Intervention task generation method and device and electronic equipment
By automatically generating and packaging intervention tasks, using patient data and intervention rules, the problems of large number of intervention tasks and low generation efficiency in digital therapy are solved, efficient and personalized intervention tasks are achieved, and the treatment effect and health management capabilities of digital therapy are improved.
Patent Information
- Application Number
- CN202311470315.8
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2023-11-06
- Publication Date
- 2025-05-06
AI Technical Summary
In digital therapy, due to diversified health needs, individual differences and customized, multi-dimensional intervention, and intervention at different stages, the number of intervention tasks is large, and the traditional artificial generation methods are inefficient and costly.
By obtaining the data of the target patient, analyzing the data to generate the index coded value, obtaining the configured intervention rules, generating the intervention task based on the intervention task triggering condition ID, and pushing the intervention content to the electronic terminal to realize the automatic generation and packaging of the intervention task.
It improves the efficiency of intervention task generation, reduces the cost of artificial generation, realizes personalized intervention task push, and enhances the therapeutic effect and health management capabilities of digital therapy.
Smart Images
Figure CN119943253A_ABST
Abstract
Description
Technical Field
[0001] The present disclosure relates to the field of data processing technology, and in particular to an intervention task generation method, device, and electronic device. Background Art
[0002] Intervention tasks in digital therapy refer to intervention and support for users through the application of scientific, personalized, and effective means. It can understand the patient's specific needs, behavior patterns, and health risks by analyzing the patient's data, and develop personalized intervention plans for each patient based on this information; it can help patients better understand and manage their health conditions by providing real-time feedback, goal setting, reminders, and education, and it can use the principles and technical means of behavioral science to encourage patients to change bad health behaviors and establish good habits. Therefore, intervention tasks are of great significance in digital therapy. Through the intervention tasks of digital therapy, we can better meet the needs of patients, improve treatment outcomes, and provide solutions for health management.
[0003] Due to the diversity of health needs, individual differences and customization, multi-dimensional intervention, intervention at different stages, etc., the number of intervention tasks in digital therapy is relatively large, and the traditional generation and allocation of intervention tasks is manual, which has high labor costs and leads to low efficiency in the generation of intervention tasks.
[0004] Therefore, there is an urgent need for an intervention task generation method, device, and electronic device with high generation efficiency. Summary of the invention
[0005] The present disclosure provides an intervention task generation method, device, and electronic device.
[0006] According to a first aspect of the present disclosure, there is provided a method for generating an intervention task, comprising:
[0007] Acquire the collected target patient data, the patient data is collected based on a set data collection engine and uniquely corresponds to the target patient, the data collection engine is set on an electronic terminal used by the target patient;
[0008] Parsing the target patient data to generate a value corresponding to the indicator code of the target patient;
[0009] Acquire a configured intervention rule, wherein the intervention rule is configured with an association relationship between an intervention task trigger condition ID and an intervention content ID;
[0010] Based on the intervention task trigger condition ID, obtain an intervention task trigger condition description, where the intervention task trigger condition description is used to describe the logical rules of the indicator coding that satisfies the task trigger;
[0011] In response to the value of the indicator code matching the intervention task trigger description, an intervention task is generated based on the intervention content ID to push the intervention content corresponding to the intervention content ID to the electronic terminal by executing the intervention task.
[0012] Optionally, the method further comprises:
[0013] According to the intervention task trigger condition ID, obtain the intervention task trigger condition;
[0014] Based on the set description template, the intervention task trigger condition is converted into an intervention task trigger condition description.
[0015] Optionally, the description template defines an indicator name field, an indicator code field, and a logical relationship field;
[0016] Correspondingly, the step of converting the intervention task trigger condition into an intervention task trigger condition description based on the set description template includes:
[0017] Parsing the intervention task triggering conditions to obtain indicator names, indicator codes, and logical relationships therefrom;
[0018] The indicator name, indicator code, and logical relationship are respectively filled into the indicator name field, indicator code field, and logical relationship field in the description template to obtain the description of the intervention task triggering condition.
