CN106951691A - Mobile telemedicine management method based on cloud platform - Google Patents

Abstract

The present invention relates to the mobile telemedicine management method based on cloud platform, the patient physiological data that patient's mobile client is gathered according to patient physiological data Acquisition Instrument generates the peculiar reference value of the illness of physiological data illness curve and the various physiological datas of correspondence patient of correspondence sufferers themselves；Cloud platform is extracted in pre- pre- the diagnose a disease disease diagnosing a disease disease model and obtain current patents of the information such as patient information and sex, age, birthplace, the occupation of the registered all patients of the cloud platform generation for all patients in preset period；Cloud platform installs default forwarding criterion transmission patient information, patient physiological data value set, the peculiar reference value of illness and pre- disease of diagnosing a disease and carries out remote diagnosis to corresponding hospital services subsystem, and forming the electronics signed with it by expert doctor goes to a doctor case history to patient.The mobile telemedicine management method effectively can be tentatively made to the valuable reference information of diagnosis illness by mobile client at patient and cloud platform, improve mobile telemedicine efficiency.

Description

Mobile telemedicine management method based on cloud platform

Technical field

The present invention relates to portable medical field, more particularly to a kind of mobile telemedicine management method based on cloud platform.

Background technology

In recent years, with mobile Internet continue to develop and intelligent terminal technology increasingly mature, " portable medical " Concept be progressively known.Portable medical be a kind of Medical Devices by patient gather patient blood pressure, The physiological datas such as heart rate, and these physiological datas are sent to the Novel medical mode of doctor terminal by mobile Internet.Example Such as, current portable medical can help patient at home by mobile terminal or computer realize reservation register, pay clearing etc. Medical procedures, greatly solve patient apart from the problem of hospital's distance is remote, the payment stand-by period of queuing up is long.

Although existing portable medical mode facilitates patient to a certain extent, it is still come with some shortcomings Place：When patient is registered by the subsystem progress reservation of mobile terminal access hospital, it usually needs input oneself by mobile terminal Essential information, such as name, contact method and home address, or even identification card number etc. are related to the information of individual privacy, one Denier can not effectively be protected to the data of the individual privacy information of patient, be very easy to cause leakage of personal information, by each Harassing call, the interference of fraudulent call are planted, the medical mood of patient is influenceed；Although some Medical Devices can gather the life of patient Data are managed, but Medical Devices do not make the processing for having real value for Illnesses Diagnoses to the physiological data of collection, but Hospital is transmitted directly to, to make final Illnesses Diagnoses by doctor completely, although facilitate patient, but also combined to doctor The illness that a large amount of physiological datas diagnose each patient causes problem, and doctor generally requires to take a substantial amount of time and could completed to every The Illnesses Diagnoses of one patient, so still reduce medical efficiency；Because mobile Internet is realized positioned at different regions Patient and the mobile interchange of doctor, cause doctor to be made when facing the difficult and complicated cases of patient and effectively study and judge comprehensively, but neglect Personal patient information's factor such as sex, age, birthplace, place of working, residence and occupation of patient has been omited to patient The influence of illness, so that the patient condition that diagnosis go out is not accurate enough.

The content of the invention

The technical problems to be solved by the invention are to provide a kind of long-range shifting based on cloud platform for above-mentioned prior art Dynamic medical control method.The mobile telemedicine management method can either effectively protect individual of the patient during portable medical Privacy information data, tentatively make to the valuable reference information of diagnosis illness, again by the mobile client at patient Personal patient information's factor such as the sex of patient, age, birthplace, place of working, residence and occupation can be made synthetic weights There is provided the information for having actual reference to doctor's Accurate Diagnosis difficult and complicated illness after weighing apparatus, portable medical quality is improved.

The present invention solve the technical scheme that is used of above-mentioned technical problem for：Mobile telemedicine management based on cloud platform Method, for including patient physiological data Acquisition Instrument, patient's mobile client, doctor's client, hospital services subsystem, medicine The mobile telemedicine management system that shop service subsystem and cloud platform are formed, patient physiological data Acquisition Instrument connection patient Mobile client, patient's mobile client and doctor's client connect hospital services subsystem respectively, hospital services subsystem and Pharmacy's service subsystem connects cloud platform respectively；Characterized in that, the mobile telemedicine management method based on cloud platform Comprise the following steps 1 to step 9：

Step 1, hospital is registered to obtain user name and login password by hospital services subsystem at cloud platform, And register the affiliated information about doctor in information for hospital and hospital；Patient is registered at cloud platform by patient's mobile client and stepped on Note registers the patient information and telephone number of patient itself to obtain user name and login password；Pharmacy is serviced by pharmacy Subsystem is registered to obtain user name and login password at cloud platform, and registers in the pharmacy information of each medicine and right Dutiable value；Cloud platform is to hospital services subsystem, patient and the corresponding user name of pharmacy's service subsystem and login password point Encryption is not made；The patient information at least gender information including patient, age information, birthplace information, place of working information, residence Residence information, occupational information, academic information, history information, height information and body weight information；

Wherein, cloud platform encryption user name and the process of login password comprise the following steps 1-1 to step 1-5：

The enrollment page of registration information is filled in step 1-1, cloud platform generation for user, and provides special for uploading The picture addition control of family head portrait picture；The registration operation time limit registered for user's registration is provided with the enrollment page, with User is set to complete registration process within the registration operation time limit of restriction；Wherein, cloud platform limits institute's addition figure in advance The maximum of piece pixel value is Pixels_max；There is enrollment page the user name input frame and donating bond that supply access customer name to enter to step on The numerical value password box that U of land password arrange according to preset order；Institute's key in setting row's serial number u u-th of numerical value password box The numerical value entered is Q_u；0≤Q_u≤9；6≤U≤10；1≤u≤U；

Step 1-2, user is after filling in and finishing the log-on message including user name and login password, by enrollment page Picture addition control the head portrait picture that user selects is added to cloud platform, and the user filled in by cloud platform storage user Name；

Step 1-3, cloud platform extracts user and adds the pixel value of head portrait picture, and obtains the height of added head portrait picture The characteristic value of angle value, width value and added head portrait picture；Added head portrait picture is designated as JPG, adds head portrait picture JPG Pixel value be designated as Pixels_JPG；Added head portrait picture JPG height value is designated as High_JPG, add head portrait picture JPG's Width value is designated as Width_JPG；Added head portrait picture JPG characteristic value is designated as Feature_JPG；

Step 1-4, cloud platform according to user add head portrait picture characteristic value and user in each numerical value password box The numerical value of key entry, calculates the difference between each key entry numerical value and added head portrait picture characteristic value respectively, and with resulting difference Value set as user login password；Wherein, the login password of user is labeled as Password；Password= {Differ_u}；Differ_u=Q_u-Feature_JPG；Differ_uRepresent numerical value Q typed in u-th of numerical value password box_uWith institute Add head portrait picture characteristic value Feature_JPGBetween difference；

Step 1-5, when cloud platform monitors that user attempts to log on by inputting the form of password, cloud platform is judging Current user name and to should the head portrait picture of user inputted by cloud platform storage and user in each numerical value password box Numerical value is corresponded to when meeting the difference set in step 1-4, then cloud platform assert that user has keyed in correct user name and correspondingly Login password；Otherwise, cloud platform refuses User logs in into the system of the cloud platform；

Step 2, the various set in advance of patient is gathered according to default collection period using patient physiological data Acquisition Instrument Physiological data, and the various physiological data values of collection are sent at patient's mobile client as patient physiological data value set Reason；Wherein, patient physiological data value set is labeled as S, S={ P_i, i=1,2 ..., I；Default collection period is labeled as T, collection To physiological data value be labeled asN=1,2 ..., N；P_iRepresent i-th kind of life in patient physiological data value set S The title of data is managed, I represents the species number of physiological data in patient physiological data value set S；N is represented in collection period T The physiological data P collected_iTotal number,Represent to be directed to physiological data P_iCollected in collection period T N-th of physiological data value；The physiological data species to be gathered is preset by patient physiological data Acquisition Instrument；

Step 3, after patient's successful log patient's mobile client, patient's mobile client is given birth to according to the patient received Manage data value set and patient information, the physiological data illness curve of generation correspondence sufferers themselves and to obtain correspondence patient each Plant the peculiar reference value of illness of physiological data；Wherein, the physiological data illness curvilinear equation and the illness of patient of sufferers themselves Peculiar reference value computing formula is as follows：

F () represents physiological data illness curvilinear equation, ε₀Default physiological data illness screening threshold value is represented,Represent correspondence patient physiological data P_iThe peculiar reference value of illness；Represent corresponding in collection period T Patient physiological data P_iAverage,Represent to be directed to physiological data P_iOffset constant during in normal condition；

Step 4, cloud platform is extracted in the patient information of the registered all patients of the cloud platform, and root in preset period According to the gender information of each patient, age information, birthplace information, place of working information, residence information, occupational information, educational background letter Breath, history information, height information and the generation of body weight information are directed to the pre- disease model of diagnosing a disease of all patients, by cloud platform according to gained The patient information that pre- diagnose a disease disease model and current patents are registered, obtains the pre- disease of diagnosing a disease of current patents, for current patents Tentatively understand the conditions of oneself；Wherein, disease model of diagnosing a disease in advance is labeled as Symptom：

