CN103514375A - Electronic medical record rapid recording system based on standard terminology - Google Patents

Abstract

The invention discloses an electronic medical record rapid entry system based on standard terms, which is composed of an intelligent medical input module and a term acquisition module. The entry of electronic medical records realized through this system can standardize the application of clinical terminology from real-world Chinese medicine to the real-world clinical scientific research of Chinese medicine, so as to ensure that clinical work can not only collect information accurately and efficiently, but also generate information that meets quality control requirements. The required clinical electronic medical records, while ensuring the timely acquisition and approval of newly generated TCM clinical terms, facilitates the further standardization and standardized application of new terms.

Description

A Quick Entry System for Electronic Medical Records Based on Standard Terminology

technical field

The invention relates to the technical field of electronic medical records, in particular to a rapid entry system for electronic medical records based on standard terminology.

Background technique

With the development of computer and Internet technology, most hospitals have realized electronic clinical records. At present, there are mainly two ways to enter electronic medical records, that is, the pre-structured medical record entry method and the post-structured medical record entry method. The post-structured input method usually uses natural language to input, which is applied to the input of free-text electronic medical records. This method has a faster input speed, but the information obtained is unstructured. In the later scientific research, it is necessary to analyze the data A large number of operations are processed; the pre-structuring method usually refers to the use of medical record templates to generate electronic medical records, and the use of medical record templates to realize the structuring of electronic medical records before medical record entry is applied to the entry of structured electronic medical records. Compared with the post-structured input method, the pre-structured input speed is generally slower, and as the structured content increases, the input speed will become slower and slower. Usually, when entering structured electronic medical records, terms are quickly entered by prompting term candidates. However, due to differences in the description of the diagnosis and treatment process in clinical and textbooks, many new medical terms will be generated in the actual diagnosis and treatment process. However, these new medical terms can usually only be manually entered into the term base or database, which delays the updating of term candidates. This system implements a rapid entry method for electronic medical records based on standard terms, and at the same time, it can automatically capture and approve new medical terms, store the approved standard terms in the medical terminology database, and quickly update the term prompt items when entering terms , used to support the rapid entry of electronic medical records.

Contents of the invention

The invention proposes a rapid entry system of electronic medical records based on standard terminology. The system decides whether to enter the free-text electronic medical record or the structured electronic medical record through the configuration table. Through term association and common Chinese character input, it can not only ensure the entry efficiency of free-text electronic medical records, but also realize the standardized entry of medical terms in structured medical records. At the same time, through the real-time acquisition of new medical terms, the term prompt items are quickly updated. This system consists of two modules: intelligent medical input and term acquisition.

1. Intelligent medical input module

This module implements a method for rapid input of medical terms in both free-text electronic medical records and structured electronic medical records, and provides users with medical term candidates through pinyin association to achieve the purpose of rapid input. At the same time, when there is no suitable medical terminology, it supports the input of general Chinese characters. This module also provides the basis for real-time acquisition of new medical terms. The module specifically includes seven sub-modules: input module, medical term base, common thesaurus, configuration table, associative algorithm, output module, and update module.

(1) Input module: used for inputting medical terms, the user inputs medical terms at the position of the cursor in the electronic medical record through the keyboard. Similar to general input method display, all candidates are displayed in batches. Firstly, medical terms matching the current input pinyin are searched out from the medical term base, and sorted according to the associative algorithm. Secondly, common words matching the current input pinyin are searched out from the commonly used thesaurus, and all common words are displayed behind the medical term.

(2) Medical term base: It is used to store terms in the medical field and various attributes of terms required for input, and provides a basis for associative input. The terms in the medical term base are stored in the form of a dictionary tree to improve the retrieval and input speed of medical terms. The term base stores the name of the term, the description of the term, the category of the term, the source of the term, the disease to which the term belongs, the document segment where the term appears, the number of occurrences of the term in a certain document segment of a certain disease, whether the term is a standard term, etc. information;

(3) Common thesaurus: store common words and phrases.

(4) Configuration table: Written in XML format, the configuration parameters determine whether to enter the pre-structured medical records or the post-structured medical records, and store various parameters at the same time for the calculation of the association algorithm. The parameters in the configuration table include: the disease type of the medical record, the name of the data element and the document segment to which the data element belongs. The configuration table is mainly used to distinguish the type of the current entry. If the parameter in the configuration table is empty, it means that the free-text electronic medical record is currently being entered; otherwise, the structured electronic medical record is being entered, and the information required by the electronic medical record can be stored in the configuration table. According to the provisions of the Ministry of Health on the structure of electronic medical records, electronic medical records are composed of data elements, data groups, document segments, and clinical documents. Terms are entered in the data element part of the electronic medical record.

