CN107958708A - Risk trend appraisal procedure and system after institute - Google Patents
Risk trend appraisal procedure and system after institute Download PDFInfo
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- CN107958708A CN107958708A CN201711400579.0A CN201711400579A CN107958708A CN 107958708 A CN107958708 A CN 107958708A CN 201711400579 A CN201711400579 A CN 201711400579A CN 107958708 A CN107958708 A CN 107958708A
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Abstract
The invention discloses risk trend appraisal procedure and system after institute, wherein the method includes the steps:The medical data of passing patient is stored, generates the historical data of medical data;Using historical data as modeling data, it is trained for the purpose of the anticipation trend that the risk to obtain patient develops, generates risk forecast model;In the treatment phase of target patient, according to preset time point taken at regular intervals and medical index information corresponding with target patient and the execution information of rehabilitation scheme are stored;Treatment stage, using the execution information of the medical data of target patient and rehabilitation scheme as input, the anticipation trend of risk development is generated by risk forecast model, and generate risk evaluation result into after being admitted to hospital from target patient.The present invention automatically generates the anticipation trend of risk development of the target patient in current rehabilitation scheme, so as to effectively improve the validity for the risk assessment for the treatment of phase after chronic institute by obtaining more abundant and comprehensive institute's external information.
Description
Technical field
The present invention relates to medical domain, more particularly to risk trend appraisal procedure and system after institute.
Background technology
The full name of chronic disease is Chronic Non-Communicable Diseases, is not to refer in particular to certain disease, but onset concealment, the course of disease are grown
And protracted inflammation is not cured, lacks exact infectious organisms cause of disease evidence, the disease that cause of disease complexity and the cause of disease are not yet identified completely
The generality general name of disease.
Common chronic disease mainly has cardiovascular and cerebrovascular disease, cancer, diabetes, chronic respiratory disease etc.;Wherein, the heart
Cranial vascular disease has comprising hypertension, cerebral apoplexy and coronary heart disease etc..
One of the characteristics of chronic disease is that treatment cycle is longer, can not complete whole treatment cycle in hospital under normal circumstances;
For this reason, it may be necessary to after patient discharge, after the autonomous institute provided according to school rehabilitation scheme continue to implement after follow-up institute treatment and
Further consultation.
Because the difference of disease, individual's difference and different level of enforcement, it may be desirable to monitoring in time and adjustment institute
The individual validity and level of enforcement of therapeutic scheme afterwards, adjusts rehabilitation scheme and obtains rehabilitation efficacy after best institute as early as possible.
At present, usually when further consultation, or, by way of regularly follow-up, come look back patient after institute this
The effect of therapeutic scheme during one, understands scheme implementation status of patient etc., and according to the information obtained by aforesaid way Lai
The effect of the rehabilitation of patient is assessed, and formulates follow-up rehabilitation scheme.
Inventor has found that at least there are following defect in the prior art:
The frequency and data volume of information after the institute for the patient that school obtains are less, the assessment thus made and follow-up rehabilitation side
Case is not readily available good effect.
The content of the invention
The technical problems to be solved by the invention how are improved for convalescent risk assessment after chronic institute
Validity, specifically:
An embodiment of the present invention provides risk trend appraisal procedure after a kind of institute, including step:
S11, the medical data of the passing patient of storage, generate the historical data of medical data;The medical data includes believing in institute
Breath, institute's external information, follow-up information and rehabilitation scheme;Information includes all doctors of patient treatment stage in institute in the institute
Treat the execution information of indication information and rehabilitation scheme;Institute's external information includes the trouble gathered by long-range Medical Devices
The medical index information of person's treatment stage after institute, and, the execution information of the rehabilitation scheme after patient's execution institute;It is described with
The execution information of all medical index information and rehabilitation scheme when visiting information including obtaining patient's further consultation and follow-up;
S12, using the historical data as modeling data, the prediction developed with obtaining risk of the patient in current rehabilitation scheme becomes
It is trained for the purpose of gesture, generates risk forecast model;
S13, the whole treatment phase from being hospitalized for treatment target patient, according to preset time point taken at regular intervals and store and the mesh
Mark the corresponding medical index information of patient, and the execution information of rehabilitation scheme;The treatment phase includes treatment stage and institute in institute
Treatment stage afterwards;
S14, from the target patient into after being admitted to hospital treatment stage, using the medical data of the target patient as input, pass through
The risk forecast model generates the anticipation trend of the risk development of the target patient;
S15, the anticipation trend generation rehabilitation scheme developed according to the risk of the target patient perform assessment result.