Symptom={ Symptom_g, g=1,2 ..., G；

Wherein, Symptom_gRepresent that the g kinds that draw of cloud platform are diagnosed a disease disease in advance, G represents that cloud platform can draw pre- disease of diagnosing a disease Total species number；Patient_wW-th of patient is represented, W represents the total number of registered all patients at cloud platform； Symptom'_wRepresent patient Patient_wThe illness title confirmed through doctor, Gender_wRepresent patient Patient_wSex letter Breath, Age_wRepresent patient Patient_wAge information, BornPlace_wRepresent patient Patient_wBirthplace information, WorkPlace_wRepresent patient Patient_wPlace of working information, Residence_wRepresent patient Patient_wResidence information, Job_wRepresent patient Patient_wOccupational information, Education_wRepresent patient Patient_wAcademic information, Medicalhistory_wRepresent patient Patient_wSuffered from illness Symptom'_wHistory information, Height_wRepresent patient Patient_wHeight information, Weight_wRepresent patient Patient_wBody weight information；Represent in cloud At platform it is registered and with patient Patient_wWith sex and with Symptom'_wPatient's total number of illness,Represent it is registered at cloud platform and with patient Patient_wWith the age and with Symptom'_wIllness Patient's total number,Represent it is registered at cloud platform and with patient Patient_wWith birthplace and With Symptom'_wPatient's total number of illness,Represent registered at cloud platform and and patient Patient_wWith place of working and with Symptom'_wPatient's total number of illness,Represent in cloud platform Place it is registered and with patient Patient_wWith residence and with Symptom'_wPatient's total number of illness, Represent it is registered at cloud platform and with patient Patient_wWith occupation and with Symptom'_wPatient's total number of illness,Represent it is registered at cloud platform and with patient Patient_wWith educational background and with Symptom'_w Patient's total number of illness,Represent it is registered at cloud platform and with patient Patient_wTogether Sample has medical history and with Symptom'_wPatient's total number of illness,Represent at cloud platform Registration and with patient Patient_wSame height and with Symptom'_wPatient's total number of illness, Represent it is registered at cloud platform and with patient Patient_wSame body weight and with Symptom'_wPatient's total number of illness； WithInclude patient Patient in signified number_w；σ₀~σ_GIt is that cloud platform is default pre- to examine Illness classification constant；

Step 5, patient's mobile client is right by the patient information of its affiliated patient, patient physiological data value set and gained Answer the peculiar reference value of illness to send to cloud platform, criterion is forwarded by patient information, patient physiological data according to default by cloud platform The pre- disease of diagnosing a disease of the patient obtained by cloud platform is logical in data network in the peculiar reference value of value set, corresponding illness and step 4 Start transmission program when smooth and be sent to corresponding hospital services subsystem；Wherein, the default forwarding criterion of cloud platform is as follows：

Represent default correspondence patient physiological data P_iThe peculiar decision threshold of illness, Hospital_optRepresent Evaluation of patient coefficient highest hospital, Min () represents to take minimum value, Score_mRepresent that evaluation of m-th of patient to hospital is beaten Score value, M represents registered at cloud platform and the marking that judged to hospital patient's total number,Represent in known time Section T₁The average value that interior all M patients give a mark to Hospital evaluation,Represent in known time section T₁Interior patient is commented hospital The undulating value of valency marking,Represent hospital in known time section T₁Interior malpractice rate；Hospital_disoptRepresent Registered at cloud platform and remove remaining hospital after evaluation of patient coefficient highest hospital；→ represent that cloud platform is believed for patient The routing direction of breath, patient physiological data value set and the peculiar reference value of correspondence illness；

Step 6, the hospital services subsystem of each hospital is at least receiving the patient information of cloud platform forwarding twice, patient After physiological data value set and the peculiar reference value of corresponding illness, hospital services subsystem automatically extracts the illness feature of patient Information, and according to the illness characteristic information of extracted patient send into affiliated hospital to should illness first visit section office doctor Client, first visit conclusion is made to the current illness of patient by the first visit doctor of first visit section office, and by first visit conclusion, the first visit of patient Sequence number and patient data are transmitted to doctor's client of the expert section office corresponding with first visit conclusion；The patient data includes The peculiar reference value of patient information, patient physiological data value set and corresponding illness；Wherein, the hospital services subsystem The process for automatically extracting patient condition's characteristic information comprises the following steps 6-1 to step 6-4：

Step 6-1, hospital services subsystem according to cloud platform forward patient information, patient physiological data value set and The number of times of the peculiar reference value of corresponding illness, obtains the preposition deviation of the last each physiological data of patient；Wherein：

Represent corresponding physiological data P during patient's kth_iPreposition deviation；K represents that cloud platform forwards patient The number of times of information, patient physiological data value set and the peculiar reference value of correspondence illness；Represent to be directed to physiological data P_iIt is in Offset constant during normal condition；

Step 6-2, hospital services subsystem according to cloud platform forward patient information, patient physiological data value set and The number of times of the peculiar reference value of corresponding illness, the rearmounted deviation of each physiological data when obtaining patient to current number of times；Wherein：

Represent corresponding physiological data P during patient the K+1 times_iRearmounted deviation；K+1 represents current cloud platform institute Forward the number of times of patient information, patient physiological data value set and the peculiar reference value of correspondence illness；Represent to be directed to physiology number According to P_iOffset constant during in normal condition；

Step 6-3, hospital services subsystem presets the illness feature decision threshold of each physiological data, and gown respectively Subsystem be engaged according to the corresponding preposition deviation of each physiological data of gained patient and rearmounted deviation, patient's correspondence physiology number is obtained According to burst deviation；Wherein：Represent correspondence patient physiological data P_iBurst deviation,Represent correspondence patient physiological data P_iPreposition deviation,Represent correspondence patient physiological data P_iRearmounted deviation Value；Correspondence physiological data P_iIllness feature decision threshold be labeled as

Step 6-4, hospital services subsystem is according to the burst deviation of each physiological data of gained patient and default each The illness feature decision threshold of physiological data carries out illness judgement respectively, to judge whether patient illness occurs：

WhenWhen, represent the physiological data P of patient_iThere is exception, then hospital services subsystem indicates that patient goes out Corresponding physiological data P is showed_iIllness；WhenWhen, represent the physiological data P of patient_iDo not occur exception, then gown Business subsystem indicates the physiological data P of patient_iNormally；

Step 7, the expert doctor in expert section office using the doctor's client of oneself receive that first visit section office send just Conclusion, the first visit sequence number of patient and patient information are examined, and sets up electronics medical case history of the patient in the hospital, while by the doctor Raw client is done the encryption process to the medical case history of electronics of patient, to protect patient's individual privacy information；Wherein, the doctor visitor The medical case history process of the electronics of family end encryption patient comprises the following steps 7-1 to step 7-4：

Step 7-1, doctor's client prestores the electronic anti-fogery stamped signature colour picture of affiliated expert doctor, and with electronics False proof stamped signature colour picture issues the audit voucher of the medical case history of electronics as doctor；Wherein, the electronics of the expert doctor is prevented Pseudo- stamped signature colour picture is designated asJ=1,2 ..., J, j represent that hospital services subsystem assigns the electricity of expert doctor Sub- stamped signature sequence number, J represents that hospital services subsystem assigns total Electronic Signature number of each expert doctor；Doct_jExpression is gathered around There is Electronic Signature serial number j doctor；

Step 7-2, doctor's client obtains the gray scale of each color in expert doctor's electronic anti-fogery stamped signature colour picture The height value and width value of value and electronic anti-fogery stamped signature colour picture, obtain expert doctor's electronic anti-fogery stamped signature colour picture The anti-pseudoindex of stamped signature；Wherein, the anti-pseudoindex of the corresponding stamped signature of expert doctor is designated asExpert doctor's electronic anti-fogery label Chapter colour pictureThe gray scale value of middle color is designated asElectronic anti-fogery stamped signature colour pictureHeight value be designated asElectronic anti-fogery stamped signature colour pictureWidth value be designated as

Wherein, V refers to total species number of all colours in expert doctor's electronic anti-fogery stamped signature colour picture,Represent v kinds color in electronic anti-fogery stamped signature colour pictureIn gray scale value；

The corresponding anti-pseudoindex of stamped signature of the gained expert doctor is sent to hospital services by step 7-3, doctor's client Subsystem storage is put on record, while by hospital services subsystem by the anti-pseudoindex of the stamped signature of the expert doctor put on record and hospital The identity information of service subsystem is integrated, to obtain the verification code information that the medical case history of electronics is consulted for patient；Wherein, correspondence institute The verification code information for stating the medical case history of electronics is labeled asHospitol_Doctj Represent expert doctor Doct_jThe hospital services subsystem held office, T_DoctjRepresent expert doctor the anti-pseudoindex of stamped signature it is effective Time value；

Step 7-4, doctor's client will consult the verification code information of the medical case history of electronics for patient in the form of short message Patient is sent in cloud platform leaves the mobile terminal of telephone number, to realize effective time of the patient in the anti-pseudoindex of stamped signature It is interior that the medical case history of the electronics of oneself is consulted by cloud platform；

Step 8, doctor's client at expert doctor extracts the various physiological data values of the patient of reception respectively, and will carry The various physiological data values taken compare judgement with corresponding normal physiological data value respectively, so that expert doctor decides whether pair Current patents make remote diagnosis, and draw the peculiar value of each physiological data of patient by doctor's client of expert doctor, with Expert doctor is helped to understand the physiological data situation of change of patient in advance；Wherein, patient physiological data P_iPeculiar value be designated as ζ_Pi：

N' represents doctor's client at expert doctor in period T₁Interior received patient physiological data P_iNumber,Represent in period T₁Interior patient's physiological data P_iUndulating value,Represent doctor's client at expert doctor For the physiological data P of normal population_iPre-set normal fluctuation constant；

When any of patient physiological data set physiological data is not in the normal range (NR) of this kind of physiological data, Then doctor's client at expert doctor is made alarm and reminded；Otherwise, doctor's client at expert doctor refuses alarm；

Step 9, expert doctor makes remote visiting to patient by doctor's client and invited and long-range just in patient's completion Examine after confirmation, patient progress of the expert doctor by its doctor's client to confirming remote visiting at hospital services subsystem is standby Case；After patient pays diagnostic fees, expert's diagnosis patient condition and by outputed for patient condition to include this special The electronic prescription of family's doctor's professional information is respectively supplied to cloud platform and the hospital services subsystem belonging to the expert doctor enters Row is put on record in real time；Patient logs in cloud platform to check electronic prescription that expert doctor provides by patient's mobile client, and presses Medicine is bought at the pharmacy's service subsystem put on record that cloud platform is provided according to electronic prescription, mobile telemedicine mistake is completed Journey.

