CN111986776A - Perioperative treatment risk intelligent prompting method - Google Patents
Perioperative treatment risk intelligent prompting method Download PDFInfo
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- CN111986776A CN111986776A CN202010641090.8A CN202010641090A CN111986776A CN 111986776 A CN111986776 A CN 111986776A CN 202010641090 A CN202010641090 A CN 202010641090A CN 111986776 A CN111986776 A CN 111986776A
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
- G16H20/40—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance relating to mechanical, radiation or invasive therapies, e.g. surgery, laser therapy, dialysis or acupuncture
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- G16H10/00—ICT specially adapted for the handling or processing of patient-related medical or healthcare data
- G16H10/60—ICT specially adapted for the handling or processing of patient-related medical or healthcare data for patient-specific data, e.g. for electronic patient records
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- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
- G16H50/30—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics for calculating health indices; for individual health risk assessment
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Abstract
Embodiments of the present disclosure provide a perioperative treatment risk intelligent prompting method, device and computer-readable storage medium. The method comprises the steps of obtaining medical record information of a patient; analyzing the medical record information, and sending an examination item prompt to the patient according to an analysis result; acquiring operation information input by a doctor; formulating an operation scheme according to the medical record information and the operation information input by the doctor; analyzing the operation scheme by a decision tree method, and sending a preoperative prompt according to an analysis result; obtaining daily ward rounds of the patient; and comparing the daily ward round record with the operation scheme, judging whether the patient can perform the operation or not and sending prompt information according to the judgment result. In this way, intelligent prompting can be carried out aiming at various risks in the perioperative period of the surgical operation, and the utilization efficiency of medical resources is improved.
Description
Technical Field
Embodiments of the present disclosure relate generally to the field of internet medicine and, more particularly, to perioperative treatment risk intelligent prompting methods, apparatuses, devices, and computer-readable storage media.
Background
Perioperative is the entire process around the operation, starting with the patient's decision to receive surgical treatment, and proceeding to surgical treatment until basic recovery.
In the perioperative period, the medical staff is required to monitor and evaluate the physical state of the patient in the whole course, so as to ensure that the surgical process of the patient can be smoothly carried out. In particular, for patients treated by surgical operation, the severity of the disease is generally higher and the treatment risk is also higher than that of the medical treatment.
The current risks in perioperative procedures are mainly dependent on human control. However, with the advance of medical improvement and graded diagnosis and treatment, the medical treatment of patients will gradually disperse from large hospitals to hospitals in all cities and towns, and due to the difference of the levels and experiences of doctors in all levels of hospitals, the medical staff cannot accurately control the risk points in the perioperative period due to the lack of advanced talents in three-four cities and towns or villages. Meanwhile, the manual control method is inefficient, and such a time is not available in clinical practice.
Disclosure of Invention
The present disclosure is directed to solving at least one of the technical problems of the related art or related art.
To this end, in a first aspect of the present disclosure, a perioperative treatment risk intelligent prompting method is provided. The method comprises the following steps:
acquiring medical record information of a patient;
analyzing the medical record information, and sending an examination item prompt to the patient according to an analysis result;
acquiring operation information input by a doctor;
formulating an operation scheme according to the medical record information and the operation information input by the doctor;
analyzing the operation scheme by a decision tree method, and sending a preoperative prompt according to an analysis result;
obtaining daily ward rounds of the patient;
and comparing the daily ward round record with the operation scheme, judging whether the patient can perform the operation or not and sending prompt information according to the judgment result.
Further, still include:
acquiring data information of an intraoperative monitoring instrument of a patient, analyzing the data information, and sending an intraoperative prompt according to an analysis result;
and acquiring data information of a postoperative monitoring instrument of the patient, analyzing the data information, and sending postoperative prompts according to analysis results.
Further, the medical record information includes gender, age, medical history, treatment history, diagnostic information, and/or examination records.
Further, the analyzing the medical record information and sending an examination item prompt to the patient according to the analysis result includes:
analyzing the medical record information, and determining the abnormal condition of the patient according to the analysis result;
and sending an examination item prompt to the patient according to the abnormal condition.
Further, the abnormal condition includes a physical examination abnormality and/or a check index abnormality.
Further, the step of formulating a surgical plan according to the medical record information and the surgical information entered by the doctor comprises:
comparing the operation information input by the doctor with the medical record information to determine the operation risk point;
and formulating an operation scheme according to the operation risk points and the medical record information.
