Clinical trial NCT04306172: Validation of EPIC's Readmission Risk Model, the LACE+ Index and SQLape as Predictors of Unplanned Hospital Readmissions
Official title: External Validation of EPIC's Readmission Risk Model, the LACE+ Index and SQLape as Predictors of Unplanned Hospital Readmissions: A Monocentric, Retrospective, Diagnostic Cohort Study in Switzerland
Study type: OBSERVATIONAL
Overall status: COMPLETED
Conditions: Hospital Readmission
Keywords: Prediction model
hospital readmission
external validation
Lead sponsor: Luzerner Kantonsspital
Sponsor class: OTHER
Collaborators: name: Universität Luzern
First posted: 2020-03-12
Enrollment: 23116
Sex: ALL
Minimum age (years): 1
Maximum age (years): 100
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: no
Observational model: COHORT
Time perspective: RETROSPECTIVE
Sampling method: NON_PROBABILITY_SAMPLE
Study population: Inpatients from an acute care hospital in Central-Switzerland

Brief 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.

Detailed description: Introduction: Readmissions after an acute care hospitalization are relatively common, costly to the health care system and are associated with significant burden for patients. As one way to reduce costs and simultaneously improve quality of care, hospital readmissions receive increasing interest from policy makers. It is only relatively recently that strategies were developed with the specific aim of reducing unplanned readmissions by applying prediction models. EPIC's Readmission Risk model, developed in 2015 for the U.S. acute care hospital setting, promises superior calibration and discriminatory abilities. However, its routine application in the Swiss hospital setting requires external validation first. Therefore, the primary objective of this study is to externally validate the EPIC's Readmission Risk model and to compare it with the LACE+ index (Length of stay, Acuity, Comorbidities, Emergency Room visits index) and the SQLape (Striving for Quality Level and analysing of patient expenditures) Readmission model.

Methods: For this reason, a monocentric, retrospective, diagnostic cohort study will be conducted. The study will include all inpatients, who were hospitalized between the 1st January 2018 and the 31st of January 2019 in the Lucerne Cantonal hospital in Switzerland. Cases will be inpatients that experienced an unplanned (all-cause) readmission within 18 or 30 days after the index discharge. The control group will consist of individuals who had no unscheduled readmission.

For external validation, discrimination of the scores under investigation will be assessed by calculating the area under the receiver operating characteristics curves (AUC). For calibration, the Hosmer-Lemeshow goodness-of-fit test will be graphically illustrated by plotting the predicted outcomes by decile against the observations. Other performance measures to be estimated will include the Brier Score, Net Reclassification Improvement (NRI) and the Net Benefit (NB).

All patient data will be retrieved from clinical data warehouses.

Eligibility criteria: Inclusion Criteria:

- All inpatients, aged one year or older (max. 100 years), who were hospitalized either between the 1st of January 2018 and the 31st of December 2018, or between the 23rd of September and the 31st of December 2019 will be included.

Exclusion criteria:

* admission/transfer from another psychiatric, rehabilitative or acute care ward from the same institution,
* discharge destination other than the patient's home or
* transfer to another acute care hospital, both being considered as treatment continuation;
* foreign residence,
* deceased before discharge,
* discharged on admission day,
* refusal of general consent, and
* unknown patient residence or discharge destination.

Primary outcomes:
measure: Discrimination at 18 days
timeFrame: 18 days after index discharge date
measure: Discrimination at 30 days
timeFrame: 30 days after index discharge date
measure: Calibration at 18 days
timeFrame: 18 days after index discharge date
measure: Calibration at 30 days
timeFrame: 30 days after index discharge date
measure: Overall Performance at 18 days
timeFrame: 18 days after index discharge date
measure: Overall Performance at 30 days
timeFrame: 30 days after index discharge date
measure: Clinical usefulness (NRI) at 18 days
timeFrame: 18 days after index discharge date
measure: Clinical usefulness (NRI) at 30 days
timeFrame: 30 days after index discharge date
measure: Clinical usefulness (NB) at 18 days
timeFrame: 18 days after index discharge date
measure: Clinical usefulness (NB) at 30 days
timeFrame: 30 days after index discharge date
Secondary outcomes:
Other outcomes:
Locations:
city: Lucerne
country: Switzerland
facility: Cantonal Hospital of Lucerne
state: Canton Lucerne
Study officials:
affiliation: University Lucerne (Switzerland)
name: Aljoscha B. Hwang
role: PRINCIPAL_INVESTIGATOR
affiliation: University Lucerne (Switzerland)
name: Stefan Boes
role: PRINCIPAL_INVESTIGATOR
References:
citation: van Walraven C, Wong J, Forster AJ. LACE+ index: extension of a validated index to predict early death or urgent readmission after hospital discharge using administrative data. Open Med. 2012 Jul 19;6(3):e80-90. Print 2012.
citation: Halfon P, Eggli Y, Pretre-Rohrbach I, Meylan D, Marazzi A, Burnand B. Validation of the potentially avoidable hospital readmission rate as a routine indicator of the quality of hospital care. Med Care. 2006 Nov;44(11):972-81. doi: 10.1097/01.mlr.0000228002.43688.c2.