Leveraging machine learning and deep-learning capabilities, SafeCare Applied Intelligence® fostered a new generation of healthcare applications, which are able to sense, reason, act, and adapt to address a range of healthcare challenges in areas such as medical errors, readmissions, redundant care and utilization, infections, and cost.
AI to Reduce Redundant Care
Duplicate & Unnecessary Hospital Testing
Gone are the days of the "shotgun" approach where panel testing is ordered and all tests are performed, regardless of likelihood of yielding a positive result.
AI to Cut Readmissions
All Cause Readmissions
Hospital readmissions are frequent, harmful, and costly to patients. Returning to the hospital for unplanned care disrupts patients’ lives, increases their risk of harmful events like healthcare-associated infections, and costs more money.
AI to Reduce Inpatient Deaths
Reduce Inpatient Mortality
Death rates provide information about important aspects of hospital care that affect patients’ outcomes – like prevention of and response to complications, emphasis on patient safety, and the timeliness of care.
AI to Predict Sepsis
Predict Sepsis Progression
Early identification of patients with non-severe sepsis is a critical first step in preventing sepsis progression. Progression of spesis to severe sepsis or septic shock is highly lethal.
AI to Prevent Infections
Prevent Hospital-acquired Infections
Patients admitted to the hospital for treatment of a medical problem sometimes get serious infections, and may even die. The days when hospital acquired infections were accepted by patients as an inevitable hazard of hospitalization are long gone.
AI to Improve Medication Safety
AI to Improve Costly Care
Target High Hospital Charges
Hospital prices increased a whopping 42% from 2007 to 2014 for inpatient care compared with 6% for physicians. To make healthcare costs more transparent, the federal government required hospitals nationwide to post their prices online.
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