CN112712805A - Method and device for generating electronic medical record report and computer readable storage medium - Google Patents
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Abstract
The application provides a method and equipment for generating an electronic medical record report and a computer readable storage medium; the method for generating the electronic medical record report comprises the steps of acquiring voice information, and carrying out voice recognition on the voice information to acquire voice characters; and matching the voice characters with elements in the element library, and after the matching is successful, generating information corresponding to the voice characters and displaying the information on the terminal in an editable form for confirmation and modification. The method can support text editing while performing voice filling.
Description
Technical Field
The invention relates to the technical field of electronic medical records, in particular to a method and equipment for generating an electronic medical record report and a computer readable storage medium.
Background
The medical record is the record of the medical personnel on the process of the medical activities of the patient such as the occurrence, development and outcome, examination, diagnosis, treatment and the like, and has important functions on medical treatment, prevention, teaching, scientific research, hospital management and the like.
At present, a medical record report is generally generated by adopting a keyboard input mode, but the method needs to consume a long time; for this reason, speech recognition techniques are widely used in the generation of medical record reports; specifically, the method for generating a medical record report based on speech recognition generally includes obtaining an audio stream, then recognizing speech information in the audio stream to obtain corresponding speech characters, searching for character keywords in the speech characters, and then matching and filling the character keywords in the speech characters to corresponding position slots to generate the medical record report.
However, this method cannot simultaneously support text editing while voice filling.
Disclosure of Invention
According to the method, the device and the computer-readable storage medium for generating the electronic medical record report, the problem that text editing cannot be simultaneously supported while voice filling is performed in the existing method can be solved.
In order to solve the technical problem, the application adopts a technical scheme that: a method for generating an electronic medical record report is provided. The method comprises the steps of obtaining voice information, and carrying out voice recognition on the voice information to obtain voice characters; and matching the voice characters with elements in the element library, and after the matching is successful, generating information corresponding to the voice characters and displaying the information on the terminal in an editable form for confirmation and modification.
Wherein, in the step of matching the phonetic characters with the elements in the element library, the method further comprises the following steps: sentence breaking processing is carried out on the voice characters according to elements corresponding to the element library so as to form a plurality of voice short sentences; performing word segmentation processing on each voice short sentence to form a plurality of structured words; and matching the plurality of structured words with elements in the element library, and after the matching is successful, generating information corresponding to the structured words and displaying the information on the terminal in an editable form for confirmation and modification.
Before the step of matching the phonetic characters with the elements in the element library, the method further comprises the following steps: acquiring medical record information of a historical medical record report and/or a latest medical record report of a current patient; and classifying characters corresponding to the medical record information to form structurable words and non-structurable words corresponding to the medical record information.
Wherein, the step of matching the phonetic characters with the elements in the element library further comprises: and after the matching fails, performing secondary matching on the plurality of structured words and the structurable words corresponding to the medical record information, and after the secondary matching succeeds, storing the matched structurable words as new elements into an element library.
Wherein, but carry out the step that the secondary matches with a plurality of structured word and the structured word that medical record information corresponds specifically includes: identifying keywords in the structured words to obtain structured keywords; and carrying out secondary matching on the structured keywords and the structurable words corresponding to the medical record information.
Wherein, but carry out the secondary with a plurality of structured word and the structured word that the case history information corresponds and match to after the secondary matches successfully, but the step of saving the structured word of matching as new element in the element storehouse still includes: and after the secondary matching fails, storing the structured words or storing the structured words as new elements into the element library, and matching the structured words with the elements in the current element library again to generate information corresponding to the structured words.
Wherein, still include: acquiring unstructured words corresponding to the voice characters; the unstructured words are words in the voice characters except the structured words;
the unstructured words are recombined with the structured words to generate a new report statement and displayed in text form.
Wherein, still include: and re-acquiring the voice information to update the information corresponding to the generated voice characters.
In order to solve the above technical problem, another technical solution adopted by the present application is: provided is an electronic medical record report generation device. The device comprises a memory and a processor which are connected with each other, wherein the memory is used for storing program instructions for realizing the generation method of the electronic medical record report related to the method; the processor is operable to execute program instructions stored by the memory.
