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Machine Learning to Predict Factors Affecting Rehabilitation Length of Stay and Healthcare Costs for Neurological Rehabilitation

NCT ID: NCT06704997

Last Updated: 2024-11-27

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

ACTIVE_NOT_RECRUITING

Total Enrollment

10000 participants

Study Classification

OBSERVATIONAL

Study Start Date

2024-06-01

Study Completion Date

2026-12-31

Brief Summary

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The aim of this retrospective study is to ascertain total direct costs, rehabilitation length of stay (RLOS) and factors associated with RLOS for neurological inpatient rehabilitation at the tertiary care hospital.

Detailed Description

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The aim of the study is to identify factors that influence RLOS and the correlated costs for neurological rehabilitation in tertiary rehab using data extracted from EPIC. It is also aimed to identify the median direct costs to find out the main contributors to the costs in the local population. Lastly, the study aims to utilise artificial intelligence or machine learning to analyse the compiled data to develop a predictive model. The model aspires to understand factors associated with extended RLOS and to predict RLOS of patients who require neurological rehabilitation, aiding preemptive measures.

Conditions

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Stroke Acquired Brain Injury Traumatic Brain Injury Brain Tumor Central Nervous System Infections Polytrauma

Study Design

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Observational Model Type

COHORT

Study Time Perspective

RETROSPECTIVE

Study Groups

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Patients with tertiary neurological rehabilitation

Patients with confirmed diagnosis of stroke, acquired brain injuries, traumatic brain injuries, brain tumours, central nervous system infections and polytrauma from acute neurological or neurosurgical units in Singapore. The cohort will be selected from the TTSH Rehabilitation Centre (TTSH RC) admissions from year 2016 to the present.

No interventions assigned to this group

Eligibility Criteria

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Inclusion Criteria

• All patients who completed inpatient rehabilitation with the index conditions in their discharge summaries

Exclusion Criteria

• Did not complete inpatient rehabilitation as they are discharged against medical advice
Minimum Eligible Age

21 Years

Maximum Eligible Age

100 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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Tan Tock Seng Hospital

OTHER

Sponsor Role lead

Responsible Party

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Chua Sui Geok, Karen

Senior Consultant Dr ( MD)

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Dr Karen Chua, MBBS

Role: PRINCIPAL_INVESTIGATOR

Tan Tock Seng Hospital

Locations

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Tan Tock Seng Hospital

Singapore, , Singapore

Site Status

Countries

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Singapore

Other Identifiers

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DSRB 2023/00873

Identifier Type: -

Identifier Source: org_study_id