CN111274237A - Medical data checking and correcting system and method - Google Patents
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Abstract
The invention relates to the technical field of medical data acquisition and processing, in particular to a medical data checking and correcting system and a method, wherein the system comprises a big data service module, a processing module, a correcting module and entry modules positioned at a plurality of hospital ends, wherein the entry modules are used for entering medical data, and the medical data comprises patient information, disease types, diagnosis and treatment information and historical data; the method comprises the steps of identifying error data recorded in medical data and then carrying out correction reminding. The invention forcibly corrects and records the error data through the recording channel of the next medical data, improves the accuracy of the medical data, and also corrects the error data through the recording party of the medical data, thereby improving the authenticity of the corrected medical data.
Description
Technical Field
The invention relates to the technical field of medical data acquisition and processing, in particular to a medical data checking and correcting system and method.
Background
The rapid development of the internet technology promotes the development of an intelligent medical management system, a corresponding database of medical data is generated at the same time, the medical data is usually collected by a hospital and then recorded into the management system, the medical data is stored by the management system, and finally, the staff at the management system checks the medical data, and the checking can only be performed on obvious errors of the medical data, such as wrongly written characters or obvious wrong names of diseases, and when more medical data are correlated, the errors of the medical data are difficult to check, so that the later analysis result deviation of the medical data is caused.
Disclosure of Invention
The invention aims to provide a medical data checking and correcting system for checking and correcting medical data.
The medical data checking and correcting system in the scheme comprises entry modules positioned at a plurality of hospital ends, wherein the entry modules are used for entering medical data, and the medical data comprises patient information, disease types, diagnosis and treatment information and historical data;
the system also comprises a big data service module, a processing module and a correction module;
the big data service module is used for storing medical data corresponding to the patient information one by one;
the processing module acquires medical data recorded into the module, identifies error data recorded into the medical data according to the medical data in the big data service module, sends a correction signal to the correction module when identifying the error data, and sends the correct recorded medical data to the big data service module for storage;
the correction module acquires correction information of error data from the entry module according to the correction signal, the correction module transmits the pass information to the processing module after acquiring the correction information, the processing module acquires the pass information and opens an entry channel of next medical data of the entry module, the correction module transmits a closing signal to the processing module when not acquiring the correction information, and the processing module acquires the closing signal and closes the entry channel of the next medical data of the entry module.
The beneficial effect of this scheme is:
the hospital side records medical data through the recording module, then the processing module identifies error data in the recorded medical data according to the medical data in the big data service module, for example, a certain item of inspection data is a range A-B, the recorded medical data is positioned outside the range, the processing module sends the medical data to the big data service module for storage when the error data is not identified, sends a correction signal to the correction module when the error data is identified, the correction module acquires correction information of the recording module, opens a recording channel of next medical data of the recording module when the correction information is acquired, closes the recording channel of the next medical data of the recording module when the correction information is not acquired, forcibly corrects and records the error data through the recording channel of the next medical data, improves the accuracy of the medical data, or corrects through the recording side of the medical data, improving the authenticity of the corrected medical data.
The medical data processing system further comprises an adaptive module, wherein the adaptive module is used for learning the numerical range of the medical data in the big data service module, the processing module judges whether the acquired recorded medical data is located in the numerical range when the correction information is not acquired within a fixed time, the processing module makes a difference between the average value of the numerical range and the medical data when the medical data is located outside the numerical range, and the correction module corrects the medical data according to the recorded medical data and the difference.
The beneficial effects are that: when corresponding correction information is not acquired within a timing long range, the numerical range of the medical data is acquired in a self-adaptive mode, and then the difference value between the error data and the average value of the numerical range is corrected, so that the problem that data entry is delayed due to the fact that correction is not performed for a long time is avoided.
Further, the processing module sends addition information to the correction module when the recorded medical data is smaller than the lower limit of the numerical range, the correction module adds the recorded medical data and the difference value according to the addition information, the processing module sends subtraction information to the correction module when the recorded medical data is larger than the upper limit of the numerical range, and the correction module subtracts the recorded medical data and the difference value according to the subtraction information.
The beneficial effects are that: and correcting the recorded medical data and the difference value according to the position of the recorded medical data outside the numerical range, so that the probability that the corrected data is positioned in the numerical range is improved.