In order to solve the above technical problem, the present application adopts another technical solution: a computer-readable storage medium is provided. The computer readable storage medium stores a program file that can be executed by a processor to implement the method for generating an electronic medical record report as described above.
The method comprises the steps of acquiring voice information, and carrying out voice recognition on the voice information to acquire voice characters; and then matching the voice characters with the elements in the element library, and automatically generating information corresponding to the voice characters after the matching is successful and displaying the information on the terminal in an editable form for confirmation and modification.
Drawings
In order to more clearly illustrate the technical solutions in the embodiments of the present invention, the drawings needed to be used in the description of the embodiments are briefly introduced below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and other drawings can be obtained by those skilled in the art without inventive efforts, wherein:
fig. 1 is a flowchart of a method for generating an electronic medical record report according to an embodiment of the present application;
FIG. 2 is a sub-flowchart of step S12 in FIG. 1 according to an embodiment of the present application;
fig. 3 is a schematic structural diagram of an apparatus for generating an electronic medical record report according to an embodiment of the present application;
fig. 4 is a schematic structural diagram of an apparatus for generating an electronic medical record report according to another embodiment of the present application;
fig. 5 is a schematic structural diagram of an electronic medical record report generation device according to an embodiment of the present application;
fig. 6 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present application.
Detailed Description
The technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are only a part of the embodiments of the present application, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
The terms "first", "second" and "third" in this application are used for descriptive purposes only and are not to be construed as indicating or implying relative importance or implying any indication of the number of technical features indicated. Thus, a feature defined as "first," "second," or "third" may explicitly or implicitly include at least one of the feature. In the description of the present application, "plurality" means at least two, e.g., two, three, etc., unless explicitly specifically limited otherwise. All directional indications (such as up, down, left, right, front, and rear … …) in the embodiments of the present application are only used to explain the relative positional relationship between the components, the movement, and the like in a specific posture (as shown in the drawings), and if the specific posture is changed, the directional indication is changed accordingly. Furthermore, the terms "include" and "have," as well as any variations thereof, are intended to cover non-exclusive inclusions. For example, a process, method, system, article, or apparatus that comprises a list of steps or elements is not limited to only those steps or elements listed, but may alternatively include other steps or elements not listed, or inherent to such process, method, article, or apparatus.
Reference herein to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the application. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. It is explicitly and implicitly understood by one skilled in the art that the embodiments described herein can be combined with other embodiments.
The intelligent voice recognition technology is widely applied to scenes before, during and after a doctor in the medical industry, including appointment registration, medical guide, medical history acquisition, voice electronic medical record, post-hospital follow-up and the like. When a diagnosis report is written in a hospital clinical examination department, 60% -70% of the diagnosis reports are professional diagnosis terms, the repetition rate is high, and the essence of the diagnosis report is the combination of some professional vocabularies. However, with the continuous update of medical equipment, information and digitalization become the development trend and target of hospitals at present and for a long time in the future. At present, in a large hospital, the input amount of diagnostic information every day is large, the diagnostic information can include examination findings and examination conclusions in medical and technical diagnostic reports of patients, and the input is generally performed by using a keyboard, so that doctors need to spend a long time (more than 50% of the time of the doctors) and write related reports according to examination conditions of the patients; meanwhile, in the case of pathological material drawing and ultrasonic examination scenes, a typist may need to be separately prepared for report entry, which causes waste of personnel.
For this reason, some manufacturers have developed speech recognition systems for the entry of medical technical reports; specifically, the existing voice input technology for medical technical reports is operated on a Personal Computer (PC), supports a fixedly constructed template structured in front of a text, and realizes voice recognition, searching for a character keyword, and then matching and filling the character keyword to a corresponding position slot to realize the input of the report; however, the technology may have the condition of no matching or wrong matching, and for a medical technology template containing a plurality of pieces of field information, keyword search cannot meet the requirements of diagnosis of medical technicians, and the difficulty of mining the medical technology template and the final diagnosis information in a complex and huge report is correspondingly increased; in addition, the existing related art can not insist on text editing while performing voice filling, and the existing voice recognition system needs a doctor to speak out a large segment of characters, so that the doctor is not willing to apply the voice recognition function in a normalized manner. For this reason, consider a kind of based on professional diagnostic terms, define the structural template in advance, and combine the voice to fill, allow doctor to receive a visit more patients at the same time, can use more time on the examination technology to promote; specifically, according to the functional modules divided according to the examination type and the examination part, different system element templates of normal diseases and abnormal diseases are mutually independent and do not interfere with each other, the templates can be conveniently and rapidly customized and generated by combining multiple parts, and all the templates are stored in an element mode and preset in advance.
