Effective hypertensive treatment using data mining in Saudi Arabia

Area of Science:

• Public Health
• Data Mining
• Epidemiology

Background:

• Non-Communicable Diseases (NCDs) pose a significant public health challenge.
• Hypertension is a major NCD risk factor affecting various age groups.
• Understanding treatment efficacy across demographics is crucial for effective healthcare strategies.

Purpose of the Study:

• To analyze Non-Communicable Diseases (NCD) risk factors in Saudi Arabia using data mining.
• To evaluate the effectiveness of different hypertension treatment modes across various age groups.
• To identify optimal treatment strategies for hypertension based on age demographics.

Main Methods:

• Utilized 2005 Saudi Arabia NCD risk factor data in collaboration with the World Health Organisation (WHO).
• Employed Oracle Data Miner (ODM) for data analysis and prediction.
• Categorized age groups (15-64 years) into 'Young' (Y) and 'Old' (O) for comparative analysis.

Main Results:

• Data mining revealed that all five treatment modes for hypertension were effective in the older age group.
• The analysis demonstrated data mining's sensitivity in determining treatment efficacy for specific age demographics.
• Hypertension treatment effectiveness varied across different age groups, with older individuals showing positive responses to all modes.

Conclusions:

• Data mining is a suitable method for analyzing NCD risk factors and treatment outcomes.
• All investigated hypertension treatment modes proved effective for older adults in the Saudi Arabian population studied.
• Further research can refine age-specific hypertension management strategies based on these findings.