CN112131868A - Clinical trial medical coding method - Google Patents
Clinical trial medical coding method Download PDFInfo
- Publication number
- CN112131868A CN112131868A CN202011011973.7A CN202011011973A CN112131868A CN 112131868 A CN112131868 A CN 112131868A CN 202011011973 A CN202011011973 A CN 202011011973A CN 112131868 A CN112131868 A CN 112131868A
- Authority
- CN
- China
- Prior art keywords
- clinical trial
- words
- coding
- result
- coded
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 62
- 238000011160 research Methods 0.000 claims abstract description 71
- 230000008569 process Effects 0.000 description 7
- 239000003814 drug Substances 0.000 description 6
- 238000007796 conventional method Methods 0.000 description 5
- 229940079593 drug Drugs 0.000 description 5
- 208000037265 diseases, disorders, signs and symptoms Diseases 0.000 description 4
- 206010020772 Hypertension Diseases 0.000 description 3
- 206010055171 Hypertensive nephropathy Diseases 0.000 description 3
- 201000010099 disease Diseases 0.000 description 3
- 238000007792 addition Methods 0.000 description 2
- 238000012217 deletion Methods 0.000 description 2
- 230000037430 deletion Effects 0.000 description 2
- 208000017169 kidney disease Diseases 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 210000000056 organ Anatomy 0.000 description 2
- 206010010164 Hypertension complications Diseases 0.000 description 1
- 210000004204 blood vessel Anatomy 0.000 description 1
- 230000007547 defect Effects 0.000 description 1
- 230000014509 gene expression Effects 0.000 description 1
- 230000036541 health Effects 0.000 description 1
- 210000003734 kidney Anatomy 0.000 description 1
- 210000001365 lymphatic vessel Anatomy 0.000 description 1
- 239000000463 material Substances 0.000 description 1
- 238000002483 medication Methods 0.000 description 1
- 239000000203 mixture Substances 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 208000024891 symptom Diseases 0.000 description 1
- 238000013519 translation Methods 0.000 description 1
- 230000002485 urinary effect Effects 0.000 description 1
- 230000002792 vascular Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/237—Lexical tools
- G06F40/242—Dictionaries
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/35—Clustering; Classification
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/10—Text processing
- G06F40/12—Use of codes for handling textual entities
- G06F40/126—Character encoding
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F40/00—Handling natural language data
- G06F40/20—Natural language analysis
- G06F40/279—Recognition of textual entities
- G06F40/289—Phrasal analysis, e.g. finite state techniques or chunking
-
- 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
- G16H10/20—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for electronic clinical trials or questionnaires
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Physics & Mathematics (AREA)
- Computational Linguistics (AREA)
- Audiology, Speech & Language Pathology (AREA)
- Artificial Intelligence (AREA)
- Epidemiology (AREA)
- Medical Informatics (AREA)
- Primary Health Care (AREA)
- Public Health (AREA)
- Data Mining & Analysis (AREA)
- Databases & Information Systems (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention discloses a clinical trial medical coding method, which comprises the following steps: uploading a source file of clinical trial research, and specifying a column of words to be coded during uploading; matching the words to be coded with the corresponding standard dictionary based on the domain corresponding to the clinical trial research institute to obtain a coding result; and matching the coding result with the words to be coded in the source file, and exporting the words as a complete result. According to the invention, the uploading of the source file, the medical coding and the export of the coding result are sequentially carried out, so that the closed-loop medical coding is realized, and the working efficiency of the medical coding is effectively improved; and based on the coding results obtained for the domain corresponding to the clinical trial research, the research can be classified according to groups, the research in the same domain shares one set of coding results, copying is not needed between the researches, the workload of medical coding is reduced, and the working efficiency is greatly improved.
Description
Technical Field
The invention relates to the technical field of biological medicines, in particular to a clinical trial medicine coding method.
