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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)

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) - Development of a health education system using artificial intelligence

Status
Active, not recruiting
Phases
Unknown
Study type
Interventional
Source
JPRN
Registry ID
JPRN-UMIN000029216
Enrollment
240
Registered
2017-09-22
Start date
2017-09-14
Completion date
Unknown
Last updated
2026-06-29

For informational purposes only — not medical advice. Sourced from public registries and may not reflect the latest updates. Terms

Conditions

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

Interventions

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
HF): Self-management education (3 months)

Sponsors

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

Eligibility

Sex/Gender
All

Inclusion criteria

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

Exclusion criteria

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

Design outcomes

Primary

MeasureTime frame
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)

Secondary

MeasureTime frame
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

Countries

Japan

Contacts

Public ContactMichiko Moriyama

Hiroshima University Graduate School of Biomedical and Health Sciences

morimich@hiroshima-u.ac.jp082-257-5365

Outcome results

None listed

Source: JPRN (via WHO ICTRP) · Data processed: Jul 3, 2026