Preferably, in the present invention, step is further included:
S21, judge whether the anticipation trend is less than target;
S22, if so, presetting the management objectives of medical index in adjusting the rehabilitation scheme of the target patient;
S23, obtain risk profile trend by the risk forecast model as input using the rehabilitation scheme after adjustment and return
Return step S21;
S24, when step S21 judging result for it is no when, generation for refer to rehabilitation scheme.
Preferably, in the present invention, the rehabilitation scheme performs assessment result and includes:
Whether risk score, the score value of the rehabilitation scheme completeness, the management of default medical index up to standard and rehabilitation suggestion.
Preferably, in the present invention, the process of institute's external information is obtained, including:
It is used as the physiological data of the medical index of patient by Medical Devices collection;
Patient user end obtains the physiological data, and institute's external information including the physiological data is sent to default long-range
Server;
The remote server updates the medical data of the patient according to institute's external information.
Preferably, in the present invention, the Medical Devices include one in batheroom scale, sphygmomanometer, blood glucose meter and cardiotach ometer
Kind and its any combination.
Preferably, in the present invention, the execution information of the rehabilitation scheme includes:
Medication record, diet record and motion recording.
Preferably, in the present invention, the process of the execution information of the rehabilitation scheme is obtained, including:
Every time during medication, patient user end is by the shooting to the medicine or the Key works Drug packing, or, by arranged on described
The scanning of the identification code of Key works Drug packing, is identified the medicine with reference to the rehabilitation scheme;
Medication record is generated according to recognition result;
Preferably, in the present invention, further include:
According to recognition result, export medicine information at the patient user end, the medicine information include the medicine whether be
Medicine should be taken, and, the title of the medicine, take mode, dosage and points for attention.
In the another side of the present invention, risk trend assessment system after a kind of institute, including remote server and trouble are additionally provided
Person's user terminal;
Suitable for performing the software program of the step after above-mentioned institute in integrated risk appraisal procedure by processor, it is stored respectively in described
In the storage device of server end and the patient.
Preferably, in the present invention, the patient user end is the mobile phone equipped with the software program.
In the present invention, historical data is built by establishing the medical data of substantial amounts of patient, then with historical data
For modeling data, to build the risk forecast model for predicting risk development trend of the patient in current rehabilitation scheme;This
Sample, works as chronic(That is, target patient)After discharge, i.e. enter after institute after the rehabilitation stage, by patient user end not
The medical index information that disconnected ground stays at home target patient needed for daily collection, and, target patient performs the rehabilitation side after institute
The execution information of case is sent in default remote server, then, can be to mesh using the risk forecast model in the present invention
The risk trend of mark patient, which is predicted and generates rehabilitation scheme, performs risk evaluation result.
As seen from the above, one aspect of the present invention is referred to using remote server come the medical treatment of the acquisition target patient of frequent
Information is marked, on the other hand, risk evaluation result can also be automatically generated by default risk forecast model, it is possible to
On the premise of excessively hospital's medical staff's workload is not increased, outside the more abundant and comprehensive institute by treatment stage after institute
Information, obtains the anticipation trend of risk development of target patient when in current rehabilitation scheme, so as to effectively improve pair
The validity of convalescent risk assessment after chronic institute.
Further, in embodiments of the present invention, can also be to medical index in rehabilitation scheme by risk forecast model
The mode being adjusted obtains more preferable anticipation trend, so can automatically obtain it is significantly more efficient refer to rehabilitation scheme,
The rehabilitation scheme thus formulated for medical staff provides effective reference, but also can be greatly enhanced the work of medical staff
Make efficiency.
