Targeted isolation of anatomic sites for form generation and medical record generation and retrieval

Abstract

The present invention includes a method for targeted isolation, segmentation, and coloring of anatomic images, anatomic maps, points of interest, and regions of interest for dynamic, translated form generation. For example, this invention includes a method whereby a description of anatomy that includes an anatomic site, and optionally laterality and other descriptors, targets and isolates diagrams from an anatomic map library that fits the anatomy description. A point of interest on a layered, hierarchical map is visualized in relation to the borders of each isolated anatomic site above, below, on the same level along with translated human readable descriptions of the pin position relative to each layer. An anatomic region of interest is also visualized in relation to sites above, below, and on the same hierarchical or layer level. Targeted isolation of each layer provides visualization, translation, descriptions, and visual selection points for a visual, translated hierarchical travel method included in this invention. A dynamic anatomy library combines with other data to generate dynamically filled in and fillable forms with relevant visualizations, codes, translations, and data. Dynamic forms that contain anatomy data are processed through a form processing engine for detection, categorization, encoding, translation, and labeling of the anatomy and non-anatomy data, and those outputs then process through a billing code engine, record generation engine, and image and visualization labeling engine. A record retrieval engine applies neural networks, computer vision, and artificial intelligence to re-create, analyze, categorize, and serve back record defined data to complete the loop.

Description

UTILITY PATENT APPLICATIONCONFIDENTIAL INFORMATIONApplicant: MoFalP, LLCAddress: 4327 Pine Ridge Circle, Monclova, OH 43542, USATitle: Targeted isolation of anatomic sites for form generation and medical record generation and retrievalFirst Named Inventor: Matthew A. MolendaAttorney: McCarthy, Lebit, Crystal & Liftman, Co. L.P. A.Customer No.: 113863Attorney Docket No.: A L.P025.PCTRELATED APPLICATIONS

[0001] This application claims priority from each of U.S. Provisional Patent Application Serial No. 63 / 265,216 and its filing date December 10, 2021 , U.S. Provisional Patent Application Serial No. 63 / 369,717 and its filing date July 28, 2021 , U.S. Provisional Patent Application Serial No. 63 / 315,289 and its filing March 1 , 2021 , U.S. Provisional Patent Application Serial No. 63 / 269,516 and its filing date March 17, 2021 , U.S. Provisional Patent Application Serial No. 63 / 362,791 and its filing date April 11 , 2021 , U.S. Provisional Patent Application Serial No. 63 / 364,393 and its filing date May 9, 2021 , U.S. Provisional Patent Application Serial No. 63 / 364,764 and its filing date May 16, 2021 , U.S. Provisional Patent Application Serial No. 63 / 365,026 and its filing date May 20, 2021 , U.S. Provisional Patent Application Serial No. 63 / 365,373 and its filing date May 26, 2021 , U.S. Provisional Patent Application Serial No. 63 / 366,107 and its filing date June 9, 2021 , U.S. Provisional Patent Application Serial No. 63 / 370,879 and its filing date August 9, 2021 , and U.S. Provisional Patent Application Serial No. 63 / 375,325 and its filing date September 12,2021. Each of these applications is hereby incorporated by reference in their entireties for all purposes.FIELD OF THE INVENTION

[0002] This invention relates to medical systems, and more particularly, to generating dynamic forms from a dynamic anatomy library including hierarchical, multidimensional maps that can be isolated, segmented, and sub-segmented through visual, coded, linguistic, and symbolic inputs, to output the most relevant visualizations, maps, and images.SUMMARY OF THE INVENTION

[0003] Current solutions used to document anatomic sites with anatomic mapping do not provide targeted isolation, segmentation, and coloring of anatomic images. They also do not serve back segmented anatomic maps, or dynamically visualize isolated points of interest relative to site borders in each level of a hierarchy or multiple layers or visualize segmented or complete anatomic sites in a hierarchy with color coding. Current solutions also do not create dynamic anatomy libraries from record defined and user defined inputs or create dynamic forms from the dynamic anatomy library and non-anatomy data that includes targeted and isolated visualizations of multidimensional anatomy maps, anatomic site translations, and re-creation abilities directly on the forms. Current solutions also do not combine anatomy data, non-anatomy information, patient data, country data, coded data, and translation data to create language agnostic, geographic location-optimized translated forms and visualizations. Current solutions are also unable to extract anatomy and non-anatomy data from both electronic and digital forms containing anatomy visualizations and use that extracted information in a plurality of engines to re-create dynamic anatomy libraries. An example of a current paper workflow that is optimized by this invention is the paper Mohs map used to document skin cancer surgery. Such maps that contain anatomic visualizations must be manually selected from a paper or electronic library, and do not have anyrelevant data filled in automatically, thus creating a lot of manual steps, handwriting, or typing, and manual record correlation (e.g., looking up pathology report information, which often contains a non-specific anatomic site) that is prone to human error. Further still, such Mohs maps that were printed and documented on paper must be manually scanned back into the patient chart and manually associated with the documented anatomic site, if that is even an option as a category in the electronic health record. This invention solves what has been pointed out as lacking in current solutions with targeted isolation, segmentation, and coloring of anatomic images, anatomic maps, points of interest, and regions of interest into a dynamic anatomy library for point visualization and translation in relation to multidimensional anatomic borders, visualized hierarchical travel and selection, dynamic, translated form generation, and for use in medical record generation and retrieval.

