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Record W2941606032 · doi:10.1111/1471-0528.15802

Telemedicine for medical abortion – time to move towards broad implementation

2019· letter· en· W2941606032 on OpenAlexaboutno aff
Daniel Grossman

Bibliographic record

VenueBJOG An International Journal of Obstetrics & Gynaecology · 2019
Typeletter
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsnot available
Fundersnot available
KeywordsAbortionTelemedicineMedical abortionMedicineHealth careUnsafe abortionMedical emergencyFamily medicineNursingFamily planningPregnancyPopulationEnvironmental healthPolitical scienceMisoprostol

Abstract

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The systematic review by Endler et al. (BJOG 2019;126:1094-102), provides reassuring evidence from a range of settings that telemedicine provision of medical abortion is safe, effective, and well-liked by patients and providers. Clinical outcomes were found to be similar to those for models of care that involved an in-person visit. The authors note that surgical evacuation rates for telemedicine patients were higher than those reported for services with in-person visits. However, these higher rates were driven by studies in settings where abortion is legally restricted, and patients may be cared for by clinicians with limited experience with medical abortion. One outcome that was not assessed in this systematic review is how telemedicine for medical abortion improves access to care. In settings where abortion is legally restricted and availability of safe abortion services may be very limited, if available at all, high-quality telemedicine services undoubtedly improve access. But even in settings where abortion is legal and safe, telemedicine appears to improve access. In an analysis of data from Iowa (USA), the introduction of telemedicine services providing medical abortion was associated with a reduction in second-trimester abortion and increased likelihood of obtaining the service for women living in areas more distant from clinics providing in-person care (Grossman et al. Am J Public Health 2013;103:73–8). The review also highlights some of the challenges with performing abortion research, particularly in settings where the service is legally restricted. Studies in these settings included in the review lacked a control group, as in-person abortion care in these countries was generally prohibited. Loss to follow-up was also high in several of these studies. Where there is a chance that women may face legal risks from accessing abortion care, they may be reticent to participate in follow-up surveys sent by email or telephone. The fact that all of the studies in the review performed in multiple settings have similar findings is reassuring despite these limitations. The findings from this systematic review should be used to inform policy and remove barriers to expanding medical abortion telemedicine services. In the USA, despite evidence documenting the safety and effectiveness of the service (Grossman et al. Obstet Gynecol 2011;118,2 Pt 1:296–303; Grossman et al. Obstet Gynecol 2017;130:778–82), 17 states have banned the use of telemedicine to provide abortion care, and many of these are the same states with limited access to clinic-based services. The US Food and Drug Administration requires that mifepristone be dispensed in a clinic, doctor's office or hospital, despite the lack of evidence supporting the need for this restriction (Mifeprex REMS Study Group et al. N Engl J Med 2017;376:790–4). This restriction has been interpreted to prohibit the mailing of mifepristone, which has limited the expansion of direct-to-patient models of telemedicine such as those described in the review in Australia and Canada and those provided by Women on Web. These restrictions are not evidence-based and limit access to care. Telemedicine is being used in many areas of medicine – from connecting specialists to primary care providers to reaching patients directly in their homes with a variety of healthcare services. Medical abortion is just one more use for this technology, and the review by Endler and colleagues demonstrates how appropriate this service is for telemedicine. Dr Grossman reports personal fees from Planned Parenthood Federation of America, outside the submitted work. A completed disclosure of interests form is available to view online as supporting information. Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.007
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.426
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.000

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.

Opus teacher head0.022
GPT teacher head0.375
Teacher spread0.353 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations14
Published2019
Admission routes1
Has abstractyes

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