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Performing a Literature Review for AI Applications in Healthcare…
Performing a Literature Review for AI Applications in Healthcare Administration
Information Sources
Journals
Abstracts
Research Articles
Machine learning tools
Copilot
ChatGPT
Data Bases
EndNote
National Library of Medicine
PubMed
Google Scholar
Potential AI Applications
Administrative Automation
Medical Coding & Billing
AI can extract diagnoses and procedures form notes to generate billing codes to improve claim processing
Clinical Documentation Assistance
AI tools can help physicians spend more quality time with their patients
Appointment Scheduling Optimization
AI can maximize clinic efficiency by predicting no-shows and matching patient needs with time slots
Prior Authorization Processing
AI can streamline this process by submitting documentation, checking policy standards
Clinical Decision Support
Treatment Recommendation System
AI analyzes patient data against clinical guidelines and research evidence to suggest optimal treatment plan
Provider Support
Addressing Provider Burnout
https://pubmed.ncbi.nlm.nih.gov/39500346/
Drug Interaction Alerts
Identify potential adverse drug interactions based on patient medical history and medication lists
Predictive Analytics
Patient Risk Stratification
AI can automate time-consuming tasks like calculating patient risk scores, retrieving relevant data and updating risk levels automatically
AI can strengthen Chronic Disease Risk Models by making them more predictive, more personalized and more procative than traditional statistical methods
AI assesses patient risk levels to allow clinicians to prioritize high-risk patients
AI can improve Hospital Readmissions Prediction by identifying which patients are most likely to return within 7-30 or 90 days
https://pubmed.ncbi.nlm.nih.gov/36434628/
Disease Progression Modeling
AI tracks disease trajectories to predict how conditions will evolve over time to help with treatment decisions and patient counseling
Resource Allocation Optimization
AI can forecast demand for hospital's resources to inform decisions for operational efficiency
Diagnostic AI
Medical Imaging Analysis
https://pubmed.ncbi.nlm.nih.gov/40547326/
Pathology Detection
AI analyzes tissue samples to identify malignant cells, tumors, markers
Early Disease Prediction
AI models process patient history and data to identify early warning signs of deadly conditions
Radiology Support System
https://pubmed.ncbi.nlm.nih.gov/37685300/
Gap Analysis
Insufficient evidence on AI + workforce burnout reduction
Lack of standardized methodologies for implementing AI in hospitals
Scarce evaluation frameworks for AI ROI
Few studies on equity impacts
Limited research on AI adoption in underserved regions