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Enregistrement W4405350159 · doi:10.1101/2024.02.17.24302708

Private sector tuberculosis care quality during the COVID-19 pandemic: A repeated cross-sectional standardized patients study of adherence to national TB guidelines in urban Nigeria

2024· preprint· en· W4405350159 sur OpenAlexafffund
Angelina Sassi, Lauren Rosapep, Bolanle Olusola-Faleye, Elaine Baruwa, Ben Johns, Mohammad Abdullah Heel Kafi, Lavanya Huria, Nathaly Aguilera Vasquez, Benjamin Daniels, Jishnu Das, Chukwuma Anyaike, Obioma Chijioke-Akaniro, Madhukar Pai, Charity Oga‐Omenka

Notice bibliographique

RevuemedRxiv · 2024
Typepreprint
Langueen
DomaineMedicine
ThématiqueTuberculosis Research and Epidemiology
Établissements canadiensUniversity of WaterlooMcGill University
Organismes subventionnairesMcGill University Health CentreMcGill UniversityGeorgetown UniversityBill and Melinda Gates FoundationUnited States Agency for International Development
Mots-clésPandemicCross-sectional studyCoronavirus disease 2019 (COVID-19)MedicineTuberculosisEnvironmental healthQuality (philosophy)2019-20 coronavirus outbreakFamily medicineVirologyInternal medicinePathologyOutbreakDiseaseInfectious disease (medical specialty)

Résumé

récupéré en direct d'OpenAlex

Abstract Only a third of TB cases in Nigeria in 2020 were diagnosed and notified, in part due to low detection and underreporting from the private health sector. Using a standardized patient (SP) survey approach, we assessed how management of presumptive TB in the private sector aligns with national guidelines and whether this differed from a study conducted before the start of the COVID-19 pandemic. Thirteen standardized patients presented a presumptive TB case to 511 private providers in urban areas of Lagos and Kano states in May and June 2021. Private provider case management was compared with national guidelines divided into three main steps: SP questioned about cough duration; sputum collection attempted for TB testing; and non-prescription of anti-TB medications, antibiotics, and steroids. SP visits conducted in May-June 2021 were directly compared to SP visits conducted in the same areas in June-July 2019. Overall, only 145 of 511 (28%, 95% CI: 24.5–32.5%) interactions were correctly managed according to Nigerian guidelines, as few providers completed all three necessary steps. Providers in 71% of visits asked about cough duration (362 of 511, 95% CI: 66.7–74.7%), 35% tested or recommended a sputum test (181 of 511, 95% CI: 31.3–39.8%), and 79% avoided prescribing or dispensing unnecessary medications (406 of 511, 95% CI: 75.6–82.8%). COVID-19 related questions were asked in only 2.4% (12 of 511, 95% CI: 1.3–4.2%) of visits. During the COVID-19 pandemic, few providers completed all steps of the national guidelines. Providers performed better on individual steps, particularly asking about symptoms and avoiding prescription of harmful medications. Comparing visits conducted before and during the COVID-19 pandemic showed that COVID-19 did not significantly change the quality of TB care. Key Messages What is already known on this topic: Less than half of new TB cases in Nigeria are diagnosed and notified. As most initial health care seeking for TB in Nigeria occurs in the private sector, increasing the quality of TB care in the private sector is of great importance. COVID-19 may have put further stressors on TB care quality due to changes in care seeking behavior, stigma against COVID-19, and disproportionate attention at the health system level on pandemic control. This study explored whether private providers’ practices are in alignment with national standards for TB screening in Nigeria, how these practices have changed following the onset of the COVID-19 pandemic, and what factors are associated with providers that deliver clinically correct TB screening services. What this study adds: Fewer than one-third of the SP visits conducted in this study were correctly managed according to the Nigerian National TB and Leprosy Control Program guidelines. Clinical correctness of TB care in the private sector of urban Nigeria has not been majorly affected by COVID-19 according to our study results. Our results indicate that very little observed attention was paid to COVID-19 in this sample of private facilities. How this study might affect research, practice or policy: Increased efforts to engage and support private providers, and implementing solutions such as working with drug shop proprietors to make referring for testing a standard part of their practice may help reduce the testing bottleneck at drug shops. Although Nigeria has maintained pre-pandemic levels of TB notification, it is important to establish high-quality screening by all providers to find the missing patients with TB and close the gap in TB notification.

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)0,002
score de la tête « metaresearch » (Gemma)0,006
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,010
Score d'incertitude au seuil0,019

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0020,006
Méta-épidémiologie (sens strict)0,0000,001
Méta-épidémiologie (sens large)0,0000,001
Bibliométrie0,0010,001
Études des sciences et des technologies0,0010,001
Communication savante0,0010,001
Science ouverte0,0000,001
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0010,000

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.

Tête enseignante Opus0,147
Tête enseignante GPT0,465
Écart entre enseignants0,318 · 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'étudeObservationnel
Domainenon disponible
GenreEmpirique

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

En bref

Citations0
Publié2024
Routes d'admission2
Résumé présentoui

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