[0004] The present invention includes a method for targeted isolation, segmentation, and coloring of anatomic images, anatomic maps, points of interest, and regions of interest for dynamic, translated form generation. For example, this invention includes a method whereby a description of anatomy that includes an anatomic site, and optionally laterality and other descriptors, targets and isolates diagrams from an anatomic map library that fits the anatomy description. A point of interest on a layered, hierarchical map is visualized in relation to the borders of each isolated anatomic site above, below, on the same level along with translated human readable descriptions of the pin position relative to each layer. An anatomic region of interest is also visualized in relation to sites above, below, and on the same hierarchical or layer level. Targeted isolation of each layer provides visualization, translation, descriptions, and visual selection points for a visual, translated hierarchical travel method included in this invention. A dynamic anatomy library combines with other data to generate dynamically filled in and fillable forms with relevant visualizations, codes, translations, and data. Dynamic forms that contain anatomy data are processed through a form processing engine for detection, categorization, encoding, translation, and labeling of the anatomy and non-anatomy data, and those outputs then process through a billing code engine, recordgeneration engine, and image and visualization labeling engine. A record retrieval engine applies neural networks, computer vision, and artificial intelligence to re-create, analyze, categorize, and serve back record defined data to complete the loop.BRIEF DESCRIPTION OF DRAWINGS

[0005] FIG. 1 depicts a flowchart of the system of the present invention.

[0006] FIG. 2 is a screenshot of a patient facial diagram displaying an enhanced anatomic site.

[0007] FIG. 3 is a screenshot of a patient facial diagram displaying a translation.

[0008] FIG. 4 depicts an exemplar pathology requisition form.

[0009] FIG. 5 depicts an exemplar timeline of dynamic anatomic site history.

[0010] FIG. 6 depicts an exemplar automatically replotted anatomic site with associated diagnosis and diagnosis extension data blocks.

[0011] FIG. 7 depicts an exemplar automatically generated Mohs map.

[0012] FIG. 8 is a screenshot of a hierarchical painting with associated treatment recommendations.

[0013] FIG. 9 depicts an example printed output of visual previews with associated treatment recommendations.

[0014] FIG. 10 depicts an example digital regiment map with associated treatment recommendations.

[0015] FIG. 11 depicts an example printed output with associated treatment recommendations.DETAILED DESCRIPTION OF DRAWINGS

[0016] The present invention targets and isolates anatomic images, maps, points of interest, and regions, to provide a dynamic anatomy library that includes visualized, coded, linguistic, and / or symbolic descriptions and definitions of anatomy. Additionally, the dynamic anatomy libraryincludes hierarchical, multidimensional maps that can be isolated, segmented, and subsegmented through visual, coded, linguistic, and symbolic inputs, to output the most relevant visualizations, maps, and images. Sites related to or nearby a point or anatomic site of interest are also shown dynamically in relation to one another with hierarchical selectors that include visual and linguistic, coded, symbolic, and cross-mapped descriptions of anatomy. The hierarchical selectors allow for simultaneous visual and descriptive travel through a hierarchy, and each option can be used to generate a form or other outputs dynamically that includes the selected visualization and translation. Additionally, for a point of interest, the hierarchical selector shows the point position relative to all overlaying and underlying anatomic sites, along with the enhanced translations.

[0017] For a distribution segment, all anatomic sites above and below the currently selected anatomic site, in layer or anatomic hierarchy, are also shown with translation, borders, colors, patterns, intensities, and surface area calculations. For dynamic, translated form generation, in addition to translated and visualized anatomy data, the forms also automatically include dynamic non-anatomy information, such as demographic information extracted from the patient chart. The forms, whether electronic or paper, are then processed for a form processing engine and relevant anatomy data, including visualizations, points of interest, distributions, and coordinates, and nonanatomy data are extracted from the dynamic forms and processed again into engines for detection, categorization, encoding, translation, and labeling for both the anatomy data and nonanatomy data. These data apply neural networks to software engines to generate medical bills, records, visualizations, and labeling protocols, which are all translatable and localizable to any coded, linguistic, or symbolic language, or to geographic region.

[0018] Another example of where isolated visualizations can be applied is to exports to PDF for each pin or distribution segment, including a pathology requisition form that generates printable labels that also include targeted, isolated visualizations of the anatomic sites along with a standardized anatomic descriptions that automatically can include laterality, prefixes, suffixes,enhanced directional modifiers, custom descriptors, automatic relationships, patient demographics, symptoms, morphologies, linked photos, linked documents, attachments, diagnoses, diagnoses extensions, billing codes, procedural descriptions, pin or distribution segment or distribution descriptions, tags, codes such as Quick Response (QR) codes, and other anatomy and non-anatomy data. The figures provide a framework for understanding this invention.

