Our AI dashboard integrates data from various sources within the EMR system, such as patient records, lab results, medical imaging, and demographic information. It then presents the data in a visual format, such as charts, graphs, and tables, making it easier for healthcare providers to interpret and understand the information.
The AI algorithms in our dashboard continuously analyze incoming data from patients, updating the dashboard in real-time. This allows healthcare professionals to monitor patients' conditions, track vital signs, and identify any deviations or anomalies promptly. Real-time monitoring enables early detection of potential issues, leading to faster interventions and improved patient outcomes.
AI algorithms can utilize historical patient data to predict future outcomes or identify potential risks. The dashboard can display predictive analytics models that provide insights into disease progression, readmission rates, treatment response, or the likelihood of specific complications. These predictions help healthcare providers make informed decisions and plan appropriate interventions.
The AI algorithms integrated into the dashboard help in providing decision-support capabilities. For example, they can suggest personalized treatment options, recommend appropriate medications based on patient characteristics, or alert healthcare providers to potential drug interactions or contraindications. Decision support features can enhance clinical decision-making and reduce errors.
An AI-based dashboard can analyze aggregated patient data to identify trends and patterns at the population level. It can help healthcare organizations monitor the health of specific patient cohorts, track disease outbreaks, identify high-risk groups, and design targeted interventions to improve population health outcomes.
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Anil has CHF, diabetes and arthritis. He has 10 different physicians and has been hospitalized three times over the past six months. He admits to not knowing how to take his medications and to falling 2-3 times recently. He was discharged two weeks ago and has many in-home services but no focused care plan. His family is concerned about his ability to live alone. Anil is worried about his insurance and how to pay for care.
Seventy-two-year-old Neena Gupta saw a different physician every other week with each one ordering different medications, or changing individual treatment plans. Neena became confused and concerned about the cost of her medications, so she just stopped taking some of her medications and missed many key physician appointments.