MedTrace Logo

Validation of EPIC's Readmission Risk Model, the LACE+ Index and SQLape as Predictors of Unplanned Hospital Readmissions

NCT04306172 · Status: COMPLETED · Type: OBSERVATIONAL · Enrollment: 23116

Last updated 2020-10-20

No results posted yet for this study

Summary

The primary objective of this study is to externally validate the EPIC's Readmission Risk model and to compare it with the LACE+ index and the SQLape Readmission model.

As secondary objective, the EPIC's Readmission Risk model will be adjusted based on the validation sample, and finally, it´s performance will be compared with machine learning algorithms.

Conditions

  • Hospital Readmission

Interventions

OTHER

An US Readmission Risk Prediction Model

Logistic regression model that predicts the risk of all-cause unplanned readmissions developed by the privately held healthcare software company EPIC.

OTHER

LACE+ score

The LACE+ score is a point score that can be used to predict the risk of post-discharge death or urgent readmission. It was developed based on administrative data in Ontario, Canada.

OTHER

SQLAPE model

The readmission risk model (Striving for Quality Level and analyzing of patient expenditures), is a computerized validated algorithm and was developed in 2002 to identify potentially avoidable readmissions.

Sponsors & Collaborators

  • Universität Luzern

    collaborator OTHER

  • Luzerner Kantonsspital

    lead OTHER

Principal Investigators

  • Aljoscha B. Hwang · University Lucerne (Switzerland)

  • Stefan Boes · University Lucerne (Switzerland)

Eligibility

Min Age
1 Year
Max Age
100 Years
Sex
ALL
Healthy Volunteers
No

Timeline & Regulatory

Start
2020-03-10
Primary Completion
2020-04-10
Completion
2020-10-01

Countries

  • Switzerland

Study Locations

More Related Trials

Read the full study record

This page highlights key information. For complete eligibility criteria, study locations, investigator contacts, and the full protocol, visit the original record on ClinicalTrials.gov.

View NCT04306172 on ClinicalTrials.gov