Further, the risk points include contraindications not complying with surgical indications and/or abnormalities in test indicators.
Further, the preoperative prompts include medication prompts, preoperative guidance prompts, and/or non-routine spare article prompts.
In a second aspect of the disclosure, an apparatus is presented, comprising:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the above-described methods according to the present disclosure.
In a third aspect of the disclosure, a computer-readable storage medium is provided, on which a computer program is stored, which program, when being executed by a processor, realizes the above-mentioned method as according to the disclosure.
According to the perioperative treatment risk intelligent prompting method provided by the embodiment of the application, the medical record information of a patient is acquired; analyzing the medical record information, and sending an examination item prompt to the patient according to an analysis result; acquiring operation information input by a doctor; formulating an operation scheme according to the medical record information and the operation information input by the doctor; analyzing the operation scheme by a decision tree method, and sending a preoperative prompt according to an analysis result; obtaining daily ward rounds of the patient; the daily ward round record and the operation scheme are compared, whether the patient can perform the operation or not is judged, and prompt information is sent according to the judgment result, so that the whole control of the health state of the patient in the whole perioperative period is realized, intelligent prompt can be performed on various risks in the perioperative period of the surgical operation, the diagnosis and treatment efficiency is improved, and the labor cost is reduced.
It should be understood that the statements herein reciting aspects are not intended to limit the critical or essential 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 apparent from the following description.
Drawings
The above and other features, advantages and aspects of various embodiments of the present disclosure will become more apparent by referring to the following detailed description when taken in conjunction with the accompanying drawings. In the drawings, like or similar reference characters designate like or similar elements, and wherein:
FIG. 1 is an exemplary system architecture diagram in which one embodiment of the present application may be applied;
FIG. 2 is a flow chart of one embodiment of a perioperative treatment risk intelligent prompting method according to the present application;
fig. 3 is a schematic structural diagram of a computer system used for implementing the terminal device or the server according to the embodiment of the present application.
Detailed Description
To make the objects, technical solutions and advantages of the embodiments of the present disclosure more clear, the technical solutions of the embodiments of the present disclosure will be described clearly and completely with reference to the drawings in the embodiments of the present disclosure, and it is obvious that the described embodiments are some, but not all embodiments of the present disclosure. All other embodiments, which can be derived by a person skilled in the art from the embodiments disclosed herein without making any creative effort, shall fall within the protection scope of the present disclosure.
In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Fig. 1 illustrates an exemplary system architecture 100 to which embodiments of the perioperative treatment risk smart prompting method of the present application may be applied.
As shown in fig. 1, the system architecture 100 may include terminal devices 101, 102, 103, a network 104, and a server 105. The network 104 serves as a medium for providing communication links between the terminal devices 101, 102, 103 and the server 105. Network 104 may include various connection types, such as wired, wireless communication links, or fiber optic cables, to name a few.
The user may use the terminal devices 101, 102, 103 to interact with the server 105 via the network 104 to receive or send messages or the like. Various communication client applications, such as a model training application, a video recognition application, a web browser application, social platform software, etc., may be installed on the terminal devices 101, 102, 103.
The terminal apparatuses 101, 102, and 103 may be hardware or software. When the terminal devices 101, 102, and 103 are hardware, they may be various electronic devices with a display screen, including but not limited to smart phones, tablet computers, e-book readers, MP3 players (Moving Picture Experts Group Audio Layer III, mpeg Audio Layer 3), MP4 players (Moving Picture Experts Group Audio Layer IV, mpeg Audio Layer 4), laptop portable computers, desktop computers, and the like. When the terminal apparatuses 101, 102, 103 are software, they can be installed in the electronic apparatuses listed above. It may be implemented as a plurality of software or software modules or as a single software or software module (e.g. an APP which may implement the method). And is not particularly limited herein.
When the terminals 101, 102, 103 are hardware, a video capture device may also be installed thereon. The video acquisition equipment can be various equipment capable of realizing the function of acquiring video, such as a camera, a sensor and the like. The user may capture video using a video capture device on the terminal 101, 102, 103.
The server 105 may be a server that provides various services, such as a background server that processes data displayed on the terminal devices 101, 102, 103. The background server can analyze and process the received data and feed back the processing result (prompt information) to the terminal equipment.
The server may be hardware or software. When the server is hardware, it may be implemented as a distributed server cluster formed by multiple servers, or may be implemented as a single server. When the server is software, it may be implemented as a plurality of software or software modules, or as a single software or software module (e.g. APP that may implement the method). And is not particularly limited herein.
