Annals of family medicine
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Annals of family medicine · Jan 2023
Impact of Primary Care Attributes on Hospitalization During the COVID-19 Pandemic: A Nationwide Prospective Cohort Study in Japan.
During a pandemic, when there are many barriers to providing preventive care, chronic disease management, and early response to acute common diseases for primary care providers, it is unclear whether primary care attributes contribute to reducing hospitalization. We aimed to examine the association between core primary care attributes and total hospitalizations during the COVID-19 pandemic. ⋯ Our study revealed that the provision of primary care, particularly high-quality primary care, was associated with decreased total hospitalization, even during a pandemic when there are many barriers to providing usual medical care. These findings support policies that seek to strengthen primary care systems during and after the COVID-19 pandemic.
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Annals of family medicine · Jan 2023
Differences in Diabetes Control in Telemedicine vs. In-Person Only Visits in Ambulatory Care Setting.
Importance: The COVID-19 pandemic has led to increased utilization of telemedicine. Patients with diabetes are a vulnerable population that require regular treatment and monitoring. Little is known about the impact visit modality on diabetes outcomes in an ambulatory setting. ⋯ Patients with 2+ telemedicine visits had significantly lower odds of uncontrolled diabetes compared to all in-person visits after adjusting for age, gender, race, ethnicity, insurance status, and comorbidities (OR: 0.88; 95% CI: 0.79 - 0.99, p = 0.03). Conclusions and Relevance: Telemedicine visits were associated with a lower odds of uncontrolled diabetes. Further work is warranted to explore the relationship between telemedicine visits, equitable access to care, and diabetes outcomes.
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Annals of family medicine · Jan 2023
The Diagnostic Value of the Patient's Reason for Encounter in Primary Care: A Retrospective Cohort Study.
Context Knowledge of incidence, prevalence and trends in morbidity support the diagnostic process of general practitioners (GPs). GPs use estimated probabilities of probable diagnoses to guide their policy on testing and referral. However, GPs estimations often are implicit and imprecise. ⋯ Other patient factors might also have relevant predictive value. Artificial intelligence can be beneficial to add more variables to build a diagnostic prediction model. This model can support GPs in the diagnostic process and can help students and residents in training.
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Annals of family medicine · Jan 2023
Assessing Representativeness of Randomised Controlled Trials using Serious Adverse Events.
Context: The applicability of randomised controlled trials of pharmacological agents to older people with frailty/multimorbidity is often uncertain, due to concerns that trials are not representative. However, assessing trial representativeness is challenging and complex. Objectives: We explore an approach assessing trial representativeness by comparing rates of trial Serious Adverse Events (SAEs: most of which reflect hospitalisations/deaths) to rates of hospitalisation/death in routine care (which, in a trial setting, would be SAEs be definition). ⋯ Conclusion: Trial participants experience fewer SAEs than expected based on age/sex/condition hospitalisation and death rates in routine care, confirming the predicted lack of representativeness. This difference is only partially explained by differences in multimorbidity. Assessing observed/expected SAE may help assess applicability of trial findings to older populations in whom multimorbidity and frailty are common.
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Annals of family medicine · Jan 2023
SaFETy Score as a Predictor of Gun Violence in Adolescent-young Adults Patients in a Primary Care Setting.
Context: Firearm injury is the leading cause of death for individuals aged 12-24. Despite far-reaching impacts of gun violence, there is insufficient data available to inform prevention strategies. Screening adolescent patients and counseling those at high risk is one promising strategy that family physicians could implement in their clinics to prevent firearm exposure. ⋯ Correlations between baseline and six months post baseline show association between the SaFETy score and a variety of different gun violence exposures including from friends, parents or guardians, and during various situations. Conclusions: When used in a primary care setting, the SaFETy score is a useful tool in helping to predict the risk of gun violence exposure in an adolescent population. Learning Objectives: Understand the relevance of the SaFETy questions in predicting gun violence & Understand the importance for primary care clinicians to predict gun violence risk Research Category: Child and Adolescent Health Study Design: Longitudinal quantitative study conducted over six month.