NFC-based patient data rapid collection method and system

Abstract

The present invention discloses a method and system for rapid collection of patient data based on NFC, and relates to the technical field of medical data collection. The method includes generating a unique electronic file for the patient, and binding the patient's identity information and basic health data through an NFC tag; presetting the collection parameters according to the patient's condition, including data type, priority and collection frequency, and writing the hierarchical configuration into the NFC tag; when the patient's collection device is close to the NFC tag, the parameter configuration stored in the tag is automatically triggered, and the corresponding sensor is activated; the NFC technology is used to realize batch reading of the data of the sensor, and the data of multiple time points are transmitted to the collection device at one time; while the data is transmitted, the collected physiological data is detected by a preset threshold to see if there is an abnormality, and the over-limit data is automatically marked. The present invention not only improves the efficiency and accuracy of patient data collection, but also enhances the security and practicality of the data.

Description

Technical Field

[0001] The present invention relates to the technical field of medical data collection, and in particular to a method and system for quickly collecting patient data based on NFC. Background Art

[0002] With the rapid development of medical information technology, the collection, storage and management of patient data has become an important research direction in the medical industry. The traditional method of collecting patient data relies on manual entry and paper file management, which is not only inefficient, but also prone to data omissions and entry errors. Especially in cases of high patient mobility or emergency situations, it is difficult to obtain complete health information in a timely manner.

[0003] In recent years, Near Field Communication (NFC) technology has become an important research direction in the field of patient identification and health data management due to its short distance, high security and convenience. By binding patient identity information with NFC tags and using NFC reading devices to achieve fast data transmission, it can not only significantly improve the efficiency of patient data collection, but also provide timely and accurate data support for clinical diagnosis and subsequent treatment of medical institutions.

[0004] However, the current patient data collection system still has many shortcomings in practical applications. For example, the existing system is usually unable to effectively verify the consistency between the patient's identity information and health data, and it is easy to cause data mismatch due to identity binding errors, thus affecting the accuracy of the diagnosis and treatment process; the real-time and integrity of data collection are not high, especially when processing large quantities of data, it is easy to have data omissions or transmission delays, and it cannot meet the needs of high-frequency data collection when the patient's condition changes rapidly; for the collected physiological data, the existing system mostly adopts a passive anomaly detection mode, and fails to provide timely feedback on abnormal data and supplement the scheduling of collection tasks. Especially in the scenario of multi-sensor collaborative collection, there is a lack of flexible configuration of collection parameters, making it difficult to achieve efficient task allocation and abnormal management. Summary of the invention

[0005] In view of the problems existing in the above-mentioned background technology, the present invention proposes a method and system for quickly collecting patient data based on NFC.

[0006] Therefore, the problem to be solved by the present invention is how to ensure the integrity and consistency of input information and the independence of multiple sensor data.

[0007] In order to solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a method for quickly collecting patient data based on NFC, which includes generating a unique electronic file for the patient, binding the patient's identity information and basic health data through an NFC tag, verifying the associated code in the NFC tag through an NFC reading device, matching the patient's identity information data and basic health data stored in the patient information database, and if the matching score M is greater than or equal to the minimum matching threshold, it is proved that the data is complete and correct, and a prompt for successful tag binding is output to complete the generation and binding of the patient's electronic file; if the matching score M is less than the minimum matching threshold, it is proved that the data is inconsistent with the NFC tag record; preset collection parameters according to the patient's condition, including data type, priority, etc. The NFC tag automatically triggers the parameter configuration stored in the tag and activates the corresponding sensor. The NFC technology is used to read the data of the sensor in batches, and the data of multiple time points are transmitted to the acquisition device at one time. While the data is being transmitted, the preset threshold is used to detect whether the collected physiological data is abnormal, and the over-limit data is automatically marked. For the data marked as abnormal, the acquisition device automatically generates a supplementary acquisition task instruction, including the target sensor, supplementary time interval and acquisition frequency. The supplementary acquisition task instruction is sent to the corresponding sensor as soon as possible after the abnormal data is detected, and the task status is displayed in real time.