Brief description of the drawings
In order to illustrate the technical solutions in the embodiments of the present application or in the prior art more clearly, below will be to embodiment or existing
There is attached drawing needed in technology description to be briefly described, it should be apparent that, drawings in the following description are only this
Some embodiments described in application, for those of ordinary skill in the art, without creative efforts,
Other attached drawings can also be obtained according to these attached drawings.
Fig. 1 is the step schematic diagram of risk trend appraisal procedure after institute described herein;
Fig. 2 is the another step schematic diagram of risk trend appraisal procedure after institute described herein;
Fig. 3 is the another step schematic diagram of risk trend appraisal procedure after institute described herein;
Fig. 4 is the another step schematic diagram of risk trend appraisal procedure after institute described herein;
Fig. 5 is the structure diagram of risk trend assessment system after institute described herein.
Embodiment
In order to make those skilled in the art more fully understand the present invention program, below in conjunction with the embodiment of the present invention
Attached drawing, is clearly and completely described the technical solution in the embodiment of the present invention, it is clear that described embodiment is only this
Invention part of the embodiment, instead of all the embodiments.Based on the embodiments of the present invention, those of ordinary skill in the art exist
All other embodiments obtained under the premise of creative work are not made, belong to the scope of protection of the invention.
In order to improve the validity for convalescent risk assessment after chronic institute, as shown in Figure 1, the present invention is real
Apply example and provide risk trend appraisal procedure after a kind of institute, as shown in Figure 1, including step:
S11, the medical data of the passing patient of storage, generate the historical data of medical data;Medical data includes information, institute in institute
External information, follow-up information and rehabilitation scheme;In institute information include patient in institute all medical index information for the treatment of stage and
The execution information of rehabilitation scheme;The patient that institute's external information includes gathering by long-range Medical Devices treatment stage after institute
Medical index information, and, patient perform institute after rehabilitation scheme execution information;Follow-up information include obtain patient's further consultation and
The execution information of all medical index information and rehabilitation scheme during follow-up;
The central inventive thinking of the embodiment of the present invention is model training to be carried out to medical data using learning model, to obtain wind
Dangerous anticipation trend, for this reason, it may be necessary to be modeled storage and the structure of data first;In embodiments of the present invention, it can be every
The whole treatment phase of patient(Including treatment stage after treatment stage in institute and institute)All medical datas recorded and stored,
Can be since when every patient is hospitalized for treatment, by patient specifically so as to accumulate the historical data to form medical data
The medical index such as blood pressure, blood glucose, heart rate and weight, therapeutic scheme or rehabilitation scheme in each therapeutic stage
Statistic record is carried out, and is stored into default remote server.
In practical applications, during remote server one side storage patient starts to discharge at the time of being hospitalized for treatment
It is interior(Treatment stage i.e. in institute), the diagnosis and treatment data of each patient, the various medical indexes measured(Such as, blood count data, blood pressure, blood
Physiological data or the sign datas such as sugar, heart rate or weight)And information in the institute such as medical scheme.
In addition, the successive treatment stage after also storing patient discharge at home(That is treatment stage after institute)Institute outside believe
Cease, the acquisition modes of institute's external information in the embodiment of the present invention generally can be the Medical Devices using some family expenses(Such as weight
Meter, sphygmomanometer, blood glucose meter and cardiotach ometer etc.)To carry out, the rehabilitation scheme that patient specifies according to the medical staff of hospital, regularly
The collection of the physiological data such as blood pressure, blood glucose, weight or heart rate is carried out, then by patient user end by these medical datas
It is uploaded in remote server;Further, it is also possible to by patient user end, will such as medication record, diet record and movement note
The execution information of the rehabilitation schemes such as record is also sent to remote server, so as to fulfill the comprehensive and high frequency of the medical data to patient
The collection of degree.
It should be noted that institute's external information further includes follow-up information, in this way, institute when can obtain patient's further consultation and follow-up
There are medical index information and the execution information of rehabilitation scheme, to make the medical data of patient more comprehensive.