Further, the information for hospital includes hospital's brief introduction, hospital department, each section office and is good at diagnosis direction and warp The cost price information that passes through of price department's examination ＆ verification, information about doctor includes physician names, affiliated section office, academic title, is good at diagnosis side To and contact method；Patient information at least includes patient's name, identification card number, age, sex, medical history, anaphylactogen Information and the kinship bond mode of patient；The electronic prescription at least includes patient's name, expert's physician names, expert doctor Raw operation card number, patient condition, remote visiting time, reimbursement of expense inventory and list of medications.

Compared with prior art, the advantage of the invention is that：

First, protect individual subscriber privacy information in terms of, cloud platform added according to user head portrait picture pixel value, Height value and width value calculate obtain the characteristic value of head portrait picture is added to characterize the information of added head portrait picture, can be with The head portrait picture of cloud platform certification user is helped, in order to which in User logs in cloud platform, cloud platform is recognized according to head portrait picture Legal identity of the user at the cloud platform is demonstrate,proved, mobile telemedicine is participated in be supplied to registered validated user to log in cloud platform Activity；

For main by being directed to user's logon information using numeral or alphabetic mode encryption merely in traditional portable medical Mode, the present invention by user add head portrait picture characteristic value and each numerical value password box in numerical value make mathematic interpolation, and The final critical parameter of certification modification logging is used as using gained difference；By calculating the spy for adding head portrait picture for user Value indicative has added the difficulty that cracks of illegal person, the numerical value that user keys in each numerical value password box be also it is random unordered and It is difficult to what is cracked, will be respectively provided with the characteristic value for adding head portrait picture for cracking difficulty and the number in each numerical value password box again herein Value makees mathematic interpolation, considerably increases the security performance of user login code, really ensure that to individual subscriber privacy information Protection；

Secondly, the sufferers themselves' that patient's mobile client is generated according to patient physiological data value set and patient information Physiological data illness curve, can help patient independently to understand the physiological data situation of oneself, via patient's mobile client institute The peculiar reference value of the illness of the various physiological datas of generation can be supplied to doctor to carry out diagnosis ginseng as important reference information Examine, this just on the premise of diagnosis quality is ensured, improves the diagnosis efficiency of doctor；

Again, cloud platform is by the way that by the big data information based on registered patient information, the sex of a large amount of patients is believed Breath, age information, birthplace information, place of working information, residence information, occupational information, academic information, history information, height Information and body weight informix are taken into account, and being formed has more representational pre- disease model of diagnosing a disease, and this can help doctor Specific a certain regional, the specific sex of solution, specific professional, specific educational background PATIENT POPULATION corresponding with the specifically information such as age bracket held The disease being easy to get, helps doctor to understand the other illnesss that patient may suffer from, and then improve diagnosis effect of the doctor to patient condition Rate；In addition, forwarding criterion and the peculiar decision threshold of illness set in advance are pre-set by cloud platform, can be different by illness Obviously patient transfers to evaluation coefficient highest hospital to be diagnosed to sample, to avoid delaying the promptly and accurately treatment of patient, This also achieves the shunting to PATIENT POPULATION's tele-medicine to a certain extent, reduces what each hospital was born active balance Diagnosis amount；

Finally, the present invention is set for this parameter of the burst deviation of physiological data, it will be appreciated that patient physiological data Change fluctuation situation, with the very first time in time by physiological data change fluctuation situation be supplied to doctor to refer to, it is to avoid patient Because there is paroxysmal disease harm patient body health.

Brief description of the drawings

Fig. 1 is the mobile telemedicine management method schematic flow sheet based on cloud platform in the embodiment of the present invention.

Embodiment

The present invention is described in further detail below in conjunction with accompanying drawing embodiment.

As shown in figure 1, the mobile telemedicine management method based on cloud platform in the present embodiment, for including patient's life Manage data collecting instrument, patient's mobile client, doctor's client, hospital services subsystem, pharmacy's service subsystem and cloud flat The mobile telemedicine management system that platform is formed, patient physiological data Acquisition Instrument connection patient's mobile client, patient's movement Client and doctor's client connect hospital services subsystem respectively, and hospital services subsystem and pharmacy's service subsystem connect respectively Connect cloud platform；Patient physiological data Acquisition Instrument selection in the present embodiment wirelessly connects patient's mobile client, with Facilitate patient's interior progress mobile telemedicine of any effectively communication range at home；The preferred Blue-tooth communication method of wireless mode； Patient's mobile client can use smart mobile phone or panel computer.Specifically, based on the long-range of cloud platform in the present embodiment Portable medical management method comprises the following steps 1 to step 9：

Step 1, hospital is registered to obtain user name and login password by hospital services subsystem at cloud platform, And register the affiliated information about doctor in information for hospital and hospital；Patient is registered at cloud platform by patient's mobile client and stepped on Note registers the patient information and telephone number of patient itself to obtain user name and login password；Pharmacy is serviced by pharmacy Subsystem is registered to obtain user name and login password at cloud platform, and registers in the pharmacy information of each medicine and right Dutiable value；Cloud platform is to hospital services subsystem, patient and the corresponding user name of pharmacy's service subsystem and login password point Encryption is not made；Cloud platform actually provides the platform of an information interchange, and cloud platform sheet for hospital and patient Body can handle the information of doctor, hospital and patient again；Patient information at least including the gender information of patient, age information, go out Dried rhizome of rehmannia information, place of working information, residence information, occupational information, academic information, history information, height information and body weight information； Information for hospital, which includes hospital's brief introduction, hospital department, each section office, to be good at diagnosis direction and audits the expense passed through through price department With pricing information, information about doctor includes physician names, affiliated section office, academic title, is good at diagnosis direction and contact method；Patient Information at least includes relatives' connection of patient's name, identification card number, age, sex, medical history, allergens and patient It is mode.Specifically, cloud platform encryption user name and the process of login password comprise the following steps 1-1 to step 1-5：

The enrollment page of registration information is filled in step 1-1, cloud platform generation for user, and provides special for uploading The picture addition control of family head portrait picture；Control is added by the picture on enrollment page, used such as hospital, pharmacy and patient Family can select the picture oneself liked as user's head portrait when oneself logging in cloud platform；Be provided with enrollment page for The registration operation time limit of family registration, so that user can only complete registration process within the registration operation time limit of restriction； For example, being limited to 10 minutes when setting registration operation, then user must complete log-on message within 10 minutes and fill in process, one Denier user's registration was operated more than 10 minutes, and user then needs to rewrite log-on message on enrollment page；Wherein, cloud platform is pre- The maximum of added picture pixels value is first limited as Pixels_max, picture pixels value is added more than the pixel set in advance Maximum Pixels_maxWhen, the enrollment page of cloud platform can point out the photo current can not to upload；Enrollment page, which has, to be supplied into use The user name input frame and donating bond of name in an account book enter the individual numerical value password boxs arranged according to preset order of U of modification logging；Setting row Typed numerical value is Q in serial number u u-th of numerical value password box_u；0≤Q_u≤9；6≤U≤10；1≤u≤U；6≤U is set ≤ 10 purpose is that password during regulation User logs in cloud platform is 6 passwords or 7 passwords or 8 as needed Password or 9 passwords or 10 passwords, such as when setting U=10, it is 10 to illustrate password during User logs in cloud platform Numerical value, the digit of password is more, and the difficulty illegally cracked by other people is bigger；For example, in 7 passwords as defined in cloud platform, That is during U=7, user has keyed in numerical value 5, i.e., Q now in the 2nd numerical value password box of row's serial number 2₂=5；

Step 1-2, user is after filling in and finishing the log-on message including user name and login password, by enrollment page Picture addition control the head portrait picture that user selects is added to cloud platform, the user filled in by cloud platform storage user Name；

Step 1-3, cloud platform extracts user and adds the pixel value of head portrait picture, and obtains the height of added head portrait picture The characteristic value of angle value, width value and added head portrait picture；Added head portrait picture is designated as JPG, adds head portrait picture JPG Pixel value be designated as Pixels_JPG；Added head portrait picture JPG height value is designated as High_JPG, add head portrait picture JPG's Width value is designated as Width_JPG；Added head portrait picture JPG characteristic value is labeled as Feature_JPG；

Cloud platform calculated according to the pixel value of added head portrait picture, height value and width value obtain add head portrait The characteristic value of picture characterizes the information of added head portrait picture, helps the cloud platform to be authenticated the head portrait picture of user, with Be easy in user's subsequent login cloud platform, by cloud platform according to head portrait picture certification user the platform legal identity；