[0009] As a preferred solution of the NFC-based patient data rapid collection method of the present invention, wherein: the patient identity information includes name, ID number, date of birth and health record number;

[0010] Based on the patient identity information, a logical consistency check is performed using a data integrity check formula to obtain an integrity score. If the integrity score is less than the integrity threshold, it proves that there are missing items or inconsistent items. The data integrity check formula is as follows: ;in, For completeness score, is the logical correctness indicator of the patient's i-th identity information field, Indicates that the field is valid. Indicates that the field is invalid; is the weight of the field, is the anomaly detection factor, is the number of data anomaly items, indicating the number of abnormal fields in the current data, and n is the number of fields in the patient identity information data.

[0011] As a preferred solution of the NFC-based patient data rapid collection method of the present invention, the calculation formula of the matching score M is as follows: ; ; Where M is the matching score, is the k data fields in the database, is the kth data field corresponding to the NFC tag, is the field consistency function, is the field importance weight, which dynamically adjusts the contribution of different fields to the overall matching degree, and p is the total number of fields to be verified.

[0012] As a preferred solution of the NFC-based patient data rapid collection method described in the present invention, the hierarchical configuration includes: dynamically allocating priority values ​​according to the importance of physiological indicators to disease management; setting a collection time interval for each physiological indicator and dynamically adjusting it according to the priority level.

[0013] As a preferred solution of the NFC-based patient data rapid acquisition method of the present invention, wherein: using NFC technology to realize batch reading of the data of the sensor, transmitting the data of multiple time points to the acquisition device at one time includes the following steps: the sensor of each patient collects physiological data regularly according to the collection frequency preset in the NFC tag through the built-in cache, and organizes the data blocks in the local cache area according to the time series; after receiving the batch reading instruction of the acquisition device, the sensor collects the physiological data according to the time interval specified in the instruction to , extract the target data blocks of the corresponding time period from the cache area and package them according to the standard data protocol; when the patient wears multiple sensors, the acquisition device establishes a virtual multi-channel connection through NFC technology. Each channel corresponds to the data stream of a sensor. The channels maintain data independence through logical sequence identification, and a polling mechanism is used to ensure that there is no data conflict between multiple channels; the sensor transmits the target data blocks in batches through NFC connection, and a check value is added to each data block during the transmission process to ensure the integrity of the data; the acquisition device parses the batch transmitted data blocks according to the sensor identification and timestamp, and stores the parsed data in the patient's electronic file, which is synchronized with the existing monitoring data.

[0014] As a preferred solution of the NFC-based patient data rapid acquisition method of the present invention, when the patient wears multiple sensors, for each sensor Assign unique logical sequence identifier;

[0015] The acquisition device scans the nearby NFC tag and activates the bound sensor through polling Establish data channels for each sensor; use time slice polling mechanism to assign fixed time slots to each channel in turn , to ensure that there is no conflict between data streams; the acquisition device verifies the independence of the data streams of each channel in real time, and the verification conditions are: the data stream source is unique, that is, , ; There is no overlapping time period between data streams, that is , ;

[0016] in, is the logical identifier set of the i-th data stream, is the logical identifier set of the j-th data flow; is the collection start time of the i-th data stream, is the collection duration of the i-th data stream, is the collection start time of the jth data stream; if the verification condition is not met, the conflict handling mechanism is triggered, all channels are suspended and time slices are reallocated.

[0017] As a preferred solution of the NFC-based patient data rapid acquisition method of the present invention, wherein: the time slice polling mechanism is adopted to allocate fixed time slots to each channel in turn The formula is expressed as: ;in, is the collection start time of the jth data stream, is the time slice allocated to channel k.

