Advances in Clinical Decision Support: Highlights of Practice and the Literature 2015-2016

Jenders, R. A.

doi:10.1055/s-0037-1606493

Cited by 9 publications

(7 citation statements)

References 24 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Patients’ reluctance to engage in decision-making underscores the need for decision aids. Though “best practice alerts” and clinical decision support systems exist as integrated tools in electronic health records, 42 this study revealed the complexity of the anticoagulation decision. The evidence for improved quality of decision-making and patient satisfaction with decision-making processes through decision support tools is well-established.…”

Section: Discussionmentioning

confidence: 91%

Exploring patient–provider decision-making for use of anticoagulation for stroke prevention in atrial fibrillation: Results of the INFORM-AF study

Pokorney

Bloom

Granger

et al. 2018

European Journal of Cardiovascular Nursing

View full text Add to dashboard Cite

Background: Atrial fibrillation is associated with stroke, yet approximately 50% of patients are not treated with guideline-directed oral anticoagulants (OACs). Aims: Given that the etiology of this gap in care is not well understood, we explored decision-making by patients and physicians regarding OAC use for stroke prevention in atrial fibrillation. Methods and results: We conducted a descriptive qualitative study among providers (N=28) and their patients with atrial fibrillation for whom OACs were indicated (N=25). We used purposive sampling across three outpatient settings in which atrial fibrillation patients are commonly managed: primary care (n=14), geriatrics (n=10), and cardiology (n=4). Eligible patients were stratified by those prescribed OAC (n=13) and not prescribed OAC (n=12). Semi-structured, in-depth interviews assessed decision-making regarding risk and OAC use. Classical content analysis was used to code narratives and identify themes. Results among patients consisted of the overarching theme of trust in provider recommendations. Sub-themes included: awareness of increased risk of stroke with atrial fibrillation; willingness to accept medications recommended by their physician; and low demand for explanatory decision aids. Among physicians, the overarching theme was decisional conflict regarding the balance between stroke and bleeding risk, and the optimal medication to prescribe. Subthemes included: absence of decision aids for communication; and misperceptions around the assessment and management of stroke risk with atrial fibrillation. Conclusions: Patient involvement in decision-making around OAC use did not occur in this study of patients with atrial fibrillation. Improved access to decision aids may increase patient engagement in the decision-making process of OAC use for stroke prevention.

show abstract

Section: Discussionmentioning

confidence: 91%

Exploring patient–provider decision-making for use of anticoagulation for stroke prevention in atrial fibrillation: Results of the INFORM-AF study

Pokorney

Bloom

Granger

et al. 2018

European Journal of Cardiovascular Nursing

View full text Add to dashboard Cite

show abstract

“…These could lead to the CDSS's failure to generalize from the training data and ultimately to undetected poor performance at the local site. Therefore, considerable care must be taken to minimize the potential adverse consequences of CDSSs . It is important to select carefully the CDSS that matches the requirements of the local site.…”

Section: Discussionmentioning

confidence: 99%

Artificial intelligence‐based clinical decision support in modern medical physics: Selection, acceptance, commissioning, and quality assurance

Mahadevaiah

Bermejo

et al. 2020

Medical Physics

View full text Add to dashboard Cite

Background Recent advances in machine and deep learning based on an increased availability of clinical data have fueled renewed interest in computerized clinical decision support systems (CDSSs). CDSSs have shown great potential to improve healthcare, increase patient safety and reduce costs. However, the use of CDSSs is not without pitfalls, as an inadequate or faulty CDSS can potentially deteriorate the quality of healthcare and put patients at risk. In addition, the adoption of a CDSS might fail because its intended users ignore the output of the CDSS due to lack of trust, relevancy or actionability. Aim In this article, we provide guidance based on literature for the different aspects involved in the adoption of a CDSS with a special focus on machine and deep learning based systems: selection, acceptance testing, commissioning, implementation and quality assurance. Results A rigorous selection process will help identify the CDSS that best fits the preferences and requirements of the local site. Acceptance testing will make sure that the selected CDSS fulfills the defined specifications and satisfies the safety requirements. The commissioning process will prepare the CDSS for safe clinical use at the local site. An effective implementation phase should result in an orderly roll out of the CDSS to the well‐trained end‐users whose expectations have been managed. And finally, quality assurance will make sure that the performance of the CDSS is maintained and that any issues are promptly identified and solved. Conclusion We conclude that a systematic approach to the adoption of a CDSS will help avoid pitfalls, improve patient safety and increase the chances of success.

show abstract

“…CDS software has shown promise in improving patient care but has been limited in its success . Problems exist with its use, such as alert fatigue.…”

Section: The Need For Precision Dosingmentioning

confidence: 99%

Precision drug dosing: A major opportunity for patients and pharmacists

Pearce

Giblin

Buckthal

et al. 2018

J Am Coll Clin Pharm

View full text Add to dashboard Cite

Precision medicine customizes drug treatment to an individual's disease and genetics in order to optimize therapeutic benefit and minimize risk. Surprisingly, drug dosing is generally not discussed as a component of precision medicine. Because dosing regimens are an independent factor modulating efficacy and toxicity, consideration should be given to the clinical significance of precision drug dosing (PDD) in patient care. Pharmacists routinely face dilemmas when they are asked for dosing recommendations for patients with characteristics that fall outside of those represented in the drug label (eg, morbid obesity, pregnancy, frailty, neonatal patients, or elderly patients). The necessary data and technology now exist to create and implement PDD software for high priority drug‐disease targets in order to assist pharmacists and prescribers in choosing the safest and most effective dose for every patient. Within 5 to 10 years, we believe this software will be available. This study discusses how pharmacists can participate in leading the implementation of these PDD tools to achieve effective and routine clinical use.

show abstract

Advances in Clinical Decision Support: Highlights of Practice and the Literature 2015-2016

Cited by 9 publications

References 24 publications

Exploring patient–provider decision-making for use of anticoagulation for stroke prevention in atrial fibrillation: Results of the INFORM-AF study

Exploring patient–provider decision-making for use of anticoagulation for stroke prevention in atrial fibrillation: Results of the INFORM-AF study

Artificial intelligence‐based clinical decision support in modern medical physics: Selection, acceptance, commissioning, and quality assurance

Precision drug dosing: A major opportunity for patients and pharmacists

Contact Info

Product

Resources

About