Crowd Accelerated Health Inteligence: Impact on Policy Making
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Abstract
In this paper, the authors discuss the recent decades of preventable poor health which have spread across the globe with tsunami-like intensity. Despite the massive health impact we are witnessing today, adequate prediction and/or prevention mechanisms remain grossly underdeveloped. Hence this tsunami continues to threaten the future prosperity of our nations bringing economies throughout the globe to their knees.
Yet, core to this discussion is that preventable poor health is by definition preventable. This tsunami appears almost entirely mediated through unintended consequences of modernization. In the pure pursuit of profit, we have unwittingly supported the choice architectures that overwhelmingly enable poor lifestyle choices in preference to optimal choices.
The authors then go on to explain why aggressive attempts at improving health care delivery (supply side) has left us remarkably inept at transforming the health as well as the health costs of crowds. This almost singular focus of Health Information Technology (HIT) on care delivery may be largely responsible for the underperformance of our predictive and preventive capacity at this time. Relying on institutional (hospital and clinic) data tracking care delivery to proactively manage the health expression of crowds may be similar to using a rear view mirror to drive a car.
Hence an urgent and paradigmatic shift in public policy making is proposed. Communities and individuals must play a key role in co-creating the knowledge engines that support evidence-based investment of public health funds. New scientific truths (eScience) must be supported through complex free living system analysis of networked communities, nudging simulators and emerging data intensive advanced modeling techniques.
Building upon this background, the authors propose the core principles of modern actionable solutions. In short this involves: the provision of mundane yet high yield health data through light instrumentation of the crowd, real time living epidemiology linked into advanced algorithms sorting the per unit co-occurrences into wellness or illness promoting event streams, simulated and actual nudging through persuasive technologies such as serious gaming to reward optimal behaviors and most importantly, timely visualization and reliable simulation to pre-evaluate and proactively direct public health investments in evidence-based ways.
Here data and insights from disparate sources and disciplines ranging from clinical and biomedical research, economics, public health policy, information systems and data mining advances, and more have been expertly organized. Discussed and defined in this paper are the malignant spread of environmentally induced human underperformance and the emerging data intensive and crowd sourced science of Reachability management which holds the promise of robust prediction and prevention.
Information technologies must be integrated with the expressed purpose of optimizing human performance and lifting our collective health talents. Gone be the days of choice architectures that silently and systematically erode our health and our economies; may our nations reclaim their heritage of a robust and prospering future through the co-production of an effective eScience.
Yet, core to this discussion is that preventable poor health is by definition preventable. This tsunami appears almost entirely mediated through unintended consequences of modernization. In the pure pursuit of profit, we have unwittingly supported the choice architectures that overwhelmingly enable poor lifestyle choices in preference to optimal choices.
The authors then go on to explain why aggressive attempts at improving health care delivery (supply side) has left us remarkably inept at transforming the health as well as the health costs of crowds. This almost singular focus of Health Information Technology (HIT) on care delivery may be largely responsible for the underperformance of our predictive and preventive capacity at this time. Relying on institutional (hospital and clinic) data tracking care delivery to proactively manage the health expression of crowds may be similar to using a rear view mirror to drive a car.
Hence an urgent and paradigmatic shift in public policy making is proposed. Communities and individuals must play a key role in co-creating the knowledge engines that support evidence-based investment of public health funds. New scientific truths (eScience) must be supported through complex free living system analysis of networked communities, nudging simulators and emerging data intensive advanced modeling techniques.
Building upon this background, the authors propose the core principles of modern actionable solutions. In short this involves: the provision of mundane yet high yield health data through light instrumentation of the crowd, real time living epidemiology linked into advanced algorithms sorting the per unit co-occurrences into wellness or illness promoting event streams, simulated and actual nudging through persuasive technologies such as serious gaming to reward optimal behaviors and most importantly, timely visualization and reliable simulation to pre-evaluate and proactively direct public health investments in evidence-based ways.
Here data and insights from disparate sources and disciplines ranging from clinical and biomedical research, economics, public health policy, information systems and data mining advances, and more have been expertly organized. Discussed and defined in this paper are the malignant spread of environmentally induced human underperformance and the emerging data intensive and crowd sourced science of Reachability management which holds the promise of robust prediction and prevention.
Information technologies must be integrated with the expressed purpose of optimizing human performance and lifting our collective health talents. Gone be the days of choice architectures that silently and systematically erode our health and our economies; may our nations reclaim their heritage of a robust and prospering future through the co-production of an effective eScience.
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