HUMAN PROGRAMMING IN PUBLIC HEALTH: HEALTH

PROMOTION AND PREVENTION

THE FIFTH INTERNATIONAL MEETING OF PUBLIC HEALTH “IMOPH 2019” PUBLIC HEALTH CHALLENGE TOWARDS DISRUPTIVE TECHNOLOGY ERA

EKO SUPRIYANTO

SENIOR CONSULTANT, E LIFE SOLUTIONS UNIVERSITI TEKNOLOGI MALAYSIA

OUTLINE

• GOAL OF PUBLIC HEALTH MANAGEMENT

• CHALLENGE IN PUBLIC HEALTH MANAGEMENT

• HUMAN PROGRAMMING IN PUBLIC HEALTH

• TECHNOLOGY 4.0 IN HUMAN PROGRAMMING

• NEW APPROACH IN HEALTH PROMOTION AND PREVENTION

• CASE STUDY 1

• CASE STUDY 2

• CASE STUDY 3

GENETIC (CHILDREN, MATERNAL, ELDERLY)DISEASES (COMM&NON COMM) FOODENVIRONMENTSPORTMENTALOCCUPATIONINTERACTION

HEALTH SYSTEM (INCL. INFRASTRUCTURE AND HUMAN CAPITAL)

HEALTH POLICY

HEALTH FINANCE

HEALTH PROMOTION

HEALTH PLANNING

HEALTH TECHNOLOGY

PUBLICHEALTH GOAL

ARTIFICIAL INTELLIGENCE

HEALTH IMPLEMENTATION

DATA

PUBLIC HEALTH MANAGEMENT

3

PUBLIC HEALTH MANAGEMENT

• GOAL• OPTIMIZED HEALTHTY LIFE EXPECTANCY

• OPTIMIZED HEALTHCARE IMPLEMENTATION / PREVENTION• OPTIMIZED HEALTH EXPENDITURE• OPTIMIZED HEALTHCARE FACILITY• OPTIMIZED HEALTHCARE PERSONEL

• OPTIMIZED HEALTH PROMOTION• OPTIMIZED HEALTH PLANNING• OPTIMIZED HEALTH POLICY

4

PUBLIC HEALTH MANAGEMENT CHALLENGE

• GENERAL ISSUE IN PUBLIC HEALTH MANAGEMENT :• OPTIMAL HEALTH POLICY• HEALTH FINANCE DISTRIBUTION• PUBLIC AWARENESS ON HEALTHY LIFE STYLE• ACTUAL / ACCURATE HEALTH INDICATOR

ACHIEVEMENT• SPECIFIC PROBLEM IN PUBLICH HEALTH

MANAGEMENT :• LACK OF DATA QUANTITY AND QUALITY• NOT OPTIMAL DATA PROCESSING TECHNIQUE• NOT EFFECTIVE RESULT REPRESENTATION /

DISSEMINATION

5

PUBLIC HEALTH MANAGEMENT CHALLENGE

• HEALTH RISK IS NOT ACCURATE AND NOTPERSONALIZED

• EFFECT OF UNHEALTHY LIFE STYLE IS NOT REAL TIME / IN SHORT TIME OBTAINED

• UNHEALTHY LIFE STYLE IS STILL SUPPORTED BY GOVERNMENT DUE TO ECONOMY AND SOCIAL SHORT TERM IMPACT

• INEFFECTIVE IMPLEMENTATION OF GOVERNMENT POLICY TO IMPLEMENT HEALTHY LIFE STYLE DUE TO LOW LEGAL ENFORCEMENT

• NO CLEAR REWARD OR PUNISHMENT GIVEN TO BY SYSTEM TO PEOPLE WHICH PRACTICE UNHEALTHY LIFE STYLE

PUBLIC HEALTH MANAGEMENT CHALLENGE

• FOOD INTAKE

• FLUID INTAKE

• AIR INTAKE

• PHYSICAL ACTIVITY

PUBLIC HEALTH MANAGEMENT CHALLENGE

• MENTAL ACTIVITY

• ENVIRONMENT CONDITION

• HUMAN INTERACTION

HUMAN PROGRAMMING IN PUBLIC HEALTH

• HUMAN PROGRAMMING IS A PROCESS TO DIRECT / MANIPULATE HUMAN THINKING AND ACTIVITIES ACCORDING TO PLANNED TARGET.

