Studies of clinical assistance applications (see Supplementary material 4 and 5 for further details).
| Application purpose | Number of studies | Application name(s) | Country of study | Outcomes measured |
|---|---|---|---|---|
| Data collection | 1 abstract [35]1 article [36] | NeoTree [35, 36] | Malawi [35]Zimbabwe [36] | Completeness of data capture and coverage [35, 36]Turnaround time for test results [36]Provision of data for quality improvement [36] |
| Digital triage | 4 articles [24, 34, 43, 49]1 abstract [50]1 pre-print [31] | Smart Triage [31, 43, 49, 50]Pedicmeter [34]NR [24] | Uganda [24, 31, 43, 49, 50]Kenya [31]Thailand [34] | Mortality [31, 43]Timely treatment [24, 31, 43, 50]Diagnosis validity [34]Admission, readmission, and length of stay [31]Feasibility and cost [43, 49]User acceptance [34, 49] |
| Guideline or clinical pathway access | 4 articles [39, 41, 45, 48]1 abstract [42] | PedsGuide [39, 48]IWK app [45]NR [41, 42] | US [39, 41, 48]Canada [45]NR [42] | Bundle and bundle element completion [42]App usage [39, 41, 48]Usability [41, 48]Mortality and length of stay [45]Appropriate antimicrobial prescribing [45] |
| Alert delivery | 1 article [38] | Sensium [38] | UK [38] | Time to alert acknowledgement [38]Alert action taken [38] |
| Prediction tool | 4 articles [33, 37, 46, 47]a1 abstract [52] | POTTER [33, 47]aPOTTER-ICU [37]aTOP [46]aNR [52] | ACS-NSQIPa,b [33, 37, 47]ACS-TQIP a,b [46]Scotland [52] | Mortality [33, 46, 47]aMorbidity (non-infectious) [33, 46, 47]aMorbidity (sepsis and infections) [33, 46, 47]aICU admission [37]aReferral for pediatric hospitalisation [52] |
US: United States; NR: not reported; UK: United Kingdom; ACS-NSQIP: American College of Surgeons National Surgical Quality Improvement Program; ACS-TQIP: American College of Surgeons Trauma Quality Improvement Program; POTTER: Predictive Optimal Trees in Emergency Surgery Risk; ICU: intensive care unit; TOP: trauma outcome predictor. a: These predictive tools were designed using the machine learning technique ‘optimal classification trees’. b: ACS-NSQIP and ACS-TQIP data comprise surgical data from participating hospitals, which may be set across numerous countries.
The supplementary materials for this article are available at: https://www.explorationpub.com/uploads/Article/file/101186_sup_1.pdf.
The authors would like to thank Mr. Jeremy Cullis, an experienced clinical librarian, for his guidance in developing the final search strategy and translating it to other databases.
KA and DK: Conceptualization, Data curation, Formal analysis, Investigation, Writing—original draft, Writing—review & editing. VL and LL: Conceptualization, Data curation, Formal analysis, Writing—review & editing. All authors read and approved the submitted version.
The authors declare that they have no conflicts of interest.
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As this study is a scoping review, all relevant data are available in the included studies.
This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.
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