DIP evaluation and operations analysis system

The DIP 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 the rules of the National Healthcare Security Administration as well as localized grouping rules, and is applied to clinical performance evaluation, clinical quality, cost control, and health insurance payment. At hospital and department level it provides comparative, compositional, and trend analysis of clinical performance indicators across dimensions, laying the groundwork for lean cost control and providing DIP benchmark data for discipline evaluation.

Policy background

In 2022 the National Healthcare Security Administration launched the Three-Year Action Plan for DRG/DIP Payment Reform, aiming to have DRG/DIP payment substantially in place across all pooling regions and designated hospitals by the end of 2024. DIP payment groups cases by a case-type catalog; the catalog is built on randomization and mean-value economic theory together with big data theory, identifying associations and patterns between disease and quality across large volumes of case data and combining the extracted data features into the final DIP catalog.

Core capabilities

• Base data: DIP, second-level catalog, first-level catalog, master index, and calculated indicator values, with the latest payment technical specifications and local specifications built in.
• Case grouping: automatic DIP grouping, grouping budget, grouping alerts, and DIP 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, DIP detail and trend analysis, DIP 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 supports localized grouping, adapting to local grouping rules and relative weights (RW); where local rules have not yet been published, grouping rules are inferred from cases already grouped. Multi-stage pre-grouping predicts, flags, and tracks insurance revenue and rejected amounts: grouping results are predicted before the patient is discharged, pre-grouping analysis is provided before the physician submits the front page, and after archiving a full quality check is run and the data quality report returned to the department. The system can be embedded in the physician workstation, monitoring and prompting in real time through an interface as the front page is completed or amended.