# Use, Utility, and User Experience of Cloud-Based Medical Imaging in Pulmonary Nodule Care in China: Mixed Methods Study

**Authors:** Ziguo Chen, Junhan Wu, Yunying Chen, Weitao Zhuang, Jiaxuan Huang, Weifeng Zhong, Zijie Li, Shuhuan Xie, Chaofan Liu, Guojie Lu, Guibin Qiao

PMC · DOI: 10.2196/86745 · Journal of Medical Internet Research · 2026-03-30

## TL;DR

This study explores how cloud-based medical imaging is used in China for managing pulmonary nodules, finding that it improves care access and reduces costs, but faces usability and interoperability challenges.

## Contribution

The study provides novel insights into the real-world use and impact of cloud-based medical imaging for pulmonary nodule care in China, including user experience and barriers to adoption.

## Key findings

- 611 out of 701 patients obtained cloud-based medical imaging, with 404 actively using it.
- CMI users accessed more internet hospitals and reported lower healthcare costs compared to nonusers.
- Qualitative findings highlight usability issues and interoperability challenges as key barriers to CMI adoption.

## Abstract

The detection of pulmonary nodules (PNs) has increased with the use of low-dose computed tomography screening. Effective management requires timely longitudinal surveillance and reliable comparison with prior examinations, yet access to previous imaging across institutions is often fragmented, leading to delays and potentially unnecessary repeat scans and costs. Cloud-based medical imaging (CMI) solutions offer a potential means of improving access and facilitating cross-institutional data exchange. However, the adoption and utility of CMI in PN care, especially in China, remain underexplored.

This study aims to evaluate the possession, use, and impact of CMI on health care utilization, patient knowledge, and financial burden, as well as to identify usability and interoperability barriers through qualitative investigation.

A mixed methods cross-sectional study was conducted from October 2022 to May 2024. The study involved 701 patients with PNs who completed structured surveys, and 20 participants (10 patients and 10 physicians) were interviewed. CMI use was defined as self-reported ability to view radiological images on a mobile device. We compared CMI users and nonusers and estimated adjusted odds ratios using multivariable logistic regression, then applied 1:1 propensity score matching to examine associations between CMI use and health care utilization, costs, and patient perceptions, and qualitative interviews were analyzed for usability themes.

The study found that 611 (87.2%) out of 701 patients had obtained CMI, with 404 (57.6%) out of 701 patients actively using it. In multivariable analysis, older age was independently associated with lower CMI use (odds ratios 0.985, 95% CI 0.972‐0.999). After 1:1 propensity score matching, CMI users accessed more internet hospitals, consulted more physicians, and reported lower health care costs compared to nonusers. Users also demonstrated higher disease knowledge. Qualitative data identified key barriers, including poor system usability, limited retention time for images, and weak interoperability. CMI was perceived as beneficial for patient convenience and clinical efficiency, though concerns over image quality and system fragmentation were prevalent.

While CMI is widely available, its usage remains suboptimal. Increased use is associated with enhanced health care engagement and reduced costs, suggesting that improving system usability and ensuring consistent access to imaging may help realize potential benefits of CMI. Future improvements should focus on ensuring long-term access, better retention protocols, and overcoming interoperability issues.

## Full-text entities

- **Diseases:** anxiety (MESH:D001007), Chronic Diseases (MESH:D002908), PN (MESH:C565820), pain (MESH:D010146), PNs (MESH:D055613), CMI (MESH:C564543)
- **Chemicals:** CMI (-)
- **Species:** Homo sapiens (human, species) [taxon 9606]

## Full text

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## Figures

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## References

26 references — full list in the complete paper: https://tomesphere.com/paper/PMC13035031/full.md

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Source: https://tomesphere.com/paper/PMC13035031