Model Agreement and Specialty Match Using 2016 Data
| Specialty | Count | Models Predicting the Same Specialty, % | Specialty Match, %a | Specialty Mismatch, %b |
|---|---|---|---|---|
| Allergy/immunology | 1,625 | 97.1 | 89.6 | 7.5 |
| Anesthesiology | 16,110 | 97.9 | 94.3 | 3.6 |
| Cardiology | 11,170 | 96.9 | 90.4 | 6.5 |
| Dermatology | 5,498 | 98.8 | 96.7 | 2.1 |
| Emergency medicine | 18,663 | 98.3 | 87.0 | 11.3 |
| Endocrinology | 2,497 | 95.8 | 83.3 | 12.5 |
| Gastroenterology | 5,960 | 97.2 | 92.4 | 4.8 |
| Hematology-oncology | 5,572 | 94.9 | 84.9 | 10.0 |
| Infectious disease | 2,328 | 91.1 | 61.2 | 29.9 |
| Nephrology | 3,691 | 96.7 | 86.9 | 9.8 |
| Neurology | 6,217 | 94.5 | 83.1 | 11.4 |
| Neurosurgery | 2,008 | 80.6 | 48.3 | 32.3 |
| Obstetrics and gynecology | 11,505 | 96.7 | 90.6 | 6.1 |
| Ophthalmology | 8,755 | 99.1 | 97.9 | 1.2 |
| Orthopedic surgery | 11,095 | 94.6 | 86.1 | 8.5 |
| Otolaryngology | 4,262 | 96.8 | 89.5 | 7.3 |
| Pathology | 4,831 | 99.3 | 97.8 | 1.5 |
| Physical medicine and rehabilitation | 3,438 | 83.2 | 41.6 | 41.6 |
| Plastic surgery | 1,795 | 80.7 | 42.2 | 38.5 |
| Primary care | 101,498 | 98.3 | 92.6 | 5.7 |
| Psychiatry | 14,974 | 97.9 | 92.1 | 5.8 |
| Pulmonology | 5,395 | 96.1 | 83.2 | 12.9 |
| Radiation Oncology | 1,903 | 95.9 | 91.0 | 4.9 |
| Radiology | 11,816 | 99.1 | 96.4 | 2.7 |
| Rheumatology | 2,030 | 97.6 | 91.7 | 5.9 |
| Surgery | 13,278 | 91.7 | 77.7 | 14.0 |
| Urology | 4,579 | 97.3 | 94.5 | 2.8 |
| Overall | 282,493 | 97.0c | 89.4c | 7.6c |
For this analysis, we applied the 2014, 2015, and 2016 combined random forests to 2016 Test data, for a total of 3 predictions based on prescribing and procedure data for a single year. Model agreement is defined as all 3 models predicting the same specialty.
↵a All 3 models predicted the self-reported specialty.
↵b All 3 models predicted a specialty that differed from the self-reported category.
↵c Mean across all specialties weighted by number in each specialty.