Impact of the COVID-19 Pandemic on Primary Care Access for Patients with Hematologic Malignancies
Notice bibliographique
Résumé
Abstract Introduction: Primary care physicians are essential to cancer care. They frequently identify signs and symptoms leading to a diagnosis of cancer, and provide ongoing support and management of non-cancer health conditions during cancer treatment. Both primary care and cancer care have been greatly affected by the COVID-19 pandemic. In the United States, cancer-related patient encounters and cancer screening decreased over 40% and 80% respectively in January to April 2020 compared to 2019 (London et al. JCO Clin Cancer Inform 2020). However, the impact of the COVID-19 pandemic on primary care access for cancer patients remain unclear. Methods: We undertook a population-based, retrospective cohort study using healthcare databases held at ICES in Ontario, Canada. Patients with a new lymphoid or myeloid malignancy diagnosed within the year prior to the COVID-19 pandemic, between July 1, 2019 and September 30, 2019 (COVID-19 cohort) were compared to patients diagnosed in years unaffected by the COVID-19 pandemic, between July 1, 2018 - September 30, 2018 and July 1, 2017 - September 30, 2017 (pre-pandemic cohort). Both groups were followed for 12 months after initial cancer diagnosis. In the COVID-19 cohort, this allowed for at least 4 months of follow-up data occurring during the COVID-19 pandemic. The primary outcome was number of in-person and virtual visits with a primary care physician. Secondary outcomes of interest included number of in-person and virtual visits with a hematologist, number of visits to the emergency department (ED), and number of unplanned hospitalizations. Outcomes, reported as crude rates per 1000 person-months, were compared between the COVID-19 and pre-pandemic cohorts using Poisson regression modelling. Results: We identified 2882 individuals diagnosed with a new lymphoid or myeloid malignancy during the defined COVID-19 timeframe and compared them to 5997 individuals diagnosed during the defined pre-pandemic timeframe. The crude rate of in-person primary care visits per 1000 person-months significantly decreased from 574.4 [95% CI 568.5 - 580.4] in the pre-pandemic cohort to 402.5 [395.3 - 409.7] in the COVID-19 cohort (p < 0.0001). Telemedicine visits to primary care significantly increased from 5.3 [4.8 - 5.9] to 173.0 [168.4 - 177.8] (p < 0.0001). The rate of combined in-person and telemedicine visits to primary care did not change from 579.8 [573.8 - 585.8] in the pre-pandemic cohort to 575.5 [566.9 - 584.2] in the COVID-19 cohort (p = 0.43). In-person visits to hematologists decreased from 504.1 [498.5 - 509.7] to 432.8 [425.3 - 440.3] (p < 0.0001), and telemedicine visits to hematologists increased from 6.6 [6.0 - 7.3] to 75.9 [72.8 - 79.1] (p < 0.0001). The rate of combined visits to hematologists did not change from 510.7 [505.1 - 516.4] to 508.7 [500.6 - 516.8] (p = 0.68). The rate of ED visits significantly decreased from 95.1 [92.7 - 97.6] in the pre-pandemic cohort to 84.7 [81.4 - 88.0] in the COVID-19 cohort (p < 0.0001). The rate of unplanned hospitalizations did not change from 64.8 [62.8 - 66.8] to 65.7 [62.9 - 68.7] (p = 0.60). Conclusions: Primary care visits for patients with hematologic malignancies did not significantly change during the pandemic, but there was a sizeable shift from in-person to telemedicine visits. Similar findings were seen for visits to hematologists. While the rate of visits to the ED decreased, potentially due to concern of being exposed to the COVID-19 virus, the shift in ambulatory practices did not seem to impact the rate of unplanned hospitalizations. Disclosures No relevant conflicts of interest to declare.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,001 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 source (Gemma direct ou Codex distillé), 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 ».