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Paul C. Tang

Bio: Paul C. Tang is an academic researcher from Stanford University. The author has contributed to research in topics: Health care & Medicine. The author has an hindex of 30, co-authored 68 publications receiving 5648 citations. Previous affiliations of Paul C. Tang include Northwestern University & Hewlett-Packard.


Papers
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Journal ArticleDOI
TL;DR: Personal health record (PHR) systems are more than just static repositories for patient data; they combine data, knowledge, and software tools, which help patients to become active participants in their own care as discussed by the authors.

1,272 citations

Journal ArticleDOI
TL;DR: The nation requires a framework for the secondary use of health data with a robust infrastructure of policies, standards, and best practices that can guide and facilitate widespread collection, storage, aggregation, linkage, and transmission of healthData.

636 citations

Journal ArticleDOI
TL;DR: The research and policy challenges for capturing research and practice-based evidence in machine-interpretable repositories are described and recommendations for accelerating the development and adoption of clinical decision support systems for evidence-based medicine are presented.

563 citations

Journal ArticleDOI
TL;DR: Only the integrated model has true transformative potential to strengthen consumers' ability to manage their own health care, and with some exceptions, the integrated PHR model is still a theoretical framework for consumer-centric health care.
Abstract: Background Integrated personal health records (PHRs) offer significant potential to stimulate transformational changes in health care delivery and self-care by patients. In 2006, an invitational roundtable sponsored by Kaiser Permanente Institute, the American Medical Informatics Association, and the Agency for Healthcare Research and Quality was held to identify the transformative potential of PHRs, as well as barriers to realizing this potential and a framework for action to move them closer to the health care mainstream. This paper highlights and builds on the insights shared during the roundtable.

360 citations

Journal ArticleDOI
TL;DR: This work describes the implementation challenges from 1999 to 2007 and postulate the evolving challenges the industry will face over the next five years.

336 citations


Cited by
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Journal ArticleDOI
09 Mar 2005-JAMA
TL;DR: Improvement in practitioner performance was associated with CDSSs that automatically prompted users compared with requiring users to activate the system and studies in which the authors were not the developers, as well as other factors.
Abstract: ContextDevelopers of health care software have attributed improvements in patient care to these applications. As with any health care intervention, such claims require confirmation in clinical trials.ObjectivesTo review controlled trials assessing the effects of computerized clinical decision support systems (CDSSs) and to identify study characteristics predicting benefit.Data SourcesWe updated our earlier reviews by searching the MEDLINE, EMBASE, Cochrane Library, Inspec, and ISI databases and consulting reference lists through September 2004. Authors of 64 primary studies confirmed data or provided additional information.Study SelectionWe included randomized and nonrandomized controlled trials that evaluated the effect of a CDSS compared with care provided without a CDSS on practitioner performance or patient outcomes.Data ExtractionTeams of 2 reviewers independently abstracted data on methods, setting, CDSS and patient characteristics, and outcomes.Data SynthesisOne hundred studies met our inclusion criteria. The number and methodologic quality of studies improved over time. The CDSS improved practitioner performance in 62 (64%) of the 97 studies assessing this outcome, including 4 (40%) of 10 diagnostic systems, 16 (76%) of 21 reminder systems, 23 (62%) of 37 disease management systems, and 19 (66%) of 29 drug-dosing or prescribing systems. Fifty-two trials assessed 1 or more patient outcomes, of which 7 trials (13%) reported improvements. Improved practitioner performance was associated with CDSSs that automatically prompted users compared with requiring users to activate the system (success in 73% of trials vs 47%; P = .02) and studies in which the authors also developed the CDSS software compared with studies in which the authors were not the developers (74% success vs 28%; respectively, P = .001).ConclusionsMany CDSSs improve practitioner performance. To date, the effects on patient outcomes remain understudied and, when studied, inconsistent.

2,875 citations

Journal ArticleDOI
31 Mar 2005-BMJ
TL;DR: Clinicians and other stakeholders should implement clinical decision support systems that incorporate these features whenever feasible and appropriate.
Abstract: Objective To identify features of clinical decision support systems critical for improving clinical practice. Design Systematic review of randomised controlled trials. Data sources Literature searches via Medline, CINAHL, and the Cochrane Controlled Trials Register up to 2003; and searches of reference lists of included studies and relevant reviews. Study selection Studies had to evaluate the ability of decision support systems to improve clinical practice. Data extraction Studies were assessed for statistically and clinically significant improvement in clinical practice and for the presence of 15 decision support system features whose importance had been repeatedly suggested in the literature. Results Seventy studies were included. Decision support systems significantly improved clinical practice in 68% of trials. Univariate analyses revealed that, for five of the system features, interventions possessing the feature were significantly more likely to improve clinical practice than interventions lacking the feature. Multiple logistic regression analysis identified four features as independent predictors of improved clinical practice: automatic provision of decision support as part of clinician workflow (P Conclusions Several features were closely correlated with decision support systems9 ability to improve patient care significantly. Clinicians and other stakeholders should implement clinical decision support systems that incorporate these features whenever feasible and appropriate.

2,412 citations

Journal ArticleDOI
TL;DR: An update of the role of inflammation in atherogenesis is provided and how translation of these advances in basic science promises to change clinical practice is highlighted.

1,824 citations

Journal ArticleDOI
TL;DR: It is essential that the medical profession play a central role in critically evaluating the evidence related to drugs, devices, and procedures for the detection, management, or prevention of disease.

1,492 citations