Comparing telemedicine to in-clinic medication abortions induced with mifepristone and misoprostol
Bibliographic record
Abstract
OBJECTIVE: The objective was to compare the practical aspects of providing medication abortions through telemedicine and in-person clinic visits so that clinics can use this information when planning to add this service. STUDY DESIGN: We conducted a comparative retrospective chart review comparing telemedicine medication abortions to a control group matched for date seen. We extracted and compared demographics, use of dating ultrasound, outcomes and unscheduled visits or communications with staff and physicians. RESULTS: During the study period, we provided 4340 medication abortions, of which 182 (4.2%) were provided through by telemedicine; 199 patients met the criteria to be in the control group. The mean age was 28.7 years for telemedicine patients and 28.1 years for in-person patients (p = .38). The mean gestational ages were also similar, 48.2 days for telemedicine patients and 46.5 days for in-person patients (p = .03). Only 33 (18.1%) of telemedicine patients had dating ultrasounds compared to 199 (100%) of in-clinic patients (p < .001). The proportions of documented completed abortions (164/182, 90.1% and 179/199, 89.9%, p = .76) were similar, as were the proportions of aspirations for completion (6/182, 3.3% and 9/199, 4.5%, p = .54) and the proportions lost to follow-up (5.5% and 6.6%, p = .66). There were 10 complications in each group (5.5% of telemedicine patients and 5.0% of in-clinic patients) (p > 0.5). Unscheduled communications with office assistants were greater in the telemedicine patients than the in-person patients (84/182, 46.2% vs. 43/199, 21.6% in-person, p < .001). CONCLUSION: We found that telemedicine patients required more unscheduled communications and received ultrasounds far less often compared to in-clinic patients. IMPLICATIONS: We could provide telemedicine without the need for ultrasound to most women. Larger studies without routine ultrasound use are needed to validate our findings. Unscheduled communication with clinic staff was more frequent with telemedicine medication abortion patients. This information may help clinics when planning to add this service.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".