Abstract
Background: Nowadays, patients can take a more active role in their chronic disease management. For decision-making specifically, this could entail the application of shared decision-making (SDM), possibly with the use of technology such as clinical decision support systems (CDSSs).
Objective: To identify how decision-making is structured in SDM-tools and CDSSs, and how effective these are for adults with chronic conditions such as COPD, ischemic heart disease, chronic heart failure, diabetes, depression or anxiety, compared to usual care.
Method: The systematic review followed the PRISMA-P guidelines and is registered in PROSPERO (ID:CRD42022290826). Randomized controlled studies published between January 2011 and December 2021 were identified in PubMed, Scopus, Embase, Web of Science, CINAHL and PsychINFO and were screened independently by two reviewers, followed by data extraction and analysis.
Result: In total 16,582 records were identified, of which 11,652 unique records were imported into an AI-tool for title and abstract screening (van de Schoot, R et al. Nature Machine Intelligence 2021; 3:125-133). One reviewer screened 835 records, of which the last 100 were irrelevant. This prompted the reviewer to mark the remaining 10,790 records as ineligible since the AI-tool proposes the most relevant records first. Thus far, 21 records are eligible for analysis, in which COPD is in the minority compared to other chronic conditions, such as diabetes.
Conclusion: This review allows us to identify knowledge gaps in decision-making for future research and design, by analysis of current SDM elements and technology in chronic disease management.
Objective: To identify how decision-making is structured in SDM-tools and CDSSs, and how effective these are for adults with chronic conditions such as COPD, ischemic heart disease, chronic heart failure, diabetes, depression or anxiety, compared to usual care.
Method: The systematic review followed the PRISMA-P guidelines and is registered in PROSPERO (ID:CRD42022290826). Randomized controlled studies published between January 2011 and December 2021 were identified in PubMed, Scopus, Embase, Web of Science, CINAHL and PsychINFO and were screened independently by two reviewers, followed by data extraction and analysis.
Result: In total 16,582 records were identified, of which 11,652 unique records were imported into an AI-tool for title and abstract screening (van de Schoot, R et al. Nature Machine Intelligence 2021; 3:125-133). One reviewer screened 835 records, of which the last 100 were irrelevant. This prompted the reviewer to mark the remaining 10,790 records as ineligible since the AI-tool proposes the most relevant records first. Thus far, 21 records are eligible for analysis, in which COPD is in the minority compared to other chronic conditions, such as diabetes.
Conclusion: This review allows us to identify knowledge gaps in decision-making for future research and design, by analysis of current SDM elements and technology in chronic disease management.
| Original language | English |
|---|---|
| Number of pages | 2 |
| Journal | European respiratory journal |
| Volume | 60 |
| DOIs | |
| Publication status | Published - 4 Sept 2022 |