Difference between revisions of "Open Source Medicine/Intro"

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The medical systems now in existence are fraught with problems. The enormous amounts of data they gather have no standard for collaboration, much research (especially pharmaceutical) is done by private companies who take decades to develop drugs, and develop drugs only for diseases that afflict large numbers of wealthy people. Drug development for diseases of poverty, like leprosy, are not pursued because it is not financially feasible. Personalized drug development is not developed because it is not financially feasible. In the USA, 45000 people dies anually because they lack health insurance <sup>[http://www.harvardscience.harvard.edu/medicine-health/articles/new-study-finds-45000-deaths-annually-linked-lack-health-coverage]</sup>.  
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Two key principles of this wiki are [[advanced automation]] and open collaboration. This page explores the application of these to healthcare, looking at how [[artificial intelligence]] can help automate healthcare and open collaboration can provide a more effective translation of knowledge into actual patient care.
  
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There is a way out: open source medicine. Make medical knowledge freely available and share it globally by a standardized system. Develop drugs openly, so that people can pursue the research that matter to them, rather than base it on bottom-line considerations.
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The medical systems now in existence are fraught with problems. The enormous amounts of data they gather remain disconnected and scattered, doctors are completely overwhelmed, much research (especially pharmaceutical) is done by private companies who take decades to develop drugs, and an unnecessary [[scarcity]] of healthcare lifts it out of the reach of the poor
  
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There is already a [http://en.wikipedia.org/wiki/List_of_open_source_healthcare_software huge amount] of open-source software already available to make the management of healthcare easier {{em}} keeping patient records, processing body-imaging information etc. This needs to be integrated over time, so that, say, the medical records program can talk to the body-scanning program.  
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There is a way out: open source medicine and advanced automation. Use modern information technology to make medical knowledge freely available and share it globally by a standardized system. Develop drugs openly, so that people can pursue the research that matters to them, rather than base it on bottom-line considerations. Organize the medical knowledge of humanity intelligently and put it at the fingertips of every doctor. Automate as much of the medical system as possible (but no more!) to take the strain off doctors.
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Another promising development is the use of distributed computing to store and process medical data. This allows a patient's medical history to be accessed from any hospital in the world. This is only possible with [[free and open-source software]]; if different doctors are using different private systems, their records will be incompatible, but if theyh are all collaborating, their records can inform one another.
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Latest revision as of 17:00, 20 May 2010

Two key principles of this wiki are advanced automation and open collaboration. This page explores the application of these to healthcare, looking at how artificial intelligence can help automate healthcare and open collaboration can provide a more effective translation of knowledge into actual patient care.

The medical systems now in existence are fraught with problems. The enormous amounts of data they gather remain disconnected and scattered, doctors are completely overwhelmed, much research (especially pharmaceutical) is done by private companies who take decades to develop drugs, and an unnecessary scarcity of healthcare lifts it out of the reach of the poor

There is a way out: open source medicine and advanced automation. Use modern information technology to make medical knowledge freely available and share it globally by a standardized system. Develop drugs openly, so that people can pursue the research that matters to them, rather than base it on bottom-line considerations. Organize the medical knowledge of humanity intelligently and put it at the fingertips of every doctor. Automate as much of the medical system as possible (but no more!) to take the strain off doctors.

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