Furthermore, type module includes the unit of warning, processing module sends the signal of warning to type module at discernment error data, the unit of warning is used for sending the information of warning according to the signal of warning.
The beneficial effects are that: and when the error data is identified, warning is carried out on the input module through the warning information, so that the timeliness of inputting the correction information is improved.
Further, the processing module acquires the medical data corrected by the correction module and judges whether the medical data is located in a numerical range, and the processing module sends a warning signal to the warning unit when the corrected medical data is located outside the numerical range.
The beneficial effects are that: and judging the medical data corrected by the correction module, and warning when the corrected medical data is out of the numerical range, so that the corrected data does not meet the requirements, and the wrong correction is avoided.
Further, the unit of warning is including being located the vibrations pad of type-in module below, the unit of warning carries out regularly long warning through the vibrations of vibrations pad.
The beneficial effects are that: vibrations are filled up through the vibrations of typing in module below and are shaken and warn, improve the real-time of warning transmission.
The processing module is used for adding entry time to the entered medical data, the cleaning module is used for sending a cleaning request to the processing module, the processing module judges the time difference between the entry time and the current time when receiving the cleaning request, when the time difference is more than a time threshold value, the processing module sends cleaning information to the cleaning module, and the cleaning module cleans the medical data in the big data service module according to the cleaning information.
The beneficial effects are that: the method comprises the steps of adding entry time to entered medical data, judging the storage duration of the medical data according to the time difference between the entry time and the current time, cleaning the medical data exceeding a time threshold value, avoiding that too long-term medical data occupy too much memory, and meanwhile, timing each piece of medical data is not needed, so that the data processing amount is reduced.
Further, the processing module sends a new signal to the cleaning module when the entered medical data is correct, the cleaning module comprises a counting unit, the counting unit counts according to the new signal, and the counting unit sends a cleaning request when the counting value reaches a number threshold.
The beneficial effects are that: the counting unit carries out technology every time one item of medical data is stored, when the counting value reaches a quantity threshold value, a cleaning request is triggered to be sent, namely, the storage time of the medical data is judged every time a certain amount of medical data is stored, then cleaning is carried out, and the problem that the data processing capacity is large due to too frequent cleaning is avoided.
The recording system further comprises an abnormal recording module, the processing module sends abnormal information to the abnormal recording module when identifying the error data, the abnormal information comprises a data type and an error type, the abnormal recording module carries out error recording according to the abnormal information, the processing module detects the recorded data type and the recorded state of the recording module, and the processing module sends the error record of the same data type to the recording module when detecting that the recorded state is the recorded state.
The beneficial effects are that: when error data are identified, the recording module records abnormal information, and sends error records to the recording module for prompting when the same type of data in the recording state are recorded, so that corresponding error records are prompted in advance, and the error data can be corrected in time when being recorded conveniently.
The medical data checking and correcting method is applied to the medical data checking and correcting system.
Drawings
FIG. 1 is a logic diagram of a system for medical data verification and correction according to an embodiment of the present invention;
fig. 2 is a flowchart of a method for checking and correcting medical data according to an embodiment of the present invention.
Detailed Description
The following is a more detailed description of the present invention by way of specific embodiments.
Example one
A medical data verification and correction system, as shown in fig. 1: including the type module that is located a plurality of hospital ends, be located the big data service module of back end, processing module, the correction module, self-adaptation module, clearance module and abnormal recording module, type the module and pass through wireless communication and processing module data interaction, processing module passes through wireless communication and big data service module data interaction, the high in the clouds treater of the available backstage of processing module, the big data service module of available high in the clouds big data server, type the module can be the notebook computer of hospital end, type the module including the unit of warning, the unit of warning is including being located the vibrations pad of type the module below.
As shown in fig. 2, the medical data verification and correction method based on the medical data verification and correction system includes the following steps:
medical data is input through the entry module that is located the hospital end and is sent to processing module through the wireless network, carries out data transmission like wireless WIFI, and a plurality of hospitals side carries out medical data entry through a plurality of entry modules, and medical data includes patient information, disease kind, diagnosis treatment information and historical data.
