WO2023156809A2 - Graphiques fantômes pour collationner et interagir avec des dossiers médicaux passés, présents et futurs - Google Patents

Graphiques fantômes pour collationner et interagir avec des dossiers médicaux passés, présents et futurs Download PDF

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Publication number
WO2023156809A2
WO2023156809A2 PCT/IB2022/000823 IB2022000823W WO2023156809A2 WO 2023156809 A2 WO2023156809 A2 WO 2023156809A2 IB 2022000823 W IB2022000823 W IB 2022000823W WO 2023156809 A2 WO2023156809 A2 WO 2023156809A2
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WIPO (PCT)
Prior art keywords
shadow
data
chart
information
anatomic
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PCT/IB2022/000823
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English (en)
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WO2023156809A8 (fr
WO2023156809A3 (fr
Inventor
Matthew A. Molenda
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Mofaip, Llc
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Priority to PCT/IB2023/000535 priority Critical patent/WO2024023584A2/fr
Priority to US18/225,872 priority patent/US20230368878A1/en
Publication of WO2023156809A2 publication Critical patent/WO2023156809A2/fr
Publication of WO2023156809A8 publication Critical patent/WO2023156809A8/fr
Publication of WO2023156809A3 publication Critical patent/WO2023156809A3/fr

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    • G—PHYSICS
    • G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
    • G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
    • G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data

Definitions

  • This invention relates to medical systems, and more particularly, to collating and interacting with health records.
  • the manual collation, presentation, and updating of information takes various trained staff people to perform these processes correctly, and it takes significant human capital to perform these tasks. Training gaps, education gaps, and inconsistencies in workflows also compound to increase human error and omission in performing the current systems’ manual tasks of collating and updating to the patient record.
  • the present invention reduces the time spent by medical assistants, scribes, and healthcare workers on manual collation and updates of healthcare data by automatically collating, displaying, and allowing interaction with past, present, and future health information in different applications, systems, and formats. Manual collation and addition of data can also occur in a unified shadow chart system that blends paper and digital data.
  • the present invention uses health data in digital shadow charts, paper shadow charts, or both to create a comprehensive record and to seamlessly blend paper and electronic documentation.
  • the charts automatically collate past, current, and future healthcare data that are automatically linked to anatomic maps and healthcare metadata for visualization, modification, augmentation, and automation of healthcare record generation, and retrieval.
  • Shadow charts collate and display information from dynamic anatomic addresses, data blocks and metadata blocks on an anatomic map translated to user language, with recreated anatomic sites and health data.
  • Automated workflows such as prescription refills, suggested diagnostic tests, flag areas of concern for follow up, etc. are included on the shadow chart.
  • Digital markup and workflow initiation on a digital shadow chart is done in real time, and physical markup on a paper shadow chart may be done in real time with certain devices like a pen that tracks position on paper or after the fact with a photographic or scanned capture of the marked-up paper shadow chart.
  • Computer vision can interpret the markups and account for any changes and the content can then be synchronized in the record in the plurality of appropriate locations, databases, and systems for the data.
  • the user can be alerted to any discrepancies upon after-the-fact synchronization, and is automatically prompted to reconcile them.
  • points of interest can be retired, selectively turned off, filtered, or selectively served based on manual interaction, user preferences or automatically using user or organizational settings.
  • the shadow chart can have features from past historical visits, deferred diagnosis or treatments or issues needing follow-up or more information, or other issues related to the patient. Additionally, it can have information about past encounters (like history, medication list, prior prescriptions, prior medical or cosmetic treatments or recommendations, prior purchases), about the current encounter (like name, date of birth, medical record number, date of service, appointment demographics, patient demographics, doctor/hospital demographics, insurance demographics, financial info), future encounters (like future appointments already scheduled, collated from a variety of databases and systems) or suggestions for future appointments, treatments, products or services.
  • past encounters like history, medication list, prior prescriptions, prior medical or cosmetic treatments or recommendations, prior purchases
  • about the current encounter like name, date of birth, medical record number, date of service, appointment demographics, patient demographics, doctor/hospital demographics, insurance demographics, financial info
  • future encounters like future appointments already scheduled, collated from a variety of databases and systems
  • the shadow chart can contain anatomic maps and images representing relevant past, current, and future information from the patient records which can be printed on paper in the user’s preferred color scheme, including but not limited to grayscale, black and white, bluescale, color, a defined color palette for color coding, in a combination of monochrome and color, or in any other contemplated color scheme as one skilled in the art would know.
  • Historical information e.g., diagnoses, treatments, follow-ups needed
  • that are associated with an anatomic site will be automatically made visible on an anatomic map representing their locations.
  • the anatomic maps on the shadow chart can be derived from anatomic site names and coordinates in two- or three dimensions, or in four-dimensions by showing changes over time. These can then be presented to the user in any dimension, as three-dimensional maps with the appropriate views or two-dimensional maps that can be printed containing the relevant information, or can be interacted with in a digital shadow chart (like rotating a three-dimensional model representing a time point or blended time points).
  • the shadow chart can automatically place different historical contexts into different sequences.
  • a skin cancer history of past treated skin cancers could be shown in sequence 1, 2, 3... while a list of skin cancers that are deferred and still needing treatment could be shown in 01 , 02, 03... order, while a list of prior biopsies that the user needs to deliver results on can be presented as a, b, c... , while the list of new ordered procedures created for that encounter can be delivered as A, B, C; while still other items can be sequenced based on dates, order of reports, order of entry, or other user sequence preferences that may be desired.
