Computerized system and method for rapid data entry of past medical diagnoses
Abstract
A system and method for rapid entry of past medical diagnoses allows for development of specific, clinically relevant diagnoses from a simple input medication through use of a developed database that maps an input medication to a specific medical diagnosis through an intermediate indications data set. Input medications are normalized to their generic or chemical name and the normalized medication data is associated to an intermediate diagnosis through a medications indications listing contained in a database. Each medication develops a short list of possible specific and/or macro-diagnoses (indications) consistent with the medications and a selected indication is concept-matched to a specific medical diagnosis in order to develop a proper diagnosis in clinically meaningful terms, from a concept-mapped portion of the database. The concept-mapped portion is developed by grouping medical terms into clinically meaningful groups and developing pointers within those groups between identified diseases and a developed indications taxonomy, itself developed by forming a composite of FDA-approved and non-FDA approved indications with respect to particular normalized medications.
Claims
exact text as granted — not AI-modified1 . A method for rapidly inputting clinically relevant diagnoses from ancillary input data, the method comprising:
entering a medication identification comprising a medication tradename into an electronic data input and processing device; normalizing, in a database, the medication identification into a standardized medication index, the medication index mapping the medication identification to a generic description of the medication; accessing a database having a plurality of stored indications and a plurality of stored diagnoses, and wherein each of the diagnosis is associated to one or more of the plurality of indications and wherein each of the stored indications is linked to said standard medication index and wherein medication identifications are associated to one or more of the plurality of indications; reverse indexing, by the electronic data input and processing device, the normalized standardized medication index to a first set of relevant ones of indications associated with said entered medication identification; displaying, on a display of the electronic data input and processing device, the first set of relevant indications to a user; selecting a particular indication of the first set displayed on the display of the electronic data input and processing device; concept matching, by the electronic data input and processing device, the selected indication of the first set to a second set of specific diagnoses, each specific diagnosis identified to the selected indication; displaying, on the display of the electronic data input and processing device, the second set of specific diagnoses to the user; selecting a particular one of the second set of specific diagnoses displayed on the display of the electronic data input and processing device; providing an electronic patient medical record application; and automatically entering the selected specific diagnosis into the application.
2 . (canceled)
3 . The method according to claim 2 , wherein the normalization step further comprises mapping a medication tradename to the medication's generic description, such that medication identification entry is made without regard to a medication label.
4 . The method according to claim 3 , the concept matching step further comprising:
establishing a categorical collection of clinically meaningful groups; associating recognized indication terminology with each group; associating specific diagnoses to a particular group in accordance with a conceptual congruence between the specific diagnosis and the group.
5 . The method according to claim 4 , wherein the clinically meaningful groups comprise pathologically related classifications and are chosen from the group consisting of viral infections, bacteriological infections, structural defects, metabolic defects, genetic defects, and autoimmune defects.
6 . A method for rapidly inputting clinically relevant diagnoses from ancillary input data, the method comprising:
receiving a medication identification comprising a medication tradename inputted into an electronic data input and processing device; normalizing, in a database, the medication identification into a standardized medication index, the medication index mapping the medication identification to a generic description of the medication; accessing a database having a plurality of stored indications and a plurality of stored diagnoses, and wherein each of the diagnosis is associated to one or more of the plurality of indications and wherein each of the stored indications is linked to said standard medication index and wherein medication identifications are associated to one or more of the plurality of indications; reverse indexing, by the electronic data input and processing device, the normalized standardized medication index to a first set of relevant ones of indications associated with said entered medication identification; displaying, on a display of the electronic data input and processing device, the first set of relevant indications to a user; receiving a selection of a particular indication of the first set; concept matching, by the electronic data input and processing device, the selected indication of the first set to a second set of specific diagnoses, each specific diagnosis identified to the selected indication; displaying, on the display of the electronic data input and processing device, the second set of specific diagnoses to the user; receiving a selection of a particular one of the second set of specific diagnoses; providing an electronic patient medical record application; and automatically entering the selected specific diagnosis into the application.Join the waitlist — get patent alerts
Track US2016354154A1 — get alerts on status changes and closely related new filings.
We store only your email — no account needed. See our privacy policy.