[0019] Referring now to the figures, FIG. 1 depicts a flowchart of the system. Anatomy data 250 in the form of an anatomic site, point, or region of interest is determined from record defined input 261 or user input 260. The anatomy data 250 correlates to a point on a layered map (such as a pin as a point or a distribution segment as a region), reference to point or region on a map (such as a list item in a list of sites with an isolated visual preview), description of an anatomic site (such as a code string, linguistic description in any language, or a symbolic description such as an ear emoji to represent the ear), coordinated description of an anatomic site (such as coordinates on a diagram corresponding to a pin or distribution segment), or an image of an anatomy or anatomic site (such as a photograph of the ear with anatomic site detection with aligned overlays and underlays). Any of these inputs creates a dynamic anatomy library of templates 251 with hierarchical, layered, custom-coordinated, corresponding maps which include targeting sites of interest and additional diagrams representing the anatomic site of interest The dynamic anatomy library visualizations are available in unadjusted and mirrored axes, allowing for visualization in outside observer-view and mirror-view (selfie view). The hierarchical maps may be complete avatars in two- or three-dimensions, or segmented anatomic areas of interest.

[0020] Non-anatomy data 258 may also be input in the system through record defined input 261 or user input 260. Non-anatomy data 258 may include data from other records such as electronic health records containing patient demographics and information, encounter demographics and information, diagnosis, diagnosis extensions, patient country, user country, geographic location, patient language, user language, procedure, treatment, symptoms, morphologies, images,multimedia, reports, and other health data, or user input 260 that is either undefined by the record, or added prior to dynamic form generation. It is contemplated that non-anatomy data 258 may include, but is not limited to, measurements, notes, drawings, markups, annotations, custom descriptions, text, patient demographics and information, encounter demographics and information, diagnosis, diagnosis extensions, patient country, user country, geographic location, patient language, user language, procedure, treatment, symptoms, morphologies, images, multimedia, reports, comments, and other health data that one skilled in the art would know. User input 260 can also modify the information prior to dynamic form generation 257. It is contemplated that modifications may include selecting a different dimension, hierarchy level, axis, description, or diagram from the dynamic anatomy library, or refining the position and description of the point of interest or other manipulation of the input as one skilled in the art would know.

[0021] The dynamic anatomy library 251 and the non-anatomy data 258 are translated and transformed into generated dynamic forms with the dynamic form generation and translation engine 257, which include anatomic images, diagrams, maps, and descriptions from the dynamic anatomy library 251 , and patient, diagnosis, and encounter information from the non-anatomy data 258. The generated forms may be printable forms 259 or electronic forms 256. A plurality of templates, diagrams, data blocks, maps, records, and known inputs are used to generate each dynamic form, and unknown inputs leave blanks that can be targeted to fill in with record defined input 250 or user input 251. Printable forms 256 are automatically filled in by the dynamic form generation engine 255 with relevant anatomy data 252 and non-anatomy data 254. In one embodiment, the printable form 256 is a Mohs map, used in micrographic dermatologic surgery, with detectable anatomic diagrams, surgical whiteboards, and checklists that contain visual representations of the anatomic site that will have surgery, along with printed pathology requisition forms and labels that have isolated visual previews of each anatomic site. Electronic forms 257 include the same data as printed forms 256 but in electronic format. In one embodiment, the electronic form is a digital consent form capable of accepting electronic inputs from the recordretrieval engine 261 to fill-in blanks on the form, such that it can accept a digital patient signature. These are only two example forms, there are countless forms used in the medical field and any could be incorporated in this system as one skilled in the art would know.

[0022] It is contemplated that both printable forms 256 and electronic forms 257 automatically account for geographic, country, and language considerations. In one exemplary embodiment, complex closure requirements are included on forms generated in the United States and in English because those requirements are only relevant to the current US-based procedural terminology billing codes used in the United States.

[0023] It is contemplated that both printable forms 256 and electronic forms 257 also automatically account for anatomy-specific information. In one exemplary embodiment, on a consent form for surgery on the temple, a warning alert about a temporal nerve injury and the consequences of injury (such as the inability to raise the eyebrow) is generated. In another exemplary embodiment, on pre-surgery checklist for nasal surgery, photo workflows are included ensure all views of the nose are photographically captured.

[0024] After printable forms 256 and electronic forms 257 are marked up, annotated, or otherwise finalized, including but not limited to, filled in blanks and checklists, corrections or edits made, markup on anatomic diagrams representing a map, annotations on anatomic diagrams representing a map, physical labels placed on physical specimen bottles, digital signatures completed, and other data, they are delivered to the form processing engine 258. Delivery to the form processing engine 258 may be through electronic or manual means. In one exemplary embodiment, computer vision analysis automatically extracts, categorizes, and digitally documents the information, including precise anatomic names and descriptions correlating with the markup, and delivers the data to the form processing engine 258. In another exemplary embodiment, a QR code representing anatomy and non-anatomy data is scanned and delivers the data, including anatomic visualizations and maps, to the form processing engine 258.

