scholarly journals Use of Decision Support Tools to Empower Pregnant Women: Systematic Review (Preprint)

2020 ◽  
Author(s):  
Elin Ngo ◽  
Maria Bich-Thuy Truong ◽  
Hedvig Nordeng
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Pregnant Women ◽  
Management Tool ◽  
Control Group ◽  
Decision Support Tools ◽  
Patient Centered ◽  
Review Management ◽  
Support Tools ◽  
Health Related

BACKGROUND Women face many health-related decisions during pregnancy. Digitalization, new technology, and a greater focus on empowering patients have driven the development of patient-centered decision support tools. OBJECTIVE This systematic review provides an overview of studies investigating the effect of patient-centered decision support tools for pregnant women. METHODS We searched 5 online databases, MEDLINE, EMBASE, Web of Science, PsycINFO, and Scopus, from inception to December 1, 2019. Two independent researchers screened titles, abstracts, and full-texts against the inclusion criteria. All studies investigating the effect of patient-centered decision support tools for health-related issues among pregnant women were included. Study characteristics and results were extracted using the review management tool Rayyan and analyzed according to topic, type of decision support tools, control group, outcome measurements, and results. RESULTS The 25 eligible studies covered a range of health topics, including prenatal screening (n=10), gestational diabetes and weight gain (n=7), lifestyle (n=3), blood pressure and preeclampsia (n=2), depression (n=1), asthma (n=1), and psychological well-being (n=1). In general, the use of decision support tools increased women's knowledge, and recording symptoms enhanced satisfaction with maternity care. CONCLUSIONS The opportunities created by digitalization and technology should be used to develop innovative patient-centered decision support tools tailored to support pregnant women. Effect on clinical outcomes should be documented.

scholarly journals Use of Decision Support Tools to Empower Pregnant Women: Systematic Review

10.2196/19436 ◽  
2020 ◽  
Vol 22 (9) ◽  
pp. e19436
Author(s):  
Elin Ngo ◽  
Maria Bich-Thuy Truong ◽  
Hedvig Nordeng
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Pregnant Women ◽  
Management Tool ◽  
Control Group ◽  
Decision Support Tools ◽  
Patient Centered ◽  
Review Management ◽  
Support Tools ◽  
Health Related

Background Women face many health-related decisions during pregnancy. Digitalization, new technology, and a greater focus on empowering patients have driven the development of patient-centered decision support tools. Objective This systematic review provides an overview of studies investigating the effect of patient-centered decision support tools for pregnant women. Methods We searched 5 online databases, MEDLINE, EMBASE, Web of Science, PsycINFO, and Scopus, from inception to December 1, 2019. Two independent researchers screened titles, abstracts, and full-texts against the inclusion criteria. All studies investigating the effect of patient-centered decision support tools for health-related issues among pregnant women were included. Study characteristics and results were extracted using the review management tool Rayyan and analyzed according to topic, type of decision support tools, control group, outcome measurements, and results. Results The 25 eligible studies covered a range of health topics, including prenatal screening (n=10), gestational diabetes and weight gain (n=7), lifestyle (n=3), blood pressure and preeclampsia (n=2), depression (n=1), asthma (n=1), and psychological well-being (n=1). In general, the use of decision support tools increased women's knowledge, and recording symptoms enhanced satisfaction with maternity care. Conclusions The opportunities created by digitalization and technology should be used to develop innovative patient-centered decision support tools tailored to support pregnant women. Effect on clinical outcomes should be documented.

scholarly journals Decision support tools to improve cancer diagnostic decision making in primary care: a systematic review

2019 ◽  
Vol 69 (689) ◽  
pp. e809-e818 ◽  
Author(s):  
Sophie Chima ◽  
Jeanette C Reece ◽  
Kristi Milley ◽  
Shakira Milton ◽  
Jennifer G McIntosh ◽  
...  
Keyword(s):  
Systematic Review ◽  
Primary Care ◽  
Decision Making ◽  
Decision Support ◽  
Cost Effectiveness ◽  
Cancer Diagnosis ◽  
Decision Support Tools ◽  
Diagnostic Decision ◽  
Support Tools ◽  
Diagnostic Decision Making