  • a square could be a checkbox associated with an anatomic site with the results listed next to it, indicating that when the user places a checkmark in the box, the system automatically documents that they provided the patient their results, answered their questions, and finished with that task.
  • a legend for each sequence could provide more information available for both the digital and paper shadow chart.
  • the digital shadow chart could pull up additional information, such as past photos, reports, and other multimedia associated with the charted items on a shadow chart. Based on user preference or selection, the additional information associated with the shadow chart could be easily retrieved for viewing or printing.
  • a paper shadow chart that contains mapped and charted items can also be modified electronically, before, during, or after an encounter with a patient; or before, during, or after printing.
  • a shadow chart can have various protocols loaded for certain commonly performed tasks/procedures. For example, for an annual physical, the map may be pre-populated with pins to locations where a part of the examination is to occur. Each pin can be customized to accept the data relevant for the particular examination task, or in a paper version, provide an area to accept the relevant data. Protocols and/or the data within can be toggled on/off to be visible on the digital shadow chart.
  • a paper shadow chart aimed at consolidating and collating context-aware information about the visit, can be marked up in a different color. For example, on a black and white printout of the shadow chart that contains a grayscale anatomic map, a user can create a markup in blue pen, erasable red pen, colored pencil, marker, colored stamps, or other forms of markup as one skilled in the art would know.
  • the color or stroke-width differential or handwriting detection from the markup can be used to detect changes and additions to the shadow chart.
  • a digital photo or scan of the shadow chart automatically can create a digital version with the updated, added, or deleted information.
  • the information can further be augmented with additional material such as with live capture of photo, multimedia, or attachments; association of prior photos, multimedia, or attachments; and/or addition/modification/deletion/moving/re-categorizing of information). Those changes and additions can then be applied across the various data systems (electronic health record, scheduling system, practice management system, billing system).
  • the shadow chart can filter records to show relevant past diagnoses and treatments.
  • the shadow chart can pull all instances of past precancerous actinic keratoses that were documented as treated and show them on an anatomic map with dates of treatment, photos or multimedia, path reports showing it was a biopsy proven at one point in time, and other clinical data.
  • the shadow chart can visually help determine if the lesion concerning for squamous cell carcinoma is a new lesion, or if it has progressed from a prior pre-cancerous lesion. This is just one of a plurality of examples relevant to diagnoses and treatments, and it is contemplated that filtering can be applied to other health data as one skilled in the art would know.
  • the user could also choose to permanently alert the user of an important history with options like “Always show on shadow charts”. Conversely, if a matter is resolved permanently the user could omit the history from future shadow charts “Resolved - hide from future shadow charts” BRIEF DESCRIPTION OF DRAWINGS
  • FIG. 1 is a flowchart illustrating information management by the system.
  • FIG. 2 is an exemplar shadow chart.
  • FIG. 3 is an enlarged view of a portion of the shadow chart in FIG. 2.
  • FIG. 4 is an enlarged view of an alternate portion of the shadow chart in FIG. 2
  • FIG. 5 is a captured image of an annotated and marked up version of the shadow chart in FIG. 2.
  • FIG. 6 is an enlarged view of a portion of the capture from FIG. 5.
  • FIG. 7 is an enlarged view of an alternate portion of the capture from FIG. 5.
  • FIG. 8 is a screenshot showing FIG. 6 converted to a digital record.
  • FIG. 9 is a screenshot showing FIG. 7 converted to a digital record.
  • FIG. 10 is an exemplar printed shadow chart showing color annotations.
  • FIG. 11 is a screenshot showing FIG. 10 converted to a digital record with correlating diagnoses based on color detection.
  • FIG. 12 is a screenshot showing FIG. 10 converted to a digital record with correlating diagnoses based on color detection automatically translated to English.
  • FIG. 13 is a screenshot showing a visual alert on a shadow chart.
  • FIG. 14 is an enlarged view of FIG. 10 depicting the Chinese laterality labels.
  • FIG. 1 is a flowchart illustrating the information management in the system 400, specifically how digital and paper shadow charts interact with past, present, and future data to create a comprehensive record.
  • Context aware data 200 a user wishes to incorporate into an electronic medical record or into shadow charts includes any data relevant to the medical record and can be anatomy data 211 and/or non-anatomy data 212.
  • the anatomy data 211 and non-anatomy data 212 are placed into appropriate places into a digital shadow chart 213.
  • the digital shadow chart 213 can then be directly printed into a paper shadow chart 214 or modified in electronic form with different selections, filters, and interaction modifiers 215.
  • filters could include, but are not limited to, diagnoses and history relevant to the practitioner, specialty, procedures, morphologies, symptoms, treatment recommendations, or anatomic sites of interest.
  • an updated paper shadow chart 214 may be printed.
  • other dynamically created paper labels and forms 216 could be created and printed.
  • Paper shadow charts 214 and dynamic forms and labels 216 may be scanned or captured with a camera through image capture and processed through computer vision 220.
  • Paper shadow charts 214 may contain anatomy visualizations and areas of non-anatomy data that can be marked up, filled in, labeled, annotated, colored, and/or drawn on.