[0025] The form processing engine 258 simultaneously delivers data 259 to the anatomy data engine 260 and non-anatomy data engine 261 that categorize, encode, translate, and label the data using neural networks and natural language processing. The two engines generate the record outputs 262 including, the billing code engine 263, the record generation engine 264, and the image and visualization labeling engine 265.

[0026] The billing code engine 263 uses anatomy data 252 including but not limited to anatomic site, surface area, intensity, nearby structures such as named nerves, and non-anatomy data 254 including but not limited to measurements, counts, diagnosis, diagnosis category, patient country, user country, user region, selected language, procedure types, procedure counts, complexity measurement, and other data. The billing code engine 263 can apply the same data agnostic to language and geography, simultaneously to different billing code sets in different countries such as CPT codes in the USA, and the OPCS Classification of Interventions and Procedures in the United Kingdom.

[0027] The record generation engine 264 transforms the anatomy data 262 and non-anatomy data 253 into translatable, dynamic records that includes but is not limited anatomic site listings, anatomic site visualizations, calculations such as surface area and intensity at a time point or at different time points, diagnosis codes, anatomic site codes, procedure codes, descriptions for all the codes, time points, areas, calculations, QR codes, digital bookmarks, file name strings, delimited metadata, PDF records, image records, other file type records, structured language records, unstructured records, database records, encrypted or unencrypted files such as zip files and PDF records, sharable collaborative session records, and other record formats. Certain encoding system, such as ICD-10 for diagnoses, combine anatomy data 262 and non-anatomy data 253 into a single code. The record generation engine 264 delivers both combined data encodings, and separated data encodings simultaneously. Therefore, this translation also works bidirectionally, so ICD-11 codes can be converted to ICD-10 and other code sets that includeanatomy and non-anatomy data through a translation engine and cross-mapping dataset, and vice versa.

[0028] The image and visualization labeling engine 265 detects, visualizes, highlights, translates, labels, and highlights anatomic sites. In one exemplary embodiment, the image and visualization labeling engine 265 applies labeling in a symbol delimited, order-less string of data that includes alphanumeric and symbolic characters representative of the anatomy and non-anatomy data. An example label could read:

[0029] ®20220216««John«»Smith«^ 19780822«d*Il83439jNDs stltm«H« OrderedProced ure*3A*Shave_Biopsy^**<Malar_region**72*AXA0M67-XK9K*^2F72*ia6yDgsDcGvs4a**5 73ns8d74hsD« FB1.09«^290.593«t488.3439«^Matthew_Molenda_MD«11102«ggrew_over

[0030] The record outputs 262 from these three engines become searchable and modifiable records for the record retrieval engine 266. In one exemplary embodiment of modification, the symbol delimited example string above is retrieved through a search for images with the diagnosis code “^2F72” and the result is modified by stripping the other content in the symbolic string. In another exemplary embodiment of modification, a record including images of anatomic sites linked to a specific diagnosis is modified by removing identifying patient data from the search results, providing a dataset and image set for a research study.

[0031] The record retrieval engine 266 is capable of capturing QR codes or anatomy visualizations (with a camera, scanner, or other capture device) and non-anatomy data on a pathology requisition form at a different time point and using the scanned information as record defined input 250 which can then be fed back into the system 215 to generate new forms and outputs. When the system 215 is looped in this manner and new forms and outputs are generated, the system allows for data linking at different points in time and in different settings on different systems, such as different electronic health records.

[0032] FIG. 2 is a representative screenshot of an anatomic visualization 10 that depicts simultaneous, hierarchical, multidimensional, real-time coloring 50 and labeling of anatomic sites under a cursor position with a color-coded legend representing the enhanced, translated anatomic site descriptions for the colored anatomic sites. Also depicted are hierarchically painted anatomy distribution segments 51 with color coding and patterned, non-patterned, and intensity visualization, auto-relation describing the relationships between pins 52 B and C in the pin list 53 (with this embodiment relating pins B and C 52, the pin list 53 describes that “B (this pin) is medial and superior from C” and “C (this pin) is lateral and inferior from B”), simultaneous hierarchical selection, relative visualization (to borders of each anatomic site), translation (with the present embodiment describing pin A 52 simultaneously as the “left (superior) paramedian forehead” in the pin list 53, and as “(superior left) forehead”, “face”, “head” and “head and neck” in the hierarchical selector 54 that also shows pin A 52 isolated and related to the borders of each targeted anatomic site in the anatomic hierarchy), and description of dynamic anatomic address (a reproducible location within the dynamic anatomy library) components, and other functions. Placed pins 52 on the anatomic visualization 10 indicate locations where patient medical events have occurred. In this example, dynamic pin descriptions indicate shave biopsies were performed on various locations on the forehead. The pin list 53 shows an isolated visual preview including information associated with each pin 52, including pin order, and pin position relative to the selected anatomic site component of the dynamic anatomic address, automatically populated diagnosis with a description and code, and the dynamic pin description in the same color as the pin, allowing for synchronization to the map and other outputs. Below the pin list 53, there are diagnoses listed in collapsed lists correlating with other pins (melanoma) and painted distribution segments 51 (dermatitis NOS and acne) on the layered anatomic map 50. Despite pins 52 and hierarchically painted distribution segments 51 with colors, patterns and opacities occupying anatomic site segments, the color-coded legend to display the multidimensional site visualizations and translated descriptions relative to the cursor point is still visualized without interruptionbecause of its underlayment. Hierarchical overlays again would cause real-time visualization obscurement issues.