Background
Medical coding is the presentation of various medical events, procedures and medications occurring during clinical trials in standardized languages using a standard medical dictionary, similar to a translation process. The internationally recognized standardized dictionaries used in Medical coding are mainly MedDRA (Medical Dictionary for Regulatory Activities) and WHODrug (World Health Organization Drug Dictionary).
The medical coding process can be coded in a manual coding and tool coding mode, the efficiency of the traditional manual coding mode is low, the coding process is easy to repeat, and the situation of front and back inconsistency is easy to occur. At present, the mode of coding by a tool is popular, however, the coding method of coding by a coding tool has a defect in coding efficiency, and cannot completely meet the requirements of users.
Therefore, in order to improve the efficiency of medical coding, a clinical trial medical coding method is urgently needed.
Disclosure of Invention
The invention aims to provide a clinical trial medical coding method, which solves the problems in the prior art and can effectively improve the efficiency of medical coding.
The invention provides a clinical trial medical coding method, which comprises the following steps:
uploading a source file of clinical trial research, and specifying a column of words to be coded during uploading;
matching the words to be coded with a standard dictionary corresponding to the clinical trial study based on a domain corresponding to the clinical trial study to obtain a coding result;
matching the coding result with the words to be coded in the source file, and exporting the coding result and the source file as a complete result.
The clinical trial medical coding method as described above, wherein preferably, the uploading a source file of a clinical trial study and specifying the column of words to be coded during uploading specifically includes:
selecting a workbook from the source file, selecting a column of words to be coded from the selected workbook, determining a corresponding column of coded words according to the selected column of the words to be coded, and adding non-repeated words in the determined words in the corresponding column into a word list to be coded;
and importing the words to be coded in the word list to be coded.
The clinical trial medical coding method as described above, wherein preferably, the matching the word to be coded with the standard dictionary corresponding to the clinical trial study based on the domain corresponding to the clinical trial study to obtain the coding result specifically includes:
when the source file is uploaded, automatically matching the words to be coded with the words in the domain corresponding to the clinical trial research institute to obtain a first automatic coding result;
automatically matching the words to be coded which cannot be automatically matched with the words in the domain with a standard dictionary corresponding to the clinical trial research to obtain a second automatic coding result;
and manually coding the words to be coded which cannot be automatically matched with the standard dictionary to obtain a manual coding result.
The clinical trial medical coding method as described above, wherein preferably, the matching the coding result with the words to be coded in the source file and exporting the coding result and the source file as a complete result specifically includes:
matching the encoding result with the words to be encoded in the source file, and attaching the encoding result to the back of the source file so as to integrate the encoding result with the source file;
switching the complete result integrating the encoding result and the source file into a target language;
the complete result is derived in the target language.
The clinical trial medical coding method as described above, wherein preferably, the clinical trial medical coding method further comprises:
and upgrading the clinical trial research and the coding results of the words in the domain corresponding to the clinical trial research.
The clinical trial medical coding method as described above, wherein preferably, the upgrading the clinical trial research and the coding result of the term in the domain corresponding to the clinical trial research includes:
uploading the new version standard dictionary;
matching the encoding result of the words in the domain corresponding to the clinical trial research with an original encoding path of an original version standard dictionary and a new encoding path of a new version standard dictionary, wherein if the original encoding path exists in the new encoding path, the encoding result path is successfully matched, and a domain entry upgrading result corresponding to the new version standard dictionary is generated;
and upgrading the encoding result of the words in the clinical trial research according to the domain entry upgrading result and the new version standard dictionary.
The clinical trial medical coding method as described above, wherein preferably, the upgrading the coding results of the words in the clinical trial study according to the domain entry upgrading results and the new version standard dictionary specifically includes:
automatically matching the coding paths of the words in the clinical trial research with the coding paths of the words in the domain corresponding to the clinical trial research to obtain an automatic upgrading result of a first research item;
automatically matching the coding path of the words which cannot be automatically matched with the words in the domain with a standard dictionary corresponding to the clinical trial research to obtain an automatic upgrading result of a second research item;
and manually matching the encoding paths of the words which are not automatically matched with the standard dictionary in the clinical trial research to obtain a research item manual upgrading result.