[0018] In the second aspect, the present invention provides a patient data rapid collection system based on NFC, which includes a file generation module, which is used to generate a unique electronic file for the patient, and bind the patient's identity information and basic health data through an NFC tag; a parameter configuration module, which is used to preset collection parameters according to the patient's condition, including data type, priority and collection frequency, and write the hierarchical configuration into the NFC tag; a parameter triggering module, which is used to automatically trigger the parameter configuration stored in the tag and activate the corresponding sensor when the patient's collection device is close to the NFC tag; a data reading module, which is used to use NFC technology to realize batch reading of data from the sensor, and transmit data from multiple time points to the collection device at one time; an abnormal marking module, which is used to detect whether the collected physiological data has abnormalities through a preset threshold while transmitting data, and automatically mark the out-of-limit data.

[0019] In a third aspect, the present invention provides a computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: when the computer program instructions are executed by the processor, the steps of the NFC-based patient data rapid collection method as described in the first aspect of the present invention are implemented.

[0020] In a fourth aspect, the present invention provides a computer-readable storage medium having a computer program stored thereon, wherein: when the computer program instructions are executed by a processor, the steps of the NFC-based patient data rapid collection method as described in the first aspect of the present invention are implemented.

[0021] The beneficial effects of the present invention are as follows: the present invention ensures the integrity and consistency of input information through a logical consistency verification algorithm, avoiding binding failures caused by missing data or logical errors; verifies the accuracy of binding data through a matching evaluation formula to prevent identity confusion or data inconsistency problems; transmits the multi-time point data cached in the patient's sensor to the acquisition device according to a standard protocol through a batch reading mechanism, and establishes a virtual multi-channel connection to ensure the independence of multiple sensor data, and performs real-time detection of the acquired data through a preset threshold, annotates abnormal data, and generates supplementary acquisition tasks to ensure data integrity. The present invention not only improves the efficiency and accuracy of patient data acquisition, but also enhances the security and practicality of the data. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] In order to more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for use in the description of the embodiments. Obviously, the drawings described below are only some embodiments of the present invention. For ordinary technicians in this field, other drawings can be obtained based on these drawings without creative work.

[0023] Figure 1 Flow chart of the NFC-based patient data rapid collection method.

[0024] Figure 2 This is the structural diagram of the NFC-based patient data rapid collection system. DETAILED DESCRIPTION

[0025] In order to make the above-mentioned objects, features and advantages of the present invention more obvious and easy to understand, the specific implementation methods of the present invention are described in detail below in conjunction with the accompanying drawings.

[0026] In the following description, many specific details are set forth to facilitate a full understanding of the present invention, but the present invention may also be implemented in other ways different from those described herein, and those skilled in the art may make similar generalizations without violating the connotation of the present invention. Therefore, the present invention is not limited to the specific embodiments disclosed below.

[0027] Secondly, the term "one embodiment" or "embodiment" as used herein refers to a specific feature, structure, or characteristic that may be included in at least one implementation of the present invention. The term "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor does it refer to a separate or selective embodiment that is mutually exclusive with other embodiments.

[0028] Example 1: Reference Figure 1~Figure 2 , which is the first embodiment of the present invention, and provides a method for quickly collecting patient data based on NFC, such as Figure 1 As shown, including,

[0029] S1: Generate a unique electronic file for the patient, and bind the patient's identity information and basic health data through NFC tags to achieve matching between data collection equipment and patients.

[0030] First, the patient's unique identity information data is collected through the patient registration terminal, including the patient's name, ID number, date of birth and health record number, and the identity information data is stored in the patient information database as the basic data for the patient's unique identification.

