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Enregistrement W2941606032 · doi:10.1111/1471-0528.15802

Telemedicine for medical abortion – time to move towards broad implementation

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

Notice bibliographique

RevueBJOG An International Journal of Obstetrics & Gynaecology · 2019
Typeletter
Langueen
DomaineMedicine
ThématiqueReproductive Health and Contraception
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésAbortionTelemedicineMedical abortionMedicineHealth careUnsafe abortionMedical emergencyFamily medicineNursingFamily planningPregnancyPopulationEnvironmental healthPolitical scienceMisoprostol

Résumé

récupéré en direct d'OpenAlex

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.

Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.

Comment cette classification a été obtenuedéplier

Prédiction machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,119
score de la tête « metaresearch » (Gemma)0,251
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: aucune
GenreSignal candidat: Éditorial · Signal consensuel: aucune
Score de désaccord entre enseignants0,119
Score d'incertitude au seuil0,627

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,1190,251
Méta-épidémiologie (sens strict)0,0010,002
Méta-épidémiologie (sens large)0,0040,007
Bibliométrie0,0050,006
Études des sciences et des technologies0,0010,002
Communication savante0,0100,020
Science ouverte0,0030,006
Intégrité de la recherche0,0060,008
Charge utile insuffisante (le modèle a refusé de juger)0,0150,001

Scores machine (provisoires)

Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.

Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.

Tête enseignante Opus0,022
Tête enseignante GPT0,375
Écart entre enseignants0,353 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreÉditorial

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations14
Publié2019
Routes d'admission1
Résumé présentoui

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