  • the image capture of the paper shadow chart 214 processed through computer vision 220 can remove artifacts such as physical shadows or pixilation or blurs, detect orientation and alignment, detect anatomic sites and their descriptions and relationships, normalize axes, and detect, categorize, and place the compiled data 250 into the correct digital locations in the electronic record.
  • the compiled data 250 may be context aware data modification, new records, and/or initiated workflows.
  • a paper shadow chart 214 could be a pathology requisition form that contains a list of biopsy sites with anatomic site descriptions and isolated visual previews of the anatomic sites that also includes physical label printing which can be placed onto physical biopsy specimens.
  • Such labels may contain anatomy information, patient information, and anatomy visualizations and may recreate a digital anatomic map and points.
  • a template could be a paper Mohs map that contains anatomy data, anatomy visualizations, non-anatomy data, and blanks to be filled in.
  • the chart is processed and categorized with computer vision 220 and the compiled data 250 is placed into the electronic record which is now modified based on the context aware data.
  • the electronic record components can then be further modified through selection, filters, and interaction modifiers 215. This process creates “augmented documentation.”
  • a paper shadow chart 214 is scanned and processed with computer vision 220 and digital photographs are linked to the anatomic sites documented on the paper shadow chart 214 thereby augmenting the electronic record and the compiled data 250 is modified based on the context aware data.
  • a shadow chart is processed with computer vision 220 which detects the chart language as English, the patient sex as male, the documented patient encounter date, and the practice specialty as dermatology. These detections created the compiled data 250 which updates the electronic record with the context aware data modification.
  • a dermatology diagnosis is resolved and the compiled data 250 triggers the removal of the diagnosis from the dermatology record modifying the record in light of the new context.
  • a paper shadow chart 214 is scanned and processed with computer vision 220 which detects a new patient encounter, an encounter date, and annotations and markups on specific anatomic locations and the compiled data 250 generates a new record from the detections.
  • a checkbox is checked on the paper shadow chart 214 indicating a medication refill is necessary.
  • the paper shadow chart 214 is scanned and computer vision 220 detects the checked box and initiates the workflow 250 to automatically refill the medication and document the refill on the electronic record.
  • the compiled data 250 can also modify or be modified by the data in the context aware data 200.
  • context aware data 200 may be comprised of: (i) practitioner information 201 ; (ii) patient demographics 202; (iii) encounter information 203; (iv) patient history 204; (v) results and reports 205; (vi) schedule calendar data 206; (vii) multimedia and images 207; (viii) financial and billing data 208; (ix) cosmetic and purchase data 209; and (x) other relevant data 210 not described elsewhere, as one skilled in the art would know.
  • Practitioner information 201 examples include clinic name, clinic location, practice specialty, physician or healthcare provider data, practice type such as surgery or medical, and other information as one skilled in the art would know. This allows for granular data filtering. In one embodiment, a physician can filter to only see shadow charts with content relevant to their specialty or only records generated by them.
  • Patient demographics 202 includes but is not limited to patient name, nickname, date of birth, patient address, patient identifiers like medical record number and/or social security number and/or license number, married name, emergency contacts, e-mail address, patient portal information, power of attorney, acceptance of policies, credit card on file status, insurance information, patient specific notes, and other information as one skilled in the art would know.
  • Encounter info 203 contains information about the reason for appointment, what was or is being or will be addressed at an appointment, who referred the patient for this encounter, encounter date, encounter time, encounter location (place of service), encounter location type (outpatient, inpatient, telemedicine), and other information as one skilled in the art would know. Further encounter information 203 may be for past, present, or future encounters.
  • Patient history 204 includes but is not limited to past diagnoses, past symptoms, past medications, active medications, past treatments, allergies, family history, past surgeries, anatomic location associated with any of the history data components, and other information as one skilled in the art would know.
  • Results and reports 205 includes but is not limited to pathology reports, blood tests, imaging reports, and statuses about the reports. For example, if a patient has been counseled on the result or if treatment has been performed or needs to be performed. Reports may also be related to imaging studies like radiographic studies including x-rays, CT scans, MRIs, ultrasounds,
  • Schedule calendar data 206 includes but is not limited to information about past, present, and future appointments, results, reports, progress notes, treatment summaries, images, and other data. It is contemplated that temporal data can be specific to date, time, and time zone or a combination of these, and that the temporal data can be arranged into a plurality of timeline views.
  • Multimedia and images 207 includes but is not limited to photos, images, videos, diagrams, and other multimedia that contain anatomic sites. The sites can be labeled as part of the multimedia or image metadata, or detected from the images and multimedia.
  • the multimedia and images 207 may also be from image related studies like radiographic studies including x- rays, CT scans, MRIs, ultrasounds, PET scans, and their variants. Additionally, it is contemplated that the shadow chart can directly link to the view of interest, such as a tumor in a CT scan at the correct zoom level and slice level.
  • Financial and billing data 208 includes but is not limited to billing codes relevant to a particular country or region, insurance information, eligibility checks, deductibles, coinsurance, patient balances, copay status and amount, credit history, credit card on file status, and other financial and billing data relevant to the delivery and payment for health care that one skilled in the art would know.
