Personal Health Forecasting

Average Ratings Feasibility


“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.

Source: Prof Viceconti releases an interview for Personal Health Foresight

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4 Responses to “Personal Health Forecasting”

  4. It’s a matter of fact that the leading opinion of medicine is to cure diseases instead of disease prevention.
    Unfortunately there is a very powerful argument for this attitude – a health and satisfied “patient” isn’t lucrative for the pharmaceutical companies. As incredible as it sounds, the less money we spend for prevention the more money they earn.

    Every one of us knows about the importance of regular exercise, an annual checkup, the danger of smoking, drinking, obesity, fast food,…. .
    Due to the fact that, as long as we are young, our body has the ability to compensate an unhealthy lifestyle, most of us are not aware of the long term consequences.
    No one consider that he could be the one who will suffer from diabetes or a heart attack. So I think that a “personal health forecasting” could help, to increase the awareness of long term consequences, for the simple reason that a bad personal health forecast will affect a person in a total other way than a general suggestion could do.
    Furthermore this new awareness can help to save costs, to increase the health of the whole population by providing anonymised data to do research on it and to disburden the health system.


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