Patient Demographics Across Cohorts
| Patient Demographics | Office | Telemedicine | Total Patients |
|---|---|---|---|
| 12,846 | 1,048 | 13,891 | |
| Race | |||
| White | 11,671 (90.90%) | 919 (87.90%) | 12,590 (90.60%) |
| Black or African American | 475 (3.69%) | 62 (5.93%) | 537 (3.84%) |
| American Indian, Alaska Native, Native Hawaiian and Other Pacific Islander | 39 (0.30%) | 3 (0.28%) | 42 (0.30%) |
| Asian | 72 (0.56%) | 7 (0.67%) | 79 (0.57%) |
| total: unknown, declined, not reported, Othera | 788 (6.04%) | 57 (5.43%) | 701 (5.04%) |
| Ethnicity | |||
| Not Hispanic OR Latino | 12,128 (94.4%) | 980 (93.70%) | 13,108 (93.80%) |
| Hispanic OR Latino | 491 (3.82%) | 54 (5.16%) | 545 (3.89%) |
| Other | 227 (1.76%) | 11 (1.05%) | 238 (1.70%) |
| Legal sex | |||
| Male | 6,395 (49.80%) | 466 (44.60%) | 6,861 (49.10%) |
| Female | 6,451 (50.20%) | 579 (55.40%) | 7,030 (50.20%) |
| Age | |||
| 0 to 19 | 97 (0.76%) | 8 (0.76%) | 105 (0.75%) |
| 20-39 years | 656 (5.11%) | 105 (10.04%) | 761 (5.44%) |
| 40-59 years | 2,453 (19.10%) | 309 (29.50%) | 2,762 (19.75%) |
| 60-79 years | 6,555 (51.00%) | 474 (45.35%) | 7,029 (50.30%) |
| 80-110 years | 3,289 (25.60%) | 159 (15.20%) | 3,448 (24.70%) |
| No Valueb | 41 (0.31%) | 1 (0.09%) | 42 (0.30%) |
| Risk score | |||
| Low risk (<9) | 4,316 (33.50%) | 424 (40.50%) | 4,740 (33.90%) |
| Med risk (9 to 16) | 4,863 (37.80%) | 299 (28.60%) | 5,162 (36.92%) |
| High risk (>16) | 2,993 (23.30%) | 239 (22.90%) | 3,232 (23.11%) |
| No value | 676 (5.26%) | 83 (7.94%) | 759 (5.42%) |
| Insurance type | |||
| High Mark, Blue Cross, WellSpan Pop Health | 2,059 (16.00%) | 240 (22.97%) | 2,299 (16.44%) |
| Medicare | 8,873 (69.10%) | 588 (56.20%) | 9,461 (67.70%) |
| Medicaid | 731 (5.26%) | 92 (8.80%) | 823 (5.89%) |
| Other commercial | 459 (3.57%) | 46 (4.40%) | 505 (3.61%) |
↵a total: unknown, declined, not reported, Other refers to patients not reported or declined or not documented due to administrative errors.
↵b Likely represents administrative error in charting.
c SlicerDicer was only able to measure proportions of encounters associated with the financial payer class and self-pay was unable to be measured. These proportions should be interpreted as approximate given that patients may have switched payers within the study time. For Medicare and Medicaid, there may be redundancy of patients who have had both payer types. Overall interpretation of above proportions is comparable distributions across the cohorts.