Table 1. Characteristics of studies.
| Author (country) | Study design | Participants and setting | Age (years) | Time scale | Intervention | Control |
|---|---|---|---|---|---|---|
| Bell et al.20 (USA) | Cluster RCT | 12 clusters: 12 primary care practices, 19,450 patients | 0–18 | 12 months 6 months prior to study start clinicians participated in an educational programme, 12 months of intervention | CDSS embedded in an electronic health record (EHR) in the form of alerts and reminders based on expert asthma guidelines. This included a data entry tool, standardised documentation for asthma severity classification, standardised drug and spirometry order sets and an asthma control plan. There was also an educational programme for professionals. | The control group experienced educational programme for professionals. It also had access to the data entry and all documentation tools but only passively, without alerts and reminders. |
| Eccles et al.21 (UK) | Cluster RCT with 2×2 incomplete block design | 60 clusters: 60 primary care practices, 1,129 patients | ⩾18 | 24 months 12 months baseline period, 12 months intervention | CDSS offered suggestions for management (including prescribing) depending on the chosen clinical scenario and requested the entry of relevant information. | Controls received intervention for angina, while the asthma intervention group was the control from the angina group as a strategy to balance the Hawthorne effect. |
| Fiks et al.22 (USA) | Cluster RCT | 20 clusters: 20 practices, 6,110 patients | 5–19 | 6 months All intervention | CDSS was an EHR-based influenza vaccination alert system. Influenza vaccine alerts appeared prominently at the top of the computer screen in bold and highlighted text whenever the electronic health record was opened for a study subject who was due for this vaccine. Also a link was provided to simplify vaccine ordering. | Described as routine care. |
| Kuilboer et al.23 (The Netherlands) | Cluster RCT | 40 clusters: 32 primary care practices with a total of 40 GPs, each control practice with a mean of 4,933 control and 4,865 intervention patients | All | 10 months 5 months baseline period, 5 months intervention | ‘AsthmaCritic’, the CDSS, relied solely on the existing data in the EHR. Once data related to the visit was entered, the system evaluated whether the patient had asthma or COPD, reviewed the physician’s treatment of asthma and COPD, and generated feedback. In this way, the doctor made the decisions and the CDSS ‘critiqued’ these decisions. | Described as usual care. |
| Martens et al.24,28 (The Netherlands) | Cluster RCT with an incomplete block design | 53 clusters, 14 practices with a total of 53 GPs | All | 12 months 6 months intervention, 6 months data collection | CDSS was part of a computer-reminder system integrated into the EHR as a prescribing module. When the GP prescribed a drug the decision support system was activated and provided information specific to the patient (e.g., age and gender) and the prescribed drug. The GP was obliged to enter a diagnosis code which the CDSS would check and use to issue relevant reminders. | One group that received prescription reminders for cholesterol-lowering drugs served as controls for the other group that received CDSS for antibiotics, asthma and COPD, and vice versa. |
| McCowan et al.25 (UK) | Cluster RCT | 40 clusters: 40 practices, 477 patients | All | 6 months No baseline data | ‘Asthma Crystal Byte’ was a stand-alone decision support system with management guidelines for asthma that aimed to improve the quality of the consultation. It included risk prediction software and printed asthma management plans. | The control group had no knowledge of the intervention and had to report parallel data on the same number of patients as were recruited to the intervention group. |
| Plaza et al.26 (Spain) | Cluster RCT | 20 clusters: 10 pulmonologists and 10 GPs, 198 patients | ⩾14 | 12 months 6 months baseline and 2 sessions of educational programme for clinicians, 12 months intervention | CDSS providing patient-tailored recommendations based on the GINA guidelines enabled clinicians to establish the severity of asthma according to the GINA classification, from relevant inputs such as PEFR, symptom frequency, quantity of corticosteroids and the clinician’s professional opinion. Then the CDSS would recommend medications according to the GINA guidelines. There were also education programmes for clinician and patients, teaching inhaler technique and general information about the condition of asthma. | The control group worked as normal but recorded additional data for comparison. |
| Tierney et al.27 (USA) | 2×2 factorial randomisation of patients | 4 clusters: 4 hospital-based academic practices with 25 faculty general internists and over 100 internal medicine residents, 1 full-time and 9 part-time pharmacists, 706 patients | ⩾18 | 36 months 28 months recruitment and baseline, 8 months intervention | CDSS generated care suggestions based on agreed guidelines. These include performing pulmonary function tests, giving influenza and pneumococcal vaccinations, prescribing advice and encouraging smoking cessation. These suggestions were presented on doctors’ workstations or were printed under a list of active medications that doctors received along with the patient’s paper chart when he/she presented for usual care. | Care suggestions were still generated by the CDSS but were not displayed to the physician or pharmacists caring for patients in the control group. |
Abbreviations: CDSS, computer decision support system; COPD, chronic obstructive pulmonary disease; GINA, The Global Initiative for Asthma; GP, general practitioner; RCT, randomised controlled trial.