In the conventional medical record report generation, a medical technology report structured processing technology is mainly realized by surrounding the field text structured construction; for example, the ultrasonic inspection report is structured, a domain ontology basic frame is constructed, then data preprocessing is carried out on an ultrasonic text, the data preprocessing comprises Chinese word segmentation, synonym replacement and text segmentation, a description block after segmentation is taken as a processing unit, a named entity recognition and entity relationship extraction algorithm is adopted to obtain entity relationship triples, and finally, contents are added to the domain ontology basic frame to construct and complete a domain ontology knowledge base; aiming at the structuralization of medical image reports, the method is mainly realized by extracting field text feature labels for different examinations in radiation by using a machine learning model and designing a mapping rule.
In the prior art, a deep learning-based framework is generally adopted to extract similarity measurement of report key information, and a classification model and a similarity model are fused. The classification search model realizes matching, and the effect is obvious under the conditions of less template types and single type. However, since there are many parts and templates, the distribution of diseases is wide, and the mutual relationship between diseases is deep, if the classification category is too fine, the effect will be significantly reduced, and if the category granularity is too coarse, the confusion of diseases is also serious. The similarity model generally adopts a deep learning network framework to obtain medical record report characteristic representation at present, but deep learning is still in an exploration stage in the processing direction of long texts.
Therefore, the method can automatically generate the electronic medical record report of the current patient according to the voice dialogue information of the doctor and the patient, and supports text editing of the user while inputting the voice.
The present application will be described in detail with reference to the accompanying drawings and examples.
Referring to fig. 1, fig. 1 is a flowchart illustrating a method for generating an electronic medical record report according to an embodiment of the present application; in the embodiment, a method for generating an electronic medical record report is provided. The method specifically comprises the following steps:
step S11: and acquiring voice information, and performing voice recognition on the voice information to acquire voice characters.
The voice information can be specifically dialogue information of a doctor and a patient, and can be specifically generated in the dialogue between the doctor and the patient; in a specific embodiment, a microphone may be used to obtain voice information; the microphone is matched with wireless and desktop voice input, the microphone can be in wireless or wired connection with computer equipment, and an element template for supporting voice input and a control instruction for positioning specific operation and selecting a content layout block in the report template can be arranged on the microphone.
Certainly, in other embodiments, devices such as a recording pen or a smart phone with a recording function may also be used to record the conversation content between the doctor and the patient and generate voice information, and then the voice information is sent to the computer through the data interface; therefore, a plurality of users can share one computer device, and the cost is saved; the data interface includes, but is not limited to, a local data interface such as a USB interface and an HDMI interface, or includes, but is not limited to, a network data interface such as a wireless local area network and a mobile communication network.
Specifically, the speech information may be recognized to obtain the speech words by using the related technology related to speech recognition in the prior art, such as the speech recognition technology referred to in 201710091103.7 and 200610107454.4, which is not limited in this application as long as the speech information can be converted into text word information.
Step S12: and matching the voice characters with elements in the element library, and after the matching is successful, generating information corresponding to the voice characters and displaying the information on the terminal in an editable form for confirmation and modification.
In the specific implementation process, a blank element template can be selected and positioned according to the voice information, namely, no element information exists on the content layout block of the element template; for example, inputting voice information "find by open examination", "conclude by open examination", "cardiac examination" or "gynecological examination", etc., the page is automatically switched to a content plate of the corresponding element template, the content plate may specifically be a blank plate, then matching the voice characters with the elements in the element library, and after the matching is successful, generating information corresponding to the voice characters in the content plate to dynamically generate the element template, and displaying the generated information in an editable form on a terminal of a computer or the like for confirmation and modification; wherein, the words of the element template can be marked by adopting spaces and colors, and all elements can be subjected to voice interaction. Compared with the prior art, the method does not need a user to record more fixed statements in advance, namely does not need to extract a preset element template, and only needs to automatically generate the element template information according to the existing text template and the element library in a hospital, thereby effectively increasing the writing flexibility of the element template information and the electronic medical record report, realizing what you see is what you say and facilitating the use of the user.