(5) Associative algorithm: According to different configuration parameters in the configuration table, the searched terms are calculated according to the associative algorithm to match their matching values, and the matching values are sorted from large to small and then displayed. The associative algorithm formula is as follows:

Match Value(w)＝Freq _ds，dn，s (w)/MAX(Freq(w))+std(w)+ctg _d (w) 1.1

Where w represents a term, MatchValue(w) represents the matching value of the term, Freq _{ds, dn, s} (w)/MAX(Freq(w) represents the term w in a certain disease type ds, a certain diagnosis dn, a certain document frequency of occurrence in segment s;

(6) Output module: For terms that match the currently input Chinese characters or pinyin, the user can use the mouse or keyboard to select the term to be input as the text to be input. If the term to be input is not in the candidate prompt, that is, it cannot be entered according to the system prompt, then it is similar to using a general input method, and the input of Chinese characters is directly performed.

(7) Update module: After the medical records are written, according to the newly entered terms from the medical terminology database, update the number of occurrences of the corresponding terms in the medical terminology database in this disease type and document segment, which will be used for the next association algorithm calculation .

2. Terminology Acquisition Module

This module provides a method for automatically acquiring new clinical medical terms during the entry of free-text electronic medical records or structured electronic medical records, which is used to acquire new clinical terms generated during the entry process of electronic medical records. This module specifically includes five sub-modules, that is, three functional sub-modules and two database sub-modules, namely: term acquisition module, term approval module, deletion module, temporary term base and medical term base.

(1) Terminology Capture Module: The system can automatically acquire new medical terms that appear in electronic medical records through this module. If the value of the data element is not in the medical term base during the entry process of the structured electronic medical record, the system automatically stores the value of the data element into the temporary term base through the term capture module. The information that needs to be stored also includes the name of the document segment where this data element is located, and the number of occurrences of the term in this document segment: if the input value is not in the medical terminology database in the entry of free-text electronic medical records, a new term will be generated through term recognition technology Recognize, store new terms into a temporary termbase.

(2) Terminology approval module: to approve all the terms in the temporary term base, and a user checks each term in the temporary term base, and saves the approved terms into the medical term base. Finally, the temporary term base is directly deleted by the delete module.

(3) Delete module: used to delete the temporary term base.

(4) Medical term base: used to store terms in the medical field required for input.

(5) Temporary term base: It is used to store new terms obtained during the electronic medical record entry process. If it is entered in a structured electronic medical record, it also stores the name of the document segment where the term is located, and the number of times the term appears in this document segment.

The beneficial effect of the present invention is that the system can realize rapid writing of TCM clinical electronic medical records based on standard terms, and at the same time acquire new TCM clinical terms that appear in the process of TCM clinical diagnosis and treatment. The entry of electronic medical records through this system can standardize the application of clinical terminology from real-world traditional Chinese medicine to real-world clinical scientific research work, so as to ensure that clinical work can not only collect information accurately and efficiently, but also generate data that meet quality control requirements. clinical electronic medical records. At the same time, ensure the timely acquisition and approval of newly generated TCM clinical terms, facilitate the further standardization and standardized application of new terms, and can be used for the rapid writing of more TCM clinical electronic medical records.

Description of drawings

Fig. 1 is a system flow chart of the present invention.

Fig. 2 is a flowchart of the intelligent medical input module.

Figure 3 is a flowchart of the term acquisition module.

Detailed ways

Take the symptoms entered in the chief complaint in the structured diabetes medical record as an example.

(1) In the example, it is entered in the structured diabetes medical record, so the content of the configuration table is not empty. The configuration table written in XML language is shown below.

(2) If it is currently necessary to enter the symptom "pain in the left upper limb" in the chief complaint, and the term exists in the medical terminology database. In a certain data element of the main complaint, first use the input module to input "left upper limb", and calculate according to the parameters in the configuration table and the association algorithm, then the first five candidates are "left upper limb pain", "left upper limb numbness", " Left upper limb soreness", "left upper limb cramping pain", "left upper limb tingling pain". Use the input module to display all the candidates, and display the first 5 candidates first.

a) If the current candidate includes the term to be entered, you can select "pain in the left upper limb" by clicking the mouse or the up and down keys on the keyboard and the Enter key, and display it in the main complaint. After entry, update the number of times that "pain in the left upper extremity" appears in the chief complaint of diabetes medical records in the medical terminology database through the update module.

b) If the currently displayed candidate items do not include the term to be entered, select backward through the mouse or keyboard to display the subsequent candidate items until the candidate item containing the term to be input appears. Then select "pain in the left upper limb" by mouse click or keyboard up and down keys and enter key, and display it in the main complaint. After entry, update the number of times that "pain in the left upper extremity" appears in the chief complaint of diabetes medical records in the medical terminology database through the update module.