Step 1-4, cloud platform according to user add head portrait picture characteristic value and user in each numerical value password box The numerical value of key entry, calculates the difference between each key entry numerical value and added head portrait picture characteristic value respectively, and with resulting difference Value set as user login password；Wherein, the login password of user is labeled as Password；Password= {Differ_u}；Differ_u=Q_u-Feature_JPG；Differ_uRepresent numerical value Q typed in u-th of numerical value password box_uWith institute Add head portrait picture characteristic value Feature_JPGBetween difference；In traditional portable medical, mainly by merely using numeral or The mode of letter carries out the encryption for user's logon information；In the present invention by user add the characteristic value of head portrait picture with it is each Numerical value in numerical value password box carries out mathematic interpolation, and is used as using gained difference the final critical parameter of certification modification logging；By The difficulty that cracks of illegal person, Yong Hu have been added in the calculating process of the characteristic value for adding head portrait picture for user The numerical value keyed in each numerical value password box is also random unordered and is difficult to what is cracked, will be respectively provided with the institute for cracking difficulty again herein The characteristic value and the numerical value in each numerical value password box for adding head portrait picture make mathematic interpolation, so as to substantially increase User logs in The security performance of password；

Step 1-5, when cloud platform monitors that user attempts to log on by inputting the form of password, cloud platform is judging Current user name and to should the head portrait picture of user inputted by cloud platform storage and user in each numerical value password box Numerical value is corresponded to when meeting the difference set in step 1-4, then cloud platform assert that user has keyed in correct user name and correspondingly Login password；Otherwise, cloud platform refuses User logs in into the system of the cloud platform；

Step 2, the various set in advance of patient is gathered according to default collection period using patient physiological data Acquisition Instrument Physiological data, and the various physiological data values of collection are sent at patient's mobile client as patient physiological data value set Reason；For example, the patient physiological data that patient physiological data Acquisition Instrument is gathered can be blood glucose level data or blood pressure data or blood fat Data or heart rate data or pulse data or spirometric data or temperature data, or blood glucose level data, blood pressure data, blood fat number According to, any combination of heart rate data, pulse data, spirometric data and temperature data；Wherein, patient physiological data value set Labeled as S, S={ P_i, i=1,2 ..., I；Default collection period is labeled as T, and the physiological data value collected is labeled asN=1,2 ..., N；P_iThe title of i-th kind of physiological data in patient physiological data value set S is represented, I represents to suffer from The species number of physiological data in person's physiological data value set S；N represents the physiological data P collected in collection period T_i Total number,Represent to be directed to physiological data P_iN-th of the physiological data value collected in collection period T；Collection Physiological data species preset by patient physiological data Acquisition Instrument；

For example, the patient physiological data that patient physiological data Acquisition Instrument is gathered is blood glucose level data, blood pressure data, blood fat number During according to heart rate data, now corresponding patient physiological data set S is { blood glucose level data, blood pressure data, blood fat data, heart rate Data }；It is corresponding, in patient physiological data set S at this moment, P₁Represent blood glucose level data, P₂Represent blood pressure data, P₃Represent Blood fat data, P₄Represent heart rate data；The species number I=4 of physiological data in now patient physiological data set S；If suffered from The physiological data P that person's physiological data collection instrument is collected in collection period T₁Total number N=10, thenRepresent For physiological data P₁, i.e., the 2nd physiological data value collected for blood glucose level data in collection period T；Wherein, in step In rapid 2, the physiological data that patient physiological data Acquisition Instrument is gathered can select as blood glucose level data or blood pressure data as needed Or blood fat data or heart rate data or pulse data or spirometric data or temperature data, or blood glucose level data, blood pressure data, Blood fat data, heart rate data, pulse data, any combination of spirometric data and temperature data.

Step 3, after patient's successful log patient's mobile client, patient's mobile client is given birth to according to the patient received Manage data value set and patient information, the physiological data illness curve of generation correspondence sufferers themselves and to obtain correspondence patient each Plant the peculiar reference value of illness of physiological data；Wherein, the physiological data illness curvilinear equation and the illness of patient of sufferers themselves Peculiar reference value computing formula is as follows：

F () represents physiological data illness curvilinear equation, ε₀Default physiological data illness screening threshold value is represented,Represent correspondence patient physiological data P_iThe peculiar reference value of illness；Represent corresponding in collection period T Patient physiological data P_iAverage,Represent to be directed to physiological data P_iOffset constant during in normal condition；

The physiology for the sufferers themselves that patient's mobile client is generated according to patient physiological data value set and patient information Data illness curve, can help patient independently to understand the physiological data situation of oneself, and via patient's mobile client institute The peculiar reference value of the illness of the various physiological datas of generation can be supplied to doctor to carry out diagnosis ginseng as important reference information Examine, this just on the premise of diagnosis illness quality is ensured, improves the accuracy rate of diagnosis and diagnosis efficiency of doctor；

Step 4, cloud platform is extracted in the patient information of the registered all patients of the cloud platform, and root in preset period According to the gender information of each patient, age information, birthplace information, place of working information, residence information, occupational information, educational background letter Breath, history information, height information and the generation of body weight information are directed to the pre- disease model of diagnosing a disease of all patients, by cloud platform according to gained The patient information that pre- diagnose a disease disease model and current patents are registered, obtains the pre- disease of diagnosing a disease of current patents, for current patents Tentatively understand the conditions of oneself；Wherein, disease model of diagnosing a disease in advance is labeled as Symptom：

Symptom={ Symptom_g, g=1,2 ..., G；

Wherein, Symptom_gRepresent that the g kinds that draw of cloud platform are diagnosed a disease disease in advance, G represents that cloud platform can draw pre- diagnose a disease Total species number of disease；Patient_wW-th of patient is represented, W represents the total number of registered all patients at cloud platform； Symptom'_wRepresent patient Patient_wThe illness title confirmed through doctor, illness title Symptom' herein_wIt is one Individual specific, determination disease name；Gender_wRepresent patient Patient_wGender information, Age_wRepresent patient Patient_w Age information, BornPlace_wRepresent patient Patient_wBirthplace information, WorkPlace_wRepresent patient Patient_w's Place of working information, Residence_wRepresent patient Patient_wResidence information, birthplace, place of working and the residence of same patient Residence is not necessarily identical；Job_wRepresent patient Patient_wOccupational information, Education_wRepresent patient Patient_wAcademic information, Medicalhistory_wRepresent patient Patient_wSuffered from illness Symptom'_wHistory information, Height_wRepresent patient Patient_wHeight information, Weight_wRepresent patient Patient_wBody weight information；Represent it is registered at cloud platform and with patient Patient_wWith sex and with Symptom'_wDisease Patient's total number of disease,Represent it is registered at cloud platform and with patient Patient_wWith age and trouble There is Symptom'_wPatient's total number of illness,Represent registered at cloud platform and and patient Patient_wWith birthplace and with Symptom'_wPatient's total number of illness,Represent flat in cloud At platform it is registered and with patient Patient_wWith place of working and with Symptom'_wPatient's total number of illness,Represent it is registered at cloud platform and with patient Patient_wWith residence and suffer from Symptom'_wPatient's total number of illness,Represent registered at cloud platform and and patient Patient_wWith occupation and with Symptom'_wPatient's total number of illness,Represent in cloud platform Place it is registered and with patient Patient_wWith educational background and with Symptom'_wPatient's total number of illness,Represent it is registered at cloud platform and with patient Patient_wEqually there is medical history and suffer from Symptom'_wPatient's total number of illness,Represent registered at cloud platform and and patient Patient_wSame height and with Symptom'_wPatient's total number of illness,Represent in cloud platform Place it is registered and with patient Patient_wSame body weight and with Symptom'_wPatient's total number of illness； WithInclude patient Patient in signified number_w；σ₀~σ_G It is the default pre- disease classification constant of diagnosing a disease of cloud platform；

In the present embodiment, cloud platform by by based on the platform register patient information big data information, And by the gender information of a large amount of patients, age information, birthplace information, place of working information, residence information, occupational information, Academic information, history information, height information and body weight informix are taken into account, have more representational pre- diagnose a disease to be formed Disease model, this can subsequently help doctor to understand specific somewhere, specific sex, specific professional, specific academic situation and specific The disease that the information such as age bracket correspondence PATIENT POPULATION easily obtains；

For example, for the elderly colony, easily suffering from the diseases such as hypertension, hyperglycaemia；For a middle-aged person colony, easily suffer from neck The diseases such as vertebra disease, protrusion of lumber intervertebral disc；For the colony of poor remote districts, easily suffer from the disease of trophism missing, such as first High or rickets；For the personnel colony of office's class, easily suffer from cervical spondylopathy or obesity；Excavate big here by cloud platform The pre- disease model of diagnosing a disease measured the information of patient and generated, is very easy to doctor and is not knowing the premise of patient specific information Under, an accurate location determination can be carried out by the cloud platform kinds of Diseases that may suffer from current to patient in advance, to provide standard True disease reference information helps patient tentatively to understand the conditions of oneself to sufferers themselves and doctor, helps doctor to understand The other illnesss that patient may suffer from, and then improve diagnosis efficiency of the doctor to patient condition；

Step 5, patient's mobile client is right by the patient information of its affiliated patient, patient physiological data value set and gained Answer the peculiar reference value of illness to send to cloud platform, criterion is forwarded by patient information, patient physiological data according to default by cloud platform The pre- disease of diagnosing a disease of the patient obtained by cloud platform is logical in data network in the peculiar reference value of value set, corresponding illness and step 4 Start transmission program when smooth and be sent to corresponding hospital services subsystem；The default forwarding criterion of cloud platform is as follows：