The processing module acquires the recorded medical data and then identifies the error data according to the medical data stored in the big data service module, the processing module sends the correct recorded medical data to the big data service module for storage, the processing module sends a correction signal to the correction module when identifying the error data, the correction module acquires the correction information of the error data from the recording module according to the correction signal, for example, the correct numerical value recorded by the recording module when the recording module has the error data is used as the correction information, the correction module acquires the correction information and sends the passing information to the processing module, the processing module acquires the passing information and opens a recording channel of the next medical data of the recording module, the opening recording through hole can be used for receiving the medical data sent by the recording module to the processing module, the correction module sends a closing signal to the processing module when not acquiring the correction information, the processing module acquires the closing signal and closes the recording channel of the next medical data of the recording module, closing the entry channel may be not receiving medical data that the entry module sent to the processing module.
After the processing module sends the correction signal, the adaptive module learns the value range of the medical data in the big data service module, for example, the value range taking the maximum value of the medical data in the big data service module as the upper limit and the minimum value as the lower limit, the processing module judges whether the acquired recorded medical data is in the value range when the correction information is not acquired within the timing length, that is, when the correction information is not timely input by the hospital end, the timing length can be set to thirty minutes, the timing length is timed by a timing unit inside the processing module, the processing module makes a difference between the average value of the value range and the medical data when the medical data is out of the value range, and the average value of the value range is calculated with the precision of different data, for example, the average value calculation with the precision of '1', for example, the average value calculation with the precision of 1, 2, 3, 4, and 5 within, 5, the mean value can also be calculated with the precision of "0.2", for example, the mean values of 2, 2.2, 2.4, 2.6, 2.8, 3 and the like in the range of 2-4, the correction module corrects according to the recorded medical data and the difference value, and the correction method comprises the following steps: the processing module sends addition information to the correction module when the recorded medical data is smaller than the lower limit of the numerical range, the correction module adds the recorded medical data and the difference value according to the addition information, the processing module sends subtraction information to the correction module when the recorded medical data is larger than the upper limit of the numerical range, the correction module subtracts the recorded medical data and the difference value according to the subtraction information, after correction is completed, the correction module sends a correction prompt signal to the processing module, and the processing module sends correction prompt information to the recording module, for example, the A data is corrected to be X, so that the hospital side can check again.
When the error data is identified, the processing module sends a warning signal to the input module in the process of identifying the error data, the warning unit is used for sending warning information according to the warning signal, meanwhile, the processing module acquires the medical data corrected by the correction module and judges whether the medical data is located in a numerical range, the processing module sends the warning signal to the warning unit when the corrected medical data is located outside the numerical range, the corrected medical data is also used as a triggering condition for warning, the warning unit is used for warning regularly and long through the vibration of the vibration pad, and the warning unit can use the vibration principle of the existing mobile phone as the vibration principle of the vibration pad.
After medical data is input into the processing module, the processing module adds input time to the input medical data, the processing module adds input time according to the internal current time, the processing module sends a newly added signal to the cleaning module when the input medical data is correct, the counting unit counts according to the newly added signal, the counting unit sends a cleaning request to the processing module when the counting value reaches a quantity threshold value, namely the cleaning module is used for sending a cleaning request to the processing module, the processing module judges the time difference between the input time and the current time when receiving the cleaning request, when the time difference is more than the time threshold value and is more than or equal to the time threshold value, the time threshold value can be the storage time set for the medical data, for example, ten years or five years, the processing module sends cleaning information to the cleaning module, and the cleaning module cleans the medical data in the big data service module according to the cleaning information, the cleaning module cleans data in a deleting mode.
When error data is identified, sending abnormal information to an abnormal recording module by a processing module, wherein the abnormal information comprises a data type and an error type, for example, the data type can be liver function detection, the error type can be numerical error, the abnormal recording module carries out error recording according to the abnormal information, for example, the numerical error which can be recorded as liver function detection, the processing module detects the recorded data type and the recorded state of the recording module, the processing module sends the error recording of the same data type to the recording module when detecting that the recorded state is the recorded state, and the recording module displays the error recording.
The method identifies the error data in the input medical data, corrects the difference between the error data and the mean value of the numerical range of the existing correct data, judges the corrected medical data, and triggers warning when the corrected medical data is incorrect, so that the accuracy, the real-time property and the authenticity of the medical data are improved, and the accuracy of analyzing the medical data in the later period is ensured; the method comprises the steps of adding entry time to entry data, then making a difference between the entry time and the current time after a certain amount of data is entered, judging whether the difference exceeds the storage time, not timing each item of medical data independently, reducing the data calculation amount, cleaning the medical data exceeding the storage time, and avoiding occupying too much storage space.