  • Cosmetic and purchase data 209 includes information about cosmetic or self-pay treatments such as laser surgery, cosmetic surgery, skin tag removal, retail purchases such as skin care, filler, botulinum toxin, and other injectable cosmetic treatment mapping, and other data that one skilled in the art would know. It is contemplated that treatment recommendations may include visual and descriptive regimen maps that explain “what products to use where” on the body with color coding on different anatomic distributions and may be for cosmetics and/or prescription, over-the-counter, and non-topical recommendations. In one embodiment, cosmetic and purchase data 209 for different settings for laser treatment could be mapped on a shadow chart. It is further contemplated that the information can be recreated or modified within the shadow chart.
  • automatic treatment recommendations based on timing can also be applied, for example that a patient’s botulinum toxin treatment should have worn off by now and the patient is due for another treatment, and the number of units used in the last treatment can be shown on the shadow chart.
  • a plurality of templates related to cosmetic treatment and follow up is possible as one skilled in the art would know.
  • Anatomy data 211 includes but is not limited to visualizations, diagrams, dynamic anatomic addresses that are trackable multidimensional locations through space (spatially relative to two-dimensional or three-dimensional anatomy) and time (fourth-dimensional anatomy), coordinates, site descriptions, hierarchical anatomy relationships, coordinated anatomy elements, uncoordinated anatomy elements, anatomy modifiers, coded descriptions of anatomy, linguistic descriptions of anatomy, symbolic descriptions of anatomy, mixed descriptions of anatomy, custom descriptions of anatomy, relational data between different anatomic sites, photographs of anatomy, maps of anatomy, localized or migrating findings (such as symptoms or morphology), anatomy specific recommendations (such as what topical treatments to use where on body), imaging containing anatomy, reports containing anatomy, notes containing anatomy, multimedia containing anatomy, and other anatomy data as one skilled in the art would know.
  • Anatomy data 211 can be used to create collation points for records from various sources and types on a shadow chart.
  • a broken bone emoji could be placed on the location of a fracture, and x-rays and imaging and their reports from different time points would automatically collate into that emoji in a digital shadow chart 213.
  • Anatomy data 211 is also data that is associated with anatomic sites, anatomic distributions, anatomic distribution intensity, visualizations, points on maps, photographs and imaging of anatomic sites, reports and records linked to anatomic sites, prescriptions and recommendations linked to anatomic sites, appointments and/or plans linked to anatomic sites, dynamic anatomy addresses that track anatomic sites, and other anatomy data.
  • An anatomic site might be a “right knee” in a patient with a history of an artificial knee replacement.
  • An anatomic distribution example is the “face, back, and chest” for a diagnosis of acne with the acne intensity being worst on the face followed by the back followed by mild involvement on the chest (face>back»chest).
  • Non-anatomy data 212 includes but is not limited to patient demographic information, nonlocalized findings, diagnoses, and conditions such as hypertension or fatigue, encounter and schedule demographic information, billing and financial information, non-anatomic information associated with records containing anatomy data, blood tests and other non-anatomy data. It is contemplated that blood tests can also be part of anatomy data when dealing with organ systems and functional systems, such as the hematopoietic system, and when describing the anatomy of blood cells under the microscope such as macroblastic or microblastic features of red blood cells. It is further contemplated that microscopic and dermatoscopic anatomy and morphology can also belong to both anatomy data and non-anatomy data. Additional non-anatomy data would also fall into this category as one skilled in the art would know.
  • FIG. 2 is an exemplar shadow chart 213 that contains past, present, and future information.
  • the shadow chart shows shadow pin descriptions 30 that are context aware diagnoses and data in light gray text.
  • Representative demographic information 10 including patient and encounter demographic information such as the patient name, date of birth, medical record number, and date of service, is shown on top left of the paper shadow chart 214.
  • shadow pins 20 for visualizations of skin cancers that still require treatment located at their anatomic locations.
  • the sequence begins at “01” and the shadow pin descriptions 30 indicate the diagnosis, the visualized anatomic location, and future information regarding the future appointment for Mohs surgery.
  • Each shadow pin 20 is on a specific anatomic site, and has a description 30 of past, present, and future information associated with it.
  • the shadow chart 213 shows shadow pin descriptions 30 that are context aware diagnoses and data in light gray text.
  • the shadow pin description 30 for the first visualization in the sequence reads “01 - Infiltrative BCC - biopsy date 2017-12-03, path #49234-B, refused tx” which tells the reader the following clinically relevant information about this shadow pin: (i) that it is in the list of skin cancers still needing treatment, and its position in the list based on the “01” designation, (ii) a visualization of the anatomic location based on the shadow pin 20 position, (iii) a diagnosis “Infiltrative BCC,” (iv) the procedure date for the original biopsy “biopsy date 2017- 12-03,” (v) the pathology result number “49234” and order on the pathology report “B”, and (vi) that the patient has not had it treated and is refusing treatment “refused tx.” It is contemplated that a reproducible and trackable anatomic site description accompanies each shadow pin 20, and that relevant
  • colors including differential colors (such as pin fill or pin drop being a different color than a pin label, or two different distributions painted that are different colors), can help to organize visualizations and inputs and categories of both shadow and new documentation.
  • shadow pins that are light in color, such as on paper can be filled in with a darker color to indicate to add the documentation to the present electronic chart, and that such addition will happen automatically with computer vision detection.
  • Shadow pins 20 that are selected on a digital shadow cart can also be edited, updated, moved, merged, hidden, deleted, converted, or expanded.
