Table 4.
Study | Procedure | Recipients | N | Collected Data |
---|---|---|---|---|
Keyworth C. et al., 2017 [44] | Pharmacists were invited to collect prescribing error data for junior doctors. They were invited to take part in semi-structured interviews exploring the perceptions of the acceptability and feasibility of MyPrescribe as a training tool aimed at improving prescribing practices. | Pharmacists (n = 11) junior doctors (n = 52) |
200 prescribing errors Interviews |
Demographics, medical specialty. Change in COM-B model (capability, opportunity, motivation, behavior). Opinions on telemedicine service. |
Morozov S. et al., 2018 [45] | A group of experts, two or three for each record, performed a distant peer review. If one of the experts considered that the discrepancy was significant, the system sent the study to another expert. If even the second disagrees, the study is redirected for the final evaluation of the third expert. | Patients | 23.199 studies | Quality control focuses on: Technical performance and detection of pathology. Scoring of the degree of discrepancy between clinical opinion |
Orchard J. et al., 2020 [46] | GPs and/or practice nurses offered screening for AF with smartphone handheld single-lead ECGs (iECGs) (KardiaMobile) to eligible patients. To support the screening eHealth tools information was extracted from patients’ electronic medical records and guideline recommendations were made regarding treatment. | Patients | 3103 patients screened | Demographics, iECG screening, medication, and diagnostic information from the practices’ electronic patient records, treatment, cost- effectiveness. |