[0019] Optionally, the step of filling the indicator name, indicator code, and logical relationship into the indicator name field, indicator code field, and logical relationship field in the description template, respectively, to obtain the description of the intervention task triggering condition includes:
[0020] The intervention task trigger condition ID is used as the key in the key-value pair, and the indicator name, indicator code, and logical relationship are respectively filled into the indicator name field, indicator code field, and logical relationship field in the description template as the values in the key-value pair, and the intervention task trigger condition description is expressed with the key-value pair.
[0021] Optionally, parsing the target patient data to generate a value corresponding to the indicator code of the target patient includes:
[0022] Get the set executable code;
[0023] Executing the executable code based on the script executor to parse the target patient data to generate a value corresponding to the indicator code of the target patient;
[0024] Optionally, the method further comprises:
[0025] Converting the intervention task trigger condition description into executable code;
[0026] The executable code is executed based on the script executor to compare the executable code with a value corresponding to the indicator code of the target patient to determine whether the indicator code matches the intervention task trigger description.
[0027] Optionally, the method further comprises:
[0028] For the target patient, a task queue is established;
[0029] The intervention task is stored in the task queue.
[0030] Optionally, the method further comprises:
[0031] Get the configured questionnaire push trigger logic;
[0032] In response to the initial user data submitted by the target patient matching the questionnaire push trigger logic, a collection questionnaire is pushed to the target patient to collect the target patient data of the target patient through the collection questionnaire.
[0033] An intervention task generating device, comprising:
[0034] A data acquisition unit, used to acquire the collected target patient data, the patient data is collected based on a set data acquisition engine and uniquely corresponds to the target patient, the data acquisition engine is set on the electronic terminal used by the target patient;
[0035] A data parsing unit, used to parse the target patient data to generate a value corresponding to the indicator code of the target patient;
[0036] A rule acquisition unit, used to acquire a configured intervention rule, wherein the intervention rule is configured with an association relationship between an intervention task trigger condition ID and an intervention content ID;
[0037] A description acquisition unit, used for acquiring an intervention task trigger condition description based on the intervention task trigger condition ID, wherein the intervention task trigger condition description is used for describing a logical rule of an indicator encoding that satisfies task triggering;
[0038] A matching unit is used to generate an intervention task based on the intervention content ID in response to the value of the indicator code matching the intervention task trigger description, so as to push the intervention content corresponding to the intervention content ID to the electronic terminal by executing the intervention task.
[0039] An electronic device comprising:
[0040] at least one processor; and
[0041] a memory communicatively connected to the at least one processor; wherein,
[0042] The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 8.
[0043] In the disclosed scheme, the collected target patient data is acquired, the patient data is acquired based on a set data acquisition engine and uniquely corresponds to the target patient, and the data acquisition engine is set on the electronic terminal used by the target patient; the target patient data is parsed to generate a value corresponding to the indicator code of the target patient; the configured intervention rule is acquired, and the intervention rule is configured with an association relationship between an intervention task trigger condition ID and an intervention content ID; based on the intervention task trigger condition ID, an intervention task trigger condition description is acquired, and the intervention task trigger condition description is used to describe the logical rules of the indicator code that satisfies the task trigger; in response to the value of the indicator code matching the intervention task trigger description, an intervention task is generated based on the intervention content ID to push the intervention content corresponding to the intervention content ID to the electronic terminal by executing the intervention task, thereby realizing automatic generation and packaging of intervention tasks based on patients, avoiding manual generation of intervention tasks, and improving efficiency.
