Data and AI platform

Palline’s data and AI platform brings together clinical and management data from inside and outside the hospital. It supports data quality, governance, security and reuse through a lakehouse data architecture, shared data services and AI tools.

Core capabilities

• Integrated lakehouse intelligent big data center: structured and unstructured data pass through the data lake (becoming data resources) into the data warehouse (becoming data assets), and on into data marts and the knowledge base.
• Data middle platform: data collection, processing, management, and services, covering extraction, structuring, transformation, master index, master data, indicator management, search, sharing services, cleansing, standardization, privacy protection, metadata quality control, asset catalog, data review, and monitoring logs.
• AI platform: anomaly detection engine, causal reasoning engine, intelligent prediction engine, and rules computation engine, together with machine learning, the industry knowledge-enhanced large model, medical knowledge graphs, intelligent annotation, and NLP.

Product strengths

The AI platform's knowledge base manages more than ten million medical information entities across 25 categories, including ICD coding, the American Medical Association CPT coding RVU dictionary values for versions from 2009 to 2020, disease analysis, clinical capability, drugs and consumables, equipment cost, and benchmarks. Entities are modeled and coded uniformly to national standards while accommodating local variation. The industry baseline and benchmark library holds baseline indicator data across more than 200 major categories and more than 300,000 records. The platform is open: it links seamlessly with Palline's lean performance, dynamic cost, intelligent budget, DRG/DIP analysis, and hospital accreditation management systems, and can also provide data services to third-party products or integrate specific applications.

Value delivered

The platform supports comprehensive inventory, effective governance, efficient activation, and secure use of data assets. It manages business, management, and technical attributes; maintains data asset catalogs from business, technical, and management perspectives; and records data lineage and processing detail.