• HUMAN PROGRAMMING INVOLVES:• HUMAN PROFILING• INTERVENTION OR ACIVITIES FORMULATION, AS

WELL AS • ACTIVITIES IMPLEMENTATION AND TARGET

MONITORING AND EVALUATION.

• HUMAN PROGRAMMING CAN BEOPTIMIZED USING INTEGRATION BETWEEN MAN AND MACHINE.

• HUMAN PROGRAMMING INCLUDES PHYSICAL, COGNITIVE AND SOCIAL INTERVENTION.

HUMAN PROGRAMMING IN PUBLIC HEALTH

• HUMAN PROGRAMMING IMPLEMENTATION• COLLECT AND RECORD PHYSICAL, COGNITIVE AND SOCIAL EMOTIONAL DATA

• SELECT TARGET INCLUDING EXPECTED DATE TO ACHIEVE TARGET

• DEFINE/IDENTIFY MODAL, ENVIRONMENT, AND MOTIVATOR

• FORMULATE METODE/ACTIVITY TO ACHIEVE TARGET

• MONITOR ACTIVITY (TIME AND RESULT)

• ANALYZE RESULT (ACHIEVEMENT AND PROBLEM)

• CHANGE ACTIVITY/METHOD

• CHANGE TARGET IF REQUIRED

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TECHNOLOGY 4.0 IN HUMAN PROGRAMMING

INPUT

DATABASE

RULE(KNOWLEDGE

BASE + INFERENCE ENGINEE)

OUTPUT

11

BLOCK DIAGRAM

TECHNOLOGY 4.0 IN HUMAN PROGRAMMING

• BLOCK DIAGRAM OF HARDWARE

INPUT DATA RECORDER

INPUT DATA STORAGE

CPUCOMMU NICATOR

DISPLAYCOMMU NICATOR

TARGET AND ACTIVITY DATA STORAGE

CPU

WEARABLE SMART ASSISTANT BIG DATA CENTRE 12

HEALTH PROMOTION AND PREVENTION:NEW APPROACH

User registrationIndividual data

recording

Risk prediction & life expectancy

calculation

Calculation results

Lifestyle recommendation

Appointment with doctor (link to Smart Clinic)

HEALTH PROMOTION AND PREVENTION:NEW APPROACH

HEALTH PROMOTION AND PREVENTION:NEW APPROACH

LEL

CASE STUDY 1

• CHRONIC KIDNEY DISEASE (CKD) RISK PREDICTION

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INPUT• LEL: GENDER , RACE, AGE,

FAMILY HISTORY• MEL: HYPERTENSION,

DIABETES, ACR, BW, GFR• HEL: SALT, WATER INTAKE,

PHYSICAL ACTIVITY, SMOKING, STRESS

DATABASE• AGE, RACE, GENDER AND FAMILY HISTORY

OF CKD PATIENT • HYPERTENSION, DIABETES, ACR,BW AND

GFR HISTORY OF CKD PATIENT• SALT, WATER INTAKE, PHYSICAL ACTIVITY,

SMOKING AND STRESS HISTOTY OF CKD PATIENT

RULEBASE• DECISION TREES

• ARTIFICIAL NEURAL NETWORK

OUTPUT• CURRENT CKD RISK

CASE STUDY 1

• RULE BASE : DECISION TREES

20SOURCE: COMPILATION FROM 113 JOURNALS (MORE THAN 210,000 DATA)

CASE STUDY 1

• OUTPUT: DECISION TREES

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CASE STUDY 1

• ARTIFICIAL NEURAL NETWORK : MODEL

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CASE STUDY 1• ARTIFICIAL INTELLIGENCE: RESULT

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CASE STUDY 2

TITLE: MULTI-LAYER NEURAL NETWORK IN THE PREDICTION OF CORANARY HEART DISEASES UTILIZING DIETARY FATTY ACIDS

CASE STUDY 2

CASE STUDY 2

CASE STUDY 3: SMART NUTRITION MANAGEMENT SYSTEM

CASE STUDY 3

CASE STUDY 3

CASE STUDY 3

CASE STUDY 3

CASE STUDY 3

CASE STUDY 3

CASE STUDY 3 smartnutrition.unaux.com

THE END

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