  • a digital shadow chart 213 has significantly more information readily available by tapping or hovering over the shadow pin 20 or pin label 30 to for example pull up a timeline of information associated with the anatomic site or pin, or with other user interface interactions that one skilled in the art would know.
  • FIG. 3 shows a magnified portion of the shadow chart 213 of FIG. 2.
  • a shadow pin description 30 for the second visualization in the “01 , 02, 03” sequence reads “02 - Invasive SCC - biopsy date 2019-12-09, path #DF9N-A, Mohs scheduled for 2019-12-18.” From this context aware shadow pin 20 and pin description 30 we know the anatomic location in a visualization, the diagnosis and details relative to the diagnosis like the biopsy date, the pathology report information, as well as future information about a scheduled appointment. It is contemplated that one skilled in the art would recognize that this represents data about the future, specifically appointment data and data on what is to be treated in the future, and that other future data could be added on a shadow chart as well.
  • FIGs 2 and 3 show workflow initiators 40 depicted at the end of shadow pin descriptions 30 as well as directly next to shadow pins 20.
  • Workflow initiators 40 relevant to a diagnosis can be used on both paper and digital shadow charts.
  • On paper shadow charts the workflow is initiated after computer vision detection of a check in the box.
  • On digital shadow charts the workflow is initiated upon checking the digital checkbox.
  • FIG. 1 In the embodiment depicted in FIG. 1
  • a workflow initiated by a workflow initiator 43 is a new documentation update for a diagnosis that includes a list of medications associated with the diagnosis where a refill of a medication is automatically sent or queued to the patient’s preferred pharmacy, and all of the documentation related to that workflow is automatically documented in the electronic health record in the relevant sections (diagnosis, progress note, refills, medication lists, etc.). Also depicted in FIG. 3, the workflow initiator 44 that appears directly next to or otherwise related to the shadow pin (instead of after the description like workflow initiator) provides visual differentiation and indicates that they are different workflows.
  • checking the workflow initiator 44 that appears directly next to the shadow pin could document that results for a test were discussed with the patient, and the diagnosis, treatment plan, counseling templates and other templates could be automatically input into the patient's electronic health record and associated with the reproducible anatomic location as determined by the shadow pin 20.
  • shadow pins 20 may have different sequences and labeling types to indicate different list memberships. It is further contemplated that color grouping, pin type changes, and order type changes can help further visually differentiate shadow information (e.g., A, B, C is different than 1 , 2, 3 is different than 01 , 02, 03 is different than a, b, c is different than i, ii, iii).
  • a shadow pin description for a shadow pin with a different sequence 60 reads as “2 - Hx BCC - tx with Mohs 2013-06-04, closed with bilobe flap.”
  • the list sequence type, shown here as “2” in a “1 , 2, 3” type sequence, is different from the previously discussed “01 , 02” sequence, and indicates historical past treatment information in this exemplar.
  • a shadow chart can also accept new inputs, for example, on an unmarked diagram and anatomic map 70 as well as on diagrams and maps that already contain shadow information. New inputs could be writing or coloring annotations and markup on paper, or digitally placed annotations and markup on a digital shadow chart.
  • Orientation and axis normalization markers 80 are automatically included on printed shadow charts 214 and included with any diagram or map or form field. These normalization markers 80 allow forms and diagrams to be printed in any size and on any size of paper and that computer vision can properly detect and place or update detections into the correct digital entry points on forms, on maps (on “land” in a geographic context or corollary) and on whitespace between diagrams when there are multiple (in the “sea” in a geographic context or corollary).
  • Each shadow form chart has a coded indicator 90 about the form, such as a QR code, that provides details of the form version, form language, form context, user preferences (e.g., how to interpret the markup and annotation), map and diagram properties, digital fields the form maps to, patient and demographic information, and other information that one skilled in the art would know.
  • a coded indicator 90 about the form such as a QR code, that provides details of the form version, form language, form context, user preferences (e.g., how to interpret the markup and annotation), map and diagram properties, digital fields the form maps to, patient and demographic information, and other information that one skilled in the art would know.
  • a shadow chart can be automatically modified based on patient characteristics.
  • male anatomy 100 is shown, but female anatomy has been filtered out to create whitespace 110 on the shadow chart.
  • the whitespace 110 could allow for non-anatomy information to be placed on a paper shadow chart.
  • the whitespace 110 can be available on a digital shadow chart when consistent workflows and visualizations are desirable.
  • the whitespace 110 and that illustrated patient characteristics assist the computer vision in determining and verifying the patient characteristics, such as patient sex or whether diagnoses or findings related to oral anatomy are included in the form context.
  • the oral anatomy 102 patient characteristic has been included in the shadow chart with an automatically included workflow initiator 40 and shadow pin 20 and context aware pin description 30.
  • shadow charts can have meaningful laterality abbreviations and symbols, depicted here in FIGs 2 and 4.
  • Context, language, and perspective aware laterality labels 120 are shown with the “R” indicating the right side of the patient in an outside observer perspective, and the “L” indicating the left side of a patient in an outside observer perspective.
  • Such laterality markers 120 in the present embodiment show the diagrams from an outside observer perspective.
  • the lateralities and modifiers (such as those describing directional modifiers like superior, lateral, medial, inferior) of anatomy can be selectively reversed into a mirror view or “selfie view” to accommodate a shadow chart that the patient can more easily perform self-documentation and self-updates on, in paper, digital, or both formats.