[0031] Based on the patient's identity information data, a logical consistency check is performed using a preset integrity check algorithm. If the integrity score is less than the integrity threshold, it proves that there are missing items or inconsistent items, and the patient is prompted to supplement or correct the identity information data. The specific data integrity check formula is as follows: ;in, is the integrity score, which indicates the integrity and consistency of the data. For the patient’s

[0032] The logical correctness indicator of the i-th identity information field (such as ID number, name, date of birth, etc.), Indicates that the field is valid. Indicates that the field is invalid. is the weight of the field, is an anomaly detection factor used to correct data deviations caused by logical conflicts (such as duplicate ID numbers or mismatched birth dates). is the number of data anomaly items, indicating the number of abnormal fields in the current data, and n is the number of fields in the patient identity information data.

[0033] Based on the corrected or supplemented patient identity information data, input the patient's basic health data, including past medical history, allergy information and emergency contact information, use an encryption algorithm to generate a unique association code between the identity and health data, and write the association code into the storage area of ​​the blank NFC tag.

[0034] Furthermore, the blank NFC tag is synchronized with the patient information database through a binding device, and is marked as activated after the binding is completed, ensuring that the NFC tag maintains a unique association with the patient's identity information data and health data.

[0035] Preferably, the consistency between the associated code in the NFC tag and the data stored in the database is verified, and a matching evaluation formula is used: ; ; Where M is the matching score, is the k data fields in the database, is the kth data field corresponding to the NFC tag, is the field consistency function, is the field importance weight, which dynamically adjusts the contribution of different fields to the overall matching degree, and p is the total number of fields to be verified.

[0036] The associated code in the NFC tag is verified by the NFC reading device, and the patient identity information data and health data stored in the patient information database are matched. If the matching score M is greater than or equal to the minimum matching threshold, the data is consistent with the bound NFC tag record, proving that the data is complete and correct, and a prompt for successful tag binding is output to complete the generation and binding of the patient's electronic file; if the matching score M is less than the minimum matching threshold, it proves that the data is inconsistent with the NFC tag record, and it is necessary to call the operator for verification, and update the data or re-bind the patient identity.

[0037] S2: Preset collection parameters according to the patient's condition, including data type (such as blood sugar, body temperature, etc.), priority and collection frequency, and write the hierarchical configuration into the NFC tag.

[0038] Specifically, based on the patient's medical data files (such as medical history data and allergy information in electronic files), a demand list of target monitoring data types is extracted, where the demand list includes priority-ordered physiological indicators (such as blood sugar, body temperature, heart rate, etc.).

[0039] Set parameter classification for each physiological indicator in the requirements list, where the classification parameters include: dynamically assigning priority values ​​according to the importance of the physiological indicator to disease management; setting a collection time interval for each physiological indicator (such as every 10 minutes or once an hour), and dynamically adjusting it according to the priority.

[0040] Generate a parameter template based on the patient's personalized needs. The template includes the target monitoring data type, collection frequency and priority information, and is stored as a configuration file in a fixed format. The template is used to guide the writing of NFC tag data. Through the NFC writing terminal, the configuration data in the parameter template (target monitoring data type, collection frequency and priority value) is written into the specific storage area of ​​the NFC tag and bound to the unique association code of the corresponding patient file; use the NFC reading device to read and verify the written configuration data to verify whether the configuration data in the NFC tag is consistent with the patient's personalized parameter template. If they are consistent, a configuration success prompt is output.

[0041] S3: When the patient's data collection device is close to the NFC tag, the parameter configuration stored in the tag is automatically triggered, activating the corresponding sensor to ensure rapid start of data collection.

[0042] Specifically, according to the parameter configuration data stored in the NFC tag, including the patient's monitoring target data type, collection frequency and priority, the built-in parsing module is used to parse the parameters to generate a collection task instruction set.

[0043] S4: Use NFC technology to batch read data from patient sensors (such as wearable devices or implanted devices) and transmit data from multiple time points to the collection device at one time.

[0044] S4.1: Each patient's sensor (such as blood glucose monitoring equipment, implantable heart rate monitor, etc.) collects physiological data at a fixed time according to the collection frequency preset in the NFC tag through the built-in cache, and organizes the data blocks in time series in the local cache area.