It should be understood that the number of terminal devices, networks, and servers in fig. 1 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation. In particular, in the case where the target data does not need to be acquired from a remote place, the above system architecture may not include a network but only a terminal device or a server.
Fig. 2 is a flowchart illustrating a perioperative treatment risk intelligent prompting method according to an embodiment of the present application. As can be seen from fig. 2, the intelligent prompting method for perioperative treatment risk in the embodiment includes the following steps:
and S210, acquiring medical record information of the patient.
In this embodiment, an executing body (for example, a server shown in fig. 1) for the perioperative treatment risk intelligent prompting method may obtain various types of information (for example, medical record information of a patient, operation information entered by a doctor, and/or daily ward round records of the patient) in a wired manner or a wireless connection manner.
Further, the execution main body may acquire various types of information (medical record information of the patient, operation information entered by a doctor, daily ward round of the patient, and the like) transmitted by an electronic device (for example, the terminal device shown in fig. 1) which is in communication connection with the execution main body, or may be various types of information which are stored locally in advance.
Wherein, the medical record information comprises the sex, age, medical history, treatment history, diagnosis information and/or examination record of the patient.
Optionally, the medical record information is a medical record filled out when the patient is admitted.
Optionally, the medical record information is acquired by a doctor or a doctor assistant through manual entry, by photographing a medical record of the hospital displayed in the HIS system and performing OCR recognition and/or voice recognition through voice entry.
And S220, analyzing the medical record information, and sending an examination item prompt to the patient according to an analysis result.
And performing big data analysis on the medical record information, acquiring the abnormal condition of the patient, and sending an examination item prompt to the patient according to the abnormal condition.
Wherein the abnormal condition comprises a physical examination abnormality and/or a check index abnormality:
the physical examination abnormality comprises scoliosis and the like;
the abnormal detection indexes comprise that white blood cells (various detection indexes) exceed a normal range and the like.
And S230, acquiring the operation information input by the doctor.
The obtaining method refers to step S210, and is not described herein again.
The operation information comprises operation type, operation access and/or operation time and other operation key information.
And S240, formulating an operation scheme according to the medical record information and the operation information input by the doctor.
And comparing the operation information input by the doctor with the medical record information to determine the operation risk point.
Wherein the risk points include high risk points such as contraindications, test indicators, age and/or skin condition not complying with surgical indications. Because the risk points of different operations are different, the examples are not given here.
And sending prompt information according to the risk points to avoid artificial careless omission.
Optionally, the doctor can adjust the surgical plan according to the prompt message. I.e., to complete the surgical protocol.
S250, analyzing the operation scheme by a decision tree method, and sending a preoperative prompt according to an analysis result;
after the operation scheme is determined (operation date), the operation scheme is analyzed through a decision tree method, the attention items and the medication information before the operation are determined, and the preoperative reminder is sent according to the attention items and the medication information.
Wherein the notice and medication information (preoperative prompt) comprises a medication prompt, a preoperative guidance prompt and/or an unconventional spare article prompt. I.e., surgical preventative medications that need to be taken in advance, preoperative indicators that need to be particularly monitored, operating room spares of drugs and/or instruments, and the like.
S260, acquiring daily ward round records of the patient;
the obtaining method refers to step S210, and is not described herein again.
Wherein the ward visit record comprises daily examination, medication, medical treatment and/or meal (drinking) of the patient.
S270, comparing the daily ward round record with the operation scheme, judging whether the patient can perform the operation or not, and sending prompt information according to the judgment result.
And comparing the daily ward round record with the operation scheme by a big data analysis and decision tree method, judging whether the operation indication is damaged and the operation can not be carried out according to the original plan, if so, sending a prompt of the incapability of carrying out the operation and the reason of the incapability of carrying out the operation. For example, if an offending medication is taken during the pre-operative period, a "patient takes XXX medication, which may result in XXX, not recommending surgery"; if not, no prompt message or normal operation prompt message is sent.
Further, the method further comprises:
acquiring data information of an intraoperative monitoring instrument of a patient, analyzing the data information, and sending an intraoperative prompt according to an analysis result;
and acquiring data information of a postoperative monitoring instrument of the patient, analyzing the data information, and sending postoperative prompts according to analysis results.
