Post on 30-Jan-2022
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
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
10
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)
CASE STUDY 1
• CHRONIC KIDNEY DISEASE (CKD) RISK PREDICTION
19
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 2
TITLE: MULTI-LAYER NEURAL NETWORK IN THE PREDICTION OF CORANARY HEART DISEASES UTILIZING DIETARY FATTY ACIDS