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The transition to value-based reimbursements compels providers to understand ways in which they can improve patient health outcomes while at the same time reduce the cost of delivery. Amongst the strategies to do so providers are educating their patients on the value of ambulatory clinics and home care in an effort to reduce the volume of avoidable hospital and emergency department admissions that are tied to higher cost and disruption in care. Fortunately, care coordination programs that focus on helping patients with prior admissions and comorbidities with home care have been shown to reduce the reliance on inpatient admittance. That said, not all patients may be enrolled in these programs and complex challenges remain in being able to identify which patients are likely to admit into acute care treatment.
AI empowers your care managers by predicting in advance which patients are likely to be admitted. Unlike existing evaluations of admission risk that are based on limited factors, AI is able to evaluate admission risk with much higher accuracy by finding hidden patterns across outpatient, inpatient, emergency department, and care management data. Based on each patient’s medical history and interactions, AI will reveal which factors contribute to their risk of admission, offering care managers with an understanding of which intervention strategies they should apply depending on each patient’s conditions. Furthermore, AI maximizes the care manager’s impact as they can triage their patients by their probability of admissions. Adding additional focus on those at the highest risk of admissions will maximize the care manager’s utilization of resources. Intervention strategies care managers could apply once they have identified which patients have a high risk of admissions include enrolling them into programs that improve care coordination, home care, transportation, and medication adherence.
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Healthcare companies are using machine learning and AI to increase top and bottom line through gaining competitive advantages, reducing expenses, and improving efficiencies. They are optimizing all areas of their business from readmission risk and occupancy rates to marketing, in order to make data-driven decisions that lead to increased profitability.