CN111274237A - Medical data checking and correcting system and method - Google Patents

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

Medical data verification and correction system and method

technical field

The invention relates to the technical field of medical data collection and processing, in particular to a medical data check and correction system and method.

Background technique

The rapid development of Internet technology has promoted the development of intelligent medical management systems, and corresponding databases of medical data have also emerged. Medical data are usually collected by the hospital and then entered into the management system. The staff of the management system department can check, and the check can only be done for obvious errors in medical data, such as typos or obvious disease name errors. Bias in post-analysis results for medical data.

SUMMARY OF THE INVENTION

The present invention aims to provide a medical data verification and correction system to verify and correct medical data.

The medical data verification and correction system in this solution includes input modules located at multiple hospital ends, the input modules are used to input medical data, and the medical data includes patient information, disease types, diagnosis and treatment information and historical data;

Also includes big data service module, processing module and correction module;

The big data service module is used to store medical data corresponding to patient information one-to-one;

The processing module obtains the medical data of the input module, the processing module identifies the wrong data in the medical data entered according to the medical data in the big data service module, and the processing module sends a correction signal to the correction module when identifying the wrong data, so the The processing module sends the correctly entered medical data to the big data service module for storage;

The correction module obtains the correction information of the erroneous data from the input module according to the correction signal, the correction module sends the pass information to the processing module after obtaining the correction information, and the processing module obtains the pass information and opens the input channel of the next medical data of the input module , the correction module sends a closing signal to the processing module when the correction information is not obtained, and the processing module obtains the closing signal and closes the input channel of the next medical data of the input module.

The beneficial effects of this program are:

The hospital enters the medical data through the input module, and then the processing module identifies the wrong data in the entered medical data according to the medical data in the big data service module. In addition, the processing module sends the medical data to the big data service module for storage when the wrong data is not identified, and sends a correction signal to the correction module when the wrong data is identified. When correcting information, open the input channel of the next medical data of the input module, close the input channel of the next medical data of the input module when the correction information is not obtained, and force the correction and input of the wrong data through the input channel of the next medical data. To improve the accuracy of medical data, it is still necessary to make corrections through the input side of the medical data to improve the authenticity of the corrected medical data.

Further, it also includes an adaptive module, the adaptive module is used to learn the numerical range of medical data in the big data service module, and the processing module judges whether the obtained input medical data is located in the time period when the correction information is not obtained. Within the numerical range, the processing module makes a difference between the mean value of the numerical range and the medical data when the medical data is outside the numerical range, and the correction module corrects according to the entered medical data and the difference.

The beneficial effect is: when the corresponding correction information is not obtained within a long time range, the numerical range of the medical data is obtained through self-adaptation, and then the error data and the mean value of the numerical range are corrected by the difference, so as to avoid the failure of the correction for a long time. Delay in data entry.

Further, the processing module sends addition information to the correction module when the input medical data is less than the lower limit of the numerical range, and the correction module adds the input medical data and the difference according to the addition information, and the processing module is in the input medical data. When it is greater than the upper limit of the numerical range, the subtraction information is sent to the correction module, and the correction module subtracts the entered medical data from the difference according to the subtraction information.

The beneficial effects are: according to the position of the entered medical data outside the numerical range, the entered medical data and the difference are corrected, and the probability of the corrected data being located in the numerical range is improved.

Further, the inputting module includes a warning unit, the processing module sends a warning signal to the inputting module when identifying the error data, and the warning unit is configured to send warning information according to the warning signal.

The beneficial effects are: when erroneous data is identified, a warning is sent to the input module through the warning information, and the timeliness of the correction information input is improved.

Further, the processing module acquires the medical data corrected by the correction module and determines whether it is within the numerical range, and the processing module sends a warning signal to the warning unit when the corrected medical data is outside the numerical range.

The beneficial effects are as follows: the medical data corrected by the correction module is judged, and an alarm is given when the corrected medical data is outside the numerical range, indicating that the corrected data does not meet the requirements, and erroneous correction is avoided.