[0044] It should be understood that the contents described in the summary of the invention are not intended to limit the key or important features of the embodiments of the present disclosure, nor are they intended to limit the scope of the present disclosure. Other features of the present disclosure will become easily understood through the following description. BRIEF DESCRIPTION OF THE DRAWINGS
[0045] The above and other features, advantages and aspects of the embodiments of the present disclosure will become more apparent with reference to the following detailed description in conjunction with the accompanying drawings. The accompanying drawings are used to better understand the present solution and do not constitute a limitation of the present disclosure. In the accompanying drawings, the same or similar reference numerals represent the same or similar elements, wherein:
[0046] Figure 1 A flowchart of a method for generating an intervention task according to an embodiment of the present disclosure is shown;
[0047] Figure 2 A block diagram of an intervention task generating device according to an embodiment of the present disclosure is shown;
[0048] Figure 3 A block diagram of an exemplary electronic device capable of implementing embodiments of the present disclosure is shown. DETAILED DESCRIPTION
[0049] In order to make the purpose, technical solution and advantages of the embodiments of the present disclosure clearer, the technical solution in the embodiments of the present disclosure will be clearly and completely described below in conjunction with the drawings in the embodiments of the present disclosure. Obviously, the described embodiments are part of the embodiments of the present disclosure, not all of the embodiments. Based on the embodiments in the present disclosure, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present disclosure.
[0050] In addition, the term "and / or" in this article is only a description of the association relationship between the associated objects, indicating that there can be three relationships. For example, A and / or B can represent: A exists alone, A and B exist at the same time, and B exists alone. In addition, the character " / " in this article generally indicates that the associated objects before and after are in an "or" relationship.
[0051] Figure 1 FIG. 1 is a flow chart of a method for generating an intervention task according to an embodiment of the present application. Figure 1 As shown, it includes:
[0052] S101, acquiring the collected target patient data;
[0053] In this embodiment, the patient data is collected based on a set data collection engine and uniquely corresponds to a target patient. The data collection engine is set on an electronic terminal used by the target patient.
[0054] Optionally, the method further comprises:
[0055] Get the configured questionnaire push trigger logic;
[0056] In response to the initial user data submitted by the target patient matching the questionnaire push trigger logic, a collection questionnaire is pushed to the target patient to collect the target patient data of the target patient through the collection questionnaire.
[0057] Here, it should be noted that the questionnaire push trigger logic includes, for example, a combination relationship of multiple set indicators and a set collection time. When the initial user data meets the combination relationship, the collection questionnaire is pushed to the user according to the set collection time.
[0058] In this embodiment, specific indicators are determined according to application scenarios, and the combination relationship can be configured by, for example, and or.
[0059] In this embodiment, the form of the initial user data is not limited.
[0060] In this embodiment, the collection questionnaire can be directly displayed on the electronic terminal, and the user only needs to fill in the relevant patient data.
[0061] In this embodiment, the type of the target patient data is not limited, for example, it can be physiological data, exercise data, sleep data, diet data, psychological data, medication data and behavioral data;
[0062] For example, the physiological data may be heart rate, blood pressure, blood sugar, respiratory rate, body temperature or respiratory oxygen content;
[0063] The exercise data may include number of steps, exercise distance, exercise duration, activity intensity (such as mild, moderate, and high), calorie consumption, and exercise type (such as walking, running, swimming, and yoga);
[0064] The sleep data may include sleep duration (such as the time interval between falling asleep and waking up), sleep quality (such as deep sleep, light sleep, rapid movement sleep, etc.), sleep cycle, number of awakenings, and sleep breathing conditions (such as sleep breathing frequency, snoring, etc.);
[0065] The dietary data may include food types (such as grains, vegetables, fruits, meat, fish, dairy products, beans, nuts, etc.), food intake nutrients (such as calories, protein, fat, carbohydrates, fiber, vitamins, minerals, etc.), eating frequency, and eating habits (such as whether to eat breakfast, whether to eat out often, whether to have dietary preferences, etc.);
[0066] The psychological data may be a psychological assessment scale (such as depression symptoms, anxiety level, stress level, etc.), an emotional record (such as happiness, sadness, anxiety, tension, etc.);
[0067] The medication data may include the name of the drug, dosage (such as the number of tablets taken, the volume of liquid medicine, the dosage of injection, etc.), frequency of medication (such as three times a day, once a week, etc.), time of medication (such as before meals in the morning, before bedtime, etc.), route of administration (such as oral, topical, injection, etc.), duration of medication, and adverse reactions (such as allergies, indigestion, skin itching, etc.);
[0068] The behavior data may be smoking or drinking.