BackgroundThe diagnosis of cancer in primary care is complex and challenging. Electronic clinical decision support tools (eCDSTs) have been proposed as an approach to improve GP decision making, but no systematic review has examined their role in cancer diagnosis.AimTo investigate whether eCDSTs improve diagnostic decision making for cancer in primary care and to determine which elements influence successful implementation.Design and settingA systematic review of relevant studies conducted worldwide and published in English between 1 January 1998 and 31 December 2018.MethodPreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were followed. MEDLINE, EMBASE, and the Cochrane Central Register of Controlled Trials were searched, and a consultation of reference lists and citation tracking was carried out. Exclusion criteria included the absence of eCDSTs used in asymptomatic populations, and studies that did not involve support delivered to the GP. The most relevant Joanna Briggs Institute Critical Appraisal Checklists were applied according to study design of the included paper.ResultsOf the nine studies included, three showed improvements in decision making for cancer diagnosis, three demonstrated positive effects on secondary clinical or health service outcomes such as prescribing, quality of referrals, or cost-effectiveness, and one study found a reduction in time to cancer diagnosis. Barriers to implementation included trust, the compatibility of eCDST recommendations with the GP’s role as a gatekeeper, and impact on workflow.ConclusioneCDSTs have the capacity to improve decision making for a cancer diagnosis, but the optimal mode of delivery remains unclear. Although such tools could assist GPs in the future, further well-designed trials of all eCDSTs are needed to determine their cost-effectiveness and the most appropriate implementation methods.

scholarly journals Decision Support Tools for Regenerative Medicine: Systematic Review

10.2196/12448 ◽  
2018 ◽  
Vol 20 (12) ◽  
pp. e12448 ◽  
Author(s):  
Ching Lam ◽  
Edward Meinert ◽  
Abrar Alturkistani ◽  
Alison R Carter ◽  
Jeffrey Karp ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Regenerative Medicine ◽  
Decision Support Tools ◽  
Support Tools

scholarly journals Can evidence-based decision support tools transform antibiotic management? A systematic review and meta-analyses

2020 ◽  
Vol 75 (5) ◽  
pp. 1099-1111 ◽  
Author(s):  
Mah Laka ◽  
Adriana Milazzo ◽  
Tracy Merlin
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Methodological Quality ◽  
Length Of Hospital Stay ◽  
Clinical Decision Support Systems ◽  
Antibiotic Prescribing ◽  
Decision Support Tools ◽  
Support Tools ◽  
Antibiotic Management ◽  
Meta Analyses

Abstract Objectives To assess the effectiveness of clinical decision support systems (CDSSs) at reducing unnecessary and suboptimal antibiotic prescribing within different healthcare settings. Methods A systematic review of published studies was undertaken with seven databases from database inception to November 2018. A protocol was developed using the PRISMA-P checklist and study selection criteria were determined prior to performing the search. Critical appraisal of studies was undertaken using relevant tools. Meta-analyses were performed using a random-effects model to determine whether CDSS use affected optimal antibiotic management. Results Fifty-seven studies were identified that reported on CDSS effectiveness. Most were non-randomized studies with low methodological quality. However, randomized controlled trials of moderate methodological quality were available and assessed separately. The meta-analyses indicated that appropriate antibiotic therapy was twice as likely to occur following the implementation of CDSSs (OR 2.28, 95% CI 1.82–2.86, k = 20). The use of CDSSs was also associated with a relative decrease (18%) in mortality (OR 0.82, 95% CI 0.73–0.91, k = 18). CDSS implementation also decreased the overall volume of antibiotic use, length of hospital stay, duration and cost of therapy. The magnitude of the effect did vary by study design, but the direction of the effect was consistent in favouring CDSSs. Conclusions Decision support tools can be effective to improve antibiotic prescribing, although there is limited evidence available on use in primary care. Our findings suggest that a focus on system requirements and implementation processes would improve CDSS uptake and provide more definitive benefits for antibiotic stewardship.

