Pre-Prescription Review System Effectiveness Analysis from a Chinese Hospital

A 24.9 KB DOCX file contains a retrospective study analyzing the impact of a Pre-prescription Review System (PPRS) on prescription rationality. The study, authored by Jiajia Gui, reports significant increases in prescription rationality rates from 92.53% to 99.94% and medical order rates from 97.77% to 99.99% following system implementation. It details changes in warning level proportions and specific issue categories like repeated medication.

Use Cases

• Analyze trends in **prescription rationality rate** and **medical order rationality rate** before and after PPRS implementation to quantify system impact.
• Model the reduction in specific prescription issues, such as **repeated medication** proportion (24.94% vs. 3.85%), to identify key areas of clinical improvement.
• Study the shift in **system warning levels** (e.g., Level 3 prescription alerts, Level 4 medical order alerts) to evaluate the refinement of alert accuracy.
• Correlate changes in the proportion of **usage and dosage issues** (34.31% vs. 19.51%) with system interventions to assess targeted effectiveness.

Strengths

• Study reports statistically significant results (P < 0.0001) for primary outcomes like prescription rationality rate.
• Analysis includes specific, quantified metrics such as the drop in repeated medication proportion from 24.94% to 3.85%.
• Data covers multiple years, showing annual increases in intercepted alerts and trends in warning level proportions.

Limitations

• Dataset is very small (24.9 KB), containing summary analysis rather than raw patient-level or prescription-level data.
• Single-center study from one tertiary hospital in Chongqing, China, limits generalizability to other healthcare settings.
• Underlying tabular data (rows, columns, sample) is unavailable, preventing direct computational analysis or model training.

Provenance

Source

Jiajia Gui via figshare.

Collection Method

Single-center real-world retrospective analysis using evidence-based methods and descriptive statistics.

Time Range

Period before and after PPRS implementation; specific years not stated.

Freshness

Last updated March 2026.

Geography

A tertiary hospital in Chongqing, China.