UMIN-CTR Clinical Trial

Public title

Development of a health education system through risk prediction and targeting using artificial intelligence based on national health insurance claim data and health information (Main research) + (Attached research: A test to improve the health guidance AI prototype) + (Attached research: Expanding target diseases)

Acronym

Development of a health education system using artificial intelligence

Scientific Title

Development of a health education system through risk prediction and targeting using artificial intelligence based on national health insurance claim data and health information (Attached research: A test to improve the health guidance AI prototype)

Scientific Title:Acronym

Development of a health education system using artificial intelligence

Region

Japan

Condition

Hypertension, Diabetes, Diabetic nephropathy, Chronic kidney disease, Myocardial infarction, Angina pectoris, Stroke, Transient ischemic attack, COPD, Heart failure

Classification by specialty

Nursing

Classification by malignancy

Others

Genomic information

NO

Narrative objectives1

We will analyze national health insurance claim data and health information by AI. Then we target high risk patients and provide them appropriate health education programs selected by AI. We evaluate the feasibility for further AI development.

Basic objectives2

Others

Basic objectives -Others

Development of a system and the evaluation (Implement the developed health guidance AI prototype to patients, confirm the improvement effect of the behavioral changes of the patients, and obtain the evaluations of the improvements of the AI from the patients and nurses to improve the accuracy of the AI.) (Conduct and evaluate health guidance for patients with COPD and heart failure. Input the data to the AI built in the main research.)

Trial characteristics_1

Others

Trial characteristics_2

Others

Developmental phase

Not applicable

Primary outcomes

Feasibility evaluation of the system (Attached research: (1) After the nurse provided the health guidance according to the health guidance provided by the AI, did the patient change behavior as planned? (2) The degree of agreement between the risks, health guidance content, and action goals presented by AI and the nurses' thoughts) (Attached research: Change levels of behaviors)

Key secondary outcomes

1. Physiological indicators: blood test (HbA1c, BS, CRE, BUN, UA, LDL- C, HDL-C, TC, TG, GOT, GPT, r-GTP, PT-INR, TP, ALB, HGB, K, P), urine test(urine protein, urine albumin), blood pressure, weight, pulse rate, fasting blood glucose(if patient has diabates and measure it)
2. Treatment change: medication, introduction of renal replacement therapy
3. Behavioral indicators: lifestyle, content of meals, presence or absence of smoking/drinking, behavioral goals and achievement (meal, exercise, medication/injection, self-monitoring)
4. Disease, development of disease/complication
5. Regulary visit to a clinic, presence or absence of hospitalization, reason for hospitalization
6. Results of questionnares (self-efficacy, QOL)
7. Records of personal health education, diet records, reports for physicians
8. Records of face-to-face instruction, voice record of telephone instruction

Study type

Interventional

Basic design

Single arm

Randomization

Non-randomized

Randomization unit

Blinding

Open -no one is blinded

Control

Uncontrolled

Stratification

Dynamic allocation

Institution consideration

Blocking

Concealment

No. of arms

1

Purpose of intervention

Educational,Counseling,Training

Type of intervention

Behavior,custom

Interventions/Control_1

Implementation of disease management programs (acquisition of self-management skills and lifestyle change, 3 month-period) (Attached research: Implementation of AI-based disease management program (1-2 months)) (Attached research (COPD & HF): Self-management education (3 months)

