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Real-world Effectiveness Evaluation of Clinical Decision Support System Based on Artificial Intelligence (AI-CDSS)

Real-world Effectiveness Evaluation of Clinical Decision Support System Based on Artificial Intelligence (AI-CDSS) on Diagnosis

Status
Completed
Phases
Unknown
Study type
Observational
Source
ClinicalTrials.gov
Registry ID
NCT05065931
Enrollment
34113
Registered
2021-10-04
Start date
2019-03-01
Completion date
2019-06-01
Last updated
2021-10-04

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

Medical Informatics Applications

Brief summary

This study intends to explore the accuracy of clinical diagnosis of AI based CDSS system and promotion of clinical work by comparing CDSS before and after the online.

Detailed description

This study intends to explore the accuracy of clinical diagnosis of AI based CDSS system and promotion of clinical work by comparing CDSS before and after the online. The difference of diagnostic accuracy before and after AI-CDSS application will be compared by the before and after design, and the role of AI-CDSS will be explored.

Interventions

OTHERAuxiliary diagnostic system by AI-CDSS

Helping clinicians to make diagnoses by using CDSS based-on AI

Sponsors

Peking University Third Hospital
Lead SponsorOTHER

Study design

Observational model
ECOLOGIC_OR_COMMUNITY
Time perspective
RETROSPECTIVE

Eligibility

Sex/Gender
ALL
Healthy volunteers
No

Inclusion criteria

* all hospitalized patients in 6 clinical departments, Otolaryngology, Orthopaedic, Respiratory Medicine, General Surgery, Cardiology and Hematology from December 2016 to February 2019.

Exclusion criteria

* Missing data for key variables

Design outcomes

Primary

MeasureTime frameDescription
Accuracy Rate of Recommended Diagnosis by CDSS, up to 12 weeksWhen the subject was discharged from the hospitalBased on the patient's discharge diagnosis as a standard, it is explored whether the diagnosis given by the CDSS is consistent with the discharge diagnosis in the patient's medical record.
Patients' hospitalization time (days), up to 24 weeksWhen the subject was discharged from the hospitalThe length of a patient's stay is the number of days he or she experiences from the time of admission to the time of discharge.
consistency between admission diagnosis and discharge diagnosis up to 12 weeksWhen the subject was discharged from the hospitalWhen the patient comes to the hospital, the clinician will write an inpatient record and give a preliminary diagnosis, which we call admission diagnosis.After the patient is hospitalized, all kinds of examinations will be improved. After all the examination results come out, the patient's diagnosis on admission may be modified. Because there are no auxiliary examination results on admission, the diagnosis on admission may not be completely correct.This modified diagnosis is called discharge diagnosis.This study compared the consistent rate of admission diagnosis and discharge diagnosis before and after CDSS on-line.

Secondary

MeasureTime frameDescription
length of confirmed time, up to 6 weeksWhen the subject was discharged from the hospitalhe length of confirmed time (days) was the duration between the preliminary admission diagnosis and the definite diagnosis.

Countries

China

Outcome results

None listed

Source: ClinicalTrials.gov · Data processed: Feb 4, 2026