[0045] S4.2: After receiving the batch reading instruction from the acquisition device, the sensor to , extract the target data block of the corresponding time period from the buffer area and package it according to the standard data protocol (such as NDEF).

[0046] S4.3: When the patient wears multiple sensors, the acquisition device establishes a virtual multi-channel connection through NFC technology, and each channel corresponds to the data stream of a sensor. The data independence is maintained between channels through logical sequence identification, and a polling mechanism is used to ensure that there is no data conflict between multiple channels.

[0047] Specifically, for each sensor Assign unique logical sequence identifiers to ensure the independence of data stream sources;

[0048] The acquisition device scans the nearby NFC tag and activates the bound sensor through polling Establish data channels for each sensor;

[0049] Adopt time slice polling mechanism to allocate fixed time slots to each channel in turn , to ensure that there is no conflict between data streams, the formula is expressed as: ;in, is the collection start time of the jth data stream, is the time slice allocated to channel k;

[0050] Furthermore, the acquisition device performs real-time independence verification on the data stream of each channel, and the verification conditions are:

[0051] The data stream has a unique source, i.e. , ;

[0052] There is no overlapping time period between data streams, that is, , ;

[0053] in, is the logical identifier set of the i-th data stream, is the logical identifier set of the j-th data flow; is the collection start time of the i-th data stream, is the collection duration of the i-th data stream, is the collection start time of the jth data stream.

[0054] If the verification conditions are not met, the conflict handling mechanism is triggered, all channels are suspended and time slices are reallocated.

[0055] Furthermore, for the independent data streams of all channels, the data timestamps are standardized through a time synchronization protocol (such as NTP) and transmitted to the acquisition device for centralized processing.

[0056] S4.4: The sensor transmits the target data blocks to the acquisition device in batches through the NFC connection. During the transmission process, a check value (such as a CRC check code) is added to each data block to ensure the integrity of the data.

[0057] Furthermore, the acquisition device verifies the received data blocks in real time, and requests retransmission of the corresponding data blocks if an abnormality is found.

[0058] S4.5: The acquisition device parses the batch-transmitted data blocks according to the sensor identification and timestamp, and stores the parsed data in the patient's electronic file, synchronizing it with the existing monitoring data.

[0059] S5: While data is being transmitted, the collected physiological data is detected to see if there are any abnormalities through preset thresholds, and the data that exceeds the limit is automatically marked, including the time, abnormal range and recommended operations.

[0060] The following annotation information is recorded for each abnormal data detected: data timestamp, abnormal range, and recommended actions (prompts generated based on preset health information in the patient's file, such as "check for hypoglycemia" or "monitor for arrhythmia").

[0061] Furthermore, the marked abnormal data is fed back to the operator of the collection equipment through sound, light or vibration signals, and the complete data is simultaneously securely encrypted and stored locally or in the cloud.

[0062] Among them, all collected data (including normal and abnormal data) are encrypted immediately after the transmission is completed, using a layered encryption algorithm. The encrypted data is stored on the local device or uploaded to the cloud according to the operation configuration.

[0063] For data marked as abnormal, the collection device automatically generates supplementary collection task instructions, including target sensors, supplementary time intervals and collection frequency. The supplementary collection task instructions are sent to the corresponding sensors as soon as the abnormal data is detected, and the task status is displayed in real time.

[0064] Furthermore, this embodiment also provides a patient data rapid acquisition system based on NFC, including:

[0065] The file generation module is used to generate a unique electronic file for the patient and bind the patient's identity information and basic health data through the NFC tag;

[0066] The parameter configuration module is used to preset the collection parameters according to the patient's condition, including data type, priority and collection frequency, and write the hierarchical configuration into the NFC tag;

[0067] The parameter trigger module is used to automatically trigger the parameter configuration stored in the NFC tag and activate the corresponding sensor when the patient's collection device is close to the NFC tag;

[0068] A data reading module is used to realize batch reading of data from the sensor using NFC technology, and transmit data at multiple time points to the acquisition device at one time;

[0069] The abnormality marking module is used to detect whether the collected physiological data has abnormalities through preset thresholds during data transmission, and automatically mark the data that exceeds the limit.