[0069] Here, it should be noted that the initial user data can be of the same type as the target patient data. To this end, a collection name and a collection time can be set in the collection questionnaire; the collection name can be "your fertility status", "have you taken opioids recently", "have you drunk alcohol today", etc.
[0070] S102, parsing the target patient data to generate a value corresponding to the indicator code of the target patient;
[0071] In this embodiment, the rule of the indicator coding is determined according to the application scenario, and no uniqueness is limited. For example, in one scenario, the collection name in the collection questionnaire is "Whether to drink alcohol today", and the corresponding indicator code can be "A1.342".
[0072] S103, obtaining a configured intervention rule, wherein the intervention rule is configured with an association relationship between an intervention task trigger condition ID and an intervention content ID;
[0073] In this embodiment, the intervention task trigger condition includes a combination relationship of multiple indicators, such as and, or. Since there may be multiple intervention task trigger conditions, in this application, different intervention task trigger conditions are distinguished by intervention task trigger condition IDs.
[0074] Similarly, intervention content refers to intervention measures for target patients, such as drug intervention, food intervention, video intervention, audio intervention, questionnaire intervention, popular science knowledge intervention, etc. In order to distinguish different intervention contents, an intervention content ID is set for each intervention content.
[0075] In this embodiment, the intervention rules may be directly stored in a relational database, for example, for easy access.
[0076] S104, based on the intervention task trigger condition ID, obtaining an intervention task trigger condition description, wherein the intervention task trigger condition description is used to describe the logical rules of the indicator coding that satisfies the task trigger;
[0077] In this embodiment, based on the description of the intervention task triggering condition, the intervention task triggering condition can be recognized by a machine, so as to realize the automatic execution of subsequent steps without human intervention.
[0078] Specifically, the form of the description of the intervention task trigger condition is not limited to uniqueness, for example, it can be implemented based on JS or Groove.
[0079] S105 . In response to a match between the value of the indicator code and the intervention task trigger description, generate an intervention task based on the intervention content ID to push the intervention content corresponding to the intervention content ID to the electronic terminal by executing the intervention task.
[0080] Optionally, before step S104, the method may further include:
[0081] According to the intervention task trigger condition ID, obtain the intervention task trigger condition;
[0082] Based on the set description template, the intervention task trigger condition is converted into an intervention task trigger condition description.
[0083] Optionally, the description template defines an indicator name field, an indicator code field, and a logical relationship field;
[0084] Correspondingly, the step of converting the intervention task trigger condition into an intervention task trigger condition description based on the set description template includes:
[0085] Parsing the intervention task triggering conditions to obtain indicator names, indicator codes, and logical relationships therefrom;
[0086] The indicator name, indicator code, and logical relationship are respectively filled into the indicator name field, indicator code field, and logical relationship field in the description template to obtain the description of the intervention task triggering condition.
[0087] In this embodiment, in the set description template, if there are multiple intervention task description conditions, the description template can be set to a nested structure, so that flexible combination relationships can be configured between different intervention task trigger condition descriptions to dynamically realize dynamic adjustment and flexible configuration of intervention rules.
[0088] In addition to the indicator name field, indicator code field, logical relationship field, etc., the set description template can also include the type field of target patient data, etc. To this end, the structured processing of the intervention rules is achieved, which is convenient for machine recognition and reading for execution.
[0089] Optionally, the step of filling the indicator name, indicator code, and logical relationship into the indicator name field, indicator code field, and logical relationship field in the description template, respectively, to obtain the description of the intervention task triggering condition includes:
[0090] The intervention task trigger condition ID is used as the key in the key-value pair, and the indicator name, indicator code, and logical relationship are respectively filled into the indicator name field, indicator code field, and logical relationship field in the description template as the values in the key-value pair, and the intervention task trigger condition description is expressed with the key-value pair.