Specifically, obtain institute external information process can with as shown in Fig. 2, including:
S31, gather the physiological data for being used as the medical index of patient by Medical Devices;
S32, patient user end obtain physiological data, and institute's external information including physiological data are sent to default remote service
Device;
S33, remote server update the medical data of patient according to institute's external information.
That is, in the embodiment of the present invention, during the whole medical treatment of each patient, medical data is to be continuously updated
, i.e. the time that the medical data of patient can be cured with receiving constantly increases.
Influence of the compliance for the treatment of stage patient for medical effect is huge after institute, have left the prison of medical staff
Superintending and directing and remind, patient is easy to the situation for missing medicine appearance occur, so that cause the implementation dynamics of rehabilitation scheme poor, and then
Influence whole medical effect.For this reason, in embodiments of the present invention, the generation of the medication record in rehabilitation scheme can also be carried out
Setting, to make patient avoid missing medicine, so as to improve the implementation dynamics of rehabilitation scheme.
For these reasons, further, in embodiments of the present invention, can also be by supervising patient for rehabilitation scheme
Implementation procedure mode, to improve the compliance of patient, and then improve the implementation dynamics of rehabilitation scheme, it is more preferable to obtain
Medical effect, specifically:
The process of the execution information of rehabilitation scheme is obtained, including:Every time during medication, patient user end passes through to medicine or medicine bag
The shooting of dress, or, by the scanning to the identification code arranged on Key works Drug packing, the medicine is known with reference to rehabilitation scheme
Not;Medication record is generated according to recognition result.That is, patient can pass through patient user end pair when medication every time
Medicine(Or Key works Drug packing)Shot or scanned and is uploaded in remote server, be used as medication record.In this way, when trouble
When person has the situation for missing medicine to occur, one side medical staff can root medication record learn holding for the rehabilitation scheme of patient
Prompting message is sent to patient and used by row information, on the other hand, remote server, or medical staff by its medical care terminal-pair
Family end, to remind patient to take medicine in time.
Preferably, in embodiments of the present invention, according to recognition result, medicine information can also be exported at patient user end,
Whether medicine information is that should take medicine including medicine, and, the title of medicine, take mode, dosage and points for attention.
The relatively deficient patient of medical knowledge or household are needed after institute in treatment stage to carry out taking or making for medicine
With so drug safety is also an important security risk;Due to that in rehabilitation scheme in embodiments of the present invention, can wrap
Include it is every kind of need to medicine to be used use or bright, so, by recognition result combination rehabilitation scheme, will can currently identify
Medicine is mapped with the medicine operation instruction in rehabilitation scheme, then, can be with sound or text by patient user end
The form of word exports whether the medicine of patient scan is to need the medicine taken to patient, and needs to take the name of medicine
Claim, take the medication instructions such as mode, dosage and points for attention, from can effectively avoid wrongly taking for medicine.
S12, using historical data as modeling data, the prediction developed with obtaining risk of the patient in current rehabilitation scheme becomes
Model training is carried out for the purpose of gesture, generates risk forecast model;
With the continuous accumulation of historical data, can using these medical datas as a kind of initial data of big data, pass through by
These medical datas carry out data training as modeling data, to build risk forecast model, so as to be follow-up trouble
Person carries out the prediction of risk trend.
In practical applications, the weight of each medical index in medical data can be determined first, i.e. to determine each doctor
Treat influence degree of the index for risk trend;Then by the various medical datas including medical index it is again modeling data, leads to
Model training is crossed to generate the anticipation trend of risk development of the patient in current rehabilitation scheme, specifically, as shown in figure 3, can
To comprise the following steps:
S41, by modeling data be divided into training data and test data according to preset ratio;
It is in the pass for learning and finding various medical datas between final progression of the disease trend during model training is carried out
The process of connection relation, can be while train by the way that modeling data is divided into training data and test data according to preset ratio
Model is built while the prediction effect of model is verified, can finally obtain effective prediction model;In practical applications, can be with
Preset ratio is set as 7 to 3, i.e. 70% data are used as training data, and in addition 30% data are used as test number
According to.It should be noted that in embodiments of the present invention, the setting value of preset ratio can be according to those skilled in the art
Need to be adjusted and set, do not do specific restriction herein.