Specifically, an element library is stored in the computer device in advance, the element library comprises a plurality of elements, and the elements in the element library relate to related elements of different departments such as ultrasound, radiation and endoscope, so that the element library can be suitable for different departments, different medical technical project examinations and the like, a set of structured template elements are customized independently without aiming at different medical technical project examinations, the element library can be called repeatedly, and less customization can be performed on the public medical technical element library based on personalization. Specifically, each element in the element library can support a voice interaction function, so that the convenience and the high efficiency of voice use are improved; each element comprises two data structures of content and corresponding operation, namely, text editing can be supported while voice filling is carried out, so that a user can carry out self-defined operation on statement attributes, word attributes, behavior attributes and the like, or carry out operation of newly adding elements and the like in an original element library; specifically, each element may be represented in json lightweight data interchange format.
In the specific implementation process, if the elements corresponding to the voice characters exist in the element library, matching is successful, information corresponding to the voice characters is generated, and meanwhile, the information can be edited and displayed on the terminal for confirmation and modification; in a specific embodiment, after the voice information is recorded, if the information needs to be modified, a user can click the content corresponding to the current content plate and directly modify the keyboard of any word of the content plate so as to perform secondary confirmation and correction on the voice input individual error information; or by retrieving the current speech information and continuing to perform the related steps of step S11 and step S12 to update the information generated in the content plate, thereby implementing the modification function and updating the current element template in real time; the method can update or modify the generated information at any time, so that the method can support text editing while performing voice filling, and fusion of various input modes is realized; in addition, the method is suitable for cross-platform use in a PC or mobile terminal device, elements in the element template information are rich, and all slot positions are defined as intention entities.
In the specific implementation process, the above steps S11-S12 can be repeated according to actual conditions until all the medical and technical examination information of the current patient is recorded in the corresponding content plate, the entry of the whole report is completed, and the electronic medical record report is generated according to the information in the content plate.
In the method for generating an electronic medical record report provided by the embodiment, voice information is acquired, and voice recognition is performed on the voice information to acquire voice characters; and then matching the voice characters with the elements in the element library, and automatically generating information corresponding to the voice characters after the matching is successful and displaying the information on the terminal in an editable form for confirmation and modification.
In an embodiment, please refer to fig. 2, fig. 2 is a sub-flowchart of step S12 in fig. 1 according to an embodiment of the present application; step S12 specifically includes:
step S121: and performing sentence breaking processing on the voice characters according to the elements corresponding to the element library to form a plurality of voice short sentences.
In a specific embodiment, after the speech text is recognized, the recognized speech text may be primarily classified through a classification model, for example, whether the recognized speech text belongs to a medical term, is related to a report, or the like is determined, so as to primarily filter out a part of irrelevant speech text, and then sentence-breaking processing is performed; for example, if the recognized speech text is "hello aorta inner diameter 3 ascending aorta inner diameter 4", the text "hello your good" may be preliminarily filtered through the classification model, and then the filtered speech text "aorta inner diameter 3 ascending aorta inner diameter 4" is punctuated, and two speech phrases formed after punctuation processing may be "aorta inner diameter 3" and "ascending aorta inner diameter 4".
Step S122: and performing word segmentation processing on each voice short sentence to form a plurality of structured words.
Specifically, for example, if the formed speech phrases are "aorta inner diameter 3" and "ascending aorta inner diameter 4", the speech phrases "aorta inner diameter 3" and "ascending aorta inner diameter 4" are participled to form the structured words "aorta", "inner diameter", "3", "ascending aorta", "inner diameter" and "4".
Step S123: and matching the plurality of structured words with elements in the element library, and after the matching is successful, generating information corresponding to the structured words and displaying the information on the terminal in an editable form for confirmation and modification.
Specifically, if the element library has elements corresponding to the structured words, matching is successful, information corresponding to the structured words is generated on the content plate of the blank element template, and the information is displayed on a computer or other terminal in an editable form for confirmation and modification.