Represent default correspondence patient physiological data P_iThe peculiar decision threshold of illness, Hospital_optRepresent Evaluation of patient coefficient highest hospital, Min () represents to take minimum value, Score_mRepresent that evaluation of m-th of patient to hospital is beaten Score value, M represents registered at cloud platform and the marking that judged to hospital patient's total number,Represent in known time Section T₁The average value that interior all M patients give a mark to Hospital evaluation,Represent in known time section T₁Interior patient is commented hospital The undulating value of valency marking,Represent hospital in known time section T₁Interior malpractice rate；Hospital_disoptRepresent Registered at cloud platform and remove remaining hospital after evaluation of patient coefficient highest hospital；→ represent that cloud platform is believed for patient The routing direction of breath, patient physiological data value set and the peculiar reference value of correspondence illness；As the physiological data P of patient_iDisease Disease difference reference valueMore than the peculiar decision threshold of default illnessWhen, then by cloud platform by the patient's The peculiar reference value of patient information, patient physiological data value set, corresponding illness and cloud platform are according to pre- disease model of diagnosing a disease Obtained pre- disease of diagnosing a disease is sent jointly to by evaluation of patient coefficient highest hospital Hospital_optDiagnosed, to ensure disease Sick diagnosis accuracy；Otherwise, cloud platform is then different by the patient information of the patient, patient physiological data value set, corresponding illness Sample reference value and cloud platform send jointly to remove Hospital according to the pre- disease of diagnosing a disease obtained by disease model of diagnosing a disease in advance_optOutside Other hospitals diagnosed.Forwarding criterion and the peculiar decision threshold of illness set in advance are pre-set by cloud platform, Can by illness difference obviously patient transfer to evaluation coefficient highest hospital to be diagnosed, with avoid delaying patient's and When accurately treat, this also achieves the shunting to PATIENT POPULATION's tele-medicine to a certain extent, reduces each active balance The diagnosis amount that hospital is born；

Step 6, the hospital services subsystem of each hospital is at least receiving the patient information of cloud platform forwarding twice, patient After physiological data value set and the peculiar reference value of corresponding illness, hospital services subsystem automatically extracts the illness feature of patient Information, and according to the illness characteristic information of extracted patient send into affiliated hospital to should illness first visit section office doctor Client, first visit conclusion is made to the current illness of patient by the first visit doctor of first visit section office, and by first visit conclusion, the first visit of patient Sequence number and patient data are transmitted to doctor's client of the expert section office corresponding with first visit conclusion；Patient data includes trouble The peculiar reference value of person's information, patient physiological data value set and corresponding illness；Specifically, hospital services subsystem is carried automatically The process of patient condition's characteristic information is taken to comprise the following steps 6-1 to step 6-4：

Step 6-1, hospital services subsystem according to cloud platform forward patient information, patient physiological data value set and The number of times of the peculiar reference value of corresponding illness, obtains the preposition deviation of the last each physiological data of patient；Wherein：

Represent corresponding physiological data P during patient's kth_iPreposition deviation；K represents that cloud platform forwards patient The number of times of information, patient physiological data value set and the peculiar reference value of correspondence illness；Represent to be directed to physiological data P_iIt is in Offset constant during normal condition；

Step 6-2, hospital services subsystem according to cloud platform forward patient information, patient physiological data value set and The number of times of the peculiar reference value of corresponding illness, the rearmounted deviation of each physiological data when obtaining patient to current number of times；Wherein：

Represent corresponding physiological data P during patient the K+1 times_iRearmounted deviation；K+1 represents current cloud platform institute Forward the number of times of patient information, patient physiological data value set and the peculiar reference value of correspondence illness；Represent to be directed to physiology number According to P_iOffset constant during in normal condition；

Step 6-3, hospital services subsystem presets the illness feature decision threshold of each physiological data, and gown respectively Subsystem be engaged according to the corresponding preposition deviation of each physiological data of gained patient and rearmounted deviation, patient's correspondence physiology number is obtained According to burst deviation；Wherein：Represent correspondence patient physiological data P_iBurst deviation,Represent correspondence patient physiological data P_iPreposition deviation,Represent correspondence patient physiological data P_iRearmounted deviation Value；Correspondence physiological data P_iIllness feature decision threshold be designated asPatient's correspondence physiological data P_iBurst deviation Characterize patient physiological data P_iBurst situation of change within a period of time, signified a period of time is specially cloud platform herein Forward the kth of patient information and the time of K+1 minor ticks.Set for this parameter of the burst deviation of physiological data, It will be seen that the change fluctuation situation of patient physiological data, is provided so that physiological data is changed into fluctuation situation in time in the very first time Give doctor's reference, it is to avoid patient is because there is paroxysmal disease harm patient body health；

Step 6-4, hospital services subsystem is according to the burst deviation of each physiological data of gained patient and default each The illness feature decision threshold of physiological data carries out illness judgement respectively, to judge whether patient illness occurs：

WhenWhen, represent the physiological data P of patient_iThere is exception, then hospital services subsystem indicates that patient goes out Corresponding physiological data P is showed_iIllness；WhenWhen, represent the physiological data P of patient_iDo not occur exception, then gown Business subsystem indicates the physiological data P of patient_iNormally；

Step 7, the expert doctor in expert section office using the doctor's client of oneself receive that first visit section office send just Conclusion, the first visit sequence number of patient and patient information are examined, and sets up electronics medical case history of the patient in the hospital, while by the doctor Raw client is done the encryption process to the medical case history of electronics of patient, to protect patient's individual privacy information；Wherein, doctor's client The medical case history process of the electronics of encryption patient comprises the following steps 7-1 to step 7-4：

Step 7-1, doctor's client prestores the electronic anti-fogery stamped signature colour picture of affiliated expert doctor, and with electronics False proof stamped signature colour picture issues the audit voucher of the medical case history of electronics as doctor；Wherein, the electronic anti-fogery label of expert doctor Chapter colour picture is designated asJ=1,2 ..., J, j represent that hospital services subsystem assigns the electronics label of expert doctor Chapter sequence number, J represents that hospital services subsystem assigns total Electronic Signature number of each expert doctor；Doct_jExpression possesses electricity Sub- stamped signature serial number j doctor；

Step 7-2, doctor's client obtains the gray scale of each color in expert doctor's electronic anti-fogery stamped signature colour picture The height value and width value of value and electronic anti-fogery stamped signature colour picture, obtain the label of expert doctor's electronic anti-fogery stamped signature colour picture The anti-pseudoindex of chapter；The anti-pseudoindex of the corresponding stamped signature of expert doctor is designated asExpert doctor's electronic anti-fogery stamped signature cromogram PieceThe gray scale value of middle color is designated asElectronic anti-fogery stamped signature colour picture's Height value is designated asElectronic anti-fogery stamped signature colour pictureWidth value be designated as

Wherein, V refers to total species number of all colours in expert doctor's electronic anti-fogery stamped signature colour picture,Represent v kinds color in electronic anti-fogery stamped signature colour pictureIn gray scale value；

The corresponding anti-pseudoindex of stamped signature of the gained expert doctor is sent to hospital services by step 7-3, doctor's client Subsystem storage is put on record, while by hospital services subsystem by the anti-pseudoindex of the stamped signature of the expert doctor put on record and hospital The identity information of service subsystem is integrated, to obtain the verification code information that the medical case history of electronics is consulted for patient；Wherein, correspondence electricity The verification code information of the medical case history of son is labeled asHospitol_DoctjTable Show expert doctor Doct_jThe hospital services subsystem held office, T_DoctjRepresent expert doctor the anti-pseudoindex of stamped signature it is effective when Between be worth；

Step 7-4, doctor's client will consult the verification code information of the medical case history of electronics for patient in the form of short message Patient is sent in cloud platform leaves the mobile terminal of telephone number, to realize effective time of the patient in the anti-pseudoindex of stamped signature It is interior that the medical case history of the electronics of oneself is consulted by cloud platform；

Step 8, doctor's client at expert doctor extracts the various physiological data values of the patient of reception respectively, and will carry The various physiological data values taken compare judgement with corresponding normal physiological data value respectively, so that expert doctor decides whether pair Current patents make remote diagnosis, and draw the peculiar value of each physiological data of patient by doctor's client of expert doctor, help Expert doctor is helped to understand the physiological data situation of change of patient in advance；Patient physiological data P_iDifference value be ζ_Pi：

N' represents doctor's client at expert doctor in period T₁Interior received patient physiological data P_iNumber,Represent in period T₁Interior patient's physiological data P_iUndulating value,Represent doctor's client at expert doctor For the physiological data P of normal population_iPre-set normal fluctuation constant；

When any of patient physiological data set physiological data is not in the normal range (NR) of this kind of physiological data, Then doctor's client at expert doctor is made alarm and reminded；Otherwise, doctor's client at expert doctor refuses alarm；

Step 9, expert doctor makes remote visiting to patient by doctor's client and invited and long-range just in patient's completion Examine after confirmation, patient progress of the expert doctor by its doctor's client to confirming remote visiting at hospital services subsystem is standby Case；After patient pays diagnostic fees, expert's diagnosis patient condition and by outputed for patient condition to include this special The electronic prescription of family's doctor's professional information is respectively supplied to cloud platform and the hospital services subsystem belonging to the expert doctor enters Row is put on record in real time；Patient logs in cloud platform to check electronic prescription that expert doctor provides by patient's mobile client, and presses Medicine is bought at the pharmacy's service subsystem put on record that cloud platform is provided according to electronic prescription, mobile telemedicine mistake is completed Journey.Electronic prescription at least includes patient's name, expert's physician names, expert doctor's operation card number, patient condition, remote visiting Time, reimbursement of expense inventory and list of medications.

With improvement, the step that cloud platform automatically generates nutritious food plan according to the illness of patient is also included after step 9 Suddenly, to help patient to be supplemented the nutrients according to the nutritious food plan, patient abnormal physiological data is occurred and recover to physiology The normal value of data.Further, also include after step 9, the expense that hospital services subsystem is paid according to all patients Data and confirm the medical patient data invited, the step of obtaining the expert doctor's list liked by patient.