S42, be modeled using training data, and is assessed using test data;
It is modeled by training data, the prediction to build for carrying out risk development of the patient in current rehabilitation scheme becomes
The model of gesture;In practical applications, the disaggregated model used in the embodiment of the present invention can be Logic Regression Models, decision tree
Model, supporting vector machine model, discriminative model or neural network model, or by model more than two of which come each other
Confirmation and amendment.
Test data can carry out outcome evaluation in modeling process, to verify the accuracy of prediction model and validity.
Step is returned after S43, parameter item and/or iterations when the result of assessment is not up to preset value, and adjustment models
Rapid S41;When the result of assessment reaches preset value, modeling terminates.
When the result of assessment is not up to preset value, illustrate that the prediction result of current risk forecast model is accurate not enough
Really, it is necessary to further train;When the result of assessment reaches preset value, illustrate the prediction result of current risk forecast model
Accurate enough, modeling terminates, which can be used for predicting that risk development of the patient in current rehabilitation scheme becomes
Gesture.
S13, the whole treatment phase from being hospitalized for treatment target patient, according to preset time point taken at regular intervals and storage and mesh
Mark the corresponding medical index information of patient, and the execution information of rehabilitation scheme;Treatment phase includes controlling after treatment stage and institute in institute
The treatment stage;
After risk forecast model structure, each target patient(Target patient is the patient of application risk prediction model)Need
The medical data of itself is used as to the input of risk forecast model;For this reason, the whole treatment from being hospitalized for treatment target patient
Phase, according to preset time point taken at regular intervals and stores medical index information corresponding with target patient, and the execution of rehabilitation scheme
Information;Treatment phase includes treatment stage after treatment stage in institute and institute;That is, target patient treats rank in the institute of hospital
Section, by by the medical data storage that medical staff is obtained to predetermined server;Then, after target patient is left hospital, also
Using the Medical Devices of some family expenses(Such as batheroom scale, sphygmomanometer, blood glucose meter and cardiotach ometer)To carry out, patient is according to hospital
The rehabilitation scheme that medical staff specifies, regularly carries out the collection of the physiological datas such as blood pressure, blood glucose, weight or heart rate, so
These medical datas are uploaded in remote server by patient user end afterwards;Further, it is also possible to by patient user end, will
The execution information of the rehabilitation schemes such as medication record, diet record and motion recording is also sent to remote server, so that real
Now to comprehensive and frequent collection of the medical data of patient.
It should be noted that institute's external information further includes follow-up information, in this way, institute when can obtain patient's further consultation and follow-up
There are medical index information and the execution information of rehabilitation scheme, to make the medical data of patient more comprehensive.
S14, from target patient into after being admitted to hospital treatment stage, using the medical data of target patient as input, pass through risk
The anticipation trend of the risk development of prediction model generation target patient;
The anticipation trend of risk development of the target patient in current rehabilitation scheme can be generated by risk forecast model, according to
The anticipation trend, can know the development trend of the current risk of target patient and cause the information such as factor existing for risk.
S15, the anticipation trend generation rehabilitation scheme developed according to the risk of target patient perform assessment result.
In order to make the prediction result of risk forecast model can be adapted to different crowds, it is necessary to be held by generating rehabilitation scheme
The mode of row assessment result, to generate the risk evaluation result of different expression mode for different crowds;Specifically, cure
Rehabilitation scheme needed for shield personnel, which performs assessment result, can bias toward single index management objectives and result simulation, so as to facilitate health
The reference of compound case and further adjustment;And for target patient, its rehabilitation scheme performs assessment result and can then lay particular stress on
In the summary of overall management result, to lift the treatment confidence of target patient, and, carry out instructing to do for patient behavior
In advance.When assessment result is used for target patient in use, can include:Risk score, the score value of rehabilitation scheme completeness, default doctor
Treat index whether management up to standard and rehabilitation suggestion etc.;For example, there is provided the particular content to the assessment result of target patient
Can be:" your current palsy risk score is 78 points, rises 6 points than last month, integral rehabilitation scheme completeness 76%, you
Blood glucose, blood pressure management it is up to standard, but your weight and blood fat management need further to strengthen, it is proposed that you use following drink
Food scheme coordinates drug therapy ... ".
