (CDRN) that aggregates electronic health record data from multiple children's hospitals to enable large-scale research. Assessing data quality to ensure suitability for conducting research is a key requirement in PEDSnet. This study presents a range of data quality issues identified over a period of 18 months and interprets them to evaluate the research capacity of PEDSnet.Results were generated by a semiautomated data quality assessment workflow. Two investigators reviewed programmatic data quality issues and conducted discussions with the data partners' extract-transform-load analysts to determine the cause for each issue.The results include a longitudinal summary of 2182 data quality issues identified across 9 data submission cycles. The metadata from the most recent cycle includes annotations for 850 issues: most frequent types, including missing data (>300) and outliers (>100); most complex domains, including medications (>160) and lab measurements (>140); and primary causes, including source data characteristics (83%) and extract-transform-load errors (9%).The longitudinal findings demonstrate the network's evolution from identifying difficulties with aligning the data to a common data model to learning norms in clinical pediatrics and determining research capability.While data quality is recognized as a critical aspect in establishing and utilizing a CDRN, the findings from data quality assessments are largely unpublished. This paper presents a real-world account of studying and interpreting data quality findings in a pediatric CDRN, and the lessons learned could be used by other CDRNs.
Precision Medicine at Georgia Tech: Introduction to the Health Data Analytics Platformhttps://smartech.gatech.edu/handle/1853/59350
Inferring pregnancy episodes and outcomes within a network of observational databases