Example two
The difference with the first embodiment is that the entry module includes an inertia identification unit, the inertia identification unit of any hospital side is used to identify inertia error information when entering medical data, for example, when a noun is entered and error is first input, the incorrect noun is used as a fast input word, the inertia identification unit replaces a changed noun through the identification entry module, for example, when the hospital side finds that a noun is error, the change replacement is performed in a replacement mode, the inertia error information includes an error noun and a corresponding correct noun, the inertia identification unit sends the inertia error information to the processing module, the processing module identifies the received medical data of multiple hospitals according to the inertia error information, when it is identified that the medical data has an inertia error, the processing module sends correction information to the correction module, and the correction module corrects the inertia error, meanwhile, the processing module sends correction prompt information to the input module with the inertia error, so that the hospital side can know the corresponding correction information in time and check the correction information again, and the accuracy of medical data is improved.
The foregoing is merely an example of the present invention and common general knowledge of known specific structures and features of the embodiments is not described herein in any greater detail. It should be noted that, for those skilled in the art, without departing from the structure of the present invention, several changes and modifications can be made, which should also be regarded as the protection scope of the present invention, and these will not affect the effect of the implementation of the present invention and the practicability of the patent. The scope of the claims of the present application shall be determined by the contents of the claims, and the description of the embodiments and the like in the specification shall be used to explain the contents of the claims.
Claims (10)
1. The medical data checking and correcting system comprises entry modules positioned at a plurality of hospital ends, wherein the entry modules are used for entering medical data, and the medical data comprises patient information, disease types, diagnosis and treatment information and historical data;
the method is characterized in that: the system also comprises a big data service module, a processing module and a correction module;
the big data service module is used for storing medical data corresponding to the patient information one by one;
the processing module acquires medical data recorded into the module, identifies error data recorded into the medical data according to the medical data in the big data service module, sends a correction signal to the correction module when identifying the error data, and sends the correct recorded medical data to the big data service module for storage;
the correction module acquires correction information of error data from the entry module according to the correction signal, the correction module transmits the pass information to the processing module after acquiring the correction information, the processing module acquires the pass information and opens an entry channel of next medical data of the entry module, the correction module transmits a closing signal to the processing module when not acquiring the correction information, and the processing module acquires the closing signal and closes the entry channel of the next medical data of the entry module.
2. The medical data collation modification system according to claim 1, wherein: the medical data processing system is characterized by further comprising a self-adaptive module, wherein the self-adaptive module is used for learning the numerical range of the medical data in the big data service module, the processing module judges whether the acquired recorded medical data is located in the numerical range when the correction information is not acquired within a fixed time, the processing module makes a difference value between the mean value of the numerical range and the medical data when the medical data is located out of the numerical range, and the correction module corrects the medical data according to the recorded medical data and the difference value.
3. The medical data collation modification system according to claim 2, wherein: the processing module sends addition information to the correction module when the recorded medical data is smaller than the lower limit of the numerical range, the correction module adds the recorded medical data and the difference value according to the addition information, the processing module sends subtraction information to the correction module when the recorded medical data is larger than the upper limit of the numerical range, and the correction module subtracts the recorded medical data and the difference value according to the subtraction information.
4. The medical data collation modification system according to claim 3, wherein: the input module comprises an alarm unit, the processing module sends an alarm signal to the input module when identifying error data, and the alarm unit is used for sending alarm information according to the alarm signal.
5. The medical data collation modification system according to claim 4, wherein: the processing module acquires the medical data corrected by the correction module and judges whether the medical data is located in the numerical range, and the processing module sends a warning signal to the warning unit when the corrected medical data is located outside the numerical range.
6. The medical data collation modification system according to claim 4, wherein: the warning unit is including being located the vibrations pad of type module below, the unit of warning carries out regularly long warning through the vibrations of vibrations pad.
7. The medical data collation modification system according to claim 1, wherein: the processing module adds entry time to the entered medical data, the cleaning module is used for sending a cleaning request to the processing module, the processing module judges the time difference between the entry time and the current time when receiving the cleaning request, when the time difference is more than a time threshold value, the processing module sends cleaning information to the cleaning module, and the cleaning module cleans the medical data in the big data service module according to the cleaning information.
