Copyright
©The Author(s) 2017.
World J Methodol. Mar 26, 2017; 7(1): 16-24
Published online Mar 26, 2017. doi: 10.5662/wjm.v7.i1.16
Published online Mar 26, 2017. doi: 10.5662/wjm.v7.i1.16
Table 2 Survey respondent characteristics
| Completion rate | n of Scores | |
| Anesthesia | 2/5 (40%) | 49 |
| Cardiology | 1/1 (100%) | 37 |
| Critical care | 14/23 (61%) | 75 |
| Dermatology | 0/0 | 1 |
| Emergency medicine | 4/6 (67%) | 62 |
| Family medicine | 2/5 (40%) | 107 |
| Gastroenterology | 3/3 (100%) | 17 |
| Hematology | 1/1 (100%) | 5 |
| Infectious disease | 2/2 (100%) | 2 |
| Internal medicine | 14/25 (56%) | 109 |
| Nephrology | 1/1 (100%) | 6 |
| Neurology | 0/1 (0%) | 23 |
| OBGYN | 1/1 (100%) | 1 |
| Oncology | 1/2 (50%) | 5 |
| Orthopedics | 0/0 | 3 |
| Pediatric | 7/13 (54%) | 25 |
| Pulmonology | 4/6 (67%) | 17 |
| Surgery | 2/3 (67%) | 66 |
- Citation: Aakre CA, Dziadzko MA, Herasevich V. Towards automated calculation of evidence-based clinical scores. World J Methodol 2017; 7(1): 16-24
- URL: https://www.wjgnet.com/2222-0682/full/v7/i1/16.htm
- DOI: https://dx.doi.org/10.5662/wjm.v7.i1.16