CARDIOVASCULAR RISK IN PATIENTS WITH DIABETES MONITORED BY MOBILE PHONE APP HEALTH PROGRAM IN BRAZIL
Author(s)
Picoli RM, Braga C
University of São Paulo, Ribeirão Preto, Brazil
Presentation Documents
OBJECTIVES Diabetes requires a variety of strategies to promote glycemic control and avoid complications. Recently, apps are being used to promote, manage and provide medical and healthcare education. By the way, the mobile phone is used to support healthcare and public health interventions, also are a useful and easy method for collection of data for healthcare research. In addition, apps have shown successful use of support telemedicine and remote healthcare in developing nations. This study aims to assess the prevalence of the cardiovascular risk factors in a group of diabetic patients monitored by a mobile phone app health care program. METHODS The mobile phone app health care program is available for Android and IOS system, patients followed up is done through a specialized telephone monitoring center, made up of a physician, nurses, nutritionists, and psychologists, which provide constant monitoring and guidance health actions. A cross-sectional descriptive study was conducted in 63,955 patients monitored by mobile phone app health care program. The number of patients with diabetes totalized 6,983 (10,92%), then data were collected considering patients with 45 years or older. The cardiovascular risk factors analyzed was smoking, cholesterol and systolic and diastolic blood pressure. RESULTS The majority of the patients (52.94%) were female, average patient age was 55.40 years for female and 54.67 for male. The overall prevalence for uncontrolled cholesterol (more than 180 mg/dl) was 27,45% (female) and 17,65%. In addition, the average systolic/diastolic blood pressure (mmHg) was 129,33/84,29 (female) and 123,17/77,58 (male). The cardiovascular risk factor smoking was 3,11% (female) and 2,97% (male). CONCLUSIONS The results of this study, considering the useful and easy method (mobile phone app health care program) for collection data can facilitate and improve the way of chronic diseases management. For that reason, it could be used to support healthcare and public health interventions.
Conference/Value in Health Info
2018-05, ISPOR 2018, Baltimore, MD, USA
Value in Health, Vol. 21, S1 (May 2018)
Code
PHS142
Topic
Epidemiology & Public Health
Topic Subcategory
Public Health
Disease
Diabetes/Endocrine/Metabolic Disorders