The clinical trial medical coding method as described above, wherein preferably, the clinical trial medical coding method further comprises:
and managing a domain corresponding to the clinical trial study.
The clinical trial medical coding method as described above, wherein preferably, the clinical trial medical coding method further comprises: managing versions of the standard dictionary.
The clinical trial medical coding method as described above, wherein preferably, the clinical trial medical coding method further comprises:
setting study parameters of the clinical trial study.
The invention provides a clinical trial medical coding method, which realizes closed-loop medical coding and effectively improves the working efficiency of medical coding by sequentially uploading a source file, medical coding and exporting a coding result; and based on the coding results obtained for the domains corresponding to the clinical trial researches, the clinical trial researches can be classified according to groups, the researches in the same domain share one set of coding results, copying is not needed between the researches, the workload of medical coding is reduced, the links of manual participation are reduced, and the working efficiency of the medical coding is greatly improved.
Furthermore, compared with the conventional method that the external source file is matched and combined after the encoding result is exported, the method can export the combined result by one key on the basis of the source file; compared with the conventional method which only can lead out the language corresponding to the standard dictionary used during encoding and needs to be processed outside when the encoding result of another language is needed, the method can lead out the Chinese/English encoding result by one key on the basis of the source file.
Furthermore, the convenience of dictionary upgrading is greatly improved and the working efficiency of medical coding is further improved by sequentially upgrading domain entries and researching entries during the dictionary upgrading.
Drawings
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention will be further described with reference to the accompanying drawings, in which:
fig. 1 is a flowchart of an embodiment of a clinical trial medical coding method provided by the present invention.
Detailed Description
Various exemplary embodiments of the present disclosure will now be described in detail with reference to the accompanying drawings. The description of the exemplary embodiments is merely illustrative and is in no way intended to limit the disclosure, its application, or uses. The present disclosure may be embodied in many different forms and is not limited to the embodiments described herein. These embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the scope of the disclosure to those skilled in the art. It should be noted that: the relative arrangement of parts and steps, the composition of materials, numerical expressions and numerical values set forth in these embodiments are to be construed as merely illustrative, and not as limitative, unless specifically stated otherwise.
As used in this disclosure, "first", "second": and the like, do not denote any order, quantity, or importance, but rather are used to distinguish one element from another. The word "comprising" or "comprises", and the like, means that the element preceding the word covers the element listed after the word, and does not exclude the possibility that other elements are also covered. "upper", "lower", and the like are used merely to indicate relative positional relationships, and when the absolute position of the object being described is changed, the relative positional relationships may also be changed accordingly.
In the present disclosure, when a specific component is described as being located between a first component and a second component, there may or may not be intervening components between the specific component and the first component or the second component. When it is described that a specific component is connected to other components, the specific component may be directly connected to the other components without having an intervening component, or may be directly connected to the other components without having an intervening component.
All terms (including technical or scientific terms) used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this disclosure belongs unless specifically defined otherwise. It will be further understood that terms, such as those defined in commonly used dictionaries, should be interpreted as having a meaning that is consistent with their meaning in the context of the relevant art and will not be interpreted in an idealized or overly formal sense unless expressly so defined herein.
Techniques, methods, and apparatus known to those of ordinary skill in the relevant art may not be discussed in detail, but are intended to be part of the specification where appropriate.
As shown in fig. 1, an embodiment of the present invention provides a clinical trial medical coding method, which specifically includes the following steps in an actual implementation process:
and S1, uploading a source file of the clinical trial research, and specifying the column of the words to be coded during uploading.
In an embodiment of the clinical trial medical coding method of the present invention, the step S1 may specifically include:
step S11, selecting a workbook from the source file, selecting a column of words to be encoded from the selected workbook, determining a corresponding column of encoded words according to the selected column of the words to be encoded, and adding non-repeated words in the determined words in the corresponding column into a word list to be encoded.
