Assessing new patient attachment to an integrated, virtual care programme in rural primary care
Bibliographic record
Abstract
INTRODUCTION: An estimated 20% of residents of Renfrew County, a rural and underserved community in Ontario, do not have a family physician or alternative primary care provider. Integrated virtual care (IVC) aims to address this crisis by enrolling individuals who are not currently attached to a primary care provider, to a named family physician who works predominantly remotely. The physician is embedded within an existing, local family health team. The aim of this study was to assess and describe the IVC model's capacity to enrol previously unattached patients in Renfrew County and provide adequate primary care. METHODS: We conducted a cross-sectional, descriptive study of data collected from patients enrolled for at least 3 months to an IVC family physician from 15 November 2021 (earliest appointment date for first IVC patients) to 30 June 2022 inclusive. RESULTS: N = 790 patients were successfully attached to a family physician and received at least 3 months of care through IVC within the study period. Of the study population, 65% were female and over 75% were under the age of 55. Among patients who were current smokers at the time of IVC enrolment (n = 115), approximately 1 in 5 (18.3%) started a smoking cessation programme following referral by their IVC physician. In addition, IVC physicians and allied health professionals performed 66 colorectal cancer screenings, 164 cervical cancer screenings and 39 breast cancer screenings during the study period, bringing many overdue patients up to date for routine testing. CONCLUSION: IVC has been successful in attaching previously unattached patients to a family physician and providing, comprehensive, team-based primary care during its initial 7 months of operation. Similar integrated primary care delivery concepts can also use these results to guide their own development and quality improvement. INTRODUCTION: On estime que 20% des habitants du comté de Renfrew, une communauté rurale et mal desservie de l'Ontario, n'ont pas de médecin de famille ou d'autre prestataire de soins primaires. Le programme de Soins virtuels intégrés (SVI) vise à résoudre cette crise en proposant aux personnes qui n'ont pas de prestataire de soins primaires de consulter un médecin de famille désigné qui travaille principalement à distance. Le médecin est intégré à une équipe de santé familiale locale existante. L'objectif de cette étude était d'évaluer et de décrire la capacité du modèle de SVI à inscrire des patients qui n'étaient pas rattachés à un prestataire de soins primaires dans le comté de Renfrew et à leur fournir des soins primaires adéquats. MTHODES: Nous avons mené une étude transversale et descriptive des données recueillies auprès des patients inscrits depuis au moins trois mois auprès d'un médecin de famille IVC entre le 15 novembre 2021 (date de rendez-vous la plus proche pour les premiers patients SVI) et le 30 juin 2022 inclus. RSULTATS: N = 790 patients ont été rattachés avec succès à un médecin de famille et ont reçu au moins 3 mois de soins par l'intermédiaire des SVI au cours de la période d'étude. Parmi la population étudiée, 65% étaient des femmes et plus de 75% avaient moins de 55 ans. Parmi les patients qui fumaient au moment de leur inscription aux SVI (n = 115), environ 1 sur 5 (18,3%) a entamé un programme de sevrage tabagique après avoir été orienté par son médecin en SVI. En outre, les médecins du centre et les professionnels paramédicaux ont effectué 66 dépistages du cancer colorectal, 164 dépistages du cancer du col de l'utérus et 39 dépistages du cancer du sein au cours de la période d'étude, ce qui a permis à de nombreux patients en retard de SE soumettre à des tests de routine. CONCLUSION: Le programme de SVI a réussi à mettre en relation des patients qui ne l'étaient pas auparavant avec un médecin de famille et à fournir des soins primaires complets en équipe au cours de ses sept premiers mois d'activité. Des concepts similaires de prestation de soins primaires intégrés peuvent également utiliser ces résultats pour guider leur propre développement et l'amélioration de la qualité.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".