Preferably, in order to assist medical staff easily to obtain the adjustment mode of rehabilitation scheme, new rehabilitation scheme is predicted
Medical effect, in the present invention, as shown in figure 4, step can also be included:
Whether S21, judge anticipation trend less than default target;
First, a target is set, i.e. expect the desired value that anticipation trend can reach;Then judge, with current doctor
Data are treated as input, whether the anticipation trend obtained by risk forecast model has been less than target, so as to judge current
Rehabilitation scheme or rehabilitation scheme execution it is whether preferable.
S22, if so, presetting the management objectives of medical index in adjusting the rehabilitation scheme of the target patient;
If anticipation trend is less than target, then illustrates that rehabilitation scheme row needs are adjusted;So by adjusting rehabilitation
Medical index is preset in scheme, rehabilitation scheme can be updated.
S23, using the rehabilitation scheme after adjustment as input by the risk forecast model acquisition risk profile trend
And return to step S21;
Every time after renewal rehabilitation scheme, new risk profile trend can be obtained by risk forecast model, then, is judged
Whether the rehabilitation scheme after renewal, the anticipation trend obtained by risk forecast model are less than target, until after renewal
Rehabilitation scheme can cross to obtain and reach the anticipation trend of target.
S24, when step S21 judging result for it is no when, generation for refer to rehabilitation scheme.
Rehabilitation scheme after renewal can cross the anticipation trend for obtaining and reaching target, illustrate that the rehabilitation scheme can take
Good Expected Results, there is good reference value, thus medical staff can come according to the rehabilitation scheme of the reference for
Target patient determines the rehabilitation scheme being more suitable for.
In the another side of the present invention, risk trend assessment system after a kind of institute is additionally provided, as shown in figure 5, including long-range
Server 01 and patient user end 02;Suitable for integrated risk appraisal procedure after embodiment intermediate court corresponding to performing Fig. 1 as processor
In step software program, be stored respectively in the storage device at server end 01 and patient user end 02.Preferably, at this
In invention, patient user end 02 is the mobile phone equipped with software program.
Due to the server end 01 in the embodiment of the present invention and the operation principle and beneficial effect at patient user end 02
Detailed record and description have been done in embodiment after the institute corresponding to Fig. 1 in integrated risk appraisal procedure, in this manner it is possible to
Suffer from the embodiment after institute in integrated risk appraisal procedure to understand the embodiment of the present invention, therefore, herein with reference to corresponding to Fig. 1
Repeat no more.
In several embodiments that the embodiment of the present invention is provided, it should be understood that disclosed system, device and side
Method, can realize by another way.For example, device embodiment described above is only schematical, for example, described
The division of unit, is only a kind of division of logic function, can there is other dividing mode, such as multiple units when actually realizing
Or component can combine or be desirably integrated into another system, or some features can be ignored, or not perform.It is another, institute
Display or the mutual coupling, direct-coupling or communication connection discussed can be by some interfaces, device or unit
INDIRECT COUPLING or communication connection, can be electrical, machinery or other forms.
The unit illustrated as separating component may or may not be physically separate, be shown as unit
The component shown may or may not be physical location, you can with positioned at a place, or can also be distributed to multiple
In network unit.Some or all of unit therein can be selected to realize the mesh of this embodiment scheme according to the actual needs
's.
In addition, each functional unit in each embodiment of the present invention can be integrated in a processing unit, can also
That unit is individually physically present, can also two or more units integrate in a unit.Above-mentioned integrated list
Member can both be realized in the form of hardware, can also be realized in the form of SFU software functional unit.
