The Effect and Feasibility of mHealth-Supported Surgical Site Infection Diagnosis by Community Health Workers After Cesarean Section in Rural Rwanda: Randomized Controlled Trial
Notice bibliographique
Résumé
BACKGROUND: The development of a surgical site infection (SSI) after cesarean section (c-section) is a significant cause of morbidity and mortality in low- and middle-income countries, including Rwanda. Rwanda relies on a robust community health worker (CHW)-led, home-based paradigm for delivering follow-up care for women after childbirth. However, this program does not currently include postoperative care for women after c-section, such as SSI screenings. OBJECTIVE: This trial assesses whether CHW's use of a mobile health (mHealth)-facilitated checklist administered in person or via phone call improved rates of return to care among women who develop an SSI following c-section at a rural Rwandan district hospital. A secondary objective was to assess the feasibility of implementing the CHW-led mHealth intervention in this rural district. METHODS: A total of 1025 women aged ≥18 years who underwent a c-section between November 2017 and September 2018 at Kirehe District Hospital were randomized into the three following postoperative care arms: (1) home visit intervention (n=335, 32.7%), (2) phone call intervention (n=334, 32.6%), and (3) standard of care (n=356, 34.7%). A CHW-led, mHealth-supported SSI diagnostic protocol was delivered in the two intervention arms, while patients in the standard of care arm were instructed to adhere to routine health center follow-up. We assessed intervention completion in each intervention arm and used logistic regression to assess the odds of returning to care. RESULTS: The majority of women in Arm 1 (n=295, 88.1%) and Arm 2 (n=226, 67.7%) returned to care and were assessed for an SSI at their local health clinic. There were no significant differences in the rates of returning to clinic within 30 days (P=.21), with high rates found consistently across all three arms (Arm 1: 99.7%, Arm 2: 98.4%, and Arm 3: 99.7%, respectively). CONCLUSIONS: Home-based post-c-section follow-up is feasible in rural Africa when performed by mHealth-supported CHWs. In this study, we found no difference in return to care rates between the intervention arms and standard of care. However, given our previous study findings describing the significant patient-incurred financial burden posed by traveling to a health center, we believe this intervention has the potential to reduce this burden by limiting patient travel to the health center when an SSI is ruled out at home. Further studies are needed (1) to determine the acceptability of this intervention by CHWs and patients as a new standard of care after c-section and (2) to assess whether an app supplementing the mHealth screening checklist with image-based machine learning could improve CHW diagnostic accuracy. TRIAL REGISTRATION: ClinicalTrials.gov NCT03311399; https://clinicaltrials.gov/ct2/show/NCT03311399.
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 distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,019 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
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.
score_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 découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».