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

Age-lower limit

20

years-old

<=

Age-upper limit

Not applicable

Gender

Male and Female

Key inclusion criteria

Beneficiaries of national Health insurances or medical care system for elderly in the later stage of life, who live in Hiroshima prefecture, are outpatients of medical facilities, and meet all criteria from 1 to 5 listed below.
1. A patient who falls into one of the two.
(1) A patient with any of the following diseases: Hypertension, Diabetes, Diabetic nephropathy, Chronic kidney disease, Myocardial infarction, Angina pectoris, Stroke, Transient ischemic attack (including a patient who quit the treatment)
(2) Based on health check-up data, a patient who has Hypertension (Grade 2 hypertension: systolic BP >= 160mmHg or diastolic BP >= 100mmHg), Hyperglycemia (HbA1c >= 7.0% or fasting blood suger >= 130mg/dl), Reduction of kidney function (eGFR < 60 or urine protein >= 2+)
2. A patients was judged by their general physician or physician in charge intended to participate in this study
3. Age >= 20 years old of both sexes
4. Not being participated in another clinical study
5. A patient who agrees with the written consent form.
(Attached research)
Outpatients of Hiroshima University Hospital aged 20 years and over with the following disease: Diabetes mellitus/diabetic nephropathy (Stage 1-4), CKD (stage G1 to G4), myocardium Infarction/angina, stroke / TIA (up to modify Rankin Scale 3)
(Attached research)
Beneficiaries of national Health insurances or medical care system for elderly in the later stage of life, who live in Hiroshima prefecture, are outpatients of medical facilities. COPD: GOLD stage 2-4, HF: AHA/ACC stage B & C

Key exclusion criteria

1) A patient was judged by the nurses (who provide the program) as unable to implement the program
2) An inpatient
3) A patient at Renal Replacement Therapy (renal transplantation, treated with dialysis)
4) A patient who has a plan for renal transplantation within 6 months
5) A patient at end stage (be given a year to live)
6) Type 1 diabetes
7) In pregnacy
8) Dementia (HDS-R <= 20/30)
9) Those who have behavioral problems and be considered as difficult to continue the program by his/her primary physician, physician in charge of diabetic care or researcher

Target sample size

240

Name of lead principal investigator

1st name	Michiko
Middle name
Last name	Moriyama

Organization

Hiroshima University

Division name

Graduate School of Biomedical and Health Sciences

Zip code

734-8553

Address

Hiroshima

TEL

082-257-5365

Email

morimich@hiroshima-u.ac.jp

Name of contact person

1st name	Michiko
Middle name
Last name	Moriyama

Organization

Hiroshima University

Division name

Graduate School of Biomedical and Health Sciences

Zip code

734-8553

Address

Hiroshima

TEL

082-257-5365

Homepage URL

https://aipom.hiroshima-u.ac.jp/

Email

morimich@hiroshima-u.ac.jp

Institute

Hiroshima University, The research project management committee for development of AI health education system

Institute

Department

Personal name

Organization

Japan Agency for Medical Research and Development (Until March 2020).
From April 2020, Hiroshima university & Hiroshima prefecture AI / IoT demonstration platform project

Organization

Division

Category of Funding Organization

Japanese Governmental office

Nationality of Funding Organization

Co-sponsor

Name of secondary funder(s)

Organization

Hiroshima University research ethics committee

Address

Kasumi 1-2-3 Minami-ku, Hiroshima, Japan

Tel

082-257-1752

Email

protocol@cimr.hiroshima-u.ac.jp

Secondary IDs

NO

Study ID_1

Org. issuing International ID_1

Study ID_2

Org. issuing International ID_2

IND to MHLW

Institutions

Date of disclosure of the study information

2017

Year

09

Month

22

Day

URL releasing protocol

Publication of results

Unpublished

URL related to results and publications

Number of participants that the trial has enrolled

131

Results

Results date posted

Results Delayed

Delay expected

Results Delay Reason

Under journal submission

Date of the first journal publication of results

Baseline Characteristics

Participant flow

Adverse events

Outcome measures

Plan to share IPD

IPD sharing Plan description

Recruitment status

Completed

Date of protocol fixation

2017

Year

09

Month

14

Day

Date of IRB

2017

Year

09

Month

14

Day

Anticipated trial start date

2017

Year

09

Month

14

Day

Last follow-up date

2021

Year

03

Month

31

Day

Date of closure to data entry

Date trial data considered complete

Date analysis concluded

Other related information

The attached research (A test of health guidance AI prototype) was discontinued on June 15, 2020 (Registered cases:0).
The attached research (Expanding target diseases: COPD & HF) was closed on Jan. 10, 2020, registered 24 cases, and 20 completed the study.

Registered date

2017

Year

09

Month

20

Day

Last modified on

2021

Year

04

Month

20

Day

Link to view the page

Value
https://center6.umin.ac.jp/cgi-open-bin/ctr_e/ctr_view.cgi?recptno=R000033394