For example, if the structured word is "ascending aorta", "inner diameter" or "4", if there are elements corresponding to the structured word "ascending aorta" or "inner diameter" in the element library, and "4" satisfies the corresponding elementsThe corresponding information is generated according to the value type of (2): "ascending aorta internal diameter (AAO):4mm "; in a specific embodiment, if the corresponding information generated is "ascending aorta internal diameter (AAO):3mm ", the information is generated as an error, and at this time, the" 3 "in the information can be updated to" 4 "by re-acquiring the voice information" ascending aorta inner diameter 4 "and re-executing step S11 to step S12. Of course, "3" may also be modified to "4" by keyboard entry to enable real-time updating of the current element template.
In a specific embodiment, elements in an element library can be specifically divided into an enumeration type, a numerical value type, a simple option type and a complex option type so as to perform fine screening on structural words matched with the elements; wherein the simple option type comprises one or more options; the complex option type is a structured element option and a free text type nested in the option.
Specifically, when the structural words obtained by segmenting the voice characters are of an enumeration type, the content of the natural text in an in-set range is corrected, and other items outside the set are not allowed to be spoken; for example, when the structured word segmented by the voice text is the "uterus back position", and the content of the corresponding element in the element library is the "uterus", the front position, the middle position and the back position are embedded in the "uterus", and the back position is not included, at this time, the matching cannot be successful; in particular embodiments, if the matching fails and the structured word has a certain generality or utility, the structured word, such as "posterior uterine position" may be added as a new element to the library for subsequent use.
When the structural words obtained by word segmentation of the voice characters are numerical types, the numerical values are judged, the numerical units are automatically optimized, and the numerical display format is correspondingly post-processed and displayed; specifically, whether the numerical value corresponding to the structured word belongs to the numerical range corresponding to the matching element is judged, if yes, the corresponding numerical value is directly generated, and if not, the corresponding numerical value cannot be generated at the corresponding position; for example, if the structural word segmented by the speech text is the numerical value "4" and the numerical range of the corresponding element is 3 to 5, it is determined whether the numerical value "4" belongs to the numerical range 3 to 5 corresponding to the matching element, and the numerical value "4" is directly generated.
When the structural words obtained by segmenting the voice words are simple option types, the best matching is carried out on the texts in the corresponding options, and the best matching is selected and structured processing is carried out; when the structural words obtained by segmenting the voice words are of the complex option type, the best matching is carried out on the text in the complex option range, and meanwhile, the type of the text in the option is judged on the basis of the structural words, namely whether the text is of an enumeration type, a numerical value type or a simple option type is judged, so that the structural operation is carried out.
Specifically, if there is no element corresponding to the structured word in the element library, the matching fails, and at this time, the secondary matching may be performed on the structurable word according to the following steps.
In a specific embodiment, before matching the phonetic text with the elements in the element library, the method further includes: acquiring medical record information of a historical medical record report and/or a latest medical record report of a current patient; and classifying characters corresponding to the medical record information to form structurable words and non-structurable words corresponding to the medical record information.
The historical medical record report can be medical record reports of other previous patients stored in the hospital, and the latest medical record report of the current patient is a medical record report formed after the previous examination of the current patient. It can be understood that, if the current patient is the initial examination, the medical record report formed this time is the latest medical record report, and there is no latest medical record report of the current patient.
The structurable words are all new intention entities automatically generated based on the element library, and can also be specifically divided into enumeration types, numerical value types, simple option types and complex option types; the unstructured words can be added with element information according to business needs, namely, the unstructured words can be selected to be generated on the content plate while the information corresponding to the structurable words is generated on the content plate according to the business needs, so that the readability of the generated information is improved; in particular, the unstructured terms may not be stored in the library of elements.
In a specific embodiment, if the matching between the structured words and the elements in the element library fails, the plurality of structured words and the structurable words corresponding to the medical record information are further subjected to secondary matching, and after the secondary matching is successful, the matched structurable words are stored in the element library as new elements, and the element library is updated in real time.
