# Rational evaluation of computed tomography scans using a risk-adjusted model in a comprehensive public tertiary hospital in China

## TL;DR

This study evaluates whether CT scans in a Chinese hospital are being used appropriately by adjusting for patient risk factors.

## Contribution

A risk-adjusted model is introduced to assess CT scan rationality in different diagnostic categories.

## Key findings

- Five of the top 10 MDCs showed over-scanning, three showed under-scanning, and two were rational.
- Age, admission condition, and insurance status significantly influence CT scan decisions.
- The model provides a framework for evaluating other medical examinations.

## Abstract

In the context of medical insurance payment reform in China, Computed tomography (CT), as a key type of large medical equipment, currently faces challenges of over-scanning or under-scanning. This study aims to identify the factors influencing the number of CT scans, perform risk adjustment on the number of CT scans, and evaluate the rationality of the number of CT scans for each major diagnostic category (MDC).

In the public tertiary general hospital in Sichuan Province, the top 10 MDCs with the highest total number of CT scans in 2023 were selected. A risk-adjusted model was used to estimate the expected number of CT scans. The utilization of CT scans was classified as over-scanning, under-scanning, and rational scanning based on the ratio of observed to expected scan numbers.

The top 10 MDCs included 29,461 encounters and 37,672 CT scans. The number of CT scans varied across different MDCs: five exhibited over-scanning, three showed under-scanning, and two demonstrated rational scanning. The risk-adjusted model revealed that age, admission condition, first-time hospitalization, medical insurance, and length of stay were statistically significant in determining both the decision to perform a CT scan and the number of CT scans conducted.

This study evaluated the rationality of the number of CT scans across the top 10 MDCs, established a methodological framework for hospital to explore the rationality of the number of other medical examinations.