Optionally, during the operation of the patient, data information of the physical sign monitoring instrument is acquired, the data information is analyzed by a big data analysis and decision tree method, and if the data information exceeds a threshold range, an alarm prompt message is sent and an acousto-optic alarm can be given at the same time. I.e., intraoperative cues.
Optionally, after the patient performs the operation, data information of the physical sign monitoring instrument is acquired, the data information is analyzed by a big data analysis and decision tree method, and if the data information exceeds a threshold range, an alarm prompt message is sent. I.e. post-operative cues.
Further, the post-operative prompts also include prolonged observation prompts and the like according to different disease types (case-specific and abnormal conditions).
Wherein the vital signs monitoring instrument is optionally determined by a type of procedure.
Preferably, according to the type of the operation, various indexes after the operation are further analyzed by a decision tree method, and a prompt is sent to the index which is possibly caused by the type of the operation and exceeds the standard normally, so that unnecessary tension of a doctor is avoided.
Further, after the patient discharge information is acquired, a prompt of discharge indication is sent to the patient, and the prompt of discharge indication is used for prompting specific prognosis risks of the disease types. The specific prompting content is determined according to the corresponding disease symptoms.
According to the perioperative treatment risk intelligent prompting method, intelligent prompting is carried out on various risks in the perioperative period, diagnosis and treatment efficiency is improved, and labor cost is reduced. For example, supplementary examination for the characteristics of medical record (history, complications, age, test results) before operation, indexes for prolonged observation for the characteristics and abnormal conditions of medical record after operation, and the like.
An embodiment of the present application further provides an apparatus, including:
one or more processors;
storage means for storing one or more programs;
when the one or more programs are executed by the one or more processors, the one or more processors are enabled to realize the perioperative treatment risk intelligent prompting method.
In addition, the embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, and when the computer program is executed by a processor, the method for intelligently prompting perioperative treatment risk is implemented.
Reference is now made to fig. 3, which illustrates a schematic block diagram of a computer system suitable for implementing a terminal device or server of an embodiment of the present application. The terminal device shown in fig. 3 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present application.
As shown in fig. 3, the computer system includes a Central Processing Unit (CPU)301 that can perform various appropriate actions and processes based on a program stored in a Read Only Memory (ROM)302 or a program loaded from a storage section 308 into a Random Access Memory (RAM) 303. In the RAM 303, various programs and data necessary for system operation are also stored. The CPU 301, ROM 302, and RAM 303 are connected to each other via a bus 304. An input/output (I/O) interface 305 is also connected to bus 304.
The following components are connected to the I/O interface 305: an input portion 306 including a keyboard, a mouse, and the like; an output section 307 including a display such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), and the like, and a speaker; a storage section 308 including a hard disk and the like; and a communication section 309 including a network interface card such as a LAN card, a modem, or the like. The communication section 309 performs communication processing via a network such as the internet. The driver 310 is also connected to the I/O interface 305 on an as needed basis. A removable medium 311 such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, or the like is mounted on the drive 310 on an as-needed basis, so that a computer program read out therefrom is mounted on the storage section 308 on an as-needed basis.
In particular, based on the embodiments of the present disclosure, the processes described above with reference to the flowcharts may be implemented as computer software programs. For example, embodiments of the present disclosure include a computer program product comprising a computer program embodied on a computer readable medium, the computer program comprising program code for performing the method illustrated in the flow chart. In such an embodiment, the computer program may be downloaded and installed from a network through the communication section 309, and/or installed from the removable medium 311. The computer program performs the above-described functions defined in the method of the present application when executed by the Central Processing Unit (CPU) 301.
It should be noted that the computer readable medium described herein can be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, 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 disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the present application, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device. In this application, however, a computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device. Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to: wireless, wire, fiber optic cable, RF, etc., or any suitable combination of the foregoing.
The flowchart and block diagrams in the figures illustrate the architecture, functionality, and operation of possible implementations of systems, methods and computer program products according to various embodiments of the present application. In this regard, each block in the flowchart or block diagrams may represent a unit, segment, or portion of code, which comprises one or more executable instructions for implementing the specified logical function(s). It should also be noted that, in some alternative implementations, the functions noted in the block may occur out of the order noted in the figures. For example, two blocks shown in succession may, in fact, be executed substantially concurrently, or the blocks may sometimes be executed in the reverse order, depending upon the functionality involved. It will also be noted that each block of the block diagrams and/or flowchart illustration, and combinations of blocks in the block diagrams and/or flowchart illustration, can be implemented by special purpose hardware-based systems which perform the specified functions or acts, or combinations of special purpose hardware and computer instructions.
