CN116307890A - Health maintenance method and system based on big data - Google Patents
Health maintenance method and system based on big data Download PDFInfo
- Publication number
- CN116307890A CN116307890A CN202310262761.3A CN202310262761A CN116307890A CN 116307890 A CN116307890 A CN 116307890A CN 202310262761 A CN202310262761 A CN 202310262761A CN 116307890 A CN116307890 A CN 116307890A
- Authority
- CN
- China
- Prior art keywords
- health care
- information
- service personnel
- cured
- health
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Granted
Links
- 230000036541 health Effects 0.000 title claims abstract description 245
- 238000012423 maintenance Methods 0.000 title claims abstract description 52
- 238000000034 method Methods 0.000 title claims abstract description 40
- 238000001514 detection method Methods 0.000 claims description 29
- 230000004044 response Effects 0.000 claims description 12
- 230000008569 process Effects 0.000 claims description 7
- 238000012216 screening Methods 0.000 claims description 6
- 238000012937 correction Methods 0.000 claims description 2
- 230000007246 mechanism Effects 0.000 abstract description 3
- 230000000694 effects Effects 0.000 description 5
- 230000008821 health effect Effects 0.000 description 4
- 206010033425 Pain in extremity Diseases 0.000 description 3
- 230000007547 defect Effects 0.000 description 2
- 238000011156 evaluation Methods 0.000 description 2
- 230000006872 improvement Effects 0.000 description 2
- 230000004048 modification Effects 0.000 description 2
- 238000012986 modification Methods 0.000 description 2
- 201000004569 Blindness Diseases 0.000 description 1
- 230000009286 beneficial effect Effects 0.000 description 1
- 230000008859 change Effects 0.000 description 1
- 238000010586 diagram Methods 0.000 description 1
- 230000002427 irreversible effect Effects 0.000 description 1
- 230000003340 mental effect Effects 0.000 description 1
- 238000012544 monitoring process Methods 0.000 description 1
- 230000036651 mood Effects 0.000 description 1
- 230000035764 nutrition Effects 0.000 description 1
- 235000016709 nutrition Nutrition 0.000 description 1
- 230000008520 organization Effects 0.000 description 1
- 230000008439 repair process Effects 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06393—Score-carding, benchmarking or key performance indicator [KPI] analysis
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q10/00—Administration; Management
- G06Q10/06—Resources, workflows, human or project management; Enterprise or organisation planning; Enterprise or organisation modelling
- G06Q10/063—Operations research, analysis or management
- G06Q10/0639—Performance analysis of employees; Performance analysis of enterprise or organisation operations
- G06Q10/06398—Performance of employee with respect to a job function
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06Q—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES; SYSTEMS OR METHODS SPECIALLY ADAPTED FOR ADMINISTRATIVE, COMMERCIAL, FINANCIAL, MANAGERIAL OR SUPERVISORY PURPOSES, NOT OTHERWISE PROVIDED FOR
- G06Q50/00—Information and communication technology [ICT] specially adapted for implementation of business processes of specific business sectors, e.g. utilities or tourism
- G06Q50/10—Services
-
- G—PHYSICS
- G16—INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR SPECIFIC APPLICATION FIELDS
- G16H—HEALTHCARE INFORMATICS, i.e. INFORMATION AND COMMUNICATION TECHNOLOGY [ICT] SPECIALLY ADAPTED FOR THE HANDLING OR PROCESSING OF MEDICAL OR HEALTHCARE DATA
- G16H20/00—ICT specially adapted for therapies or health-improving plans, e.g. for handling prescriptions, for steering therapy or for monitoring patient compliance
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02A—TECHNOLOGIES FOR ADAPTATION TO CLIMATE CHANGE
- Y02A90/00—Technologies having an indirect contribution to adaptation to climate change
- Y02A90/10—Information and communication technologies [ICT] supporting adaptation to climate change, e.g. for weather forecasting or climate simulation
Landscapes
- Business, Economics & Management (AREA)
- Human Resources & Organizations (AREA)
- Engineering & Computer Science (AREA)
- Economics (AREA)
- Strategic Management (AREA)
- Tourism & Hospitality (AREA)
- Educational Administration (AREA)
- Entrepreneurship & Innovation (AREA)
- Development Economics (AREA)
- General Business, Economics & Management (AREA)
- Theoretical Computer Science (AREA)
- Marketing (AREA)
- General Physics & Mathematics (AREA)
- Physics & Mathematics (AREA)
- Operations Research (AREA)
- Quality & Reliability (AREA)
- Game Theory and Decision Science (AREA)
- Health & Medical Sciences (AREA)
- General Health & Medical Sciences (AREA)
- Primary Health Care (AREA)
- Epidemiology (AREA)
- Medical Informatics (AREA)
- Public Health (AREA)
- Medical Treatment And Welfare Office Work (AREA)
Abstract
The invention belongs to the technical field of health and maintenance, and discloses a health and maintenance method and system based on big data, wherein the method comprises the following steps: storing information of service personnel to be cured and information of potential service personnel to be cured; formulating a health care scheme according to the health care items of the personnel to be health care, and generating a health care curve of predicted health care data indexes and time of the health care items; acquiring the health care data index information of the to-be-health care service personnel at the appointed time, and comparing the health care data index information with the predicted health care index data corresponding to the appointed time to obtain a predicted deviation; if the predicted deviation is greater than the set value, sending alarm information; sending health maintenance prompt information to potential health maintenance service personnel; updating information of service personnel to be cured; matching Kang Yang with appropriate health care services team: the method and the system of the invention are based on the judgment of big data, specify the health care service team, and carry out secondary matching service team by scoring mechanism during health care service, thereby greatly improving the health care service level.