[0033] FIG. 3 depicts the same anatomic visualization 10 and color-coded legend 12 of FIG. 2 in a Spanish translation. The translation occurs in real-time and simultaneously, allowing for multiple users to use the same tools and visualizations in a shared, real-time session but in different languages. It is contemplated that the software application is capable of translating diagnosis extensions and extended descriptions and all displayed text, including automatic enhanced descriptions of the multidimensional anatomic maps, points, distribution segments, and visualizations, in any coded, linguistic, or symbolic language. Also depicted is a quick zoom 56 functionality that has translated isolated diagram visualizations 57 to selectively target, find, and zoom in on multidimensional anatomic areas of interest. Also depicted is a hierarchical selector 54 with options for a hierarchical painting method to paint diagnoses with different colors, patterns, intensities, opacities, and properties to multidimensional anatomic maps or avatars. It is contemplated that surface areas and intensity of involvement are also automatically calculated based on anatomic distribution.

[0034] FIG. 4 depicts an exemplar pathology requisition form 280 generated by the system which includes dynamic anatomy library information and two copies of each isolated visual preview, showing the pin position relative to each visual preview. The table section 281 includes the procedures associated with the patient. Each row represents a surgical procedure, and photos and other data are automatically placed into the form. The pre-cut label section 282 has a corresponding summary of each procedure appearing in the table section 281. The first isolated visual preview is on the row that describes the anatomic site, diagnosis, and notes. The second isolated visual preview appears in the label section 282 of the pathology requisition form 280. It is contemplated that the paper size could be adjusted automatically to accommodate users based on their geographic standards. This is just one of a plurality of templates for different forms and outputs that use isolated visual previews of the dynamic anatomy library. It is contemplated thatit would be possible to export groups, entire maps, or entire avatars with the relevant rotations. In one exemplary embodiment, physical labels are applied to specimen bottles in this use case, the reproducible isolated visual preview along with the enhanced anatomic description on each label provides a new patient safety enhancement to ensure that bottles are labeled correctly, and the specimens make it into the correct bottles. The reproducible visualization helps reduce medical errors associated with incorrect labeling. In the present example, a plurality of QR codes is generated, creating workflows that allow for dynamic anatomy library visualization and anatomy data recreation at another site, such as at a separate pathology lab for an evolving report, such as an evolving pathology report linked to the same anatomic site (dynamic anatomic address) over time and in different systems. In one embodiment, patient demographics, insurance information, encounter information, originating clinic, notes, diagnoses, and other non-anatomy data are added automatically through QR codes, simplifying the intake process on the receiving end. Thus, the present invention includes a method to precisely reproduce anatomic site names, infinitely scalable vector visualizations and multidimensional maps of anatomy with precise pin locations, and non-anatomy information, compressed into a single code such as a small QR code that fits on a small label (less than one inch needed for the code), and small isolated visual previews on the same label, that may also be used to recreate or confirm the correct anatomic site. In one embodiment, the physical label fits on a small skin biopsy specimen bottle. A single QR code recreates the entire encounter on a different day on a different system (such as at a receiving lab), and recreates pins, distributions segments, and visualizations, tags, notes, buckets, test IDs, pin IDs, and other information related to the dynamic anatomic address. It is contemplated, each pin or distribution segment in the list can have separate QR codes as well. Dynamic anatomic address recreation enabled by this software engine allows for data to be appended, merged, changed (e.g., new pathology diagnosis), visualized, and tracked at different time points. It further is contemplated, the QR codes are optionally encrypted and evolve over time.

[0035] FIG. 5 depicts an evolving report 290. Dynamic anatomy library visualization, anatomy data, and non-anatomy data recreation at different time points allows for evolving reports that automatically collate, display, and analyze information from different sources. The QR code evolves along with the report and can be optionally encrypted. Data from different sources, including different clinics, all collate and aggregate together to achieve this living, evolving report. In the present embodiment, there is a pathology report, a digital microscopic image of the slide, automatic diagnosis encoding and cross-mapping based on anatomic site component of the dynamic anatomy library, anatomy specific alerts, procedure specific alerts, insurance alerts (this case requires authorization) that automatically delivers the possible billing codes for which to seek authorization (based on the anatomic site component of the dynamic anatomic address, and automatic diagnosis category, and country-specific requirements), links to authorizations correspondences, and other information related to the anatomic site and this report. Once surgery occurs, the actual surgical photos automatically become part of this evolving report based on the anatomic site or pin ID components of the dynamic anatomic address. This powerful report collates all relevant health information regarding this anatomic site and diagnosis combination, automatically, over time. This is in contrast to current systems that have this information relevant to the anatomic site in fragmented databases, tables, tables, and even systems. Furthermore, the translation engines enable real-time, simultaneous, accurate translation and corresponding visualization for the evolving report in any coded, linguistic, or symbolic language.

