Table 1.
Characteristics of the sources of evidence by optimisation target
| Optimisation target n (%) | ||||
|---|---|---|---|---|
| Characteristic | Overall N = 183 | Implementation N = 39 | Intervention N = 142 | Both N = 2 |
| Year of publication | ||||
| 2013 | 15 (8.2%) | 3 (7.7%) | 11 (7.7%) | 1 (50%) |
| 2014 | 14 (7.7%) | 1 (2.6%) | 12 (8.5%) | 1 (50%) |
| 2015 | 11 (6.0%) | 2 (5.1%) | 9 (6.3%) | 0 (0%) |
| 2016 | 4 (2.2%) | 2 (5.1%) | 2 (1.4%) | 0 (0%) |
| 2017 | 6 (3.3%) | 2 (5.1%) | 4 (2.8%) | 0 (0%) |
| 2018 | 7 (3.8%) | 0 (0%) | 7 (4.9%) | 0 (0%) |
| 2019 | 17 (9.3%) | 5 (13%) | 12 (8.5%) | 0 (0%) |
| 2020 | 15 (8.2%) | 4 (10%) | 11 (7.7%) | 0 (0%) |
| 2021 | 17 (9.3%) | 3 (7.7%) | 14 (9.9%) | 0 (0%) |
| 2022 | 32 (17%) | 9 (23%) | 23 (16%) | 0 (0%) |
| 2023 | 22 (12%) | 1 (2.6%) | 21 (15%) | 0 (0%) |
| 2024 | 23 (13%) | 7 (18%) | 16 (11%) | 0 (0%) |
| Setting | ||||
| Community health | 92 (50%) | 18 (46%) | 72 (51%) | 2 (100%) |
| Hospitals | 51 (28%) | 21 (54%) | 30 (21%) | 0 (0%) |
| General population | 20 (11%) | 0 (0%) | 20 (14%) | 0 (0%) |
| Education | 11 (6.0%) | 0 (0%) | 11 (7.7%) | 0 (0%) |
| Clinical | 7 (3.8%) | 0 (0%) | 7 (4.9%) | 0 (0%) |
| Other | 2 (1%) | 0 (0%) | 2 (1.4%) | 0 (0%) |
| Optimisation framework used | 44 (24%) | 14 (36%) | 30 (21%) | 0 (0%) |
| MOST | 28 (15%) | 1 (2.6%) | 27 (19%) | 0 (0%) |
| PDSA | 11 (6.0%) | 9 (23%) | 2 (1.4%) | 0 (0%) |
| Lean | 3 (1.6%) | 3 (7.7%) | 0 (0%) | 0 (0%) |
| Model for improvement1 | 1 (0.5%) | 1 (2.6%) | 0 (0%) | 0 (0%) |
| Optimisation success defined | 20 (11%) | 7 (18%) | 13 (9.2%) | 0 (0%) |
| Optimisation successful | 134 (73%) | 27 (69%) | 105 (74%) | 2 (100%) |
| Study design | ||||
| Factorial | 69 (38%) | 9 (23%) | 58 (41%) | 2 (100%) |
| Fractional factorial | 8 (4.4%) | 1 (2.6%) | 7 (4.9%) | 0 (0%) |
| RCT2 | 46 (25%) | 3 (7.7%) | 43 (30%) | 0 (0%) |
| Pre-post | 22 (12%) | 18 (46%) | 4 (2.8%) | 0 (0%) |
| Crossover | 16 (8.7%) | 2 (5.1%) | 14 (9.9%) | 0 (0%) |
| Cluster RCT2 | 7 (3.8%) | 3 (7.7%) | 4 (2.8%) | 0 (0%) |
| SMART | 5 (2.7%) | 0 (0%) | 5 (3.5%) | 0 (0%) |
| Other | 10 (5.5%) | 3 (7.7%) | 7 (4.9%) | 0 (0%) |
| Adaptive design used | 2 (1.1%) | 0 (0%) | 2 (1.4%) | 0 (0%) |
| Statistical framework | ||||
| Frequentist | 181 (99%) | 39 (100%) | 140 (99%) | 2 (100%) |
| Bayesian | 2 (1.1%) | 0 (0%) | 2 (1.4%) | 0 (0%) |
| Country | ||||
| USA | 69 | 13 | 56 | 0 |
| UK | 32 | 4 | 28 | 0 |
| Australia | 13 | 5 | 6 | 2 |
| Canada | 10 | 4 | 6 | 0 |
| Netherlands | 9 | 1 | 8 | 0 |
| Spain | 6 | 1 | 5 | 0 |
| China | 5 | 1 | 4 | 0 |
| France | 5 | 0 | 5 | 0 |
| Germany | 5 | 2 | 3 | 0 |
| India | 5 | 1 | 4 | 0 |
| Sweden | 5 | 1 | 4 | 0 |
| Other3 | 37 | 8 | 29 | 0 |
1One study used both PDSA and Model for improvement
2RCT Randomised control trial
3Other countries include: Switzerland, Belgium, Ireland, Italy, Romania, Botswana, Brazil, Côte d’Ivoire, Cameroon, Poland, Egypt, Ethiopia, Finland, Israel, Japan, Malawi, New Zealand, Pakistan, Rwanda, Nigeria, Singapore, South Africa, Austria, United Arab Emirates, Taiwan (Republic of China), Puerto Rico