8. The medical data collation modification system according to claim 5, wherein: the processing module sends a new adding signal to the cleaning module when the input medical data are correct, the cleaning module comprises a counting unit, the counting unit counts according to the new adding signal, and the counting unit sends a cleaning request when the counting value reaches a number threshold value.
9. The medical data collation modification system according to claim 1, wherein: the recording device comprises a recording module and a processing module, wherein the recording module is used for recording the input data type of the input module and the input state of the input module, the processing module is used for sending abnormal information to the recording module when identifying error data, the abnormal information comprises the data type and the error type, the abnormal recording module is used for recording the error according to the abnormal information, the processing module is used for detecting the input data type and the input state of the input module, and the processing module is used for sending the error record of the same data type to the input module when detecting that the input state is the input state.
10. A medical data collation modification method using the medical data collation modification system according to any one of claims 1 to 9.
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Cited By (2)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113052556A (en) * | 2021-03-30 | 2021-06-29 | 贵州数智联云工程科技有限公司 | Three-dimensional-based auxiliary approval process management system and method |
CN113066551A (en) * | 2021-04-13 | 2021-07-02 | 常州市第二人民医院 | Guiding type electronic medical record inputting system and method |
Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4672537A (en) * | 1976-09-07 | 1987-06-09 | Tandem Computers Incorporated | Data error detection and device controller failure detection in an input/output system |
US20120239996A1 (en) * | 2011-03-20 | 2012-09-20 | Fujitsu Limited | Memory controller, information processing apparatus and method of controlling memory controller |
CN107403526A (en) * | 2017-08-03 | 2017-11-28 | 恒银金融科技股份有限公司 | Abnormity correction method for banknote recognition module of circulating movement |
CN107506578A (en) * | 2017-08-09 | 2017-12-22 | 浙江工业大学 | Clinical monitoring system of medical health that multichannel wireless data communication was handled based on ARM |
CN109785921A (en) * | 2018-12-03 | 2019-05-21 | 南方医科大学南方医院 | A kind of medical data input method, system, device and storage medium |
CN110600090A (en) * | 2019-08-23 | 2019-12-20 | 和宇健康科技股份有限公司 | Clinical examination data processing method, device, medium and terminal equipment |
-
2020
- 2020-01-20 CN CN202010063293.3A patent/CN111274237A/en active Pending
Patent Citations (6)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
US4672537A (en) * | 1976-09-07 | 1987-06-09 | Tandem Computers Incorporated | Data error detection and device controller failure detection in an input/output system |
US20120239996A1 (en) * | 2011-03-20 | 2012-09-20 | Fujitsu Limited | Memory controller, information processing apparatus and method of controlling memory controller |
CN107403526A (en) * | 2017-08-03 | 2017-11-28 | 恒银金融科技股份有限公司 | Abnormity correction method for banknote recognition module of circulating movement |
CN107506578A (en) * | 2017-08-09 | 2017-12-22 | 浙江工业大学 | Clinical monitoring system of medical health that multichannel wireless data communication was handled based on ARM |
CN109785921A (en) * | 2018-12-03 | 2019-05-21 | 南方医科大学南方医院 | A kind of medical data input method, system, device and storage medium |
CN110600090A (en) * | 2019-08-23 | 2019-12-20 | 和宇健康科技股份有限公司 | Clinical examination data processing method, device, medium and terminal equipment |
Non-Patent Citations (2)
Title |
---|
ZHIPENG CAI;: "Design and experimental verification of a recording scheme for body surface potential mapping", 《2017 CHINESE AUTOMATION CONGRESS (CAC)》 * |
孙能胜: "北京市监狱管理局中心医院信息系统的设计与应用", 《信息科技辑》 * |
Cited By (3)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN113052556A (en) * | 2021-03-30 | 2021-06-29 | 贵州数智联云工程科技有限公司 | Three-dimensional-based auxiliary approval process management system and method |
CN113052556B (en) * | 2021-03-30 | 2024-09-27 | 贵州数智联云工程科技有限公司 | Three-dimensional-based auxiliary approval process management system and method |
CN113066551A (en) * | 2021-04-13 | 2021-07-02 | 常州市第二人民医院 | Guiding type electronic medical record inputting system and method |
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