Among them, only one list, i.e., a disease or symptom, needs to be specified when using MedDRA dictionary coding, and a medication route and an indication need to be specified when using whodug dictionary coding in addition to a drug name. The source file refers to clinical trial data in clinical trial research, and is usually a file in an Excel format, which workbook (sheet) in Excel is selected to be imported in step S11, and then which column needs to be encoded is selected for the selected sheet, and then non-repeated words in the words corresponding to the column are added to the word list to be encoded. In a specific implementation, in step S11, each word to be encoded is determined, and is added to the word list to be encoded, and at the same time, the word list to be encoded is updated once, if a word in a corresponding column already exists in the word list to be encoded, the word in the corresponding column is not added to the word list to be encoded, and if a word in a corresponding column does not exist in the word list to be encoded, the word in the corresponding column is added to the word list to be encoded, that is, there is no repeated word in the determined word list to be encoded.
And step S12, importing the words to be coded in the word list to be coded.
And importing words to be coded by taking the workbook as a unit.
And S2, uploading a source file of the clinical trial research, and specifying the column of the words to be coded during uploading.
In an embodiment of the clinical trial medical coding method of the present invention, the step S2 may specifically include:
and step S21, when the source file is uploaded, automatically matching the words to be coded with the words in the domain corresponding to the clinical trial research institute to obtain a first automatic coding result.
Where a domain may be understood as a set of words that match a path of a coded result in a dictionary, a clinical trial study may correspond to only one domain, and a domain may correspond to multiple clinical trial studies.
Step S22, automatically matching the words to be coded which are not automatically matched with the words in the domain with the standard dictionary corresponding to the clinical trial research to obtain a second automatic coding result
The standard dictionary corresponding to the clinical trial study includes but is not limited to MedDRA, WHODrug and the like.
And step S23, manually coding the words to be coded which cannot be automatically matched with the standard dictionary to obtain a manual coding result.
When manual coding is carried out, the words to be coded need to be understood, corresponding standard words are searched in a standard dictionary according to semantics, and then the selected results are coded to the appointed words to be coded. Specifically, in the manual encoding, an encoder is caused to retrieve all information (e.g., name, number, level, etc.) relating to a word to be encoded in a standard dictionary, and the retrieval result is stored one key. Therefore, compared with the prior art that the coders record the retrieval results one by one on the standard dictionary official website, the flexibility of retrieval is improved, and the coding efficiency is greatly improved.
Step S3, matching the encoding result with the words to be encoded in the source file, and exporting the encoding result and the source file as a complete result.
In an embodiment of the clinical trial medical coding method of the present invention, the step S3 may specifically include:
step S31, matching the encoding result with the words to be encoded in the source file, and attaching the encoding result to the back of the source file to integrate the encoding result with the source file.
When the coding result and the source file are integrated, the word list to be coded in the source file is compared with the coding columns in the coding result, and if the comparison result is consistent, the coding result is attached to the back of the source file to be used as a complete result. Compared with the conventional method that the external source file needs to be matched and combined after the coding result is exported, the method can export the combined result by one key on the basis of the source file.
Step S32, switching the complete result integrating the coding result and the source file into a target language;
and step S33, exporting the complete result in the target language.
As an example and not limitation, when the target language is switched, the Chinese result or the English result can be selected to be derived, and compared with the conventional language corresponding to the standard dictionary only used when encoding is derived and when the encoding result of another language is needed, the encoding result of Chinese/English needs to be processed externally, the method of the invention is based on the source file and can derive the Chinese/English encoding result by one key. For example, in the current research, coding is performed according to the chinese language, and an english result may be selected during export, and at this time, corresponding results are taken out from an english standard dictionary according to coding paths (e.g., LLT _ Code (low-level language coding path), PT _ Code (first-choice language coding path), SOC _ Code (system organ classification coding path), etc.) in the chinese result, and are integrated into a final export file, thereby greatly improving efficiency.
Further, the clinical trial medical coding method further comprises:
and S4, upgrading the clinical trial research and the coding results of the words in the domain corresponding to the clinical trial research.
