Table 2.
Studies characteristic
| Lead Author, Year: Yishen Wang MBBS, 2016 |
| Study Title: Clinical pre-test of a computerised antithrombotic risk assessment tool for stroke prevention in atrial fibrillation patients: giving consideration to NOACs |
| Country: Australia |
| Aim of Study: The study wanted to pre-test a CDSS tool that would help clinicians in selecting antithrombotics. |
| Study Design:A cross-sectional study |
| Setting: 369 general practice patients with atrial fibrillation (AF) participating in the previous study (2012) were involved here. Their age was ≥65 years with a confirmed diagnosis of AF New South Wales. Their information was available in the former study database. |
| Participants Characteristics: 393 patients with AF [mean age 78.0 (±7.0) years], 54.5% were male and 45.8% (n = 180) were aged ≥80 years. |
| Type of CDSS Tools Utilized: An updated version of CARATV2.0 based on latest clinical evidence. |
| Outcomes: CARATV2.0 recommended warfarin for 360 (91.6%) patients, NOAC for 5 (1.3%) patients, either rivaroxaban or apixaban for 6 (1.5%) patients, andapixaban for 9 (2.2%). This was in the case where warfarin was recommended as first-line therapy. |
| Lead Author, Year: Lise Bonnevie, 2004 |
| Study Title: The use of computerized decision support systems in preventive cardiology-principal results from the national PRECARD@ survey in Denmark |
| Country: Denmark |
| Aim of Study: Conduct a cardiovascular disease risk assessment and management in Danish patients since 1999 using the PRECARD® program. |
| Study Design: A cross-sectional study |
| Setting: 3568 general practitioners registered in Denmark were contacted. An online survey conducted on 592 general practitioners in Denmark. |
| Participants Characteristics: 400/3568 took the postal survey and 291/400(73%) responded. The participants were subdivided into users 60(22%) [males 45(75%)] and mean age 49.7 years, ex-user 28(10%) [males 18(64%)] and mean age 51 years, and never user 191(68%) [males 126(66%)] and mean age 51.7 years. |
| Type of CDSS Tools Utilized: The PRECARD® program for CVD risk assessment and management. |
| Outcomes: 21.5% GPs use the program, 10% have used it before, and the program is utilized at a rate of 64% weekly. The usage of the program affects the patients favourably by enhancing the dialogue between them and the practitioner. However, it also prolongs consultation time. |
| Lead Author, Year: Lars O. Karlsson, 2018 |
| Study Title: A clinical decision support tool for improving adherence to guidelines on anticoagulant therapy in patients with atrial fibrillation at risk of stroke: A cluster-randomized trial in a Swedish primary care setting (the CDS-AF study) |
| Country: Sweden |
| Aim of Study: To assess whether adherence to guidelines regarding the prevention of stroke can be increased by using a CDSS tool. |
| Study Design: A cluster randomized trial |
| Setting: 444,347 Swedish patients obtained from 43 primary care clinics county of Östergötland will be into CDSS and control groups for the randomized study. |
| Participants Characteristics: Patients with atrial fibrillation at risk of stroke, 43 primary care clinics in the county of Ö stergö tland, Sweden (population 444,347, patients with AF |
| Type of CDSS Tools Utilized: A CDSS embedded in a standard electronic health record (EHR) and uses medical record data to identify patients with AF and one or more risk factors who have not yet been prescribed anticoagulant medication, according to the CHA2DS2-VASc algorithm. |
| Outcomes: CARATV2.0 suggested any NOAC for 279 (70.9%) patients, rivaroxaban or apixaban for 80 (20.4%) patients, apixaban for 9 (2.3%) patients, and warfarin for 12 (3.1%) patients. This was in the case of where NAOCs were recommended as first-line therapy. |
| Lead Author, Year: Giampiero Mazzaglia, 2016 |
| Study Title: Effects of a computerized decision support system in improving pharmacological management in high-risk cardiovascular patients: A cluster-randomized open-label controlled trial. |
| Country: Italy |
| Aim of Study: Testing if using CDSS can favourably affect the prevalence of preventive therapies according to the recommendation guidelines and check whether the number of days of drug interactions will reduce among patients with a high risk of cardiovascular diseases. |
| Study Design: A cluster randomized controlled trial |
| Setting: 197 general practitioners were randomly assigned to groups that will either receive alerting computerized decision support system integrated into standard software (intervention arm) or the standard software alone (control arm) |
| Participants Characteristics: Diabetic patients, 21230 patients with diabetes, 3956 with acute myocardial infarction, and 2158 with stroke were analysed, 197 Italian general practitioners, high-risk cardiovascular patients. |
| Type of CDSS Tools Utilized: A CDSS embedded in a standard EHR and uses medical record data to identify patients with AF and one or more risk factors who have not yet been prescribed anticoagulant medication, according to the CHA2DS2-VASc algorithm. |
| Outcomes: For 279 (70.9%) patients, CARATV2.0 recommended any NOAC, rivaroxaban or apixaban for 80 (20.4%) patients, apixaban for 9 (2.3%) patients, and warfarin for 12 (3.1%) patients. When NAOCs were suggested as first-line therapy, this was the situation. |
| Lead Author, Year: Derk L. Arts, 2017 |
| Study Title: Effectiveness and usage of a decision support system to improve stroke prevention in general practice: A cluster randomized controlled trial |
| Country: The Netherlands |
| Aim of Study: Using a non-obtrusive CDSS integrated into the workflow to increase guideline adherence. Also, to figure out why people don't follow guidelines. |
| Study Design: A cluster randomized controlled trial |
| Setting: A randomized control experiment on the Dutch general practices. To prevent contamination bias, randomization was done at the GP practice level. The allocation ratios were 2:1:1 and 1:1:1. The ‘sample’ function was used to generate a random sequence from the list of GP practices provided by DA in the statistical environment R. GPs were aware that they were assigned to a system variant, but they were unaware of their assignment and how the variants differed. |
| Participants Characteristics: 781 patients were included randomized into post-study control (259 patients) [mean age(SD): 73.73 (14.7)] and post-study intervention (522 patients) [mean age(SD): 72.79 (12.61). |
| Type of CDSS Tools Utilized: Real-time, non-interruptive, and based on data from electronic health records were all attributes positively associated with effectiveness when a decision support system was established. The recommendations were based on the CHA2DS2-VAsc for stroke risk stratification, which is used in the Dutch general practitioners guideline for atrial fibrillation. |
| Outcomes: There was a decreased utilization of the system (5%) which dropped over time. There was a 58% rate of dismissal and 42% rate of acceptance to notifications (76 were responded to). Acceptance had improved in both groups by a factor of 8% and 5% but the difference was not significant between the analysed groups. |