Quick history of the medical document.
A static record of what was important to the doctor. A doctor sees a patient, writes a note on paper, and puts it on top of the note stack. After several years information becomes lost.
When we started using computers in healthcare it was to type notes rather than write them by hand.
In the more recent past we began generating our documents with pre-populated segments of text.
Computers help with transmitting orders and results but the encounter remains the same, or even worse due to auto generated text .
The future of healthcare is a faster and more accurate diagnosis and resolution of problems. With the ever increasing amount and types of data being generated to manage complex patients, physicians will require systems that help them meet these challenges. It will involve a self learning healthcare system that will ultimately provide autonomous patient management, under the watchful eye of a physician.
Information is of two types: human derived and sensor derived. The progression toward the future model is a progression from human derived information to sensor derived information. In the distant future we will not have to rely on us humans to describe or explain our symptoms.
Sensor derived information will allow us to avoid ambiguous and vague symptoms, getting us to the actual cause of the problem and to a quicker resolution.
So what are these elements and what makes our system so novel? The primary categories are problems, todos, and encounters.
A problem is a set of related data that has a unique name and conceptual meaning.
Todos are tasks that are expected to resolve a problem.
Encounters are a log of computer actions that the doctor did during an encounter.
Created with images by NEC Corporation of America - "NEC-Medical-137" • pedrosimoes7 - "Older woman profile" • www.ilmicrofono.it - "bodycare, clinic, clipboard, doc, doctor, female," • Unsplash - "computer business typing" • Pacific Air Forces - "120615-F-FD024-006" • FirmBee - "office tax business" • johnvoo_photographer - "bacteria/viruses" • ColiN00B - "dna dns biology" • Pezibear - "child girl blond" • beba - "leaves green shadow play" • Rosa Menkman - "Filtering Failure" • sipa - "clouds nature clouds form" • OakleyOriginals - "63Dad seeing patients" • kev-shine - "Technology" • Greg Burkett - "Analysis" • Unsplash - "books pages story" • Unsplash - "barley cereal grain"