The standard dictionary (MedDRA, WHODrug) is usually released 2 times a year, and since clinical research time is generally longer than half a year, most of the time when a new version dictionary is released requires that the coding words of the clinical research be upgraded to the latest version.
In an embodiment of the clinical trial medical coding method of the present invention, the step S4 may specifically include:
step S41, uploading the new version standard dictionary;
step S42, matching the encoding result of the words in the domain corresponding to the clinical trial research with the original encoding path in the original version standard dictionary and the new encoding path in the new version standard dictionary, if the original encoding path exists in the new encoding path, successfully matching the encoding result path, and generating the domain entry upgrading result corresponding to the new version standard dictionary;
illustratively, the word to be encoded is "nephropathy with hypertension", and the encoding result is LLT: "hypertensive nephropathy", PT: "hypertensive nephropathy", HLT: "hypertension complications", HLGT: "vascular hypertension disease", SOC: if the original coding path exists in the new coding path, the coding result path is successfully matched, and a domain entry upgrading result corresponding to a new standard dictionary is generated. If the original encoding path does not exist in the new encoding path, the encoding result path matching is unsuccessful, and the encoding result needs to be updated through the research item updating process. It is assumed that hypertensive nephropathy belongs to a path corresponding to diseases of blood vessels and lymphatic vessels in the MedDRA standard dictionary of version 20, and a path corresponding to diseases of kidney and urinary system in the standard dictionary of version 21, and the original coding path of nephropathy with hypertension does not exist in the new coding path, and therefore, the original coding path is not put in the domain of the new version.
And step S43, upgrading the encoding result of the words in the clinical trial research according to the domain entry upgrading result and the new version standard dictionary.
Further, in an embodiment of the clinical trial medical coding method of the present invention, the step S43 may specifically include:
and S431, automatically matching the coding paths of the words in the clinical trial research and the words in the domain corresponding to the clinical trial research to obtain an automatic upgrading result of the first research item.
And S432, automatically matching the coding path of the words which cannot be automatically matched with the words in the domain with the standard dictionary corresponding to the clinical trial study to obtain the automatic upgrading result of the second study item.
And step S433, manually matching the coding paths of the words which cannot be automatically matched with the standard dictionary in the clinical trial research to obtain a research item manual upgrading result.
After the domain is upgraded, the coding words researched by the clinical trial are upgraded, specifically, the words are matched according to the latest domain word list and the latest dictionary, and the words which cannot be completely matched need to be manually coded again. Dictionary upgrading is a difficult point for a medical coding process, and convenience of dictionary upgrading is greatly improved by sequentially performing domain entry upgrading and research entry upgrading.
Further, the clinical trial medical coding method further comprises:
and step S5, setting research parameters of the clinical trial research.
In particular, relevant parameters are set at the study level, such as the domain used for the study, and the version, language, etc. of each standard dictionary (e.g., MedDRA, WHODrug, etc.). And a refinement setting can be made for each standard dictionary, such as whether or not "master SOC (system organ classification)" coding is adopted for the MedDRA dictionary.
Further, the clinical trial medical coding method further comprises:
and step S6, managing the domain corresponding to the clinical trial research institute.
In particular, the management of the domain is mainly at least one of addition and/or deletion and/or modification and/or querying of the domain. For words which cannot be automatically coded, manual coding is needed, results after manual coding can be uniformly stored in a domain, so that the domain can be understood as a set of results of manually coded word coding, and for words existing in the domain, automatic matching can be performed when automatic coding is performed next time, and manual coding is not needed again.
Different from the traditional manual coding words managed according to research levels, the method can classify the researches according to groups through domain management, the researches using the same domain share a set of manual coding results, the copying is not needed between the researches, and the workload brought by dictionary upgrading is reduced.
Further, the clinical trial medical coding method further comprises:
and step S7, managing the version of the standard dictionary.