[0070] This embodiment also provides a computer device, which is suitable for the NFC-based patient data rapid collection method, including a memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the NFC-based patient data rapid collection method proposed in the above embodiment.

[0071] The computer device may be a terminal, and the computer device includes a processor, a memory, a communication interface, a display screen and an input device connected through a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and a computer program. The internal memory provides an environment for the operation of the operating system and the computer program in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, an operator network, NFC (near field communication) or other technologies. The display screen of the computer device may be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device may be a touch layer covered on the display screen, or a key, trackball or touchpad provided on the housing of the computer device, or an external keyboard, touchpad or mouse, etc.

[0072] This embodiment also provides a storage medium on which a computer program is stored. When the program is executed by a processor, the method for quickly collecting patient data based on NFC as proposed in the above embodiment is implemented.

[0073] In summary, the present invention ensures the integrity and consistency of input information through a logical consistency verification algorithm to avoid binding failures caused by missing data or logical errors; verifies the accuracy of binding data through a matching evaluation formula to prevent identity confusion or data inconsistency problems; and transmits the multi-time point data cached in the patient's sensor to the acquisition device according to a standard protocol through a batch reading mechanism, while establishing a virtual multi-channel connection to ensure the independence of multiple sensor data, and performs real-time detection of the acquired data through a preset threshold, annotates abnormal data, and generates supplementary acquisition tasks to ensure data integrity. The present invention not only improves the efficiency and accuracy of patient data acquisition, but also enhances the security and practicality of the data.

[0074] Example 2: Referring to Table 1, this is the second example of the present invention. This example provides a method for quickly collecting patient data based on NFC. In order to verify the beneficial effects of the present invention, scientific demonstration is carried out through simulation experiments.

[0075] 50 patients with chronic diseases in the inpatient department of a medical institution were selected as test subjects. The experiment was divided into an experimental group (using a rapid data collection method based on NFC) and a control group (using traditional manual data entry and collection methods), with 25 people in each group, and the experimental time was 14 days.

[0076] Before the trial, all patients completed the entry of basic information, including name, ID number, date of birth, medical history, etc. The experimental group generated an electronic file through the patient registration terminal, and used NFC tags to bind the patient's identity information and health data. The invented integrity verification algorithm and matching evaluation formula were used to verify the data consistency to ensure that the NFC tag was correctly bound. At the same time, according to the health needs of each patient, a personalized collection parameter template was set for the experimental group, including collection frequency, target data type and priority, and written into the NFC tag.

[0077] During the experiment, patients in the experimental group brought the NFC acquisition device close to the NFC tag to trigger parameter configuration and activate the sensor. The sensor collected the patient's physiological data (such as blood sugar, blood pressure, heart rate, etc.) in real time and transmitted it in batches to the data acquisition device using NFC technology. The control group recorded the physiological data in paper files through manual operation, and then the medical staff manually entered the data into the database.

[0078] At the end of the experiment, the quality of collected data, collection efficiency, abnormal data annotation and supplementary collection task execution were evaluated, and the following data indicators were recorded:

[0079] Collection efficiency, data integrity: the number of missing items and erroneous items in the data, abnormal response time: the time from abnormal data detection to completion of supplementary collection (unit: minutes) and patient satisfaction score: compare the satisfaction of patients in the experimental group and the control group with the data collection process (full score 10 points). Some experimental data are as follows:

[0080] Table 1 Experimental data record table

[0081] Project Name Collection efficiency (minutes / time) Data integrity (number of errors) Abnormal response time Data loss rate (%) Supplementary collection mission times Patient satisfaction rating Patient A in the experimental group 1.2 0 3 0.0 1 9.5 Patient B in the experimental group 1.4 0 2.5 0.0 2 9.0 Patient C in the experimental group 1.3 0 3.2 0.0 1 9.2 Patient X in the control group 8.5 2 10 5.0 3 6.5 Patient Y in the control group 9.0 3 11 7.0 4 6.0 Patient Z in the control group 8.8 2 9.5 6.5 3 6.2

[0082] It can be seen from the experimental data that the average data collection time for patients in the experimental group was 1.3 minutes per time, while that for the control group was 8.8 minutes per time. The results show that the NFC-based rapid data collection method significantly shortens the collection time and greatly improves efficiency by automatically activating sensors and transmitting batch data, especially when high-frequency monitoring is required. The efficiency advantage is particularly significant; no errors were found in the experimental group, while each patient in the control group had data errors or missing data, with an average number of 2.3 errors. This shows that the present invention effectively reduces data errors caused by manual input through logical consistency verification and matching evaluation formulas, ensuring the reliability of data quality;

[0083] The average time from abnormal data detection to supplementary collection in the experimental group was 2.9 minutes, while it took more than 10 minutes in the control group. The NFC-based system can annotate abnormal data in real time and automatically generate supplementary collection task instructions, which significantly improves the system's response speed to abnormal events and helps to take medical intervention measures in a timely manner;

[0084] The average satisfaction score of the experimental group patients was 9.2, while that of the control group was 6.2. It can be seen that the automated operation process of the experimental group significantly reduced the operation complexity of patients and improved the experience.

[0085] In summary, the present invention not only significantly outperforms the existing manual entry method in terms of efficiency and accuracy through NFC tag binding and data collection technology, but also solves the shortcomings of the existing technology in terms of low efficiency, prone to errors, slow response, etc. through an automated abnormal data supplement mechanism and data security design.

[0086] It should be noted that the above embodiments are only used to illustrate the technical solutions of the present invention rather than to limit it. Although the present invention has been described in detail with reference to the preferred embodiments, those skilled in the art should understand that the technical solutions of the present invention may be modified or replaced by equivalents without departing from the spirit and scope of the technical solutions of the present invention, which should all be included in the scope of the claims of the present invention.

