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Summarize patient data and get concise information based on medical history
In Argentina, 33% of a physician’s time during consultations is spent recording and reviewing data in Electronic Health Records (EHRs) instead of direct interaction with patients [1].
In Colombia, EHR design does not always facilitate the immediate understanding of complex data, leading to errors in clinical decision-making [2].
Globally:Physicians spend an estimated 2–4 hours daily using EHRs, equating to 50% oftheir workday [3].
In Latin America: Studies highlight uneven adoption of EHRs, frequent errors, andprolonged data retrieval times [3].
Human Cost:Administrative burdens lead to burnout in 63% of physicians using EHRs [4].
Automated Summaries: Extract and present the most relevant clinical history information in a condensed and prioritized format.
Intelligent Data Analysis: Identify patterns and correlations in patient data to support decision-making.
Ease of Integration: Operates on existing EHR platforms without disrupting workflows [3].
The assistant is based on PubMed, which offers a wide range of biomedical research data, ensuring evidence-based insights. Additionally, the assistant integrates electronic health records (EHR), clinical trial databases, and patient medical records to provide a multifaceted view of each patient's medical history, ensuring summaries are accurate, relevant, and useful in the diagnostic process.
In Argentina, 33% of a physician’s time during consultations is spent recording and reviewing data in Electronic Health Records (EHRs) instead of direct interaction with patients [1].
In Colombia, EHR design does not always facilitate the immediate understanding of complex data, leading to errors in clinical decision-making [2].
Globally:Physicians spend an estimated 2–4 hours daily using EHRs, equating to 50% oftheir workday [3].
In Latin America: Studies highlight uneven adoption of EHRs, frequent errors, andprolonged data retrieval times [3].
Human Cost:Administrative burdens lead to burnout in 63% of physicians using EHRs [4].
Automated Summaries: Extract and present the most relevant clinical history information in a condensed and prioritized format.
Intelligent Data Analysis: Identify patterns and correlations in patient data to support decision-making.
Ease of Integration: Operates on existing EHR platforms without disrupting workflows [3].
Time Saved: Physicianscould save 2–3 hours daily, allowing more patient care or focus on criticaltasks [1].
Efficiency: Lackof optimized tools perpetuates diagnostic errors, increasing healthcare costsby up to 50% per patient due to unnecessary tests and treatments [2].
AdministrativeTime Reduction: AI can cut EHR management timeby 40% [1].
ImprovedDiagnostic Precision: Enhances identificationof complex conditions by 25% through automatic detection of critical data [3].
ProfessionalSatisfaction: Reduces burnout by 30% throughdecreased administrative workload, improving work-life balance [4].
EconomicImpact: Healthcare systems could save up to$12,000 per physician annually by optimizing resources and reducing errors [2].
The assistant is based on PubMed, which offers a wide range of biomedical research data, ensuring evidence-based insights. Additionally, the assistant integrates electronic health records (EHR), clinical trial databases, and patient medical records to provide a multifaceted view of each patient's medical history, ensuring summaries are accurate, relevant, and useful in the diagnostic process.