[0091] For example, when the intervention task triggering condition description is expressed in key-value pairs, it may be structured as follows:
[0092] {"rules":[{"rules":[{"values":[],"resType":"text","operator":"notNull","indicatorsCode":"*****","indicatorsName":"*****","indicatorsGroupType":1}],"combinator":"and"}],"combinator":"and"}
[0093] Where rules represents intervention rules, resType represents the type field of target patient data, operator represents the logical relationship field, indicatorsCode represents the indicator code field, indicatorsName represents the indicator name field, and [] represents a nesting symbol.
[0094] In this embodiment, based on the above structure, a structured description of the triggering conditions of the intervention task is implemented, and at the same time, the complexity of the description is reduced, with strong recognizability and readability.
[0095] In this embodiment, in a specific implementation, the key-value pair may be saved in the form of a JSON string.
[0096] In this embodiment, since the target patient data has different types, such as text and numerical types, the intervention task triggering conditions will also have corresponding different logical relationships. Therefore, a logical relationship dictionary mapping is set, and the mapping relationship between different types of target patient data and logical relationships is defined in the logical relationship dictionary mapping. The types include ext, number, datetime, date, time, etc. The logical relationship is represented by operator. The mapping relationship between the target patient data and the logical relationship is as follows:
[0097] datetime:eq,neq,lt,lte,gt,gte,between,notNull,nothing
[0098] date:eq,neq,lt,lte,gt,gte,between,notNull,nothing
[0099] time:eq,neq,lt,lte,gt,gte,between,notNull,nothing
[0100] number:eq,neq,lt,lte,gt,gte,between,notNull,nothing
[0101] text:eq,neq,contains,doesNotContain,notNull,nothing
[0102] eq means "equal to"
[0103] neq means "not equal to"
[0104] lt means "less than"
[0105] lte means "less than or equal to"
[0106] gt means "greater than"
[0107] gte means "greater than or equal to"
[0108] Between means "between two values"
[0109] notNull means it cannot be empty
[0110] Nothing means empty.
[0111] In this embodiment, when generating the intervention task trigger condition description, the mapping dictionary is queried to quickly and accurately find the matching relationship between different types of target patient data and logical relationships, thereby improving the efficiency and accuracy of generating the intervention task trigger condition description.
[0112] Optionally, parsing the target patient data to generate a value corresponding to the indicator code of the target patient includes:
[0113] Get the set executable code;
[0114] The executable code is executed based on a script executor to parse the target patient data to generate a value corresponding to the indicator code of the target patient.
[0115] In this embodiment, the automatic execution of the analysis is achieved based on the executable code, without the need for human intervention.
[0116] Optionally, the method further comprises:
[0117] Converting the intervention task trigger condition description into executable code;
[0118] The executable code is executed based on the script executor to compare the executable code with a value corresponding to the indicator code of the target patient to determine whether the indicator code matches the intervention task trigger description.
[0119] Exemplarily, the executable code converted from the trigger condition description of the intervention task of the above structure is as follows:
[0120]
[0121] func(obj)
[0122] A1.342 represents the code of the indicator "Did you drink alcohol today?". The meaning of this code is: if the value of the indicator "Did you drink alcohol today?" is "yes", it returns true; if the value is "no", it returns false.
[0123] In this embodiment, converting the intervention task trigger condition description into executable code includes: extracting target patient data and indicator code from the intervention task trigger condition description based on a set conversion function, and adding an executable function to generate executable code.
[0124] Optionally, the method further comprises:
[0125] For the target patients, a task queue is established;
[0126] The intervention task is stored in the task queue.
