This post is part of a series detailing the problems of current electronic healthcare records. To orient yourself, you can start at the index page on “presentation” on the iota wiki. You will find this and other pages on that wiki as well. The wiki pages will be continuously updated.
Since current electronic health care record systems have no knowledge of diseases as entities, we can’t drill down into the structure to locate necessary detail about the diagnosis or treatment of that disease. The information about diseases is spread out in the huge block of text that forms the EHR for a patient, so the only way to locate information in that is by searching on particular words or terms one could hope is related to the treatments one is looking for. Interestingly, not one of the EHR systems the author has seen has implemented even the most rudimentary search abilities such as “Find”. It’s hard to believe that these multimillion dollar systems don’t even have the features the lowly “Notepad” app has had since the inception of Windows in the 80’s, but that is the case. This leaves us with nothing else than eyeballing all the text manually, from start to finish. A clearly absurd state of affairs.
Search, even if implemented right, helps only in some edge cases. If you look for a reason why a certain medication was given or not given, it can help. If you look for treatments for a known disease, it can also help, but if you look for issues in the patient’s history that you don’t know about yet (the most important and most frequent search we do in an EHR in primary care), you’re out of luck even with a search function since you don’t know what you are searching for. A search can fill the function of an index, but not of a table of contents.
A summary of contents could be in the form of a “tag cloud”, but no EHR the author is aware of has even attempted to implement any such feature. Implementing a “tag cloud” of terms used in a medical record, if done right and with taste, could make the search problem somewhat more tractable by making it easier to navigate the old unstructured information from current EHR systems. It would not by any means replace “issues” as a structure, but would be helpful when linking legacy information to “issues” in a modern iotaMed based EHR.
In specialist care, the balance is somewhat different. Since searching for unrelated diseases is less frequent, a search on words or terms is relatively more important (one more often knows what one is looking for) and both a “Find” function and a “tag cloud” are even more sorely missed than in primary care. Even though both of these functions would be very useful, their usefulness arises from the fact that the lack of “issues” makes the EHR information such a mess to begin with. In the presence of “issues”, there would rarely be a reason to do a free search at all over an EHR, since information would be found in the place where it belongs.
This is not a reason to cast aside “Find” and “tag clouds” even for specialist care, since the legacy data in current EHR systems will be with us for a very long time still, before it all can be linked up with “issues” and brought into an “issue”-based structure. And even then, in that far future, “Find” and “tag clouds” will be essential tools, albeit not anymore the only tools to aid in the comprehension of the medical record.