  • the “L” would be replaced with “R” and the “R” would be replaced with “L” in English, on select views where such mirroring makes sense.
  • all views do not have to be switched simultaneously, and they can be selectively or individually switched in perspective; and both perspectives can be shown simultaneously in different use cases.
  • such labels could be language aware. For a user preferring Spanish, for example, the laterality labels would automatically display as “D” for derecho instead of “R”, and “I” for izquierdo instead of “L.”
  • diagrams and maps on shadow charts can contain automatic past, present, and future interaction points, but can also simultaneously serve as present interaction areas for markup and annotation, including drawings and different color schemes, legends, and dictionaries based on context and user and organizational preferences.
  • filters and user interaction prior to paper shadow chart printing could modify what is shown on the shadow chart.
  • digital shadow charts can dynamically apply filters, view changes, and display additional information, tools, markup, and annotations; and that one skilled in the art would understand additional applications for this technology.
  • FIG. 3 shows a workflow initiator 43 at the end of a pin description 30 to send a refill on a medication.
  • the workflow initiator 43 is currently unchecked.
  • a user could initiate the medication refill by checking the box. Checking the box on a digital shadow chart would automatically refill the medication and document the refill on the electronic record. Alternately, if checked on a paper shadow chart, computer vision could detect the checkmark on the image capture and automatically refill the medication and document the refill on the electronic record.
  • An alternate workflow initiator 44 shown before a pin 20 and pin description 30 represents a different type of workflow for automatically documenting and tracking counseling on a new pathology result in electronic health record.
  • FIG. 4 shows a portion of an anatomic diagram 70 does not contain any shadow pins or shadow documentation such as distribution mapping.
  • the same anatomic diagram, representing the back of the body, contains a shadow pin 20 and a context aware description 30.
  • the shadow chart In digital format, the shadow chart has interactive components associated with the pins, pin descriptions, anatomic sites, labels, distribution segments, shapes, and other digital components that a user can use to update the electronic medical record with relevant information.
  • the shadow documentation can be interacted with, and the portions of anatomic diagrams that do not contain shadow pins or shadow documentation can be marked up and annotated.
  • FIG. 5 is an exemplar captured image 150 of an annotated and marked up paper shadow chart, containing artifacts from capture like perspective warp artifacts and a light-created shadow artifact 141. These undesired artifacts can be accounted for and ultimately resolved when the captured image 150 is analyzed with computer vision.
  • the paper orientation and normalization of the axis is also accomplished as the computer vision can detect the normalization markers 80 and the resulting digitized version will have perspective correction, adjusted rotation, and unwanted artifacts removed.
  • the present exemplar contains numerous new markups, annotations, shadings, workflow initiations, and modifications.
  • a shadow pin has been updated with a new pin “x” 26 which in this context aware example means “cryosurgery” was performed in the anatomic location for a premalignant lesion called an actinic keratosis.
  • the same type of pin can be shaded with different order and list types, exemplifying that different documentation and workflow types can be performed by the same shadow pin type.
  • Information about a pin can be added by writing over the pin description 31 in one exemplified workflow - in the present embodiment, “01 - Infiltrative BCC - biopsy date 2017-12-03, path #49234-B, refused tx” has been updated with handwriting to say “wants to schedule since bleeding” indicating that the patient now wishes to treat the skin cancer because of symptoms of bleeding, and prompting interaction with future appointment scheduling workflows. Additionally, a diagnosis has been crossed out 32 to remove or archive the information from the record. It is contemplated that different inks, pigments, shapes, or patterns could additionally be used to initiate different workflows and processes. Checked checkbox 41 on the printed paper shadow chart will initiate and complete workflows to refill medication in the electronic record after image capture and analysis with computer vision.
  • Checked checkbox 51 initiates the workflow of automatically documenting and tracking counseling on a new pathology result. Specifically, documenting counseling, treatment recommendations, and next steps for a “venous lake” diagnosis for the patient, with the anatomic location of the venous lake being consistently documented at the shaded in shadow pin that previously read as “New Result - Specimen B on path #201-32d8 - Dx: Venous lake” and the updated additional pin description reading: “Benign - reassurance. Sutures removed today” thus automatically documenting manual descriptions of the healthcare interventions performed at that anatomic location.
  • the paper shadow chart 150 also contains new markup and annotations.
  • New markup annotation 27 indicated with “o” in this example means that “cryosurgery was performed to inflamed seborrheic keratoses at the marked locations,” whereas new markup annotation 28 indicated with “w” in this example means that “cryosurgery was performed to warts at the marked locations.” It is contemplated that different detectable properties like characters, shapes, labels, orders, pins, symbols, colors, intensities, patterns, shading, lines, and markers can be interpreted through a plurality of templates based on context and preferences and settings.
  • detections on a paper shadow chart can be categorized and displayed based on their detected properties, so an “x” and “o” and “w” on the paper shadow chart may use the same pin, but different colors on the digital shadow chart (such as a snowflake or star or asterisk meaning cryosurgery, but different colors could indicate different diagnoses and diagnosis categories).
  • Non-anatomic information 212 can also be added to a shadow chart in any detected or patient characteristic-generated whitespace, such as adding diagnoses not associated with the anatomic site or automatically added through specialty context.
