More and more people are shifting their technological focus to smartphones, what with a wide and ever-increasing variety of downloadable apps that all aim to make life just a little bit easier. When it comes to health-related apps, app developers are now beginning to integrate the latest advancements in health sciences in order to design apps that both sick and well patients can benefit from.
Merz Pharmaceuticals recently released a health app that allows middle-aged and older adults (40-65 years old) to determine how much at risk they are for developing a form of dementia over the following 20 years. The CAIDE Dementia Risk App (Cardiovascular risk factors, Aging and Incidence of DEmentia) is a product of a working partnership with Stockholm’s Karolinska Institutet, and is absolutely free to download.
All that users have to do to determine someone’s risk for developing dementia is to open up the CAIDE app and input patient data such as gender, date of birth, height and weight, serum cholesterol, blood pressure, level of regular physical activity, and educational attainment. A green result is low risk, orange is moderate, and red is high risk. After getting the result, a physician then has an opportunity to discuss relevant interventions.
The CAIDE app features an easy to understand traffic light color scheme risk gauge, and is also a big help to health professionals when they try to explain certain preventive interventions to patients determined to be at risk. For now, both versions of the app — one for doctors, and the other for health consumers — can only be run on an iPhone or iPad, and is available in a number of languages aside from the default English: German, French, Spanish, and Russian.
To know more about the CAIDE app, visit http://www.merz.com.
Integrating health seeking behavior into apps is gaining popularity among app developers and tech consumers. Some apps are even integrating diagnostics, such as the one scientists from the University of Houston are currently working on, which may be able to help in the early diagnosis of skin cancer.
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