Further, the warning unit includes a vibration pad located below the input module, and the warning unit performs a long-time warning through the vibration of the vibration pad.

The beneficial effects are: vibrating warning is performed through the vibration pad under the input module, and the real-time performance of warning transmission is improved.

Further, it also includes a cleaning module, the processing module adds an entry time to the entered medical data, the cleaning module is used to send a cleaning request to the processing module, and the processing module determines the time difference between the entry time and the current time when receiving the cleaning request. , when the time difference is above the time threshold, 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: adding an entry time to the entered medical data, and judging the storage time of the medical data according to the time difference between the entry time and the current time, and then cleaning up the medical data exceeding the time threshold to avoid the occupation of the medical data that has been accumulated for too long. Too much memory, and at the same time, there is no need to time each piece of medical data, reducing the amount of data processing.

Further, the processing module sends a new signal to the cleaning module when the entered medical data is correct, the cleaning module includes a counting unit, the counting unit counts according to the newly added signal, and the counting unit reaches the number threshold when the count value reaches a threshold. when sending a cleanup request.

The beneficial effects are: every time a piece of medical data is stored, the counting unit performs technology, and when the count value reaches a quantity threshold, a clearing request is triggered, that is, every time a certain amount of medical data is stored, the medical data storage time is judged, and then the cleaning is carried out. , to avoid cleaning too frequently and causing a large amount of data processing.

Further, it also includes an abnormal record module, the processing module sends abnormal information to the abnormal record module when identifying the error data, the abnormal information includes a data type and an error type, and the abnormal record module records the error according to the abnormal information, so The processing module detects the input data type of the input module and the input state of being input, and the processing module sends an error record of the same data type to the input module when detecting that the input state is being input.

The beneficial effect is: when the wrong data is identified, the recording module records the abnormal information, and the same type of data in the input state is sent to the input module to prompt the error record, and the corresponding error record is reminded in advance, which is convenient for the error data to be input. be corrected in a timely manner.

The medical data checking and correcting method uses the above-mentioned medical data checking and correcting system.

Description of drawings

1 is a logical block diagram of a medical data verification and correction system in Embodiment 1 of the present invention;

FIG. 2 is a flowchart of a method for checking and correcting medical data in Embodiment 1 of the present invention.

Detailed ways

The following is further described in detail through specific embodiments.

Example 1

The medical data verification and correction system, as shown in Figure 1, includes an input module located at multiple hospitals, a big data service module located at the backend, a processing module, a correction module, an adaptive module, a cleaning module and an abnormal recording module. Communication and processing module data interaction, processing module interacts with big data service module data through wireless communication, processing module can use back-end cloud processor, big data service module can use cloud big data server, input module can be a hospital laptop, input module It includes a warning unit, and the warning unit includes a vibration pad under the input module.

The medical data verification and correction method based on the above medical data verification and correction system, as shown in Figure 2, includes the following contents:

The medical data is input through the input module at the hospital side and sent to the processing module through the wireless network. For example, wireless WIFI is used for data transmission. Multiple hospitals input medical data through multiple input modules. The medical data includes patient information, disease types, diagnosis and treatment. information and historical data.

After the processing module obtains the entered medical data, it identifies the wrong data according to the medical data stored in the big data service module, and the processing module sends the correct entered medical data to the big data service module for storage. The correction module sends the correction signal, and the correction module obtains the correction information of the wrong data from the input module according to the correction signal. For example, when the input module has the wrong data, the correct value entered is used as the correction information, and the correction module obtains the correction information and sends it to the processing module. information, the processing module obtains the passing information and opens the input channel for the next medical data of the input module. The opening of the input through hole can be used to receive the medical data sent by the input module to the processing module. When the correction module does not obtain the correction information, it sends a closing signal to the processing module. , the processing module obtains the closing signal and closes the entry channel of the next medical data of the entry module. Closing the entry channel may not receive the medical data sent by the entry module 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. When the correction information is not obtained within the timing length, it is judged whether the acquired input medical data is within the value range, that is, when the hospital does not input the correction information in time, the timing length can be set to 30 minutes, and the timing length is determined by the internal timing of the processing module. The unit is timed, and the processing module makes a difference between the mean value of the numerical range and the medical data when the medical data is outside the numerical range. For example, for the mean value of 1, 2, 3, 4, and 5 in the range of 1-5, the mean value can also be calculated with "0.2" as the precision, such as 2, 2.2, 2.4, 2.6, 2.8, 3, etc. in the range of 2-4. The correction module corrects according to the entered medical data and the difference. The correction method is: the processing module sends addition information to the correction module when the entered medical data is less than the lower limit of the value range, and the correction module makes the entered medical data according to the addition information. The data is added to the difference, and the processing module sends subtraction information to the correction module when the entered medical data is greater than the upper limit of the value range, and the correction module subtracts the entered medical data from the difference according to the subtraction information. The module sends a correction prompt signal to the processing module, so that the processing module sends correction prompt information to the input module, for example, the A data has been corrected to X, which can be checked by the hospital again.