Specifically, the keywords in the structured words are identified to obtain the structured keywords, then the structured keywords are secondarily matched with the structurable words corresponding to the medical record information, and after the secondary matching is successful, the matched structurable words are stored in an element library as new elements; it is to be understood that the new elements likewise include content and corresponding operations; and then, matching the structured words with the elements in the element library, and after the matching is successful, generating information corresponding to the structured words in the content plate and displaying the information on the terminal in an editable form, so that the user can confirm and modify the generated information. The specific process of identifying the keywords in the structured words can refer to the specific process of searching the text keywords in the speech text in the prior art, and the same or similar technical effects can be achieved, which is not described herein again.
Specifically, if the secondary matching fails, it is indicated that the historical medical record report and/or the latest medical record report of the current patient also have no element corresponding to the structured word; at this time, the structured words can be directly abandoned, or the generation instruction is obtained according to the actual requirement, so that the information corresponding to the structured words is directly generated on the content plate; for example, if the structured word "no obvious abnormal mitral valve" cannot be matched in the element library, the speech information "no obvious abnormal mitral valve recording is finished" can be directly obtained, and after the speech information "recording is finished" is recognized by the computer device, the control system directly generates "no obvious abnormal mitral valve" on the current content plate; in a specific embodiment, the structured word "no significant abnormality of mitral valve" can be further selected to be saved or stored as a new element in the element library for later recall.
In the specific implementation process, in order to improve the readability of the generated electronic medical record report and the fluency of related text contents, the method can also comprise the steps of acquiring unstructured words except for structured words in the recognized voice words, recombining the unstructured words and the structured words to generate a new report sentence and storing the new report sentence in a content block in a text form; in particular embodiments, the information corresponding to the unstructured words may not be color-coded.
In the specific implementation process, the generated related information content can be further stored in a two-dimensional element table mode so as to be called later when scientific research analysis is carried out.
According to the method for generating the electronic medical record report, the medical record information of the historical medical record report and/or the latest medical record report of the current patient is further acquired, so that the phonetic characters are subjected to secondary matching according to the medical record information, the accuracy of the electronic medical record report can be effectively improved, the occurrence of missed problems such as rare diseases or other disease symptoms can be reduced, and more references can be provided for subsequent medical analysis.
According to the method for generating the electronic medical record report, the corresponding information is automatically generated on the content plate according to the voice information through the mode based on the minimum granularity of the element, so that the element is automatically generated, the corresponding element template can be dynamically updated in real time in the process, the element template does not need to be preset in advance, and the writing flexibility of the element template and the electronic medical record report is effectively improved; meanwhile, compared with the traditional scheme of extracting the key information and extracting the structural elements through the neural network, the method combines a classification model, the quality control of the element template and a post-structural processing model, and performs fine screening and structural definition fusion on the basis of the prior knowledge obtained by the key information and the classification model, so that the characteristics of different departments, examinations, different parts and different diseases can be better distinguished, the element library is reused, and the element verification and post-structural storage are performed on the medical technical report comprehensively to a certain extent, namely, the element is stored in a two-dimensional element table mode, and the system processing efficiency and the use convenience are effectively improved.
Referring to fig. 3, fig. 3 is a schematic structural diagram of an apparatus for generating an electronic medical record report according to an embodiment of the present application; in the present embodiment, an electronic medical record report generation apparatus 30 is provided, and the electronic medical record report generation apparatus 30 is specifically configured to execute the method for generating an electronic medical record report according to the above-described embodiment; specifically, the electronic medical record report generating device 30 may include a voice interaction module 31 and an electronic medical record report generating module 32.
The voice interaction module 31 is configured to obtain voice information, and perform voice recognition on the voice information to obtain voice characters.
The electronic medical record report generating module 32 is connected to the voice interaction module 31, and is configured to acquire the element library, match the voice text with the elements in the element library, and after the matching is successful, generate information corresponding to the voice text and display the information on the terminal in an editable form for confirmation and modification, thereby forming an electronic medical record report.
In a specific embodiment, the electronic medical record report generating module 32 is specifically configured to perform sentence-breaking processing on the speech text according to the elements corresponding to the element library to form a plurality of speech phrases; performing word segmentation processing on each voice short sentence to form a plurality of structured words; then matching a plurality of structured words with elements in an element library, and after the matching is successful, generating information corresponding to the structured words and displaying the information on a terminal in an editable form for confirmation and modification; and then forming an electronic medical record report according to the information generated on the content section.