  • non-anatomic information 212 is annotated in a previous whitespace, the handwritten diagnoses of “(1) Pacemaker due to A. fib” and “(2) history of prosthetic heart valve - needs Abx” prompt documentation and workflow processes relevant to the context such as alerts “bipolar or heat cautery should be used due to presence of pacemaker” or “patient is allergic to amoxicillin, and has a prosthetic heart valve requiring antibiotics prior to skin surgery, prescribe azithromycin prior to surgery?”.
  • FIG. 6 is a magnified view of the lower left portion of the capture from FIG. 5. New annotations 27 and re-documented annotations 21 are depicted. Re-documented annotations 21 , indicated by filling in existing shadow pins, denotes an update to the existing record at that location and automatically documents context aware documentation into the electronic chart. In one embodiment, this could be no evidence of reoccurrence for melanoma or refill of a prescription. It is contemplated this automatic documentation and workflow and process completion is context aware based on settings, preferences, specialty, language, country, and other characteristics.
  • the new annotations 27, indicated by the character “o,” denotes new healthcare data.
  • the “o” may be interpreted as procedures performed on specific diagnoses at the indicated locations such as “cryosurgery to inflamed seborrheic keratosis.”
  • FIG. 7 is a magnified view of the upper central portion of the capture from FIG. 5.
  • New annotations 25, updated documentation 31 , removal or archiving of documentation 32, redocumentation 21 , and an initiated workflow 41 are depicted.
  • updated documentation 31 for a shadow pin description is provided with annotations including a filled in shadow pin 21 and written words over the existing shadow pin description.
  • Shadow documentation may be removed or archived 32 through an annotation that crosses out the existing shadow pin description.
  • annotations to indicate re-documentation may be done by filling in existing shadow pins to denote an update to the existing record at that location.
  • a diagnosis for rosacea may be re-documented for a patient experiencing an outbreak.
  • FIG. 8 is a screenshot of a portion of an annotated paper shadow chart converted to a digital record by computer vision.
  • the digital record has new pins 29.
  • the new pins 29 were extracted, categorized, and plotted based on the computer vision detections of the handwritten annotations 27 in FIG.
  • each new digital pin 29 has a corresponding anatomic site description 329, pin description 330, a diagnosis 331 , and other associated data 332 (such as photographs, attachments, and links). It is contemplated that the pin description 330 can optionally be shown or hidden on the anatomic diagram 70 to avoid crowding.
  • Re-documented shadow pin 23 and accompanying pin description 33 are generated from the filled in shadow pin 21 in FIG. 6 and are automatically updated to include context aware information.
  • the redocumented shadow pin 23 and accompanying pin description includes the label “No evidence of recurrence” for a history of melanoma that was examined and documented during the patient encounter. It is contemplated that the automatically applied documentation and workflow and process completion is context aware based on settings, preferences, specialty, language, country, and other characteristics as one skilled in the art would know. It is further contemplated that the documentation points can be modified, moved, deleted, augmented with more information such as photographs, attachments, and links.
  • FIG. 9 is a screen shot of a portion of an annotated paper shadow chart converted to a digital record by computer vision.
  • the digital record has new pins 29 and redocumented pins for infiltrative BCC 340, rosacea 344, Hx BCC 348 diagnoses.
  • the new pins and redocumented pins were extracted, categorized, and plotted based on the computer vision detections of the handwritten annotations in FIG. 7.
  • the history of the record for redocumented infiltrative BCC 340 began as an anatomic diagram with existing documentation including a shadow pin 20 and shadow pin description 30 in FIG. 2.
  • the location was annotated by hand with a filled in shadow pin 21 and handwritten text 31 over the existing documentation as depicted in FIG. 7 and is now shown with a redocumented pin 340 and accompanying updated shadow pin description 341.
  • the history of the record for redocumented rosacea 344 began as an anatomic diagram with existing documentation including a shadow pin and shadow pin description that was annotated by hand with a filled in shadow pin 22 and checked workflow initiator 41 over the existing documentation as depicted in FIG. 7 and is now shown with a redocumented pin 344 and accompanying updated shadow pin description 345.
  • the new pins 29 appear as asterisks and have corresponding anatomic site descriptions 329, pin descriptions 330, a diagnosis 331, and other associated data 332 (such as photographs, attachments, and links) shown in a side panel 350 on the screen.
  • the pin description 330 can optionally be shown or hidden on the anatomic diagram 70 to avoid crowding.
  • different colors can further be used to enhance the tracking and recording of information on the shadow charts.
  • the automatically applied documentation and workflow and process completion is context aware based on settings, preferences, specialty, language, country, and other characteristics as one skilled in the art would know.
  • the documentation points can be modified, moved, deleted, augmented with more information such as photographs, attachments, and links.
  • FIG. 10 is an example of distribution coloring 155 with different colors and intensities on a paper shadow chart 213.
  • the picture of the shadow chart additionally has orientation and axis normalization markers 80 for enhanced alignment of the shadow documentation relative to the diagrams.
  • Context data such as language for the shadow chart can be determined by detected areas like a QR code 90.
  • This shadow chart also has blank fields 151 for patient demographics indicating that it could be used as a backup chart without shadow information, useful in times where internet access is limited or not available such as during an internet outage or in remote military operations.
  • the shadow chart could later be scanned, at which time computer vision will detect information in the blanks and create a digital record.
