Status of AI-Enabled Clinical Decision Support Systems Implementations in China

Abstract

Background AI-enabled Clinical Decision Support Systems (AI + CDSSs) were heralded to contribute greatly to the advancement of health care services. There is an increased availability of monetary funds and technical expertise invested in projects and proposals targeting the building and implementation of such systems. Therefore, understanding the actual system implementation status in clinical practice is imperative.

Objectives The aim of the study is to understand (1) the current situation of AI + CDSSs clinical implementations in Chinese hospitals and (2) concerns regarding AI + CDSSs current and future implementations.

Methods We investigated 160 tertiary hospitals from six provinces and province-level cities. Descriptive analysis, two-sided Fisher exact test, and Mann-Whitney U-test were utilized for analysis.

Results Thirty-eight of the surveyed hospitals (23.75%) had implemented AI + CDSSs. There were statistical differences on grade, scales, and medical volume between the two groups of hospitals (implemented vs. not-implemented AI + CDSSs, p <0.05). On the 5-point Likert scale, 81.58% (31/38) of respondents rated their overall satisfaction with the systems as “just neutral” to “satisfied.” The three most common concerns were system functions improvement and integration into the clinical process, data quality and availability, and methodological bias.

Conclusion While AI + CDSSs were not yet widespread in Chinese clinical settings, professionals recognize the potential benefits and challenges regarding in-hospital AI + CDSSs.

Keywords

artificial intelligence - AI-enabled clinical decision support systems - clinical decision support systems - clinical implementation - survey

Ethical Approval

This study was submitted to and approved by the Ethics Review Committee, Children's Hospital of Shanghai/Shanghai Children's Hospital, Shanghai Jiao Tong University. The informed consent obtained from study participants was written on the front page of the electronic questionnaires.

Publication History

Received: 14 February 2021

Accepted: 17 August 2021

Article published online:
25 October 2021

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