Clinical documentation is a significant driver of burnout among physicians. Ambient artificial intelligence (AI) scribes, which leverage generative large language models to automate the creation of clinical notes from patient–physician conversations, are rapidly emerging as a potential solution. While these tools promise to enhance efficiency and reduce administrative tasks, concerns about the quality, accuracy and potential biases persist. There is now a need for a systematic synthesis of evidence to evaluate the impact of these technologies in clinical practice. To assess the effects of ambient AI scribes on physicians’ clinical documentation, the specific objectives are to: (1) evaluate the effectiveness of these tools on documentation, including accuracy and completeness; (2) synthesise evidence on the impact on physician efficiency after adoption, including time spent on documentation and (3) examine physicians’ satisfaction with these tools, including physicians’ perceived burden.

A systematic review of quantitative or mixed-method studies as well as preprints will be conducted. We will perform a comprehensive search of four electronic databases (PubMed, IEEE Xplore, APA PsycInfo and Web of Science, along with medRix and ClinicalTrials.gov for preprints) for empirical studies published between January 2023 and March 2026. The review will synthesise studies comparing physicians’ use of ambient AI scribes with traditional documentation approaches. Given the anticipated heterogeneity of the studies, a narrative synthesis will be employed to summarise the findings. Where common quantitative outcomes exist, effect sizes will be calculated using Hedges’ g, mean differences or risk ratios/odds ratios as appropriate. The overall quality of evidence will be assessed using the Grading of Recommendations Assessment, Development and Evaluation (GRADE) framework.

As no patient data are involved in the data collection, no ethical approval is acquired. Results will be disseminated in a peer-reviewed, open-access journal, and presented at relevant academic conferences.

CRD420251149086.

Inside CKD aims to assess the burden of chronic kidney disease (CKD) and the cost-effectiveness of screening programmes in Belgium.

Microsimulation-based modelling.

Data derived from national statistics and key literature from Belgium.

Virtual populations of ≥10 million individuals, representative of Belgian populations of interest, were generated based on published data and cycled through the Inside CKD model. Baseline input data included age, estimated glomerular filtration rate (eGFR), urine albumin-creatinine ratio (UACR) and CKD status.

Outcomes included the clinical and economic burden of CKD during 2022–2027 and the cost-effectiveness of two different CKD screening programmes (one UACR measurement and two eGFR measurements or only two eGFR measurements, followed by renin-angiotensin-aldosterone system inhibitor treatment in newly diagnosed eligible patients). The economic burden estimation included patients diagnosed with CKD stages 3–5; the screening cost-effectiveness estimation included patients aged ≥45 years with no CKD diagnosis and high-risk subgroups (with cardiovascular disease, hypertension, type 2 diabetes or aged ≥65 years).

Between 2022 and 2027, CKD prevalence is estimated to remain stable and substantial at approximately 1.66 million, with 69.9% undiagnosed. The total healthcare cost of patients diagnosed with CKD is expected to remain stable at approximately 2.15 billion per year. The one UACR, two eGFR measurement screening programme was cost-effective in all populations, with an incremental cost-effectiveness ratio of 3623 per quality-adjusted life year (QALY) gained in those aged ≥45 years, well below the estimated willingness-to-pay threshold of 43 839 per QALY gained.

Without changes to current practice, the disease burden of CKD in Belgium is predicted to remain substantial over the next few years. This highlights the need for timely diagnosis of CKD and demonstrates that, in line with guideline recommendations, implementing a CKD screening programme involving UACR and eGFR measurements followed by treatment would be cost-effective.