A Systematic Review of Decision-Support Tools for Regenerative Medicine

2018 ◽  
Author(s):  
Ching Lam ◽  
Edward Meinert ◽  
Abrar Alturkistani ◽  
Alison Carter ◽  
Jeffery M. Karp ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Regenerative Medicine ◽  
Decision Support Tools ◽  
Support Tools

Interactive versus static decision support tools for COVID-19: An experimental comparison (Preprint)

2021 ◽  
Author(s):  
Alice Röbbelen ◽  
Malte L Schmieding ◽  
Marvin Kopka ◽  
Felix Balzer ◽  
Markus A Feufel
Keyword(s):  
Decision Support ◽  
Mental Effort ◽  
Experimental Comparison ◽  
Control Group ◽  
Decision Support Tools ◽  
Self Assessment ◽  
Decision Algorithm ◽  
Support Tools ◽  
Case Vignettes

BACKGROUND During the COVID-19 pandemic, medical laypersons with symptoms indicative of a COVID-19 infection commonly seek guidance on whether and where to seek medical care. Numerous web-based decision support tools (DSTs) have been developed, both by public and commercial stakeholders, to assist their decision-making. Though most of the DST’s underlying algorithms are similar and simple decision trees, their mode of presentation differs: some DSTs present a static flowchart, while others are designed as a conversational agent, guiding the user through the decision tree’s node step-by-step in an interactive manner. OBJECTIVE To investigate whether interactive DSTs provide greater decision support than non-interactive (ie, static) flowcharts. METHODS We developed mock interfaces for two DST (one static, one interactive), mimicking patient-facing, freely available DSTs for COVID-19 related self-assessment. Their underlying algorithm was identical and based on the Center for Disease Control’s guidelines. We recruited adult US residents online. which participants. Participants appraised the appropriate social and care-seeking behavior for seven fictitious descriptions of patients (case vignettes). Participants in the experimental groups received either the static or interactive mock DST as support, while the control group appraised the case vignettes unsupported. We determined participants’ accuracy, decision certainty (after deciding) and mental effort to measure quality of decision support. Participants’ ratings of the DSTs’ usefulness, ease of use, trust and future intention to use the tools served as measure to analyze differences in participants’ perception of the tools. We used ANOVAs and t-tests to assess statistical significance. RESULTS Our survey yielded 196 responses. The mean number of correct assessments was higher in the experimental groups (interactive DST group: M=11.71, SD=2.37; static DST group: M=11.45, SD=2.48) than in the control group (M=10.17, SD=2.00; F(2,193)=8.6, p<.001). Decisional certainty was significantly higher in the experimental groups (interactive DST group: M=80.7%, SD=14.1%; static DST group: M=80.5%, SD=15.8%) compared to the control group (M=65.8%, SD=20.8%; F(2, 193)=15.7, p<.001). Differences for mental effort between the three study were non-significant. Effect sizes of differences between the two experimental groups were small and non-significant for all three measures of quality of decision support and most measures of users’ perception of the DSTs. CONCLUSIONS When the decision space is limited as is the case in common COVID-19 self-assessment DSTs, static flowcharts might prove as beneficial in enhancing decision quality as interactive tools. Given that static flowcharts reveal the underlying decision algorithm more transparently and require less effort to develop, they might prove more efficient in providing guidance to the public. Further research should validate our findings on different use cases, elaborate on the trade-off between transparency and convenience in DSTs, and investigate whether subgroups of users benefit more one type of user interface than the other.

Shared Decision-Support Tools in Hospital Emergency Departments: A Systematic Review

2019 ◽  
Vol 45 (4) ◽  
pp. 386-393 ◽  
Author(s):  
Valle Coronado-Vázquez ◽  
Juan Gómez-Salgado ◽  
Javier Cerezo-Espinosa de los Monteros ◽  
Miren Arantzazu García-Colinas
Keyword(s):  
Systematic Review ◽  
Decision Support ◽  
Emergency Departments ◽  
Decision Support Tools ◽  
Shared Decision ◽  
Hospital Emergency ◽  
Support Tools ◽  
Hospital Emergency Departments
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