[0127] In the above embodiment, the intervention content may be, for example:
[0128] For example, the drug intervention task includes drug name (e.g., doglitin tablets), route of administration (e.g., oral), drug dosage (e.g., tablets), dosage (e.g., 1 tablet each time), frequency of use (e.g., 3 times a day), and time of use (e.g., 10:35, 10:45, 10:55);
[0129] The food intervention tasks include food name (such as herbal dietary fiber powder), consumption method (such as preparation), food dosage (such as 10 grams each time), and consumption time (such as 9:00);
[0130] The video intervention task includes file name (such as HIIT fat burning challenge), file type (such as video), intervention frequency (such as 3 times a day), and intervention time (such as 11:00, 15:00, 18:00);
[0131] The audio intervention task includes a file name (such as a 35-minute non-jumping 5,000-step weight loss and fat burning walking training), a file type (such as audio), an intervention frequency (such as once a day), and an intervention time (such as 06:00).
[0132] Figure 2 Schematic diagram of the structure of an intervention task generation device according to an embodiment of the present application. Figure 2 As shown, it includes:
[0133] A data acquisition unit, used to acquire the collected target patient data, the patient data is collected based on a set data acquisition engine and uniquely corresponds to the target patient, the data acquisition engine is set on the electronic terminal used by the target patient;
[0134] A data parsing unit, used to parse the target patient data to generate a value corresponding to the indicator code of the target patient;
[0135] A rule acquisition unit, used to acquire a configured intervention rule, wherein the intervention rule is configured with an association relationship between an intervention task trigger condition ID and an intervention content ID;
[0136] A description acquisition unit, used for acquiring an intervention task trigger condition description based on the intervention task trigger condition ID, wherein the intervention task trigger condition description is used for describing a logical rule of an indicator encoding that satisfies task triggering;
[0137] A matching unit is used to generate an intervention task based on the intervention content ID in response to the value of the indicator code matching the intervention task trigger description, so as to push the intervention content corresponding to the intervention content ID to the electronic terminal by executing the intervention task.
[0138] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working process of the described module can refer to the corresponding process in the aforementioned method embodiment, and will not be repeated here.
[0139] In the technical solution disclosed herein, the acquisition, storage and application of user personal information involved are in compliance with the provisions of relevant laws and regulations and do not violate public order and good morals.
[0140] According to an embodiment of the present disclosure, the present disclosure also provides an electronic device and a readable storage medium.
[0141] Figure 3 A schematic block diagram of an electronic device 300 that can be used to implement an embodiment of the present disclosure is shown. The electronic device is intended to represent various forms of digital computers, such as laptop computers, desktop computers, workstations, personal digital assistants, servers, blade servers, mainframe computers, and other suitable computers. The electronic device can also represent various forms of mobile devices, such as personal digital processing, cellular phones, smart phones, wearable devices, and other similar computing devices. The components shown herein, their connections and relationships, and their functions are merely examples and are not intended to limit the implementation of the present disclosure described and / or required herein.
[0142] The electronic device 300 includes a computing unit 301, which can perform various appropriate actions and processes according to a computer program stored in a ROM 302 or a computer program loaded from a storage unit 308 into a RAM 303. In the RAM 303, various programs and data required for the operation of the electronic device 300 can also be stored. The computing unit 301, the ROM 302, and the RAM 303 are connected to each other via a bus 304. An I / O interface 305 is also connected to the bus 304.
[0143] A number of components in the electronic device 300 are connected to the I / O interface 305, including: an input unit 306, such as a keyboard, a mouse, etc.; an output unit 307, such as various types of displays, speakers, etc.; a storage unit 308, such as a disk, an optical disk, etc.; and a communication unit 309, such as a network card, a modem, a wireless communication transceiver, etc. The communication unit 309 allows the electronic device 300 to exchange information / data with other devices through a computer network such as the Internet and / or various telecommunication networks.
[0144] The computing unit 301 may be a variety of general and / or special processing engines with processing and computing capabilities. Some examples of the computing unit 301 include, but are not limited to, a central processing unit (CPU), a graphics processing unit (GPU), various dedicated artificial intelligence (AI) computing chips, various computing units running machine learning model algorithms, digital signal processors (DSPs), and any appropriate processors, controllers, microcontrollers, etc. The computing unit 301 performs the various methods and processes described above, such as the intervention task generation method. For example, in some embodiments, the intervention task generation method may be implemented as a computer software program, which is tangibly contained in a machine-readable medium, such as a storage unit 308. In some embodiments, part or all of the computer program may be loaded and / or installed on the electronic device 300 via ROM 302 and / or a communication unit 309. When the computer program is loaded into RAM 303 and executed by the computing unit 301, one or more steps of the intervention task generation method described above may be performed. Alternatively, in other embodiments, the computing unit 301 may be configured to perform the intervention task generation method in any other appropriate manner (e.g., by means of firmware).