[0036] FIG. 6 is an anatomic visualization 10 which has been automatically replotted based on the basal cell carcinoma shown in the evolving report in FIG. 5, updated with the correct diagnosis and diagnosis extension data blocks. The anatomic site name component 17 remains the same. The pin diagnosis 315 has dynamically changed to represent the pathology diagnosis, rather than the preoperative diagnosis. Context aware menus based on the pinpoint on a layered, multidimensional map are shown automatically to produce segmented form options 316 based on the dynamic anatomy library and the non-anatomy data. In this embodiment, the view of the nosewith basal cell carcinoma that was automatically plotted originated from a pathology report from a different lab on a different system and generates a dynamic form with the isolated diagram and map with information from the current user’s system. As one skilled in the art would know, Mohs maps documenting cancer mapping are drawn on with manual markup to represent different colors of tissue ink, so the pin visualization is intentionally omitted from the form selector 316 and the isolated segmented form selectors 312, but the enhanced linguistic description of the anatomic site is included on the Mohs maps. The form is filled in and marked up electronically or printed and physically marked up. Electronic and physical markup on paper can automatically be detected by a form processing engine and both the anatomy data and non-anatomy data is processed by engines for detection, categorization, encoding, translation, and labeling. Also depicted is a dynamic context menu 310 appears over the nose part of the face diagram to show different isolated segmentations 312 available to include in a dynamic form, in this case, a printed Mohs Map.

[0037] FIG. 7 is an exemplar of an automatically generated form 300. In the present embodiment, the form is a Mohs map used in micrographic dermatologic surgery. The form 300 contains a diagram, map, alerts, and country specific information all generated from the dynamic anatomy library and the non-anatomy data. Patient demographics, encounter demographics, information from the pathology report, diagnosis information, and diagnosis extensions are automatically filled in. A QR code (redacted) automatically links this form and other documentation, such as photos during surgery, to the correct dynamic anatomic address.

[0038] If this form is printed, augmented documentation workflows use computer vision to automatically detect, categorize, digitize, and place handwritten markup, apply it to the map, and attach it to the correct dynamic anatomic address in the correct position in the healthcare and encounter timeline. Anatomic site specific and procedure specific alerts and checklists are shown, with this one being related to the Mohs surgery on the nose. Electronic markup and form filling can also be done, shown by the drawing toolbar. This achieves seamless blending of paper anddigital workflows related to surgical documentation, and the QR code provides quick access to add photos to the correct dynamic anatomic address from any device, even one that is not logged in. In one embodiment, the patient can send photos from their own phone to the dynamic anatomic address. It is contemplated that the same concept can apply to other dynamic anatomic addresses as well, such as in telemedicine workflows.

[0039] Uses for such dynamic forms generated by the dynamic anatomy library and non-anatomy data include, but are not limited to: patient intake; consent forms 301 for procedures with outside observer view, mirror view, and relevant photos and can accept patient signatures digitally or on paper; mapping and documenting treatments and procedures with automatic calculation counting, translation, and coding, cross-linking of records, association with mapped regions of interest, anatomic sites; Mohs maps 300; cosmetic treatment records; automatically translated patient education handouts explaining how to use, and where to use medications (oral, topical, injectable, and other delivery methods); surgical whiteboards 302 that can be printed on paper or digital screens.

[0040] Digital screens pull up additional metadata associated with the surgery anatomic site in question, provide visual verification that a consent form was signed; include a timeline and photos associated with the anatomic site, path report associated with the surgery, and other health metadata. Automatic display of relevant information or alerts that needs attention in bold, different color like red (e.g., allergies) based on automated non-anatomy data extracted from patient info. As photos, multimedia, and other metadata are added to a patient record and dynamic anatomic address, for example with a different device like a phone, they automatically sync to the patient record and become visible on the digital whiteboard 302 in one embodiment.

[0041] It is contemplated the digital whiteboard 302 also responds to voice commands. Exemplar voice commands include:

[0042] “Hey Whiteboard, show me the pathology report’

[0043] “Hey Whiteboard, show me the digital slide”

[0044] “Hey Whiteboard, show me the pre-biopsy photo”

[0045] “Hey whiteboard, show me the future spots that need treatment”

[0046] “Hey whiteboard, show me the pre-operative photos.”

[0047] “Hey whiteboard, show me the shadow chart”

[0048] “Hey whiteboard, show me the consent form for today’s procedure”

[0049] “Hey whiteboard, send postoperative Keflex 500mg - take 1 pill twice daily for 14 days to Rite Aid on Central Avenue”

[0050] It is contemplated that the digital whiteboard 302, through voice command or other user input (touch, mouse, eye tracking), can document additional details and is language agnostic, responding to any language, including mixed languages like mixed Spanish and English language.

[0051] It is further contemplated that the digital whiteboard 302 can also speak alerts back to user, for a conversational update to the record or treatment plan: “You asked me to send Keflex, and there are 2 interactions and patient has a reported history of allergy to penicillins. Would you like to select an alternative?”

