Decision support systems in healthcare: systematic review, meta-analysis and prediction, with example of COVID-19
Objective: The objective of this study was to provide an overview of Decision Support Systems (DSS) applied in healthcare used for diagnosis, monitoring, prediction and recommendation in medicine. Methods: We conducted a systematic review using PRISMA (Preferred Reporting Items for Systematic R...
| Main Authors: | , , , |
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| Format: | Article |
| Language: | English |
| Published: |
AIMS Press
2023-02-01
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| Series: | AIMS Bioengineering |
| Subjects: | |
| Online Access: | https://www.aimspress.com/article/doi/10.3934/bioeng.2023004?viewType=HTML |
| _version_ | 1797821042933104640 |
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| author | Houssem Ben Khalfallah Mariem Jelassi Jacques Demongeot Narjès Bellamine Ben Saoud |
| author_facet | Houssem Ben Khalfallah Mariem Jelassi Jacques Demongeot Narjès Bellamine Ben Saoud |
| author_sort | Houssem Ben Khalfallah |
| collection | DOAJ |
| description | Objective:
The objective of this study was to provide an overview of Decision Support Systems (DSS) applied in healthcare used for diagnosis, monitoring, prediction and recommendation in medicine.
Methods:
We conducted a systematic review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines of articles published until September 2022 from PubMed, Cochrane, Scopus and web of science databases. We used KH coder to analyze included research. Then we categorized decision support systems based on their types and medical applications.
Results:
The search strategy provided a total of 1605 articles in the studied period. Of these, 231 articles were included in this qualitative review. This research was classified into 4 categories based on the DSS type used in healthcare: Alert Systems, Monitoring Systems, Recommendation Systems and Prediction Systems. Under each category, domain applications were specified according to the disease the system was applied to.
Conclusion:
In this systematic review, we collected CDSS studies that use ML techniques to provide insights into different CDSS types. We highlighted the importance of ML to support physicians in clinical decision-making and improving healthcare according to their purposes. |
| first_indexed | 2024-03-13T09:46:56Z |
| format | Article |
| id | doaj.art-d2be912ad5624fde9ede43c5ddc83c83 |
| institution | Directory Open Access Journal |
| issn | 2375-1495 |
| language | English |
| last_indexed | 2024-03-13T09:46:56Z |
| publishDate | 2023-02-01 |
| publisher | AIMS Press |
| record_format | Article |
| series | AIMS Bioengineering |
| spelling | doaj.art-d2be912ad5624fde9ede43c5ddc83c832023-05-25T01:21:46ZengAIMS PressAIMS Bioengineering2375-14952023-02-01101275210.3934/bioeng.2023004Decision support systems in healthcare: systematic review, meta-analysis and prediction, with example of COVID-19Houssem Ben Khalfallah0Mariem Jelassi1 Jacques Demongeot2Narjès Bellamine Ben Saoud31. RIADI Laboratory, ENSI, Manouba University, 2010, La Manouba, Tunisia1. RIADI Laboratory, ENSI, Manouba University, 2010, La Manouba, Tunisia2. AGEIS laboratory, UGA, 38700, La Tronche, France1. RIADI Laboratory, ENSI, Manouba University, 2010, La Manouba, TunisiaObjective: The objective of this study was to provide an overview of Decision Support Systems (DSS) applied in healthcare used for diagnosis, monitoring, prediction and recommendation in medicine. Methods: We conducted a systematic review using PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analysis) guidelines of articles published until September 2022 from PubMed, Cochrane, Scopus and web of science databases. We used KH coder to analyze included research. Then we categorized decision support systems based on their types and medical applications. Results: The search strategy provided a total of 1605 articles in the studied period. Of these, 231 articles were included in this qualitative review. This research was classified into 4 categories based on the DSS type used in healthcare: Alert Systems, Monitoring Systems, Recommendation Systems and Prediction Systems. Under each category, domain applications were specified according to the disease the system was applied to. Conclusion: In this systematic review, we collected CDSS studies that use ML techniques to provide insights into different CDSS types. We highlighted the importance of ML to support physicians in clinical decision-making and improving healthcare according to their purposes.https://www.aimspress.com/article/doi/10.3934/bioeng.2023004?viewType=HTMLdecision support systemhealthcareclinical decision support systemdecision-making support systems |
| spellingShingle | Houssem Ben Khalfallah Mariem Jelassi Jacques Demongeot Narjès Bellamine Ben Saoud Decision support systems in healthcare: systematic review, meta-analysis and prediction, with example of COVID-19 AIMS Bioengineering decision support system healthcare clinical decision support system decision-making support systems |
| title | Decision support systems in healthcare: systematic review, meta-analysis and prediction, with example of COVID-19 |
| title_full | Decision support systems in healthcare: systematic review, meta-analysis and prediction, with example of COVID-19 |
| title_fullStr | Decision support systems in healthcare: systematic review, meta-analysis and prediction, with example of COVID-19 |
| title_full_unstemmed | Decision support systems in healthcare: systematic review, meta-analysis and prediction, with example of COVID-19 |
| title_short | Decision support systems in healthcare: systematic review, meta-analysis and prediction, with example of COVID-19 |
| title_sort | decision support systems in healthcare systematic review meta analysis and prediction with example of covid 19 |
| topic | decision support system healthcare clinical decision support system decision-making support systems |
| url | https://www.aimspress.com/article/doi/10.3934/bioeng.2023004?viewType=HTML |
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