Claims (5)

1. the mobile telemedicine management method based on cloud platform, for including patient physiological data Acquisition Instrument, patient's movement The mobile telemedicine that client, doctor's client, hospital services subsystem, pharmacy's service subsystem and cloud platform are formed Management system, patient physiological data Acquisition Instrument connection patient's mobile client, patient's mobile client and doctor's client difference Hospital services subsystem is connected, hospital services subsystem and pharmacy's service subsystem connect cloud platform respectively；Characterized in that, institute State the mobile telemedicine management method based on cloud platform and comprise the following steps 1 to step 9：

Step 1, hospital is registered to obtain user name and login password by hospital services subsystem at cloud platform, and is stepped on Remember the affiliated information about doctor in information for hospital and hospital；Patient registered by patient's mobile client at cloud platform with Obtain user name and login password, and the patient information and telephone number of registration patient itself；Pharmacy services subsystem by pharmacy System is registered at cloud platform to obtain user name and login password, and registers the information of each medicine and correspondence valency in the pharmacy Lattice；Cloud platform is made respectively to hospital services subsystem, patient and the corresponding user name of pharmacy's service subsystem and login password Encryption；The patient information at least gender information including patient, age information, birthplace information, place of working information, residence Information, occupational information, academic information, history information, height information and body weight information；

Wherein, cloud platform encryption user name and the process of login password comprise the following steps 1-1 to step 1-5：

The enrollment page of registration information is filled in step 1-1, cloud platform generation for user, and offer specially supplies upload user head As the picture addition control of picture；The registration operation time limit registered for user's registration is provided with the enrollment page, to use Family can only complete registration process within the registration operation time limit of restriction；Wherein, cloud platform limits added picture picture in advance The maximum of element value is Pixels_max；Enrollment page enters to log in close with the user name input frame and donating bond for supplying access customer name The numerical value password box that U of code arrange according to preset order；It is typed in setting row's serial number u u-th of numerical value password box Numerical value is Q_u；0≤Q_u≤9；6≤U≤10；1≤u≤U；

Step 1-2, user passes through the figure on enrollment page after filling in and finishing the log-on message including user name and login password The head portrait picture that user selects is added to cloud platform, and the user name filled in by cloud platform storage user by piece addition control；

Step 1-3, cloud platform extracts user and adds the pixel value of head portrait picture, and obtains the height of added head portrait picture The characteristic value of value, width value and added head portrait picture；Wherein, head portrait picture is added labeled as JPG, adds head portrait figure Piece JPG pixel value is labeled as Pixels_JPG；Added head portrait picture JPG height value is labeled as High_JPG, add head portrait Picture JPG width value is labeled as Width_JPG；Added head portrait picture JPG characteristic value is labeled as Feature_JPG；

${\mathrm{Feature}}_{JPG}={\log }_2\left(\frac{{\mathrm{Pixels}}_{JPG}}{{\mathrm{High}}_{JPG}\·{\mathrm{Width}}_{JPG}}-\frac{{\mathrm{High}}_{JPG}\·{\mathrm{Width}}_{JPG}}{{\mathrm{High}}_{JPG}+{\mathrm{Width}}_{JPG}}\right);{\mathrm{Pixels}}_{JPG}\≤{\mathrm{Pixels}}_{\max };$

Step 1-4, cloud platform adds the characteristic value of head portrait picture according to user and user keys in each numerical value password box Numerical value, the difference between each key entry numerical value and added head portrait picture characteristic value is calculated respectively, and with resulting difference collection Cooperate the login password for user；Wherein, the login password of user is labeled as Password；Password={ Differ_u}； Differ_u=Q_u-Feature_JPG；Differ_uRepresent numerical value Q typed in u-th of numerical value password box_uWith added head portrait figure Piece characteristic value Feature_JPGBetween difference；

Step 1-5, when cloud platform monitors that user attempts to log on by inputting the form of password, cloud platform is judging current User name and to should user the numerical value that has been inputted by cloud platform storage and user in each numerical value password box of head portrait picture Correspond to when meeting the difference set in step 1-4, then cloud platform assert that user has keyed in correct user name and corresponding stepped on Record password；Otherwise, cloud platform refuses User logs in into the system of the cloud platform；

Step 2, the various physiology set in advance of patient are gathered according to default collection period using patient physiological data Acquisition Instrument Data, and it is sent to the processing of patient's mobile client using the various physiological data values of collection as patient physiological data value set； Wherein, patient physiological data value set is labeled as S, S={ P_i, i=1,2 ..., I；Default collection period is labeled as T, collects Physiological data value be labeled asP_iRepresent i-th kind of physiology in patient physiological data value set S The title of data, I represents the species number of physiological data in patient physiological data value set S；N represents the institute in collection period T The physiological data P collected_iTotal number,Represent to be directed to physiological data P_iN-th collected in collection period T Individual physiological data value；The physiological data species to be gathered is preset by patient physiological data Acquisition Instrument；

Step 3, after patient's successful log patient's mobile client, patient's mobile client is according to the patient's physiology number received According to value set and patient information, generate the physiological data illness curve of correspondence sufferers themselves and obtain the various lifes of correspondence patient Manage the peculiar reference value of illness of data；Wherein, the illness difference of the physiological data illness curvilinear equation of sufferers themselves and patient Reference value computing formula is as follows：

$f\left({\mathrm{Data}}_{P_i,n}^{Phy}\right)=\left\{\begin{array}{cc}\frac{{\mathrm{Decide}}_{P_i}^{Phy}}{\stackrel{\‾}{{\mathrm{Data}}_{P_i}^{Phy}}}\·{\mathrm{Data}}_{P_i,n}^{Phy}+{\log }_2\left(\stackrel{\‾}{{\mathrm{Data}}_{P_i}^{Phy}}\right),& {\mathrm{Decide}}_{P_i}^{Phy}>{\mathrm{\ϵ}}_0\\ 0,& {\mathrm{Decide}}_{P_i}^{Phy}\≤{\mathrm{\ϵ}}_0\end{array}\right.;i=1,\mathrm{2...},I;$

${\mathrm{Decide}}_{P_i}^{Phy}=\sqrt{\frac{1}{I}\underset{i=1}{\overset{I}{\mathrm{\Σ}}}{\left({\mathrm{Data}}_{P_i,n}^{Phy}-\stackrel{\‾}{{\mathrm{Data}}_{P_i}^{Phy}}\right)}^2};\stackrel{\‾}{{\mathrm{Data}}_{P_i}^{Phy}}=\frac{1}{I}\underset{i=1}{\overset{I}{\mathrm{\Σ}}}{\mathrm{Data}}_{P_i,n}^{Phy}+{\mathrm{\Δ}}_{P_i}^{Phy};n=1,2,\mathrm{...},N;$

F () represents physiological data illness curvilinear equation, ε₀Default physiological data illness screening threshold value is represented,Table Show correspondence patient physiological data P_iThe peculiar reference value of illness；Represent corresponding patient's physiology number in collection period T According to P_iAverage,Represent to be directed to physiological data P_iOffset constant during in normal condition；

Step 4, cloud platform is extracted in the patient information of the registered all patients of the cloud platform in preset period, and according to each The gender information of patient, age information, birthplace information, place of working information, residence information, occupational information, academic information, disease History information, height information and the generation of body weight information are examined in advance for the pre- disease model of diagnosing a disease of all patients by cloud platform according to gained The patient information that illness model and current patents are registered, obtains the pre- disease of diagnosing a disease of current patents, so that current patents are preliminary Understand the conditions of oneself；Wherein, disease model of diagnosing a disease in advance is labeled as Symptom：

Symptom={ Symptom_g, g=1,2 ..., G；

${\mathrm{Symptom}}_g=\left\{\begin{array}{cc}{\mathrm{Symptom}}_1,& {\mathrm{\σ}}_{{\mathrm{\ξ}}_w}\∈({\mathrm{\σ}}_0,{\mathrm{\σ}}_1\];\\ {\mathrm{Symptom}}_2,& {\mathrm{\σ}}_{{\mathrm{\ξ}}_w}\∈({\mathrm{\σ}}_1,{\mathrm{\σ}}_2\];\\ {\mathrm{Symptom}}_3,& {\mathrm{\σ}}_{{\mathrm{\ξ}}_w}\∈({\mathrm{\σ}}_2,{\mathrm{\σ}}_3\];\\ & ...\\ {\mathrm{Symptom}}_{G-1},& {\mathrm{\σ}}_{{\mathrm{\ξ}}_w}\∈({\mathrm{\σ}}_{G-2},{\mathrm{\σ}}_{G-1}\];\\ {\mathrm{Symptom}}_G,& {\mathrm{\σ}}_{{\mathrm{\ξ}}_w}\∈({\mathrm{\σ}}_{G-1},{\mathrm{\σ}}_G\];\end{array}\right.;$

${\mathrm{\σ}}_{{\mathrm{\ξ}}_w}=\sqrt{\frac{1}{10}\underset{r=1}{\overset{10}{\mathrm{\Σ}}}{\left({\mathrm{\ξ}}_r^w-{\mathrm{\λ}}_{{\mathrm{\ξ}}_r^w}\·\stackrel{\‾}{{\mathrm{\ξ}}_r^w}\right)}^2};{\mathrm{\λ}}_{{\mathrm{\ξ}}_r^w}=\frac{{\left({\mathrm{\ξ}}_r^w\right)}^2}{\underset{r=1}{\overset{10}{\mathrm{\Σ}}}{\left({\mathrm{\ξ}}_r^w\right)}^2};\stackrel{\‾}{{\mathrm{\ξ}}_r^w}=\frac{1}{10}\underset{r=1}{\overset{10}{\mathrm{\Σ}}}{\mathrm{\ξ}}_r^w;$