(3) If the symptom "left upper limb swelling" needs to be entered in the chief complaint, and the term does not exist in the medical terminology database. In a certain data element of the main complaint, first use the input module to input "left upper limb", and calculate according to the parameters in the configuration table and the association algorithm, then the first five candidates are "left upper limb pain", "left upper limb numbness", " Left upper limb soreness", "left upper limb cramping pain", "left upper limb tingling pain". Use the input module to display all the candidates, and display the first 5 candidates first. Since the current term to be entered does not exist in the medical terminology database, after calculation by the association algorithm, there is no "swelling of the left upper limb" among the candidates prompted by the input module, and the input module is directly used to input "swelling". Since this term is not in the term base, the update module is not called, but the new term is acquired through the term acquisition module. After new terms are captured, they are deposited into a temporary termbase. Review all the terms in the temporary term base by invoking the term approval module, and approve all the terms in the temporary term base, that is, a user approves the term "left upper limb swelling" in the temporary term base.

a) If the term is approved, the term will be stored in the medical terminology database. After approving all the terms in the temporary term base, call the delete module to directly delete the temporary term base;

b) If the term has not passed the approval, temporarily put the term in the clinical terminology database. After approving all the terms in the temporary term base, call the delete module to directly delete the temporary term base.

Claims (1)

1. the electronic health record Rapid input system based on standard terminology, is characterized in that, this input system is comprised of intelligent medical science load module and term acquisition module two parts:

(1) intelligent medical science load module: this module realize a kind of both can be at free text type electronic health record, can in structured electronic patient record, carry out the method for fast medical term input again, by phonetic associating mode, for user provides medical terminology candidate item, reach the object of Rapid input; In the situation that there is no suitable medical terminology, support the typing of general Chinese character simultaneously; Intelligence medical science load module comprises load module, medical terminology storehouse, conventional dictionary, allocation list, association's algorithm, output module, seven submodules of update module:

(a) load module: for inputting medical terminology, first from medical terminology library searching, go out the medical terminology matching with current input Pinyin, by association's algorithm, sort, then from conventional dictionary, search out the everyday words matching with current input Pinyin, all everyday words are all presented at after medical terminology;

(b) medical terminology storehouse: for storing the input required term of medical domain and the various attributes of term, the term in medical terminology storehouse is stored in the mode of dictionary tree; In terminology bank, store the title of term, the classification of the description of term, term, disease kind, the term under the source of term, term occurs whether document section, term are the information such as standard terminology at certain sick occurrence number, term of planting in certain document section;

(c) conventional dictionary: storage everyday words and phrase;

(d) allocation list: write with XML form, the parameter of storage comprises: the affiliated sick kind of case history, the title of data element and the document section under data element; If parameter is empty in allocation list, illustrate that current is in the typing of carrying out free text type electronic health record; Otherwise be in the typing of carrying out structured electronic patient record;

(e) association's algorithm: according to configuration parameters different in allocation list, the term searching out is calculated to its matching value by association's algorithm, by showing after the descending sequence of matching value, association's algorithmic formula is:

MatchV alue(w)＝Freq _ds，dn，s(w)/MAX(Freq(w))+std(w)+ctg _d(w)

Wherein w represents certain term, and Match Value (w) represents the matching value of term, Freq _{ds, dn, s}(w)/MAX (Freq (w)) represents the frequency that term w occurs in certain sick ds of kind, certain diagnosis dn, certain document section s;

(f) output module: for searching out the term matching with current input Chinese character or phonetic, user can use mouse or keyboard to select the term that will input as the word that will input; If term to be entered, in candidate's prompting, does not directly carry out the input of Chinese character;

(g) update module: after medical record writing, according to new typing from the term in medical terminology storehouse, upgrade the number of times that corresponding term in medical terminology storehouse is sickly planted, occurred in document section at this, for association's algorithm next time, calculate;

(2) term acquisition module: this module provides a kind of when free text type electronic health record or the typing at structured electronic patient record, automatically carry out the method that new clinical medical term obtains, the new clinical term producing for the Input Process obtaining at electronic health record; Term acquisition module comprises term trapping module, term authorization module, removing module and interim terminology bank and medical terminology storehouse totally 3 function sub-modules and 2 database submodules:

(a) term trapping module: system can be by the new medical terminology occurring in this module automatic acquisition electronic health record; If in the Input Process of structured electronic patient record, the value of data element is not in medical terminology storehouse, and system stores the value of this data element, data element place document name section, term in interim terminology bank in information such as this document section occurrence numbers automatically by term trapping module; If in the typing of free text type electronic health record, the value of input, not in medical terminology storehouse, is carried out new terminology identification by term recognition technology, and new terminology is stored in interim terminology bank;

(b) term authorization module: by a user, all terms in interim terminology bank are authorized, deposited the term by authorization in medical terminology storehouse;

(c) removing module: for deleting interim terminology bank;

(d) medical terminology storehouse: for storing the term of the required medical domain of input;

(e) interim terminology bank: the new terminology obtaining for being stored in electronic health record Input Process, and the document section, term of storing term place are in this document section occurrence number.

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