When erroneous data is identified, the processing module sends a warning signal to the input module, and the warning unit is used to send warning information according to the warning signal. At the same time, the processing module obtains the medical data corrected by the correction module and judges whether it is within the range of values. Inside, the processing module sends a warning signal to the warning unit when the corrected medical data is outside the value range, and the corrected medical data is still wrong as the triggering condition of the warning, so that the warning unit can give a long-time warning through the vibration of the vibration pad. The unit can use the vibration principle of the existing mobile phone as the vibration principle of the vibration pad.

After the medical data is entered into the processing module, the processing module adds the entry time to the entered medical data, the processing module adds the entry time according to the internal current time, and the processing module sends the new addition to the cleaning module when the entered medical data is correct The signal is counted by the counting unit according to the newly added signal, and when the counting value reaches the number threshold, the counting unit sends a cleaning request to the processing module, that is, the cleaning module is used to send a cleaning request to the processing module, so that the processing module can judge when it receives the cleaning request. The time difference between the entry time and the current time. When the time difference is above the time threshold, that is, when the time difference is greater than or equal to the time threshold, the time threshold can be the storage time set for medical data, such as ten years or five years, from the processing module to the cleaning module. Send the cleaning information, and let the cleaning module clean the medical data in the big data service module according to the cleaning information, and the cleaning module cleans the data by deleting.

When the error data is identified, the processing module sends the exception information to the exception recording module. The exception information includes the data type and the error type. For example, the data type can be liver function detection, and the error type can be numerical error. Error record, for example, it can be recorded as a numerical error of liver function test, the processing module detects the input data type of the input module and the input status being input, and the processing module sends the same data type error to the input module when it detects that the input status is being input record, the error record is displayed by the input module.

The present invention identifies the erroneous data in the entered medical data, corrects the difference between the erroneous data and the average value of the numerical range of the existing correct data, and then judges the corrected medical data. Trigger to give an alarm, improve the accuracy, real-time and authenticity of medical data, and ensure the accuracy of medical data analysis in the later stage; add the entry time to the input data, and then change the time difference between the entry time and the current time after a certain amount of data is entered Make a difference value, and judge whether the difference value exceeds the storage time. There is no need to time each medical data separately, reduce the amount of data calculation, and clean up the medical data that has exceeded the storage time to avoid taking up too much storage space.

Embodiment 2

The difference from the first embodiment is that the input module includes an inertial identification unit, and the inertial identification unit of any hospital is used to identify the inertial error information when entering medical data. The wrong noun is used as a quick input word, and the inertial recognition unit replaces the changed noun by identifying the input module. For example, when the hospital finds that a certain noun is wrong, it is modified and replaced by replacement. The inertial error information includes the wrong noun and the corresponding correct one. Noun, the inertial identification unit sends the inertial error information to the processing module, and the processing module identifies the medical data received from multiple hospitals according to the inertial error information. When the inertial error is identified in the medical data, the processing module sends to the correction module. Correction information, the correction module corrects the inertial error, and at the same time, the processing module sends correction prompt information to the input module with the inertial error, so that the hospital can know the corresponding correction information in time, and at the same time, the hospital can check again to improve the Accuracy of medical data.