${\mathrm{\ξ}}_1^w={\mathrm{\ξ}}_{{\mathrm{Gender}}_w},{\mathrm{\ξ}}_2^w={\mathrm{\ξ}}_{{\mathrm{Age}}_w},{\mathrm{\ξ}}_3^w={\mathrm{\ξ}}_{{\mathrm{BornPlace}}_w},{\mathrm{\ξ}}_4^w={\mathrm{\ξ}}_{{\mathrm{WorkPlace}}_w},{\mathrm{\ξ}}_5^w={\mathrm{\ξ}}_{{\mathrm{Residence}}_w};$

${\mathrm{\ξ}}_6^w={\mathrm{\ξ}}_{{\mathrm{Job}}_w},{\mathrm{\ξ}}_7^w={\mathrm{\ξ}}_{{\mathrm{Education}}_w},{\mathrm{\ξ}}_8^w={\mathrm{\ξ}}_{{\mathrm{Medicalhistory}}_w},{\mathrm{\ξ}}_9^w={\mathrm{\ξ}}_{{\mathrm{Height}}_w},{\mathrm{\ξ}}_{10}^w={\mathrm{\ξ}}_{{\mathrm{Weight}}_w};$

${\mathrm{\ξ}}_{{\mathrm{Gender}}_w}=\frac{{\mathrm{Num}}_{{\mathrm{Gender}}_w}\left({\mathrm{Symptom}}_w^{\′}\right)}{W},{\mathrm{\ξ}}_{{\mathrm{Age}}_w}=\frac{{\mathrm{Num}}_{{\mathrm{Age}}_w}\left({\mathrm{Symptom}}_w^{\′}\right)}{W},$

${\mathrm{\ξ}}_{{\mathrm{BornPlace}}_w}=\frac{{\mathrm{Num}}_{{\mathrm{BornPlace}}_w}\left({\mathrm{Symptom}}_w^{\′}\right)}{W},{\mathrm{\ξ}}_{{\mathrm{WorkPlace}}_w}=\frac{{\mathrm{Num}}_{{\mathrm{WorkPlace}}_w}\left({\mathrm{Symptom}}_w^{\′}\right)}{W},$

${\mathrm{\ξ}}_{{\mathrm{Residence}}_w}=\frac{{\mathrm{Num}}_{{\mathrm{Residence}}_w}\left({\mathrm{Symptom}}_w^{\′}\right)}{W},{\mathrm{\ξ}}_{{\mathrm{Job}}_w}=\frac{{\mathrm{Num}}_{{\mathrm{Job}}_w}\left({\mathrm{Symptom}}_w^{\′}\right)}{W},$

${\mathrm{\ξ}}_{{\mathrm{Education}}_w}=\frac{{\mathrm{Num}}_{{\mathrm{Education}}_w}\left({\mathrm{Symptom}}_w^{\′}\right)}{W},{\mathrm{\ξ}}_{{\mathrm{Medicalhistory}}_w}=\frac{{\mathrm{Num}}_{{\mathrm{Medicalhistory}}_w}\left({\mathrm{Symptom}}_w^{\′}\right)}{W},$

${\mathrm{\ξ}}_{{\mathrm{Height}}_w}=\frac{{\mathrm{Num}}_{{\mathrm{Height}}_w}\left({\mathrm{Symptom}}_w^{\′}\right)}{W},{\mathrm{\ξ}}_{{\mathrm{Weight}}_w}=\frac{{\mathrm{Num}}_{{\mathrm{Weight}}_w}\left({\mathrm{Symptom}}_w^{\′}\right)}{W};$

Wherein, Symptom_gRepresent that the g kinds that draw of cloud platform are diagnosed a disease disease in advance, G represents that cloud platform can draw total kind of pre- disease of diagnosing a disease Class number；Patient_wW-th of patient is represented, W represents the total number of registered all patients at cloud platform；Symptom'_wRepresent Patient Patient_wThe illness title confirmed through doctor, Gender_wRepresent patient Patient_wGender information, Age_wRepresent Patient Patient_wAge information, BornPlace_wRepresent patient Patient_wBirthplace information, WorkPlace_wRepresent patient Patient_wPlace of working information, Residence_wRepresent patient Patient_wResidence information, Job_wRepresent patient Patient_w Occupational information, Education_wRepresent patient Patient_wAcademic information, Medicalhistory_wRepresent patient Patient_w Suffered from illness Symptom'_wHistory information, Height_wRepresent patient Patient_wHeight information, Weight_wRepresent patient Patient_wBody weight information；Represent it is registered at cloud platform and with patient Patient_wThe same sex Not and with Symptom'_wPatient's total number of illness,Represent it is registered at cloud platform and with trouble Person Patient_wWith the age and with Symptom'_wPatient's total number of illness,Represent flat in cloud At platform it is registered and with patient Patient_wWith birthplace and with Symptom'_wPatient's total number of illness,Represent it is registered at cloud platform and with patient Patient_wWith place of working and suffer from Symptom'_wPatient's total number of illness,Represent registered at cloud platform and and patient Patient_wWith residence and with Symptom'_wPatient's total number of illness,Represent in cloud platform Place it is registered and with patient Patient_wWith occupation and with Symptom'_wPatient's total number of illness,Represent it is registered at cloud platform and with patient Patient_wWith educational background and with Symptom'_w Patient's total number of illness,Represent it is registered at cloud platform and with patient Patient_wTogether Sample has medical history and with Symptom'_wPatient's total number of illness,Represent at cloud platform Registration and with patient Patient_wSame height and with Symptom'_wPatient's total number of illness, Represent it is registered at cloud platform and with patient Patient_wSame body weight and with Symptom'_wPatient's total number of illness； WithInclude patient Patient in signified number_w；σ₀~σ_GIt is that cloud platform is default pre- to examine Illness classification constant；

Step 5, patient's mobile client is sick by the patient information of its affiliated patient, patient physiological data value set and gained correspondence Disease difference reference value is sent to cloud platform, and criterion is forwarded by patient information, patient physiological data value collection according to default by cloud platform The pre- of the patient obtained by cloud platform diagnoses a disease disease when data network is unobstructed in conjunction, the peculiar reference value of corresponding illness and step 4 Start transmission program and be sent to corresponding hospital services subsystem；The default forwarding criterion of cloud platform is as follows：

$\left\{\begin{array}{cc}{\mathrm{Decide}}_{P_i}^{Phy}>{\mathrm{Decide}}_{P_i,{\mathrm{th}}_0}^{Phy}& \→{\mathrm{Hospital}}_{opt}\\ {\mathrm{Decide}}_{P_i}^{Phy}\≤{\mathrm{Decide}}_{P_i,{\mathrm{th}}_0}^{Phy}& \→{\mathrm{Hospital}}_{disopt}\end{array}\right.;{\mathrm{Hospital}}_{opt}=Min\left(\frac{{\mathrm{\σ}}_{score,T_1}}{E_{score,T_1}}+{\mathrm{\δ}}_{medi-mal,T_1}\right);$

${\mathrm{\σ}}_{score,T_1}=\sqrt{\frac{1}{M}\underset{m=1}{\overset{M}{\mathrm{\Σ}}}{\left({\mathrm{Score}}_m-E_{score,T_1}\right)}^2};E_{score,T_1}=\frac{1}{M}\underset{m=1}{\overset{M}{\mathrm{\Σ}}}\left({\mathrm{Score}}_m\right);$

Represent default correspondence patient physiological data P_iThe peculiar decision threshold of illness, Hospital_optRepresent patient Evaluation coefficient highest hospital, Min () represents to take minimum value, Score_mEvaluation marking value of m-th of patient to hospital is represented, M represents registered at cloud platform and the marking that judged to hospital patient's total number,Represent in known time section T₁It is interior The average value that all M patients give a mark to Hospital evaluation,Represent in known time section T₁Interior patient gives a mark to Hospital evaluation Undulating value,Represent hospital in known time section T₁Interior malpractice rate；Hospital_disoptRepresent flat in cloud Registered at platform and remove remaining hospital after evaluation of patient coefficient highest hospital；→ represent cloud platform for patient information, trouble The routing direction of person's physiological data value set and the peculiar reference value of correspondence illness；

Step 6, the hospital services subsystem of each hospital is at least receiving the patient information of cloud platform forwarding twice, patient's physiology After data value set and the peculiar reference value of corresponding illness, hospital services subsystem automatically extracts the illness feature letter of patient Breath, and according to the illness characteristic information of extracted patient send into affiliated hospital to should illness first visit section office doctor it is objective Family end, first visit conclusion is made to the current illness of patient by the first visit doctor of first visit section office, and by first visit conclusion, the first visit sequence of patient Number and patient data be transmitted to doctor's clients of the expert section office corresponding with first visit conclusion；The patient data includes The peculiar reference value of patient information, patient physiological data value set and corresponding illness；

Wherein, the process that the hospital services subsystem automatically extracts patient condition's characteristic information comprises the following steps 6-1 to step Rapid 6-4：

Step 6-1, hospital services subsystem forwards patient information, patient physiological data value set and correspondingly according to cloud platform The peculiar reference value of illness number of times, obtain the preposition deviation of the last each physiological data of patient；Wherein：

${\mathrm{\σ}}_{P_{i,K}}^{Phy}=\sqrt{\frac{1}{K}\underset{n=1}{\overset{K}{\mathrm{\Σ}}}\left({\left({\mathrm{Data}}_{P_i,n}^{Phy}-{\stackrel{\‾}{{\mathrm{Data}}_{P_i}^{Phy}}}^{\′}\right)}^2\right)},{\stackrel{\‾}{{\mathrm{Data}}_{P_i}^{Phy}}}^{\′}=\frac{1}{K}\underset{n=1}{\overset{K}{\mathrm{\Σ}}}{\mathrm{Data}}_{P_i,n}^{Phy}+{\mathrm{\Δ}}_{P_i}^{Phy};$