Referring to fig. 4, fig. 4 is a schematic structural diagram of an electronic medical record report generation apparatus according to another embodiment of the present application; in this embodiment, another electronic medical record report generation apparatus 40 is provided, and compared with the electronic medical record report production apparatus 30 provided in the first embodiment, the electronic medical record report generation apparatus 40 further includes a medical record information acquisition module 42; specifically, the electronic medical record report generating device 40 may specifically include a voice interaction module 41, a medical record information obtaining module 42, and an electronic medical record report generating module 43.
The specific structure and function of the voice interaction module 41 are the same as or similar to those of the voice interaction module 31 in the device 30 for generating an electronic medical record report provided in the first embodiment, and the same or similar technical effects can be achieved.
The medical record information acquiring module 42 is configured to acquire medical record information of a historical medical record report and/or a latest medical record report of a current patient, and classify characters corresponding to the medical record information to form structurable words and non-structurable words corresponding to the medical record information. Specifically, if the current patient is the initial examination, the medical record information acquiring module 42 only acquires the historical medical record report.
The electronic medical record report generating module 43 is connected to the voice interaction module 41 and the medical record information acquiring module 42, and is configured to acquire the element library, match the voice characters with elements in the element library, and after the matching is successful, generate information corresponding to the voice characters and display the information on the terminal in an editable form for confirmation and modification, thereby forming an electronic medical record report.
In a specific embodiment, the electronic medical record report generating module 43 is specifically configured to perform sentence-breaking processing on the speech text according to the elements corresponding to the element library to form a plurality of speech phrases; performing word segmentation processing on each voice short sentence to form a plurality of structured words; and then matching the plurality of structured words with elements in the element library, generating information corresponding to the structured words after the matching is successful, displaying the information on a terminal in an editable form for confirmation and modification, and then forming an electronic medical record report according to the information generated on the content layout block.
Specifically, after the matching fails, the electronic medical record report generating module 43 is further configured to perform secondary matching on the plurality of structured words and the structurable words corresponding to the medical record information, store the matched structurable words as new elements into the element library after the secondary matching is successful, obtain the updated element library again, match the plurality of structured words and the elements in the updated element library, generate information corresponding to the structurable words in the content block after the matching is successful, display the information on the terminal in an editable form, and generate the electronic medical record report based on the information on the content block.
Referring to fig. 5, fig. 5 is a schematic structural diagram of an electronic medical record report generation apparatus according to an embodiment of the present application; in the embodiment, an electronic medical record report generating device is provided, and the electronic medical record report generating device includes a memory 500 and a processor 501 connected to each other; the memory 500 is used for storing program instructions for implementing the method for generating an electronic medical record report according to the above embodiments; the processor 501 is used to execute program instructions stored by the memory 500.
The processor 501 may also be referred to as a CPU (Central Processing Unit). The processor 501 may be an integrated circuit chip having signal processing capabilities. The processor 501 may also be a general purpose processor, a Digital Signal Processor (DSP), an Application Specific Integrated Circuit (ASIC), a Field Programmable Gate Array (FPGA) or other programmable logic device, discrete gate or transistor logic, discrete hardware components. A general purpose processor may be a microprocessor or the processor may be any conventional processor or the like.
The storage 500 may be a memory bank, a TF card, etc., and may store all information in the electronic medical record report generating device, including the input raw data, the computer program, the intermediate operation result, and the final operation result, which are stored in the storage 500. It stores and retrieves information based on the location specified by the controller. With the memory 500, the generating device of the electronic medical record report has a memory function, and can work normally. The storage 500 in the electronic medical record report generation device can be classified into a main storage (internal storage) and an auxiliary storage (external storage) according to the use of the storage, and also into an external storage and an internal storage. The external memory is usually a magnetic medium, an optical disk, or the like, and can store information for a long period of time. The memory refers to a storage component on the main board, which is used for storing data and programs currently being executed, but is only used for temporarily storing the programs and the data, and the data is lost when the power is turned off or the power is cut off.
The electronic medical record report generating device further comprises other devices, and the functions of the electronic medical record report generating device are the same as those of other devices and functions in the electronic medical record report generating device in the prior art, and are not described herein again.