Specifically, when managing the version of the standard dictionary, the source file (txt format) downloaded from the MedDRA or whodrum official website is uploaded into the system by setting certain parameters (e.g., whether to use "main SOC" coding, whether to remove duplicate entries from the chinese version dictionary, etc.). Since the two dictionaries differ in structure (e.g., fields, formatting), they need to be stored separately in the background database, but at least one of the additions and/or deletions and/or modifications and/or queries can be made uniformly at the front end in the dictionary version management interface.
Further, the clinical trial medical coding method further comprises:
step S8, the role of the user is managed.
Different roles such as coders and reviewers exist in the medical coding process, tasks which can be performed by each role are different, and detailed task authority configured for each role can be managed through role management.
In summary, the clinical trial medical coding method provided by the embodiment of the invention realizes closed-loop medical coding and effectively improves the working efficiency of medical coding by uploading source files, medical coding, exporting coding results, upgrading dictionaries, managing domains, managing dictionary versions, setting research and managing user roles; and based on the coding results obtained for the domains corresponding to the clinical trial researches, the clinical trial researches can be classified according to groups, the researches in the same domain share one set of coding results, copying is not needed between the researches, the workload of medical coding is reduced, the links of manual participation are reduced, and the working efficiency of the medical coding is greatly improved.
Furthermore, compared with the conventional method that the external source file is matched and combined after the encoding result is exported, the method can export the combined result by one key on the basis of the source file; compared with the conventional method which only can lead out the language corresponding to the standard dictionary used during encoding and needs to be processed outside when the encoding result of another language is needed, the method can lead out the Chinese/English encoding result by one key on the basis of the source file.
Furthermore, the convenience of dictionary upgrading is greatly improved and the working efficiency of medical coding is further improved by sequentially upgrading domain entries and researching entries during the dictionary upgrading.
Thus, various embodiments of the present disclosure have been described in detail. Some details that are well known in the art have not been described in order to avoid obscuring the concepts of the present disclosure. It will be fully apparent to those skilled in the art from the foregoing description how to practice the presently disclosed embodiments.
Although some specific embodiments of the present disclosure have been described in detail by way of example, it should be understood by those skilled in the art that the foregoing examples are for purposes of illustration only and are not intended to limit the scope of the present disclosure. It will be understood by those skilled in the art that various changes may be made in the above embodiments or equivalents may be substituted for elements thereof without departing from the scope and spirit of the present disclosure. The scope of the present disclosure is defined by the appended claims.
Claims (10)
1. A clinical trial medical coding method, comprising:
uploading a source file of clinical trial research, and specifying a column of words to be coded during uploading;
matching the words to be coded with a standard dictionary corresponding to the clinical trial study based on a domain corresponding to the clinical trial study to obtain a coding result;
matching the coding result with the words to be coded in the source file, and exporting the coding result and the source file as a complete result.
2. The clinical trial medical coding method according to claim 1, wherein uploading a source file of a clinical trial study and specifying a column of words to be coded when uploading, specifically comprises:
selecting a workbook from the source file, selecting a column of words to be coded from the selected workbook, determining a corresponding column of coded words according to the selected column of the words to be coded, and adding non-repeated words in the determined words in the corresponding column into a word list to be coded;
and importing the words to be coded in the word list to be coded.
3. The clinical trial medical coding method according to claim 2, wherein the matching the word to be coded with a standard dictionary corresponding to the clinical trial study based on the domain corresponding to the clinical trial study to obtain a coding result specifically includes:
when the source file is uploaded, automatically matching the words to be coded with the words in the domain corresponding to the clinical trial research institute to obtain a first automatic coding result;
automatically matching the words to be coded which cannot be automatically matched with the words in the domain with a standard dictionary corresponding to the clinical trial research to obtain a second automatic coding result;
and manually coding the words to be coded which cannot be automatically matched with the standard dictionary to obtain a manual coding result.
4. The clinical trial medical coding method according to claim 1, wherein the matching the coding result with the words to be coded in the source file and the deriving the coding result and the source file as a complete result specifically comprises:
matching the encoding result with the words to be encoded in the source file, and attaching the encoding result to the back of the source file so as to integrate the encoding result with the source file;
switching the complete result integrating the encoding result and the source file into a target language;
the complete result is derived in the target language.