Represent corresponding physiological data P during patient's kth_iPreposition deviation；K represent cloud platform forward patient information, The number of times of patient physiological data value set and the peculiar reference value of correspondence illness；Represent to be directed to physiological data P_iIn normal Offset constant during state；

Step 6-2, hospital services subsystem forwards patient information, patient physiological data value set and correspondingly according to cloud platform The peculiar reference value of illness number of times, the rearmounted deviation of each physiological data when obtaining patient to current number of times；Wherein：

${\mathrm{\σ}}_{P_{i,K+1}}^{Phy}=\sqrt{\frac{1}{K+1}\underset{n=1}{\overset{K+1}{\mathrm{\Σ}}}\left({\left({\mathrm{Data}}_{P_i,n}^{Phy}-{\stackrel{\‾}{{\mathrm{Data}}_{P_i}^{Phy}}}^{\′}\right)}^2\right)},{\stackrel{\‾}{{\mathrm{Data}}_{P_i}^{Phy}}}^{\′}=\frac{1}{K+1}\underset{n=1}{\overset{K+1}{\mathrm{\Σ}}}{\mathrm{Data}}_{P_i,n}^{Phy}+{\mathrm{\Δ}}_{P_i}^{Phy};$

Represent corresponding physiological data P during patient the K+1 times_iRearmounted deviation；K+1 represents that current cloud platform is forwarded The number of times of patient information, patient physiological data value set and the peculiar reference value of correspondence illness；Represent to be directed to physiological data P_i Offset constant during in normal condition；

Step 6-3, hospital services subsystem presets the illness feature decision threshold of each physiological data, and hospital services respectively System obtains patient's correspondence physiological data according to the corresponding preposition deviation of each physiological data of gained patient and rearmounted deviation Happen suddenly deviation；Wherein： Represent correspondence patient physiological data P_iBurst deviation,Table Show correspondence patient physiological data P_iPreposition deviation,Represent correspondence patient physiological data P_iRearmounted deviation；Correspondence Physiological data P_iIllness feature decision threshold be labeled as

Step 6-4, hospital services subsystem is according to the burst deviation and default each physiology of each physiological data of gained patient The illness feature decision threshold of data carries out illness judgement respectively, to judge whether patient illness occurs：

WhenWhen, represent the physiological data P of patient_iThere is exception, then hospital services subsystem indicates that patient occurs in that Correspondence physiological data P_iIllness；WhenWhen, represent the physiological data P of patient_iDo not occur exception, then hospital services System indicates the physiological data P of patient_iNormally；

Step 7, the expert doctor in expert section office receives the first visit knot that first visit section office send using the doctor's client of oneself By, the first visit sequence number of patient and patient information, and set up patient and gone to a doctor case history in the electronics of the hospital, while by doctor visitor Family end is done the encryption process to the medical case history of electronics of patient, to protect patient's individual privacy information；Wherein, doctor's client The medical case history process of the electronics of encryption patient comprises the following steps 7-1 to step 7-4：

Step 7-1, doctor's client prestores the electronic anti-fogery stamped signature colour picture of affiliated expert doctor, and with electronic anti-fogery Stamped signature colour picture issues the audit voucher of the medical case history of electronics as doctor；Wherein, the electronic anti-fogery label of the expert doctor Chapter colour picture is designated asJ represents that hospital services subsystem assigns the electronics label of expert doctor Chapter sequence number, J represents that hospital services subsystem assigns total Electronic Signature number of each expert doctor；Doct_jExpression possesses electricity Sub- stamped signature serial number j doctor；

Step 7-2, doctor's client obtain expert doctor's electronic anti-fogery stamped signature colour picture in each color gray scale value with And the height value and width value of electronic anti-fogery stamped signature colour picture, obtain the stamped signature of expert doctor's electronic anti-fogery stamped signature colour picture Anti- pseudoindex；Wherein, the anti-pseudoindex of the corresponding stamped signature of expert doctor is designated asExpert doctor's electronic anti-fogery stamped signature is color Chromatic graph pieceThe gray scale value of middle color is designated asElectronic anti-fogery stamped signature colour pictureHeight value be designated asElectronic anti-fogery stamped signature colour pictureWidth value be designated as

${{\mathrm{\σ}}_{Grayscale}}^{{\mathrm{Doct}}_j}=\sqrt{\frac{1}{V}\underset{v=1}{\overset{V}{\mathrm{\Σ}}}\left({\left({\mathrm{Grayscale}}_v^{{\mathrm{Doct}}_j}-{{\mathrm{\τ}}_{Grayscale}}^{{\mathrm{Doct}}_j}\right)}^2\right)};v=1,2,\mathrm{...},V;$

Wherein, V refers to total species number of all colours in expert doctor's electronic anti-fogery stamped signature colour picture,Table Show v kinds color in electronic anti-fogery stamped signature colour pictureIn gray scale value；

The corresponding anti-pseudoindex of stamped signature of the gained expert doctor is sent to hospital services subsystem by step 7-3, doctor's client System storage is put on record, while by hospital services subsystem by the anti-pseudoindex of the stamped signature of the expert doctor put on record and hospital services The identity information of subsystem is integrated, to obtain the verification code information that the medical case history of electronics is consulted for patient；Wherein, the correspondence electricity The verification code information of the medical case history of son is labeled asHospitol_DoctjTable Show expert doctor Doct_jThe hospital services subsystem held office, T_DoctjRepresent expert doctor the anti-pseudoindex of stamped signature it is effective when Between be worth；

Step 7-4, doctor's client sends the verification code information that the medical case history of electronics is consulted for patient in the form of short message To patient in cloud platform leaves the mobile terminal of telephone number, to realize that patient is led within the effective time of the anti-pseudoindex of stamped signature Cross cloud platform and consult the medical case history of the electronics of oneself；

Step 8, doctor's client at expert doctor extracts the various physiological data values of the patient of reception respectively, and by extraction Various physiological data values compare judgement with corresponding normal physiological data value respectively, so that expert doctor decides whether to current Patient makes remote diagnosis, and draws the peculiar value of each physiological data of patient by doctor's client of expert doctor, to help Expert doctor understands the physiological data situation of change of patient in advance；Wherein, patient physiological data P_iPeculiar value be designated as ζ_Pi：

${\mathrm{\σ}}_{{\mathrm{Data}}_{P_i,n}^{Phy},T_1}=\sqrt{\frac{1}{N^{\′}}\underset{n=1}{\overset{N^{\′}}{\mathrm{\Σ}}}{\left({\mathrm{Data}}_{P_i,n}^{Phy}-E_{{\mathrm{Data}}_{P_i}^{Phy}}\right)}^2},E_{{\mathrm{Data}}_{P_i}^{Phy}}=\frac{1}{N^{\′}}\underset{n=1}{\overset{N^{\′}}{\mathrm{\Σ}}}{\mathrm{Data}}_{P_i,n}^{Phy};$

N' represents doctor's client at expert doctor in period T₁Interior received patient physiological data P_iNumber, Represent in period T₁Interior patient's physiological data P_iUndulating value,Represent doctor's client at expert doctor for just The physiological data P of ordinary person group_iPre-set normal fluctuation constant；

When any of patient physiological data set physiological data is not in the normal range (NR) of this kind of physiological data, then specially Doctor's client at family doctor is made alarm and reminded；Otherwise, doctor's client at expert doctor refuses alarm；

Step 9, expert doctor makes remote visiting to patient by doctor's client and invited and true in patient's completion remote visiting After recognizing, expert doctor is put on record the patient of confirmation remote visiting by its doctor's client at hospital services subsystem； After patient pays diagnostic fees, expert's diagnosis patient condition simultaneously includes expert doctor by what is outputed for patient condition The electronic prescription of raw professional information is respectively supplied to cloud platform and the hospital services subsystem belonging to the expert doctor carry out it is real When put on record；Patient logs in cloud platform to check electronic prescription that expert doctor provides by patient's mobile client, and according to electricity Sub- prescription buys medicine at the pharmacy's service subsystem put on record that cloud platform is provided, and completes mobile telemedicine process.

2. the mobile telemedicine management method according to claim 1 based on cloud platform, it is characterised in that the hospital Information includes hospital's brief introduction, hospital department, each section office and is good at diagnosis direction and audits the expense valency passed through through price department Lattice information, information about doctor includes physician names, affiliated section office, academic title, is good at diagnosis direction and contact method；The patient Information at least includes relatives' connection of patient's name, identification card number, age, sex, medical history, allergens and patient It is mode；The electronic prescription at least include patient's name, expert's physician names, expert doctor's operation card number, patient condition, Remote visiting time, reimbursement of expense inventory and list of medications.

3. the mobile telemedicine management method according to claim 1 based on cloud platform, it is characterised in that in step 9 The step of nutritious food plan is also automatically generated according to the illness of patient including cloud platform afterwards, to help patient according to the battalion Support meal plans to supplement the nutrients, patient abnormal physiological data is occurred and recover to the normal value of physiological data.

4. the mobile telemedicine management method according to claim 1 based on cloud platform, it is characterised in that in step 9 Also include afterwards, cost data and confirm the medical patient data invited that hospital services subsystem is paid according to all patients, The step of obtaining the expert doctor's list liked by patient.

5. the mobile telemedicine management method according to claim 1 based on cloud platform, it is characterised in that in step 2 In, the physiological data that the patient physiological data Acquisition Instrument is gathered is blood glucose level data or blood pressure data or blood fat data or heart rate Data or pulse data or spirometric data or temperature data, or blood glucose level data, blood pressure data, blood fat data, heart rate number According to, any combination of pulse data, spirometric data and temperature data.