Literature DB >> 29861205

Decision Support Tools: Realizing the Potential to Improve Quality of Care.

Michelle M Graham1, Matthew T James2, John A Spertus3.   

Abstract

Delivering evidence-based, personalized care that engages patients requires profound changes in the structure, process, and organization of care, along with revised incentives to support such changes. Health care providers must absorb and apply a vast, usually overwhelming, amount of scientific information to provide high-quality patient care. Accordingly, care remains inconsistent, with unintentional adverse consequences. Decision support tools can provide patient-specific assessments that support clinical decisions, improve prescribing practices, reduce medication errors, improve the delivery of primary as well as secondary prevention, and improve adherence to standards of care. Decision support tools are created using an individual patient's genetic, sociodemographic, and clinical characteristics to improve the delivery of precise, personalized care. Implementation requires ease of use for busy clinicians; uptake improves with active education, and gradual adoption of a tool integrated into care processes without disrupting clinical work flow. As health care systems continue to evolve and computerized support increases, increased implementation of decision support tools that are provided automatically as part of usual work flow, with clinically actionable recommendations at the point of care, requiring accountability for deviations from recommended therapy, represent an important opportunity to enhance quality of care by tailoring treatment to risk, improving the consistency of health care delivery, increasing patient knowledge and engagement, and avoiding specific therapeutic interventions in patients who will receive no benefit. However, successful implementation also requires strategies to engage providers in accepting and using these tools to improve care.
Copyright © 2018 Canadian Cardiovascular Society. Published by Elsevier Inc. All rights reserved.

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Mesh:

Year:  2018        PMID: 29861205     DOI: 10.1016/j.cjca.2018.02.029

Source DB:  PubMed          Journal:  Can J Cardiol        ISSN: 0828-282X            Impact factor:   5.223


  3 in total

1.  Psychometric evaluation of the Decision Support Tool for Functional Independence in community-dwelling older people.

Authors:  S C van Bijsterveld; J A Barten; E A L M Molenaar; N Bleijenberg; N J de Wit; C Veenhof
Journal:  J Popul Ageing       Date:  2022-03-29

Review 2.  Leveraging the timing and frequency of patient decision aids in longitudinal shared decision-making: A narrative review and applied model.

Authors:  Lara R LoBrutto; Gemmae Fix; Renda S Wiener; Amy M Linsky
Journal:  Health Expect       Date:  2022-06-02       Impact factor: 3.318

3.  Clinical decision support malfunctions related to medication routes: a case series.

Authors:  Adam Wright; Scott Nelson; David Rubins; Richard Schreiber; Dean F Sittig
Journal:  J Am Med Inform Assoc       Date:  2022-10-07       Impact factor: 7.942

  3 in total

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