[0145] Various implementations of the systems and techniques described above herein can be implemented in digital electronic circuit systems, integrated circuit systems, field programmable gate arrays (FPGAs), application specific integrated circuits (ASICs), application specific standard products (ASSPs), systems on chips (SOCs), load programmable logic devices (CPLDs), computer hardware, firmware, software, and / or combinations thereof. These various implementations may include: being implemented in one or more computer programs that can be executed and / or interpreted on a programmable system including at least one programmable processor, which can be a special purpose or general purpose programmable processor that can receive data and instructions from a storage system, at least one input device, and at least one output device, and transmit data and instructions to the storage system, the at least one input device, and the at least one output device.
[0146] The program code for implementing the method of the present disclosure may be written in any combination of one or more programming languages. These program codes may be provided to a processor or controller of a general-purpose computer, a special-purpose computer, or other programmable data processing device, so that the program code, when executed by the processor or controller, enables the functions / operations specified in the flow chart and / or block diagram to be implemented. The program code may be executed entirely on the machine, partially on the machine, partially on the machine and partially on a remote machine as a stand-alone software package, or entirely on a remote machine or server.
[0147] In the context of the present disclosure, a readable storage medium may be a tangible medium that may contain or store a program for use by or in conjunction with an instruction execution system, device, or equipment. A readable storage medium may be a machine-readable signal medium or a machine-readable storage medium. A readable storage medium may include, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, device, or device, or any suitable combination of the foregoing. More specific examples of readable storage media may include an electrical connection based on one or more lines, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
[0148] To provide interaction with a user, the systems and techniques described herein can be implemented on a computer having: a display device for displaying information to the user; and a keyboard and a pointing device (e.g., a mouse or trackball) through which the user can provide input to the computer. Other types of devices can also be used to provide interaction with the user; for example, the feedback provided to the user can be any form of sensory feedback (e.g., visual feedback, auditory feedback, or tactile feedback); and input from the user can be received in any form (including acoustic input, voice input, or tactile input).
[0149] The systems and techniques described herein may be implemented in a computing system that includes back-end components (e.g., as a data server), or a computing system that includes middleware components (e.g., an application server), or a computing system that includes front-end components (e.g., a user computer with a graphical user interface or a web browser through which a user can interact with implementations of the systems and techniques described herein), or a computing system that includes any combination of such back-end components, middleware components, or front-end components. The components of the system may be interconnected by any form or medium of digital data communication (e.g., a communications network). Examples of communications networks include: a local area network (LAN), a wide area network (WAN), and the Internet.
[0150] A computer system may include a client and a server. The client and the server are generally remote from each other and usually interact through a communication network. The relationship of client and server is generated by computer programs running on respective computers and having a client-server relationship with each other. The server may be a cloud server, a server of a distributed system, or a server combined with a blockchain.
[0151] It should be understood that the above-mentioned various forms of processes can be used to reorder, add or delete steps. For example, the steps recorded in this disclosure can be executed in parallel, sequentially or in different orders, as long as the desired results of the technical solution of this disclosure can be achieved, and this document is not limited here.
[0152] The above specific implementations do not constitute a limitation on the protection scope of the present disclosure. It should be understood by those skilled in the art that various modifications, combinations, sub-combinations and substitutions can be made according to design requirements and other factors. Any modification, equivalent substitution and improvement made within the spirit and principle of the present disclosure shall be included in the protection scope of the present disclosure.