The above descriptions are only embodiments of the present invention, and common knowledge such as well-known specific structures and characteristics in the solution are not described too much here. It should be pointed out that for those skilled in the art, some modifications and improvements can be made without departing from the structure of the present invention. These should also be regarded as the protection scope of the present invention, and these will not affect the implementation of the present invention. Effectiveness and utility of patents. The scope of protection claimed in this application shall be based on the content of the claims, and the descriptions of the specific implementation manners in the description can be used to interpret the content of the claims.

Claims (10)

1. A medical data verification and correction system, comprising input modules located at multiple hospital ends, the input modules are used for inputting medical data, and the medical data includes patient information, disease types, diagnosis and treatment information and historical data; It is characterized in that: it also includes a big data service module, a processing module and a correction module; The big data service module is used to store medical data corresponding to patient information one-to-one; The processing module obtains the medical data of the input module, the processing module identifies the wrong data in the medical data entered according to the medical data in the big data service module, and the processing module sends a correction signal to the correction module when identifying the wrong data, so the The processing module sends the correctly entered medical data to the big data service module for storage; The correction module obtains the correction information of the erroneous data from the input module according to the correction signal, the correction module sends the pass information to the processing module after obtaining the correction information, and the processing module obtains the pass information and opens the input channel of the next medical data of the input module , the correction module sends a closing signal to the processing module when the correction information is not obtained, and the processing module obtains the closing signal and closes the input channel of the next medical data of the input module. 2. The medical data verification and correction system according to claim 1, further comprising an adaptive module, the adaptive module is used to learn the numerical range of the medical data in the big data service module, and the processing module When the correction information is not obtained within the time period, it is judged whether the acquired input medical data is within the numerical range, and the processing module makes a difference between the mean value of the numerical range and the medical data when the medical data is outside the numerical range. The entered medical data and the difference are corrected. 3. The medical data verification and correction system according to claim 2, wherein the processing module sends addition information to the correction module when the input medical data is less than the lower limit of the numerical range, and the correction module will record the input data according to the addition information. The medical data is added to the difference, and the processing module sends subtraction information to the correction module when the entered medical data is greater than the upper limit of the numerical range, and the correction module subtracts the entered medical data from the difference according to the subtraction information. 4. The medical data verification and correction system according to claim 3, characterized in that: the input module comprises a warning unit, the processing module sends a warning signal to the input module when identifying the error data, and the warning unit is used for according to the warning Signals to send warning messages. 5. The medical data verification and correction system according to claim 4, wherein the processing module obtains the medical data corrected by the correction module and judges whether it is within the numerical value range, and the processing module is located in the corrected medical data at Send a warning signal to the warning unit when the value is out of range. 6 . The medical data verification and correction system according to claim 4 , wherein the warning unit comprises a vibration pad located below the input module, and the warning unit performs a long-time warning through the vibration of the vibration pad. 7 . 7. The medical data verification and correction system according to claim 1, further comprising a cleaning module, the processing module adds an entry time to the input medical data, and the cleaning module is used to send a cleaning request to the processing module, When the processing module receives the cleaning request, it judges the time difference between the entry time and the current time, and when the time difference is above the time threshold, the processing module sends cleaning information to the cleaning module, and the cleaning module sends the cleaning information to the big data service module according to the cleaning information. of medical data. 8. The medical data verification and correction system according to claim 5, wherein 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, and the counting unit Counting is performed according to the newly added signal, and the counting unit sends a cleaning request when the count value reaches a quantity threshold. 9. The medical data verification and correction system according to claim 1, further comprising an abnormality recording module, and the processing module sends abnormality information to the abnormality recording module when identifying wrong data, and the abnormality information includes a data type and error type, the abnormal recording module performs error recording according to the abnormal information, the processing module detects the input data type of the input module and the input state of being input, and the processing module detects that the input state is being input. Send an error record of the same data type. 10. A medical data verification and correction method using the medical data verification and correction system according to any one of claims 1 to 9.

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