Difference between revisions of "Healthcare AI Use Cases"
From PatientRecovery
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* Medication Adherence: Which patients are most likely to be noncompliant with medications? | * Medication Adherence: Which patients are most likely to be noncompliant with medications? | ||
| − | + | Payers and Health Plans <br> | |
| + | * Trend: Which members are likely to see large increases in their overall health risk over the next three to six months? | ||
| + | * Readmissions: Which members are most likely to be readmitted to the hospital? | ||
| + | * Medication Adherence: Which members are most likely to be noncompliant with medication plans? | ||
| + | * Palliative Care: Which members are most likely to benefit from discussions with a palliative care specialist? | ||
| + | * ED Over-Utilization: Which members are most likely to benefit from establishing a relationship with a primary care provider? | ||
| + | * Disenrollment: Which members will most likely to disenroll? | ||
| + | * Fraud: How do new data sources allow health plans to spot fraud sooner? | ||
| + | * Payment Integrity: How can AI help ensure proper reimbursement? | ||
Other <br> | Other <br> | ||
Revision as of 08:54, 10 July 2020
ClosedLoop AI Use Cases
Hospitals
- Appointmnet No-Shows - Predict patients most likely to miss appointments
- Predict patients most likely to acquire infections like sepsis
- Predict patients most likely to benefit from periodic check ups
- Leakage - Network Integrity - Out of Network
Health Insurers
- Risk Adjustment - Suspect Diagnosis
- Preventable Hospitalizations
- Readmissions - Predict patient readmissions
- Chronic Disease Onset and Progression - Predict onset or progression of chronic diseases.
- Patients with highest overall risk in the next 6 months or year
Providers & ACOs
- Total Risk: Who will be my most expensive patients this year
- ED Over-Utilization: Which of my patients would most benefit from establishing a relationship with a primary care provider?
- Readmissions: Which patients are most likely to be readmitted to the hospital?
- Transportation: Which patients are most likely to need help with transportation in order to make it to their appointments
- Rising Risk: Which patients are likely to see large increases in their overall health risk over the next 30/60 days?
- Chronic Disease: Which patients are most likely to develop or progress in the severity of a chronic disease
- Medication Adherence: Which patients are most likely to be noncompliant with medications?
Payers and Health Plans
- Trend: Which members are likely to see large increases in their overall health risk over the next three to six months?
- Readmissions: Which members are most likely to be readmitted to the hospital?
- Medication Adherence: Which members are most likely to be noncompliant with medication plans?
- Palliative Care: Which members are most likely to benefit from discussions with a palliative care specialist?
- ED Over-Utilization: Which members are most likely to benefit from establishing a relationship with a primary care provider?
- Disenrollment: Which members will most likely to disenroll?
- Fraud: How do new data sources allow health plans to spot fraud sooner?
- Payment Integrity: How can AI help ensure proper reimbursement?
Other
- Identify patients' with collapsed lungs - artificial intelligence-enabled mobile X-ray system flags images of patients who need immediate intercession, ensuring that patients with collapsed lungs receive more timely care. (7/8/20)
- Predicts patients' hospitalization risk and triages them to appropriate care - uses AI tech, EHR data and a questionnaire to perform clinical intake of patients visiting ER, Urgent Care or Home (6/30/20)
- Diagnosed breast cancer at a higher rate than 11 pathologists. AI model using algorithms and deep learning (12/12/17)