5. The clinical trial medical coding method according to claim 1, further comprising:
and upgrading the clinical trial research and the coding results of the words in the domain corresponding to the clinical trial research.
6. The clinical trial medical coding method according to claim 5, wherein the upgrading the clinical trial study and the coding results of the words in the domain corresponding to the clinical trial study specifically includes:
uploading the new version standard dictionary;
matching the encoding result of the words in the domain corresponding to the clinical trial research with an original encoding path of an original version standard dictionary and a new encoding path of a new version standard dictionary, wherein if the original encoding path exists in the new encoding path, the encoding result path is successfully matched, and a domain entry upgrading result corresponding to the new version standard dictionary is generated;
and upgrading the encoding result of the words in the clinical trial research according to the domain entry upgrading result and the new version standard dictionary.
7. The clinical trial medical coding method according to claim 6, wherein the upgrading the coding results of the words in the clinical trial study according to the domain entry upgrading results and the new version standard dictionary specifically comprises:
automatically matching the coding paths of the words in the clinical trial research with the coding paths of the words in the domain corresponding to the clinical trial research to obtain an automatic upgrading result of a first research item;
automatically matching the coding path of the words which cannot be automatically matched with the words in the domain with a standard dictionary corresponding to the clinical trial research to obtain an automatic upgrading result of a second research item;
and manually matching the encoding paths of the words which are not automatically matched with the standard dictionary in the clinical trial research to obtain a research item manual upgrading result.
8. The clinical trial medical coding method according to claim 1, further comprising:
and managing a domain corresponding to the clinical trial study.
9. The clinical trial medical coding method according to claim 1, further comprising: managing versions of the standard dictionary.
10. The clinical trial medical coding method according to claim 1, further comprising:
setting study parameters of the clinical trial study.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011011973.7A CN112131868A (en) | 2020-09-22 | 2020-09-22 | Clinical trial medical coding method |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202011011973.7A CN112131868A (en) | 2020-09-22 | 2020-09-22 | Clinical trial medical coding method |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN112131868A true CN112131868A (en) | 2020-12-25 |
Family
ID=73839967
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202011011973.7A Pending CN112131868A (en) | 2020-09-22 | 2020-09-22 | Clinical trial medical coding method |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN112131868A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113705166A (en) * | 2021-07-28 | 2021-11-26 | 浙江太美医疗科技股份有限公司 | Method and device for encoding medical events |
| CN115017326A (en) * | 2022-05-12 | 2022-09-06 | 青岛普瑞盛医药科技有限公司 | Medical coding method and device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130046529A1 (en) * | 2009-12-22 | 2013-02-21 | Health Ewords Pty Ltd. | Method and System for Classification of Clinical Information |
| CN105069123A (en) * | 2015-08-13 | 2015-11-18 | 易保互联医疗信息科技（北京）有限公司 | Automatic coding method and system for Chinese surgical operation information |
| US20180246876A1 (en) * | 2017-02-27 | 2018-08-30 | Medidata Solutions, Inc. | Apparatus and method for automatically mapping verbatim narratives to terms in a terminology dictionary |
| CN108920453A (en) * | 2018-06-08 | 2018-11-30 | 医渡云（北京）技术有限公司 | Data processing method, device, electronic equipment and computer-readable medium |
| CN109408820A (en) * | 2018-10-17 | 2019-03-01 | 长沙瀚云信息科技有限公司 | A kind of medical terminology mapped system and method, equipment and storage medium |