If the integrated unit is realized in the form of SFU software functional unit and is used as independent production marketing or use
When, it can be stored in a computer read/write memory medium.Based on such understanding, technical scheme is substantially
The part to contribute in other words to the prior art or all or part of the technical solution can be in the form of software products
Embody, which is stored in a storage medium, including some instructions are used so that a computer
Equipment(Can be personal computer, server, or network equipment etc.)Perform the complete of each embodiment the method for the present invention
Portion or part steps.And foregoing storage medium includes:USB flash disk, mobile hard disk, read-only storage(ROM, Read-Only
Memory), random access memory(RAM, Random Access Memory), ReRAM, MRAM, PCM, NAND Flash,
NOR Flash, Memristor, magnetic disc or CD etc. are various can be with the medium of store program codes.
The above, the above embodiments are merely illustrative of the technical solutions of the present invention, rather than its limitations;Although with reference to before
Embodiment is stated the present invention is described in detail, it will be understood by those of ordinary skill in the art that:It still can be to preceding
State the technical solution described in each embodiment to modify, or equivalent substitution is carried out to which part technical characteristic;And these
Modification is replaced, and the essence of appropriate technical solution is departed from the spirit and scope of various embodiments of the present invention technical solution.
Claims (10)
1. risk trend appraisal procedure after a kind of institute, it is characterised in that including step:
S11, the medical data of the passing patient of storage, generate the historical data of medical data;The medical data includes believing in institute
Breath, institute's external information, follow-up information and rehabilitation scheme;Information includes all doctors of patient treatment stage in institute in the institute
Treat the execution information of indication information and rehabilitation scheme;Institute's external information includes the trouble gathered by long-range Medical Devices
The medical index information of person's treatment stage after institute, and, the execution information of the rehabilitation scheme after patient's execution institute;It is described with
The execution information of all medical index information and rehabilitation scheme when visiting information including obtaining patient's further consultation and follow-up;
S12, using the historical data as modeling data, the prediction developed with obtaining risk of the patient in current rehabilitation scheme becomes
It is trained for the purpose of gesture, generates risk forecast model;
S13, the whole treatment phase from being hospitalized for treatment target patient, according to preset time point taken at regular intervals and store and the mesh
Mark the corresponding medical index information of patient, and the execution information of rehabilitation scheme;The treatment phase includes treatment stage and institute in institute
Treatment stage afterwards;
S14, from the target patient into after being admitted to hospital treatment stage, with the medical data of the target patient and rehabilitation scheme
Execution information is input, and the anticipation trend of the risk development of the target patient is generated by the risk forecast model;
S15, the anticipation trend generation rehabilitation scheme developed according to the risk of the target patient perform assessment result.
2. the risk trend appraisal procedure after institute according to claim 1, it is characterised in that further include step:
S21, judge whether the anticipation trend is less than target;
S22, if so, presetting the management objectives of medical index in adjusting the rehabilitation scheme of the target patient;
S23, obtain risk profile trend by the risk forecast model as input using the rehabilitation scheme after adjustment and return
Return step S21;
S24, when step S21 judging result for it is no when, generation for refer to rehabilitation scheme.
3. the risk trend appraisal procedure after institute according to claim 1, it is characterised in that the rehabilitation scheme performs assessment
As a result include:
Whether risk score, the score value of the rehabilitation scheme completeness, the management of default medical index up to standard and rehabilitation suggestion.
4. the risk trend appraisal procedure after institute according to claim 1, it is characterised in that obtain the mistake of institute's external information
Journey, including:
It is used as the physiological data of the medical index of patient by Medical Devices collection;
Patient user end obtains the physiological data, and institute's external information including the physiological data is sent to default long-range
Server;
The remote server updates the medical data of the patient according to institute's external information.
5. the risk trend appraisal procedure after institute according to claim 4, it is characterised in that the Medical Devices include weight
One kind and its any combination in meter, sphygmomanometer, blood glucose meter and cardiotach ometer.
6. the risk trend appraisal procedure after institute according to claim 1, it is characterised in that the rehabilitation scheme performs letter
Breath includes:
Medication record, diet record and motion recording.