Referring to fig. 6, fig. 6 is a schematic structural diagram of a computer-readable storage medium according to an embodiment of the present application; in the present embodiment, a computer-readable storage medium is provided, which stores a program file 600, and the program file 600 can be executed by a processor to implement the method for generating an electronic medical record report according to the above-mentioned embodiments.
The program file 600 may be stored in the storage medium in the form of a software product, and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute all or part of the steps of the methods according to the embodiments of the present application. The aforementioned storage device includes: various media capable of storing program codes, such as a usb disk, a mobile hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, or terminal devices, such as a computer, a server, a mobile phone, and a tablet.
In the several embodiments provided in the present application, it should be understood that the disclosed method and apparatus may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, e.g., a unit or division of units is merely a logical division, and other divisions may be realized in practice, e.g., a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
Units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, and can also be realized in a form of a software functional unit.
The integrated unit, if implemented in the form of a software functional unit and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present application may be substantially implemented or contributed to by the prior art, or all or part of the technical solution may be embodied in a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, a network device, or the like) or a processor (processor) to execute all or part of the steps of the method according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
The above embodiments are merely examples and are not intended to limit the scope of the present disclosure, and all modifications, equivalents, and flow charts using the contents of the specification and drawings of the present disclosure or those directly or indirectly applied to other related technical fields are intended to be included in the scope of the present disclosure.
Claims (10)
1. A method for generating an electronic medical record report is characterized by comprising the following steps:
acquiring voice information, and performing voice recognition on the voice information to acquire voice characters;
and matching the voice characters with elements in an element library, and after the matching is successful, generating information corresponding to the voice characters and displaying the information on a terminal in an editable form for confirmation and modification.
2. The method for generating an electronic medical record report of claim 1, wherein the step of matching the phonetic text with the elements in the element library further comprises:
sentence breaking processing is carried out on the voice characters according to the elements corresponding to the element library to form a plurality of voice short sentences;
performing word segmentation processing on each voice short sentence to form a plurality of structured words;
and matching a plurality of structured words with elements in an element library, and after the matching is successful, generating information corresponding to the structured words and displaying the information on a terminal in an editable form for confirmation and modification.
3. The method for generating an electronic medical record report of claim 2, wherein before the step of matching the phonetic text with the elements in the element library, the method further comprises:
acquiring medical record information of a historical medical record report and/or a latest medical record report of a current patient;
and classifying characters corresponding to the medical record information to form structurable words and non-structurable words corresponding to the medical record information.
4. The method of generating an electronic medical record report of claim 3 wherein the step of matching the phonetic text with the elements in the element library further comprises:
and after the matching fails, performing secondary matching on the plurality of structured words and the structurable words corresponding to the medical record information, and after the secondary matching is successful, storing the matched structurable words as new elements into the element library.
5. The method for generating an electronic medical record report according to claim 4, wherein the step of secondarily matching the plurality of structured words with the structurable words corresponding to the medical record information specifically comprises:
identifying keywords in the structured words to obtain structured keywords;
and performing secondary matching on the structured keywords and the structurable words corresponding to the medical record information.
6. The method for generating an electronic medical record report according to claim 4, wherein the step of matching the plurality of structured terms with the structurable terms corresponding to the medical record information for the second time, and storing the matched structurable terms as new elements into the element library after the matching for the second time is successful further comprises:
and after the secondary matching fails, storing the structured words or storing the structured words as new elements into the element library, and matching the structured words with the elements in the current element library again to generate information corresponding to the structured words.
7. The method for generating an electronic medical record report according to claim 2, further comprising:
acquiring an unstructured word corresponding to the voice character; wherein the unstructured words are words in the speech characters except the structured words;
recombining the unstructured terms with the structured terms to generate and display in textual form a new report statement.
8. The method for generating an electronic medical record report according to any one of claims 1-7, further comprising:
and re-acquiring the voice information to update the information corresponding to the generated voice characters.
9. An electronic medical record report generation device, comprising a memory and a processor connected with each other, wherein the memory is used for storing program instructions for implementing the generation method of the electronic medical record report according to any one of claims 1 to 8; the processor is configured to execute the program instructions stored by the memory.
10. A computer-readable storage medium, in which a program file is stored, the program file being executable by a processor to implement the method of generating an electronic medical record report according to any one of claims 1-8.
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