DRG evaluation and operations analysis system

The DRG evaluation and operations analysis system is a new-generation hospital information management system centered on the inpatient medical record front page and the electronic medical record. It supports CHS-DRG and CN-DRG as well as localized grouping rules derived from them, and is applied to clinical performance evaluation, clinical quality, cost control, and health insurance payment. The system helps raise medical record quality and the DRG grouping rate, supports multi-dimensional and multi-indicator analysis, and allows indicators to be customized to the hospital's requirements.

Policy background

In 2022 the National Healthcare Security Administration launched the Three-Year Action Plan for DRG/DIP Payment Reform, which — by expanding coverage, building mechanisms, laying foundations, and promoting coordination — aimed to have DRG/DIP payment substantially in place across all pooling regions and designated hospitals by the end of 2024. DRG payment groups cases on a case-mix logic: different disease types are distinguished by diagnosis, different treatment plans within the same case type are distinguished by procedure, and cases with the same disease and treatment are further separated by factors such as age, complications, and weight.

Core capabilities

• Baseline data: MDC, ADRG, DRG, CC/MCC, calculated indicator values, and within-group analysis.
• Case grouping: automatic DRG grouping, grouping budget, grouping alerts, and DRG assignment for individual cases.
• Medical record quality control: analysis of ungrouped cases, optimization of existing coding, and optimization of omitted coding.
• Indicator analysis: basic indicator analysis, indicator trend analysis, DRG detail and trend analysis, DRG summary analysis, RW distribution analysis, case-mix structure analysis, diagnosis analysis, procedure analysis, clinical quality analysis, specialty indicator analysis, and progressive analysis.
• Health insurance payment: basic payment analysis, payment trend forecasting, RW distribution analysis, specialty payment analysis, and specialty trend analysis.

Product strengths

The system builds a case grouping model that draws on intelligent diagnosis matching together with clinical diagnosis, procedures, clinical pathways, comorbidities, and complications. Cases with "similar clinical characteristics" and "comparable resource consumption" are merged into pre-grouping analysis, raising front-page quality and the grouping rate. Drug and consumable consumption indices are forecast for each case type using big data. Analysis can be drilled down layer by layer to each discharged case and its corresponding order detail. Pareto progressive analysis uses performance incentives on priority DRGs, specialties, service volume, and RW to keep physician behavior aligned with hospital strategy.