7. the risk trend appraisal procedure after institute according to claim 6, it is characterised in that
The process of the execution information of the rehabilitation scheme is obtained, including:
Every time during medication, patient user end is by the shooting to the medicine or the Key works Drug packing, or, by arranged on described
The scanning of the identification code of Key works Drug packing, is identified the medicine with reference to the rehabilitation scheme;
Medication record is generated according to recognition result.
8. the risk trend appraisal procedure after institute according to claim 7, it is characterised in that further include:
According to recognition result, export medicine information at the patient user end, the medicine information include the medicine whether be
Medicine should be taken, and, the title of the medicine, take mode, dosage and points for attention.
9. risk trend assessment system after a kind of institute, it is characterised in that including remote server and patient user end;
Suitable for performing the software program of the step as described in any in claim 1 to 8 by processor, the clothes are stored respectively in
Business device end and the storage device at the patient user end.
10. the risk trend assessment system after institute according to claim 9, it is characterised in that the patient user end is dress
There is the mobile phone of the software program.
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Cited By (14)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN108735301A (en) * | 2018-05-18 | 2018-11-02 | 杭州认识科技有限公司 | Medical follow up method, apparatus and electronic equipment |
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Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103020454A (en) * | 2012-12-15 | 2013-04-03 | 中国科学院深圳先进技术研究院 | Method and system for extracting morbidity key factor and early warning disease |
CN105046406A (en) * | 2015-06-25 | 2015-11-11 | 成都厚立信息技术有限公司 | Inpatient medical management quality assessment method |
CN105792731A (en) * | 2013-07-18 | 2016-07-20 | 帕克兰临床创新中心 | Patient care surveillance system and method |
CN106777909A (en) * | 2016-11-28 | 2017-05-31 | 深圳市人民医院 | Gestational period health risk assessment system |
CN107358047A (en) * | 2017-07-13 | 2017-11-17 | 刘峰 | Diabetic assesses and management system |
-
2017
- 2017-12-22 CN CN201711400579.0A patent/CN107958708A/en active Pending
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
CN103020454A (en) * | 2012-12-15 | 2013-04-03 | 中国科学院深圳先进技术研究院 | Method and system for extracting morbidity key factor and early warning disease |
CN105792731A (en) * | 2013-07-18 | 2016-07-20 | 帕克兰临床创新中心 | Patient care surveillance system and method |
CN105046406A (en) * | 2015-06-25 | 2015-11-11 | 成都厚立信息技术有限公司 | Inpatient medical management quality assessment method |
CN106777909A (en) * | 2016-11-28 | 2017-05-31 | 深圳市人民医院 | Gestational period health risk assessment system |
CN107358047A (en) * | 2017-07-13 | 2017-11-17 | 刘峰 | Diabetic assesses and management system |
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CN113192642B (en) * | 2021-04-01 | 2023-02-28 | 四川大学华西医院 | Surgical patient postoperative recovery state prediction model construction system |
CN113192642A (en) * | 2021-04-01 | 2021-07-30 | 四川大学华西医院 | Method for constructing prediction model of postoperative recovery state of surgical patient |
CN113053535B (en) * | 2021-04-20 | 2022-07-22 | 四川大学华西医院 | Medical information prediction system and medical information prediction method |
CN113053535A (en) * | 2021-04-20 | 2021-06-29 | 四川大学华西医院 | Medical information prediction system and medical information prediction method |
CN113744879A (en) * | 2021-07-27 | 2021-12-03 | 北京航空航天大学 | Brain stroke prognosis health-care evaluation system based on prognosis scoring algorithm |
CN114822845A (en) * | 2022-04-14 | 2022-07-29 | 深圳市铱硙医疗科技有限公司 | Rehabilitation management method and system based on doctor use |
CN116805525A (en) * | 2023-08-21 | 2023-09-26 | 营动智能技术(山东)有限公司 | Chronic disease informationized management method, system and storage medium |
CN116805525B (en) * | 2023-08-21 | 2023-11-07 | 营动智能技术(山东)有限公司 | Chronic disease informationized management method, system and storage medium |
CN118197615A (en) * | 2024-02-28 | 2024-06-14 | 北京凯普顿医药科技开发有限公司 | Postoperative risk prediction method and system based on big data and artificial intelligence |
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