Personal Health Forecasting
“Personal Health Forecasting” (PHF) can be described like this: continuously all your health-related information is collected digitally, through the healthcare information systems, the PHS solutions, wearable sensors, intelligent implants and pharma packaging, ambient sensors in our house and workplace, etc. All these data, combined with all information we log directly during our daily life, are stored in a private secure cloud that initially can be accessed only by the patient him/herself. However, we can grant access to some of this information to our relatives, carers, GPs, or hospital specialists, by setting policies that define if the access is continuous, intermittent, sporadic, and whether it needs to be constantly re-authorised or not. A huge works has to be done to make the user interfaces so simple and intuitive that they do not constitute an additional barrier for the weaker members of our societies.
Another thing we can do is to expose some of our personal health data to remote processing services, typically provided by the healthcare institutions but also by for-profit entities, which continuously process such data with VPH-based predictive models, which return forecasts on how our health status will evolve in the near and distant future. Such personal health forecasting services can be designed around generic wellness programmes (such as the ten thousands steps initiative), or around very specific conditions (management of type 2 diabetes, management of post-operative stage in breast cancer, stroke recovery, etc.).
Personal health forecasting services can be designed to simply provide life style coaching, raise alarms and warnings to carers and healthcare services, support participative programmes where the patient is expected to undertake specific activities that are monitored by PHS solutions and tuned by PHF services, or trigger healthcare provisions when specific combinations of health states appear.
All personal health data will be aggressively anonymised (and where the law requires accompanied by an informed consent) before they are replicated in national warehouse for secondary use. Two important uses will be continuous validation of Personal Health Forecasting models (by comparing the predicted states to those actually observed in the same subject), and what we call Public eHealth, decisions support systems for policy makers capable of forecasting the healthcare needs of the population in the near and far future.
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