UMIN-CTR Clinical Trial

Basic information
Public title	Development of an AI-based system for predicting falls and fall-related injuries in hospitals
Acronym	Development of an AI-based system for predicting falls and fall-related injuries in hospitals
Scientific Title	Development of an AI-based system for predicting falls and fall-related injuries in hospitals
Scientific Title:Acronym	Development of an AI-based system for predicting falls and fall-related injuries in hospitals
Region	Japan

Condition
Condition	None (All patients admitted during the study period)
Classification by specialty	Not applicable
Classification by malignancy	Others
Genomic information	NO

Objectives
Narrative objectives1	Development and validation of a system for predicting falls and fall-related injuries in hospital with large data sets.
Basic objectives2	Efficacy
Basic objectives -Others
Trial characteristics_1
Trial characteristics_2
Developmental phase

Assessment
Primary outcomes	Falls and fall-related injuries obtained from incident reports
Key secondary outcomes	Scores of fall risk assessment tool

Base
Study type	Observational

Study design
Basic design
Randomization
Randomization unit
Blinding
Control
Stratification
Dynamic allocation
Institution consideration
Blocking
Concealment

Intervention
No. of arms
Purpose of intervention
Type of intervention
Interventions/Control_1
Interventions/Control_2
Interventions/Control_3
Interventions/Control_4
Interventions/Control_5
Interventions/Control_6
Interventions/Control_7
Interventions/Control_8
Interventions/Control_9
Interventions/Control_10

Eligibility
Age-lower limit	Not applicable
Age-upper limit	Not applicable
Gender	Male and Female
Key inclusion criteria	The patients who had been hospitalized in Fujita Health University Hospital from April 2012 to March 2020 and those who had been hospitalized in Fujita Health University Nanakuri Memorial Hospital from April 2016 to March 2020.
Key exclusion criteria	A person who has asked to be excluded from the study to the researcher listed in the disclosure document on the website.
Target sample size	300000

Research contact person
Name of lead principal investigator	1st name Yohei Middle name Last name Otaka
Organization	Fujita Health University
Division name	Department of Rehabilitation Medicine I, School of Medicine
Zip code	470-1192
Address	1-98 Dengakugakubo, Kutsukake, Toyoake, Aichi
TEL	0562-93-2167
Email	yootaka@fujita-hu.ac.jp

Public contact
Name of contact person	1st name Shin Middle name Last name Kitamura
Organization	Fujita Health University
Division name	Faculty of Rehabilitation, School of Health Sciences
Zip code	470-1192
Address	1-98 Dengakugakubo, Kutsukake, Toyoake, Aichi
TEL	0562-93-9000
Homepage URL
Email	shin.kitamura@fujita-hu.ac.jp

Sponsor
Institute	Fujita Health University
Institute
Department

Funding Source
Organization	None
Organization
Division
Category of Funding Organization	Self funding
Nationality of Funding Organization

Other related organizations
Co-sponsor	FRONTEO, Inc.
Name of secondary funder(s)

IRB Contact (For public release)
Organization	Fujita Health University
Address	1-98 Dengakugakubo, Kutsukake, Toyoake, Aichi
Tel	0562-93-2865
Email	f-irb@fujita-hu.ac.jp

Secondary IDs
Secondary IDs	NO
Study ID_1
Org. issuing International ID_1
Study ID_2
Org. issuing International ID_2
IND to MHLW

Institutions
Institutions	藤田医科大学（愛知県）

Other administrative information
Date of disclosure of the study information	2020 Year 08 Month 03 Day

Related information
URL releasing protocol
Publication of results	Unpublished

Result
URL related to results and publications
Number of participants that the trial has enrolled	69291
Results
Results date posted
Results Delayed
Results Delay Reason
Date of the first journal publication of results
Baseline Characteristics
Participant flow
Adverse events
Outcome measures
Plan to share IPD
IPD sharing Plan description

Progress
Recruitment status	No longer recruiting
Date of protocol fixation	2020 Year 05 Month 25 Day
Date of IRB	2020 Year 07 Month 27 Day
Anticipated trial start date	2020 Year 08 Month 03 Day
Last follow-up date	2025 Year 03 Month 31 Day
Date of closure to data entry
Date trial data considered complete
Date analysis concluded

Other

Other related information

We will retrospectively analyze the medical records of patients who had been hospitalized in the two hospitals. The data will be divided into two parts. Using one of the data sets, we will develop an AI-based prediction system for the risks for falls and fall-related injuries for each patient. Then, we will validate the system against the actual incidents and the scores of the fall risk assessed tools using the other data sets.

Management information
Registered date	2020 Year 08 Month 03 Day
Last modified on	2022 Year 08 Month 05 Day

Link to view the page
URL(English)	https://center6.umin.ac.jp/cgi-open-bin/icdr_e/ctr_view.cgi?recptno=R000047155