[0052] It is further contemplated that the digital whiteboard 302 can load a patient through a QR code from a paper, wrist band, or electronic display, can load the correct patient through patient RFID tracking, facial recognition, or through other verification means (e.g., fingerprint) to ensure the whiteboard is displaying the correct patient information.

[0053] It is further contemplated that the paper or digital whiteboard 302 can be used in a verbal timeout procedure; and automatically log the time out. Commands can be interpreted in any linguistic language, and document on the correct dynamic form version and correct anatomic location and visualization.

[0054] FIG. 8 further depicts hierarchical painting that includes treatment recommendations 90 associated with the specific anatomic sites generated by a user for a particular patient in a particular encounter 18. Patients often receive multiple recommendations, sometimes with ten or more products listed, and can understandably get confused on what to use, where, and when. Visual hierarchical painting through mapping with anatomic site or site group descriptions can help to color code this information in an easily digestible format for the patient, in any language and creates a visual map of recommendations. It is contemplated that recommendations could build upon each other in areas of overlap. It is further contemplated that clinicians can stamp their recommendations or highlight areas for where to apply their recommendations on standardized maps or directly on patient images creating a personalized visual map of recommendations with simultaneous condensed and simplified translated text descriptions of “what to use where” on their body.

[0055] Workflow of associating anatomic sites and regimens can flow in either direction. A user can assign a color to an anatomic site, then add products, treatments, and recommendations to the painted anatomic sites. Conversely, products could be assigned a color and then the products could be painted onto the avatar. Anatomic areas are defined by area names and colors. It is contemplated that when recommendations are asymmetric, the visualizations and sites can be plotted from the outside observer perspective by the physician, and viewed in a mirror perspective by the patient to enhance patient understanding.

[0056] FIG. 9 depicts an exemplar output 90 with the treatment recommendation 90 for the anatomic site 18. It is contemplated that the output can be printed, digital, or both, with relevant isolated visual previews as well. It is contemplated that regimen mapping can be applied to treatment mapping as well, such as documenting different types of cosmetic procedures or settings. It is further contemplated that printed outputs could be made into labels and then affixed directly to the container for products, including over the counter products, to better instruct the patient how and where each product should be used to minimize confusion particularly when thereare multiple products being used at different times of day. Printed physical labels inform a patient about the product regimen such as, how to use it, where to use it, frequency, warnings, and more. It is contemplated that emoji labels can also be utilized to communicate how the patient should use the medication. For example, a pill could show a mouth with a cup of water to indicate it should be taken with orally, a pill and a food emoji could indicate it should be taken with food, or a pill with a no sign and a cheese emoji could indicated avoid diary when taking.

[0057] FIGs. 10 and 11 depict an electronic regimen map 100 with printable labels 102 and affiliated educational instructions 105, respectively. In the current embodiment, the educational instructions 105 provide visualizations by product, by area, and by condition. While a paper workflow generates a digestible report that can be handed to the patient; the electronic regimen can be saved into the patient’s chart for tracking the regimen over time and initiation of other workflows. The electronic regimen can evolve over time, with input from the patient and the professional, in their preferred language. It is contemplated, in an electronic evolving regimen, the patient could give feedback on a product, report a side effect from a product, initiate a refill request for a product, find up to date manufacturer’s coupons for a product, view product recall information, ask their professional about the product, report stopping the product, report starting a new product, or other electronic tasks. It is further contemplated that automatic alerts could be sent to the patient and physician if there is a product recall and automatic reminders could be sent to the patient if they are expected to be running low. From the electronic regimen, when there are office-dispensed products recommended, a single link could add all the office-dispensed products that are in stock to a ticket system with real-time pricing update for the patient to initiate a purchase and the patient could also purchase remotely for products from the office / retail facility.

[0058] In one embodiment, products can be registered including information including but not limited to: photo, product name, product ingredients, product SKU, product category in user country (Rx, office dispensed, OTC), product vehicle, product warnings, product directions, product suggested frequency, product side effects, product anatomic sites to avoid, productrecommended anatomic sites, product substitutes, product key recommended ingredients, product active ingredients, product availability in user country, product synonyms, and other product metadata. A patient can then select a product that was already recommended, from the global product library, from the localized product library (e.g., based on country), or from their custom / favorite library of products. Automatic product recommendations and warnings will populate based on user preferences, patient condition, user frequency of selection, patient allergies or adverse reactions, patient interactions with other medications or conditions, patient has tried product already and failed, product availability (backordered, discontinued, banned in this country / region, etc.), substitutions, and other metadata. The patient can then print a physical label with a product image / thumbnail and the regimen for easy correlation and visual recognition by the patient. A product thumbnail can be expanded to show other metadata about the product on the electronic regimen.