  • the exemplar shows shaded annotations in various colors 155 at anatomic distribution sites. It is contemplated that different colors would indicate different relevant information allowing computer vision to detect and interpret the color variations. Context awareness allows for these detections to be categorized and documented correctly into the electronic medical record. In one embodiment, blue could correlate to a diagnosis of “dermatitis”, green could correlate to a diagnosis of “lupus”, and red could correlate to a diagnosis of “psoriasis.” Computer vision would automatically color the distributions on digital records in their correct colors, associate diagnoses, and group the anatomic sites into consolidated named distributions when possible.
  • FIG. 11 depicts a screenshot of a converted digital record of FIG. 10.
  • the detected distributions 156 appear in the same colors as the shaded annotations 155 in FIG. 10.
  • the side panel 350 includes the corresponding anatomic site descriptions 329, pin descriptions 330, diagnoses 331 , and other associated data 332, shown here in Chinese which indicates the QR Code 90 in FIG. 10 provided language context for the chart as Chinese. It is contemplated that these anatomic site descriptions in this example are automatically combinable to be “bilateral malar region” or “butterfly rash” in their Chinese translations as one skilled in the art would know.
  • the side panel 350 further organizes the generated information by color-coded distribution with a color indicator 158 matching the color on the anatomic diagram 70.
  • FIG. 14 is a magnified view of a portion of FIG. 10 more clearly illustrating these laterality labels 120 in Chinese. It is further contemplated that these detections, descriptions, diagnoses, colors, photos, attachments, and links are automatically translatable to any coded, linguistic or symbolic language.
  • FIG. 12 shows the converted digital record from FIG. 11 automatically translated to English with the laterality labels 120 and side panel 350 information, including anatomic site descriptions 329, pin descriptions 330, diagnoses 331 , and other associated data 332, all shown in English.
  • these anatomic site descriptions in this example are automatically combinable to be “bilateral malar region” or “butterfly rash” as one skilled in the art would know. It is further contemplated that these detections, descriptions, diagnoses, colors, photos, attachments, and links are automatically translatable to any coded, linguistic, or symbolic language.
  • FIG. 13 depicts a screenshot that illustrates a visual alert 175 on the shadow chart that displays anatomy specific warnings. It is contemplated that the visual alert 175 can optionally be highlighted on alternate views 176 and angles of the affected anatomy, in different perspectives. Such alerts can appear on digital shadow charts, paper shadow charts, both, or neither based on context awareness. For example, if the medical assistant who normally takes blood pressure during the rooming process has the electronic health record open, the alert can be shown to them during the vitals capture stage of the encounter. A smart and connected blood pressure cuff could also verbally alert the assistant in this example.

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Abstract

La présente invention comprend un procédé pour collationner, organiser, afficher et interagir avec des données de santé passées, présentes et futures relatives à un patient. Lorsque les données de santé sont associées à l'anatomie, les données de santé sont automatiquement visualisées avec des emplacements, des images, des diagrammes et des cartes pertinents au même titre que des points anatomiques interactifs ou des distributions contenant des informations sensibles au contexte relatives à l'anatomie, à la spécialité, au diagnostic, à la procédure, au langage ou à d'autres données. La présente invention utilise des données de soins de santé dans des graphiques fantômes numériques, ou des graphiques fantômes papier, ou les deux, pour créer un dossier complet et pour mélanger de façon fluide des documents en version papier et version électronique. Les graphiques collationnent automatiquement des données de soins de santé passées, actuelles et futures qui sont automatiquement liées à des cartes anatomiques et des données de soins de santé pour une visualisation, modification, augmentation et automatisation de la génération de dossiers médicaux, et une récupération. Des graphiques fantômes collationnent et affichent des informations à partir d'adresses anatomiques dynamiques, de blocs de données et de blocs de métadonnées sur une carte anatomique traduite en langage utilisateur, avec des sites anatomiques recréés et des données de santé. Des flux de travail automatisés tels que des renouvellements d'ordonnances, des tests diagnostiques suggérés, des zones de préoccupation à suivre, etc., sont inclus sur le graphique fantôme. Le lancement d'un marquage numérique et d'un flux de travail sur un graphique fantôme numérique se fait en temps réel, et un marquage physique sur un graphique fantôme en papier peut se faire en temps réel avec certains dispositifs tels qu'un stylo qui suit une position sur un papier ou après coup avec une capture photographique ou scannée du graphique fantôme en papier marqué. La vision artificielle peut interpréter les marques et prendre en compte tout changement et le contenu peut ensuite être synchronisé dans le dossier dans la pluralité d'emplacements, de bases de données et de systèmes appropriés pour les données. L'utilisateur peut être alerté de divergences lors de la synchronisation après coup et est automatiquement invité à les rapprocher. Pour éviter un encombrement dans le graphique fantôme, des points d'intérêt peuvent être retirés, désactivés de manière sélective, filtrés et/ou servis de manière sélective, sur la base d'une interaction manuelle, de préférences de l'utilisateur ou automatiquement à l'aide de paramètres de l'utilisateur ou de l'organisme.
PCT/IB2022/000823 2021-12-10 2022-12-29 Graphiques fantômes pour collationner et interagir avec des dossiers médicaux passés, présents et futurs WO2023156809A2 (fr)

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US202263362791P 2022-04-11 2022-04-11
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US202263366816P 2022-06-22 2022-06-22
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