| CN110705214A (en) * | 2019-08-27 | 2020-01-17 | 天津开心生活科技有限公司 | Automatic coding method and device |
-
2020
- 2020-09-22 CN CN202011011973.7A patent/CN112131868A/en active Pending
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20130046529A1 (en) * | 2009-12-22 | 2013-02-21 | Health Ewords Pty Ltd. | Method and System for Classification of Clinical Information |
| CN105069123A (en) * | 2015-08-13 | 2015-11-18 | 易保互联医疗信息科技（北京）有限公司 | Automatic coding method and system for Chinese surgical operation information |
| US20180246876A1 (en) * | 2017-02-27 | 2018-08-30 | Medidata Solutions, Inc. | Apparatus and method for automatically mapping verbatim narratives to terms in a terminology dictionary |
| CN108920453A (en) * | 2018-06-08 | 2018-11-30 | 医渡云（北京）技术有限公司 | Data processing method, device, electronic equipment and computer-readable medium |
| CN109408820A (en) * | 2018-10-17 | 2019-03-01 | 长沙瀚云信息科技有限公司 | A kind of medical terminology mapped system and method, equipment and storage medium |
| CN110705214A (en) * | 2019-08-27 | 2020-01-17 | 天津开心生活科技有限公司 | Automatic coding method and device |
Non-Patent Citations (2)
| Title |
|---|
| 李庆娜等: "研制中医学不良反应编码术语集", 中国循证医学杂志, vol. 18, no. 11, pages 1169 - 1172 * |
| 陆梦洁;刘玉秀;: "MedDRA及其在不良事件分析中的应用", 药学学报, no. 11, pages 38 - 43 * |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113705166A (en) * | 2021-07-28 | 2021-11-26 | 浙江太美医疗科技股份有限公司 | Method and device for encoding medical events |
| CN115017326A (en) * | 2022-05-12 | 2022-09-06 | 青岛普瑞盛医药科技有限公司 | Medical coding method and device |
| CN115017326B (en) * | 2022-05-12 | 2023-08-18 | 青岛普瑞盛医药科技有限公司 | Medical coding method and device |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US20210090693A1 (en) | Clinical data management system | |
| Meystre et al. | Automation of a problem list using natural language processing | |
| US8589424B1 (en) | Method and system for accurate medical-code translation | |
| US10878010B2 (en) | System and method for clinical trial candidate matching | |
| US9147040B2 (en) | Point-in-time query system | |
| CN112131868A (en) | Clinical trial medical coding method | |
| US20080162426A1 (en) | Find features | |
| US20180357381A1 (en) | Method and System for Generating Persistent Local Instances of Ontological Mappings | |
| KR20230040572A (en) | System for standardized processing clinical trial data by therapeutic area | |
| CN117766084A (en) | Clinical trial data audit report (DRR) generation method, system and storage medium | |
| CN112131867A (en) | Clinical trial medical coding system | |
| CN117539893A (en) | Data processing method, medium, device and computing equipment | |
| CN111177117B (en) | Data processing method for traditional Chinese medicine medical records | |
| Annane et al. | Multilingual mapping reconciliation between english-french biomedical ontologies | |
| WO2017132145A1 (en) | System and method for optimizing electronic medical terminology post-coordination coding | |
| CN103229170B (en) | Standardized database access system and method | |
| WO2006005715A1 (en) | System for interrogating heterogeneous databases and method for interrogation | |
| GB2573512A (en) | Database and associated method | |
| Sadegh-Zadeh et al. | Medical linguistics | |
| EP2031521A1 (en) | System and method for translating the content of a terminological database | |
| Klann et al. | A numerical similarity approach for using retired Current Procedural Terminology (CPT) codes for electronic phenotyping in the Scalable Collaborative Infrastructure for a Learning Health System (SCILHS) | |
| Beale et al. | The GEHR Object Model Architecture | |
| Niyonkuru et al. | Leveraging Generative AI to Accelerate Biocuration of Medical Actions for Rare Disease | |
| CN117976116A (en) | Intelligent analysis method for accelerating rehabilitation surgical data | |
| Unni et al. | SPHN Strategy to Unravel the Semantic Drift Between Versions of Standard Terminologies |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| WD01 | Invention patent application deemed withdrawn after publication |
Application publication date: 20201225 |
|
| WD01 | Invention patent application deemed withdrawn after publication |