The units described in the embodiments of the present application may be implemented by software or hardware. The described units may also be provided in a processor, and may be described as: a processor includes an information measuring unit, a travel track determining unit, a mapping relation determining unit, and a driving strategy generating unit. Here, the names of these units do not constitute a limitation on the unit itself in some cases, and for example, the information measuring unit may also be described as a "unit that measures the state information of the own vehicle and the surrounding scene information".
As another aspect, the present application also provides a non-volatile computer storage medium, which may be the non-volatile computer storage medium included in the apparatus in the above-described embodiments; or it may be a non-volatile computer storage medium that exists separately and is not incorporated into the terminal. The non-transitory computer storage medium stores one or more programs that, when executed by a device, cause the device to: acquiring medical record information of a patient; analyzing the medical record information, and sending an examination item prompt to the patient according to an analysis result; acquiring operation information input by a doctor; formulating an operation scheme according to the medical record information and the operation information input by the doctor; analyzing the operation scheme by a decision tree method, and sending a preoperative prompt according to an analysis result; obtaining daily ward rounds of the patient; and comparing the daily ward round record with the operation scheme, judging whether the patient can perform the operation or not and sending prompt information according to the judgment result.
The above description is only a preferred embodiment of the application and is illustrative of the principles of the technology employed. It will be appreciated by those skilled in the art that the scope of the invention herein disclosed is not limited to the particular combination of features described above, but also encompasses other arrangements formed by any combination of the above features or their equivalents without departing from the spirit of the invention. For example, the above features may be replaced with (but not limited to) features having similar functions disclosed in the present application.
Claims (10)
1. An intelligent prompting method for perioperative treatment risk is characterized by comprising the following steps:
acquiring medical record information of a patient;
analyzing the medical record information, and sending an examination item prompt to the patient according to an analysis result;
acquiring operation information input by a doctor;
formulating an operation scheme according to the medical record information and the operation information input by the doctor;
analyzing the operation scheme by a decision tree method, and sending a preoperative prompt according to an analysis result;
obtaining daily ward rounds of the patient;
and comparing the daily ward round record with the operation scheme, judging whether the patient can perform the operation or not and sending prompt information according to the judgment result.
2. The method of claim 1, further comprising:
acquiring data information of an intraoperative monitoring instrument of a patient, analyzing the data information, and sending an intraoperative prompt according to an analysis result;
and acquiring data information of a postoperative monitoring instrument of the patient, analyzing the data information, and sending postoperative prompts according to analysis results.
3. The method of claim 2, wherein the medical record information includes gender, age, medical history, treatment history, diagnostic information, and/or examination records.
4. The method of claim 3, wherein analyzing the medical record information and sending an examination item prompt to the patient based on the analysis comprises:
analyzing the medical record information, and determining the abnormal condition of the patient according to the analysis result;
and sending an examination item prompt to the patient according to the abnormal condition.
5. The method of claim 4, wherein the abnormal condition comprises a physical anomaly and/or a verification indicator anomaly.
6. The method of claim 5, wherein formulating a surgical plan based on the medical record information and the surgical information entered by the physician comprises:
comparing the operation information input by the doctor with the medical record information to determine the operation risk point;
and formulating an operation scheme according to the operation risk points and the medical record information.
7. The method of claim 6, wherein the risk points include contraindications not complying with surgical indications and/or abnormalities in test indicators.
8. The method of claim 7, wherein the preoperative cues comprise medication cues, preoperative guidance cues, and/or unusual spare article cues.
9. An apparatus, comprising:
one or more processors;
storage means for storing one or more programs;
when executed by the one or more processors, cause the one or more processors to implement the generation method of any one of claims 1-8.
10. A computer-readable storage medium, on which a computer program is stored, which program, when being executed by a processor, carries out the method according to any one of claims 1 to 8.
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Cited By (1)
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| CN116721764A (en) * | 2023-08-10 | 2023-09-08 | 武汉楚精灵医疗科技有限公司 | Preoperative prompting method and device |
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| CN110532367A (en) * | 2019-09-02 | 2019-12-03 | 广州市妇女儿童医疗中心 | A kind of information cuing method and system |
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| CN116721764A (en) * | 2023-08-10 | 2023-09-08 | 武汉楚精灵医疗科技有限公司 | Preoperative prompting method and device |
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