Claims
1. A method for generating an intervention task, characterized in that: include: Acquire the collected target patient data, the patient data is collected based on a set data collection engine and uniquely corresponds to the target patient, the data collection engine is set on an electronic terminal used by the target patient; Parsing the target patient data to generate a value corresponding to the indicator code of the target patient; Acquire a configured intervention rule, wherein the intervention rule is configured with an association relationship between an intervention task trigger condition ID and an intervention content ID; Based on the intervention task trigger condition ID, obtain an intervention task trigger condition description, where the intervention task trigger condition description is used to describe the logical rules of the indicator coding that satisfies the task trigger; In response to the value of the indicator code matching the intervention task trigger description, an intervention task is generated based on the intervention content ID to push the intervention content corresponding to the intervention content ID to the electronic terminal by executing the intervention task.
2. The method according to claim 1, characterized in that The method further comprises: According to the intervention task trigger condition ID, obtain the intervention task trigger condition; Based on the set description template, the intervention task trigger condition is converted into an intervention task trigger condition description.
3. The method according to claim 1, characterized in that The description template defines an indicator name field, an indicator code field, and a logical relationship field; Correspondingly, the step of converting the intervention task trigger condition into an intervention task trigger condition description based on the set description template includes: Parsing the intervention task triggering conditions to obtain indicator names, indicator codes, and logical relationships therefrom; The indicator name, indicator code, and logical relationship are respectively filled into the indicator name field, indicator code field, and logical relationship field in the description template to obtain the description of the intervention task triggering condition.
4. The method according to claim 3, characterized in that: The step of filling the indicator name, indicator code, and logical relationship into the indicator name field, indicator code field, and logical relationship field in the description template to obtain the description of the intervention task triggering condition includes: The intervention task trigger condition ID is used as the key in the key-value pair, and the indicator name, indicator code, and logical relationship are respectively filled into the indicator name field, indicator code field, and logical relationship field in the description template as the values in the key-value pair, and the intervention task trigger condition description is expressed with the key-value pair.
5. The method according to any one of claims 1 to 4, characterized in that: The parsing of the target patient data to generate a value corresponding to the indicator code of the target patient includes: Get the set executable code; The executable code is executed based on a script executor to parse the target patient data to generate a value corresponding to the indicator code of the target patient.
6. The method according to claim 5, characterized in that The method further comprises: Converting the intervention task trigger condition description into executable code; The executable code is executed based on the script executor to determine whether the indicator code matches the intervention task trigger description.
7. The method according to claim 6, characterized in that The method further comprises: For the target patient, a task queue is established; The intervention task is stored in the task queue.
8. The method according to claim 1, characterized in that The method further comprises: Get the configured questionnaire push trigger logic; In response to the initial user data submitted by the target patient matching the questionnaire push trigger logic, a collection questionnaire is pushed to the target patient to collect the target patient data of the target patient through the collection questionnaire.
9. An intervention task generating device, characterized in that: include: A data acquisition unit, used to acquire the collected target patient data, the patient data is collected based on a set data acquisition engine and uniquely corresponds to the target patient, the data acquisition engine is set on the electronic terminal used by the target patient; A data parsing unit, used to parse the target patient data to generate a value corresponding to the indicator code of the target patient; A rule acquisition unit, used to acquire a configured intervention rule, wherein the intervention rule is configured with an association relationship between an intervention task trigger condition ID and an intervention content ID; A description acquisition unit, used for acquiring an intervention task trigger condition description based on the intervention task trigger condition ID, wherein the intervention task trigger condition description is used for describing a logical rule of an indicator encoding that satisfies task triggering; A matching unit is used to generate an intervention task based on the intervention content ID in response to the value of the indicator code matching the intervention task trigger description, so as to push the intervention content corresponding to the intervention content ID to the electronic terminal by executing the intervention task.
10. An electronic device, characterized in that: include: at least one processor; as well as a memory communicatively connected to the at least one processor; wherein, The memory stores instructions that can be executed by the at least one processor, and the instructions are executed by the at least one processor to enable the at least one processor to perform the method of any one of claims 1 to 8.