Optimization of medical information systems by using additional factors
D Zagulova2, R Muhamedyev1, I Ualiyeva1, A Mansharipova3, E Muhamedyeva4
COMPUTER MODELLING & NEW TECHNOLOGIES 2014 18(1) 100-108
1 International IT University, CT&SE department, Jandosova/Manasa 34a/8a, Almaty 050040, Kazakhstan
2 Tomsk State University, Lenin Prospekt 36, Tomsk, 634050, Russia
3 Kazakh-Russian Medical University, Torekulova str. 71, Almaty 050004, Kazakhstan
4 Riga Technical University, Kalku 1, Rīga LV-1658, Latvia
Increasing longevity is one of the most important problems of modern Gerontology. Solution of these problems is connected principally with the use of information and communication technologies. Creation of a comprehensive health information system requires consideration of many factors, such as qualitative screening system based on patients’ self-assessment, identification of possible errors that affect decision-making and patients’ personal characteristics. The work presents the results of elderly Almaty and Almaty Region population survey conducted with the help of Active Longevity Portal designed for data collection, analysis and assistance to the elderly population of Kazakhstan. The results showed that the number of medical consultations is directly related to health self-assessment and anxiety levels. Detection of cardiovascular diseases (CVD) with the help of effort angina self-assessment demonstrated low sensitivity. Correlation between the Kettle's index of effort angina self-assessment, the impact of Physical Component Score (PCS) of SF-12 test onto the manifestation of cardiovascular disease in hereditary background, anxiety level and coronary heart disease manifestation, impact of Health Survey estimated by Physical Component Score (PCS) and Mental Component Score (MCS) SF- 12 test onto the correspondence between Effort Angina Questionnaire and CVD patient state was detected. Studies showed that detection of diseases through Questionnaire Survey self-assessment in certain situations may lead to significant errors. Consideration of these factors will help to build a more powerful information system in which personal data will be combined with clinical data and expert estimates.