Background: Burnout among clinicians, including physicians, is a growing concern in healthcare. An overwhelming burden of clinical documentation is a significant contributor. While medical scribes have been employed to mitigate this burden, they have limitations such as cost, training needs, and high turnover rates. Artificial intelligence (AI) scribe systems can transcribe, summarize, and even interpret clinical conversations, offering a potential solution for improving clinician well-being. We aimed to evaluate the effectiveness of AI scribes in streamlining clinical documentation, with a focus on clinician experience, healthcare system efficiency, and patient engagement. Methods: We conducted a systematic review following Cochrane methods and PRISMA guidelines. Two reviewers conducted the selection process independently. Eligible intervention studies included quantitative and mixed-methods studies evaluating AI scribe systems. We summarized the data narratively. Results: Eight studies were included. AI scribes demonstrated positive effects on healthcare provider engagement, with users reporting increased involvement in their workflows. The documentation burden showed signs of improvement, as AI scribes helped alleviate the workload for some participants. Many clinicians have found AI systems to be user-friendly and intuitive, although some have expressed concerns about scribe training and documentation quality. A limited impact on reducing burnout was found, although documentation time improved in some studies. Conclusions: Most of the studies reported in this review involved small sample sizes and specific healthcare settings, limiting the generalizability of the findings to other contexts. Accuracy and consistency can vary significantly depending on the specific technology, model training data, and implementation approach. AI scribes show promise in improving documentation efficiency and clinician workflow, although the evidence remains limited and heterogeneous. Broader and real-world evaluations are needed to confirm their effectiveness and inform responsible implementations.

Context: More than 18M people worldwide (150K Canadians) are living with Long COVID resulting in debilitating sequalae and disabilities that impact their quality of life and capacity to return to work. A new care model is needed for persons living with this complex and multi-systemic disease. Objectives: What is the best-available evidence about care models for persons living with Long COVID? Design: Rapid Living Systematic Review. Method: We systematically searched seven electronic databases (MEDLINE, Embase, Web of Science, COVID-END, L-OVE, CDRS and WHO Ovid) on May 27 ^th , 2021. Two independent reviewers screened titles, abstracts and full text. We included studies reporting on 1- persons living with Long COVID and 2- proposing a specific care model (i.e., dedicated clinic, care pathway). We extracted characteristic of studies (e.g., countries, study design, age group), referral pathways targeted (e.g., hospitalized, community), reporting of the care model implementation with number of patients, clinical settings of care model (e.g., primary care), healthcare professions included in the care model, care model principles (e.g., person-centred care) and care model components (e.g., standardized symptoms assessment). We used descriptive statistics and frequency count. Results: We screened 2181 citations, read 65 full text and included 12 eligible articles reporting on care models for Long COVID. Half studies were from the United Kingdom. 7 out of 12 models reported conceptual models without a description of implementation. All but one model was designed for discharge and long-term follow-up of hospitalized patients and half models were designed for non- hospitalized or patients who lived with the disease only in the community. Nine out of 12 care models included primary care, 8 out of 12 included specialized clinics and all studies included rehabilitation services. A total of 30 healthcare professions and medical specialties were proposed for staffing Long COVID services. More than half studies proposed multidisciplinary teams, integrated/coordination of care, evidence-based care and patient-centred care as key care model principles. Standardized symptom assessment, follow-up system and virtual care were the most frequent care model components. Conclusion: The implementation of care models for Long COVID is underway in several countries. Care models need to include both hospitalized and non-hospitalized patients. A complete care model for this population appears to design a care pathway integrating primary care, rehabilitation services and specialized clinics for medical assessment. The entry into care pathways is likely possible through a centralized referral system. It is possible to design sustainable and equitable care pathways for Long COVID in Canada integrated in current infrastructure. Protocol/Topic Registration: CRD42021282266 Summary: An estimated 150K Canadians, mostly women, are facing debilitating sequalae and disabilities from Long COVID that impact their quality of life and capacity to return to work. A new care model is needed for persons with this complex and multi-systemic disease. We identified international care models describing the integration of primary care, rehabilitation services and specialized assessment clinics for Long COVID. Implications: Limited evidence from this review of international care models for Long COVID point out to a care model for the Canadian context that should be co- designed with patients, clinicians, decision makers and researchers, and include: 1- A coordination unit to centrally receive referrals from both hospitalized and community-based patients; 2- Training of primary care teams to screen and support medical needs; 3- Integrated local multidisciplinary rehabilitation services; and 4- Access to medical specialty clinics for advanced testing and diagnoses. What is the current situation?: More than 150K Canadians are with living the affliction of Long COVID, the patient-led term to describe long-term consequences of COVID-19. Long COVID is a multi-systemic and unpredictable disease impacting quality of life and return to work in middle aged population. To avoid widespread long-term disabilities impacting public health, Canadian provinces are seeking to organize a sustainable and equitable care model for Long COVID. What is the objective?: To provide the best-available evidence about care models for persons living with Long COVID. How was the review conducted?: We systematically searched seven electronic databases (MEDLINE, Embase, Web of Science, COVID-END, L-OVE, CDRS and WHO Ovid) on May 27th, 2021. Two independent reviewers screened title, abstract and full text. We included studies reporting on 1- persons living with Long COVID (post- hospitalized and community based) and 2- a specific care model (i.e., dedicated clinic, care pathway). We extracted characteristic of studies, referral pathways, clinical settings of care model, healthcare professions included in the care models, care model principles, care model components and reporting of the care model implementation. What did the review find?: We found 12 international care models for Long COVID that covers follow-up of patients discharged following a hospitalization and patients who had lived the infection in the community. Most reported elements included in these care models were a coordination unit, primary care pathways, access to multidisciplinary rehabilitation and specialized medical services. The impact and costs of these care models are not yet reported.

Objective Information regarding the impact of COVID-19 in children with brain-based disabilities, or those at risk of developing such conditions, remains scarce. The objective was to evaluate if children with brain-based disabilities are more likely to (1) develop COVID-19, (2) develop complications from the disease, and (3) to have a poorer prognosis. Study design We conducted a rapid review using search strategies iteratively developed and tested by an experienced medical information specialist in consultation with the review team and a panel of knowledge users. Searches were initially performed on April 18th, 2021, and updated on October 31st, 2020. Four reviewers individually performed study selection using pilot-tested standardized forms. Single reviewers extracted the data using a standardized extraction form that included study characteristics, patients’ characteristics, and outcomes reported. Results We identified 1448 publications, of which 29 were included. Studies reported data on 2288 COVID-19 positive children, including 462 with a brain-based disability, and 72 at risk of developing such disability. Overall, the included studies showed a greater risk to develop severe COVID-19 disease in children with brain-based disabilities. Although mortality is very low, the case-fatality rate appeared to be higher in children with disabilities compared to children without disabilities. Conclusions Our review shows that children with brain-based disabilities are overrepresented in hospitalization numbers compared to children without disabilities. However, most studies included children that were hospitalized from COVID-19 in secondary and tertiary care centers. Results of this review should therefore be interpreted with caution.

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