2020
DOI: 10.1186/s12913-020-05688-3
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Economic impact of clinical decision support interventions based on electronic health records

Abstract: Background Unnecessary healthcare utilization, non-adherence to current clinical guidelines, or insufficient personalized care are perpetual challenges and remain potential major cost-drivers for healthcare systems around the world. Implementing decision support systems into clinical care is promised to improve quality of care and thereby yield substantial effects on reducing healthcare expenditure. In this article, we evaluate the economic impact of clinical decision support (CDS) interventions based on elect… Show more

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Cited by 30 publications
(34 citation statements)
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References 64 publications
(195 reference statements)
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“…37 Implementing such strategies along the continuum of AKI-related AI resources such as risk stratification and prediction, alerts, decision support, and long-term follow-up could substantially improve patient outcomes and reduce the burden of AKI on the healthcare system. 38 Collaborative opportunities exist throughout the clinical healthcare systems -both within and between adult and pediatric centers -as well through partnerships with industry to make steady progress along these lines. The likelihood of finding a "one size fits all" approach is low, and we think we should attempt one best tool for each one of these tasks: Whether AI based or not, each tool must be designed for its own purpose and rigorously tested for sensitivity, specificity, and accuracy.…”
Section: Conclusion: the Pursuit Of Perfection Is The Enemy Of Progressmentioning
confidence: 99%
“…37 Implementing such strategies along the continuum of AKI-related AI resources such as risk stratification and prediction, alerts, decision support, and long-term follow-up could substantially improve patient outcomes and reduce the burden of AKI on the healthcare system. 38 Collaborative opportunities exist throughout the clinical healthcare systems -both within and between adult and pediatric centers -as well through partnerships with industry to make steady progress along these lines. The likelihood of finding a "one size fits all" approach is low, and we think we should attempt one best tool for each one of these tasks: Whether AI based or not, each tool must be designed for its own purpose and rigorously tested for sensitivity, specificity, and accuracy.…”
Section: Conclusion: the Pursuit Of Perfection Is The Enemy Of Progressmentioning
confidence: 99%
“…For example, by using data from electronic health records, patient reminder letters can be generated and personalized with each patient’s name and address, preferred language, the name of the patient’s primary care provider, and their history of CRC screening (eg, type and time of most recent test). Although it takes resources to program electronic health records and to set up these strategies initially, clinic health information technology and automated calling and texting systems can support implementation ( 27 , 28 ). Whether clinics can maintain these interventions solely with their own resources after CRCCP technical and financial support has ended remains to be seen.…”
Section: Implications For Public Healthmentioning
confidence: 99%
“…Evidence has shown that electronic decision support systems (EDSS), especially in primary health care settings, can lead to better quality care as well lower health costs. 37,38 Researchers at The George Institute for Global Health developed its first EDSS platform in 2011. It provides clinical decision support tools for chronic disease management and prevention in primary health care services.…”
Section: Decision Support Tools For Cardiovascular Disease Management...mentioning
confidence: 99%