Claims

1. A method for rapid collection of patient data based on NFC, characterized in that: include: Generate a unique electronic file for the patient, bind the patient's identity information and basic health data through the NFC tag, verify the associated code in the NFC tag through the NFC reading device, match the patient's identity information data and basic health data stored in the patient information database, and if the matching score M is greater than or equal to the minimum matching threshold, it proves that the data is complete and correct, and outputs a successful tag binding prompt to complete the generation and binding of the patient's electronic file; If the matching score M is less than the minimum matching threshold, the proof data is inconsistent with the NFC tag record; Preset collection parameters according to the patient's condition, including data type, priority, and collection frequency, and write the hierarchical configuration into the NFC tag; When the patient's acquisition device is close to the NFC tag, the parameter configuration stored in the tag is automatically triggered to activate the corresponding sensor; Using NFC technology to read the data of the sensor in batches, and transmitting the data of multiple time points to the collection device at one time; While data is being transmitted, the collected physiological data is detected to see if there are any abnormalities through a preset threshold, and the over-limit data is automatically marked. For data marked as abnormal, the collection device automatically generates a supplementary collection task instruction, including the target sensor, supplementary time interval and collection frequency. The supplementary collection task instruction is sent to the corresponding sensor as soon as the abnormal data is detected, and the task status is displayed in real time. The patient's identity information includes name, ID number, date of birth and health record number; A logical consistency check is performed based on the patient identity information using a data integrity check formula to obtain an integrity score. If the integrity score is less than the integrity threshold, it proves that there are missing items or inconsistent items. The data integrity check formula is as follows: ； in, For completeness score, is the logical correctness indicator of the patient's i-th identity information field, Indicates that the field is valid. Indicates that the field is invalid; is the weight of the field, is the anomaly detection factor, is the number of data anomaly items, indicating the number of abnormal fields in the current data, and n is the number of fields in the patient identity information data; The calculation formula of the matching score M is as follows: ； ； Among them, M is the matching score, is the k data fields in the database, is the kth data field corresponding to the NFC tag, is the field consistency function, is the field importance weight, dynamically adjusting the contribution of different fields to the overall matching degree, and p is the total number of fields to be verified; The hierarchical configuration includes: Dynamically assign priority values ​​based on the importance of physiological indicators to disease management; Set the collection time interval for each physiological indicator and adjust it dynamically according to the priority level; Using NFC technology to read the data of the sensor in batches and transmitting the data of multiple time points to the collection device at one time includes the following steps: Each patient's sensor collects physiological data regularly according to the collection frequency preset in the NFC tag through the built-in cache, and organizes the data blocks in time series in the local cache area; After receiving the batch reading instruction from the acquisition device, the sensor to , extract the target data blocks of the corresponding time period from the buffer area and package them according to the standard data protocol; When the patient wears multiple sensors, the acquisition device establishes a virtual multi-channel connection through NFC technology. Each channel corresponds to the data stream of a sensor. The channels maintain data independence through logical sequence identification, and a polling mechanism is used to ensure that there is no data conflict between multiple channels. The sensor transmits the target data blocks in batches through the NFC connection, and a checksum is added to each data block during the transmission process to ensure the integrity of the data; The acquisition device parses the batch-transmitted data blocks according to the sensor identification and timestamp, and stores the parsed data in the patient's electronic file, synchronizing it with the existing monitoring data.

2. The NFC-based patient data rapid collection method according to claim 1, characterized in that: When the patient wears multiple sensors, Assign unique logical sequence identifier; The acquisition device scans the nearby NFC tag and activates the bound sensor through polling Establish data channels for each sensor; Adopt time slice polling mechanism to allocate fixed time slots to each channel in turn , ensuring that there is no conflict between data streams; The acquisition device performs real-time independence verification on the data stream of each channel. The verification conditions are: The data stream has a unique source, i.e. , ; There is no overlapping time period between data streams, that is, , ; in, is the logical identifier set of the i-th data stream, is the logical identifier set of the j-th data flow; is the collection start time of the i-th data stream, is the collection duration of the i-th data stream, is the collection start time of the jth data stream; If the verification conditions are not met, the conflict handling mechanism is triggered, all channels are suspended and time slices are reallocated.

3. The NFC-based patient data rapid collection method according to claim 2, characterized in that: The time slice polling mechanism is used to allocate fixed time slots to each channel in turn. The formula is expressed as: ； in, is the collection start time of the jth data stream, is the time slice allocated to channel k.

4. The NFC-based patient data rapid collection system is based on the NFC-based patient data rapid collection method according to any one of claims 1 to 3, characterized in that: Also includes: The file generation module is used to generate a unique electronic file for the patient and bind the patient's identity information and basic health data through the NFC tag; The parameter configuration module is used to preset the collection parameters according to the patient's condition, including data type, priority and collection frequency, and write the hierarchical configuration into the NFC tag; The parameter trigger module is used to automatically trigger the parameter configuration stored in the NFC tag and activate the corresponding sensor when the patient's collection device is close to the NFC tag; A data reading module is used to realize batch reading of data from the sensor using NFC technology, and transmit data at multiple time points to the acquisition device at one time; The abnormality marking module is used to detect whether the collected physiological data has abnormalities through preset thresholds during data transmission, and automatically mark the data that exceeds the limit.

5. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the NFC-based patient data rapid collection method described in any one of claims 1 to 3 are implemented.

6. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the NFC-based patient data rapid collection method according to any one of claims 1 to 3 are implemented.

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