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The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review

Background: To deal with complexity in cancer care, computerized clinical decision support systems (CDSSs) are developed to support quality of care and improve decision-making. We performed a systematic review to explore the value of CDSSs using automated clinical guidelines, Artificial Intelligence...

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Autores principales: Klarenbeek, Sosse E., Weekenstroo, Harm H.A., Sedelaar, J.P. Michiel, Fütterer, Jurgen J., Prokop, Mathias, Tummers, Marcia
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2020
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226340/
https://www.ncbi.nlm.nih.gov/pubmed/32331449
http://dx.doi.org/10.3390/cancers12041032
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author Klarenbeek, Sosse E.
Weekenstroo, Harm H.A.
Sedelaar, J.P. Michiel
Fütterer, Jurgen J.
Prokop, Mathias
Tummers, Marcia
author_facet Klarenbeek, Sosse E.
Weekenstroo, Harm H.A.
Sedelaar, J.P. Michiel
Fütterer, Jurgen J.
Prokop, Mathias
Tummers, Marcia
author_sort Klarenbeek, Sosse E.
collection PubMed
description Background: To deal with complexity in cancer care, computerized clinical decision support systems (CDSSs) are developed to support quality of care and improve decision-making. We performed a systematic review to explore the value of CDSSs using automated clinical guidelines, Artificial Intelligence, datamining or statistical methods (higher level CDSSs) on the quality of care in oncology. Materials and Methods: The search strategy combined synonyms for ‘CDSS’ and ‘cancer.’ Pubmed, Embase, The Cochrane Library, Institute of Electrical and Electronics Engineers, Association of Computing Machinery digital library and Web of Science were systematically searched from January 2000 to December 2019. Included studies evaluated the impact of higher level CDSSs on process outcomes, guideline adherence and clinical outcomes. Results: 11,397 studies were selected for screening, after which 61 full-text articles were assessed for eligibility. Finally, nine studies were included in the final analysis with a total population size of 7985 patients. Types of cancer included breast cancer (63.1%), lung cancer (27.8%), prostate cancer (4.1%), colorectal cancer (3.1%) and other cancer types (1.9%). The included studies demonstrated significant improvements of higher level CDSSs on process outcomes and guideline adherence across diverse settings in oncology. No significant differences were reported for clinical outcomes. Conclusion: Higher level CDSSs seem to improve process outcomes and guidelines adherence but not clinical outcomes. It should be noticed that the included studies primarily focused on breast and lung cancer. To further explore the impact of higher level CDSSs on quality of care, high-quality research is required.
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spelling pubmed-72263402020-05-18 The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review Klarenbeek, Sosse E. Weekenstroo, Harm H.A. Sedelaar, J.P. Michiel Fütterer, Jurgen J. Prokop, Mathias Tummers, Marcia Cancers (Basel) Review Background: To deal with complexity in cancer care, computerized clinical decision support systems (CDSSs) are developed to support quality of care and improve decision-making. We performed a systematic review to explore the value of CDSSs using automated clinical guidelines, Artificial Intelligence, datamining or statistical methods (higher level CDSSs) on the quality of care in oncology. Materials and Methods: The search strategy combined synonyms for ‘CDSS’ and ‘cancer.’ Pubmed, Embase, The Cochrane Library, Institute of Electrical and Electronics Engineers, Association of Computing Machinery digital library and Web of Science were systematically searched from January 2000 to December 2019. Included studies evaluated the impact of higher level CDSSs on process outcomes, guideline adherence and clinical outcomes. Results: 11,397 studies were selected for screening, after which 61 full-text articles were assessed for eligibility. Finally, nine studies were included in the final analysis with a total population size of 7985 patients. Types of cancer included breast cancer (63.1%), lung cancer (27.8%), prostate cancer (4.1%), colorectal cancer (3.1%) and other cancer types (1.9%). The included studies demonstrated significant improvements of higher level CDSSs on process outcomes and guideline adherence across diverse settings in oncology. No significant differences were reported for clinical outcomes. Conclusion: Higher level CDSSs seem to improve process outcomes and guidelines adherence but not clinical outcomes. It should be noticed that the included studies primarily focused on breast and lung cancer. To further explore the impact of higher level CDSSs on quality of care, high-quality research is required. MDPI 2020-04-22 /pmc/articles/PMC7226340/ /pubmed/32331449 http://dx.doi.org/10.3390/cancers12041032 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).
spellingShingle Review
Klarenbeek, Sosse E.
Weekenstroo, Harm H.A.
Sedelaar, J.P. Michiel
Fütterer, Jurgen J.
Prokop, Mathias
Tummers, Marcia
The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review
title The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review
title_full The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review
title_fullStr The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review
title_full_unstemmed The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review
title_short The Effect of Higher Level Computerized Clinical Decision Support Systems on Oncology Care: A Systematic Review
title_sort effect of higher level computerized clinical decision support systems on oncology care: a systematic review
topic Review
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7226340/
https://www.ncbi.nlm.nih.gov/pubmed/32331449
http://dx.doi.org/10.3390/cancers12041032
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