[0059] The foregoing descriptions of specific embodiments of the present invention are presented for purposes of illustration and description. They are not intended to be exhaustive nor are they intended to limit the invention to precise forms disclosed and, obviously, many modifications and variations are possible in light of the above teaching. The embodiments are chosen and described in order to best explain principles of the invention and its practical application, to thereby enable others skilled in the art to best utilize the invention and its various embodiments with various modifications as are suited to the particular use contemplated. It is intended that a scope of the invention be defined broadly by the drawings and specification appended hereto and to their equivalents. Therefore, the scope of the invention is in no way to be limited only by any adverse inference under the rulings of Warner-Jenkinson Company, v. Hilton Davis Chemical, 520 US 17 (1997) or Festo Corp. v. Shoketsu Kinzoku Kogyo Kabushiki Co., 535 U.S. 722 (2002), or other similar caselaw or subsequent precedent should not be made if any future claims are added or amended subsequent to this patent application.

Claims

CLAIMSWhat is claimed is:

1. A computer-implemented method for generating dynamic forms for medical records comprising: inputting, using a processor, anatomy data relating to a medical record; creating a dynamic anatomy library of templates wherein the library of templates comprises a plurality of anatomic diagrams, images, and / or hierarchical, layered, custom-coordinated, corresponding maps which include targeting sites of interest and additional visualizations representing anatomic site of interest; wherein the anatomic site of interest is isolatable on a layered, hierarchical map and / or visualizable in relation to the borders of each isolated anatomic site above, below, and on the same level, along with translated human readable descriptions of the anatomic site of interest position relative to each layer; inputting, using a processor, non-anatomy data relating to a medical record; translating the dynamic anatomy library of templates and the non-anatomy data with the dynamic form generation and translation engine to generate dynamic forms wherein the dynamic forms may include anatomic images, diagrams, maps, encoding, descriptions, translations, and / or labeling anatomic sites as well as patient, diagnosis, and / or encounter information; transforming the dynamic forms with targeted isolation, segmentation, and / or coloring of anatomic images, anatomic maps, points of interest, and / or regions of interest; wherein the targeted isolation, segmentation, and / or coloring of each layer of the hierarchical map provides simultaneous visualization, translation, descriptions, and visual selection points for a visual, translated hierarchical travel and / or selection method.

2. The method of claim 1, wherein the anatomy data is user input and / or record input.

3. The method of claim 1, where the anatomy data is a point on a layered map, reference to point or region on a map, description of the anatomic site, coordinated description of the anatomic site, and / or an image of the anatomic site.

4. The method of claim 1, wherein the dynamic anatomy templates are available in unadjusted and mirrored axes.

5. The method of claim 1, wherein the hierarchical, layered, custom-coordinated, corresponding maps are complete avatars.

6. The method of claim 1, wherein the hierarchical, layered, custom-coordinated, corresponding maps are segmented and / or isolated anatomic areas of interest.

7. The method of claim 1, wherein the anatomic site of interest is a pin and / or an area.

9. The method of claim 1 , wherein the non-anatomy data is user input and / or record input..

10. The method of claim 1 , wherein the non-anatomy data is patient demographics and information, encounter demographics and information, diagnosis, diagnosis extensions, patient country, user country, geographic location, patient language, user language, procedure, treatment, symptoms, morphologies, images, multimedia, reports, and / or other health data11. The method of claim 1 , wherein the dynamic forms contain the inherent ability to re-create, translate, cross-map, plot, map, visualize, and / or encode anatomy data and non-anatomy data.

12. The method of claim 11 wherein a QR code less than one inch in size can recreate anatomy data and non-anatomy data.

13. The method of claim 1 , wherein the dynamic forms are printable forms.

14. The method of claim 13, wherein the printable forms are automatically filled in by the dynamic form generation and translation engine with relevant data.

15. The method of claim 13, wherein the dynamic forms are supplemented with detectable anatomic diagrams, surgical whiteboards, and checklists that contain visual representations of the anatomic site16. The method of claim 1 , wherein the dynamic forms are electronic forms.

17. The method of claim 1 , wherein the dynamic forms automatically account for geographic, country, and language considerations.

18. The method of claim 1 , wherein the targeted isolation provides visualization, translation, descriptions, and visual selection points for a visual, translated hierarchical travel and / or selection method19. A computerized electronic system for generating dynamic forms for medical records configured to: receive anatomy data input; create a dynamic anatomy library of templates wherein the library of templates comprises a plurality of anatomic diagrams, images, and / or hierarchical, layered, custom-coordinated, corresponding maps which may include targeting sites of interest and additional visualizations representing anatomic site of interest; receive non-anatomy data input; translate and transform the dynamic anatomy library of templates and the non-anatomy data with the dynamic form generation and translation engine to generate dynamic forms wherein the dynamic forms include anatomic images, diagrams, maps, avatars, and descriptions as well as patient, diagnosis, and / or encounter information; display the generated dynamic form on a graphical user interface wherein the generated dynamic form compiles anatomy data and non-anatomy data for the anatomic site of interest into a comprehensive dynamic record.

20. The system of 19 wherein the display shows a visualization of anatomic sites and site segments relative to different layers and hierarchical levels, with simultaneously translated descriptions.

21. The system of 19 wherein the visualization depicts the anatomic point of interest in different layers and hierarchical levels, with simultaneously translated descriptions.

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