Description
Technical Field
The invention relates to the technical field of health care, in particular to a health care method and system based on big data.
Background
The description of the background art to which the present invention pertains is merely for illustrating and facilitating understanding of the summary of the invention, and should not be construed as an explicit recognition or presumption by the applicant that the applicant regards the prior art as the filing date of the first filed application.
Along with the improvement of the living standard of people, the health care service becomes an important component in the life of people increasingly, however, the current health care service has a certain blindness, namely, people needing the health care service generally arrive at a physical examination hospital or clinic, and the service personnel are found to judge what health care service is needed after detection.
This has the disadvantage that many health services personnel are actually adept at, i.e. one or more, not performing the health services well, and the desirer is not able to give health services team feedback, even if not satisfied, i.e. not performing health at this team next time, however, the person is not a machine, repair is done that can be reworked or replaced, the life of the person is precious, and health effects are often irreversible.
Disclosure of Invention
The embodiment of the invention aims to provide a health maintenance method and system based on big data.
The method of the embodiment of the invention is realized by the following scheme:
a health method based on big data comprises the following steps:
storing information of service personnel to be cured and information of potential service personnel to be cured;
formulating a health care scheme according to the health care items of the personnel to be health care, and generating a health care curve of predicted health care data indexes and time of the health care items;
acquiring the health care data index information of the to-be-health care service personnel at the appointed time, and comparing the health care data index information with the predicted health care index data corresponding to the appointed time to obtain a predicted deviation; if the predicted deviation is greater than the set value, sending alarm information;
sending health maintenance prompt information to potential health maintenance service personnel;
receiving feedback information of potential to-be-cured service personnel, and classifying the feedback information to obtain second to-be-cured service personnel information, intention to-be-cured service personnel information and temporary unnecessary potential to-be-cured service personnel information; sending a health care case matched with a health care item of an intention to-be-maintained service person to the intention to-be-maintained service person; sending a questionnaire to a potential to-be-cured attendant which is not required temporarily, wherein the questionnaire comprises a non-curing willingness reason, and according to the non-curing reason matching solution, sending the matching solution to the potential to-be-cured attendant which is not required;
receiving response information of a potential to-be-cured service personnel to a matched solution, and analyzing the response information to obtain third to-be-cured service personnel information; combining the second to-be-cured service personnel information, the third to-be-cured service personnel information and the to-be-cured service personnel information to form first to-be-cured service personnel information, and replacing the stored to-be-cured service personnel information with the first to-be-cured service personnel information;
matching Kang Yang with appropriate health care services team:
scoring the whole health care service in the health care process of obtaining the health care service personnel to be health care, and generating a manual scoring item M i The method comprises the steps of carrying out a first treatment on the surface of the Said M i The effective limit value of (2) is M;
acquiring data information before rehabilitation, generating a first report, acquiring data information after rehabilitation, and generating a second report; the first report and the second report are sent to an expert group, and the expert group scores an expert for making a scheme according to the first report and the second report to obtain an expert group scoring item T; t has a locking value of T 0 ;
If T is less than or equal to T 0 Uploading the report to a decision-making team to request replacement of the health maintenance service team;
if T > T 0 ,Then according toAnd (5) manually scoring the items and scoring by an expert group to obtain the nutrition service score:
wherein, for randomly extracting the data information of the artificial scoring item with the number k from the total artificial scoring item, if Q is not less than Q Standard of Uploading the report to a health care services team; if Q is smaller than Q Standard of And uploading the report to a decision-making team to request replacement of the health-care service team.
Further, if the predicted deviation is greater than the set value, the method includes the steps of: classifying the prediction deviation to obtain a good prediction deviation, a bad prediction deviation and a reverse prediction deviation; if the predicted deviation is good, archiving the predicted deviation to a database to be observed; if the deviation is the deviation of the forward error prediction, sending information for adjusting the health and maintenance scheme to service personnel; and if the deviation is the reverse prediction deviation, sending information for changing the health and maintenance scheme to service personnel.
Further, the method further comprises the steps of: collecting the time for the health maintenance service personnel to detect the health maintenance data indexes, and if the time interval for the health maintenance service personnel to detect the health maintenance data indexes exceeds a threshold value, then:
if the predicted deviation of the last detection of the healthy data index of the service personnel to be healthy is not more than 40% of the set value; sending a health index detection prompt to the to-be-cured service personnel; if the time interval of the detection of the health care data index of the service personnel to be health care exceeds N times of the threshold value, an alarm is sent to the service personnel to carry out manual reminding; the n=0.25 set value/predicted deviation value;
if the predicted deviation of the last detection of the healthy data index of the service personnel to be healthy is more than 40% of the set value; sending a health index detection prompt to the service personnel to be cured, and sending an alarm to the service personnel at the same time, wherein the service personnel carry out manual prompt;
if the predicted deviation of the last time of the healthy data index detection of the service personnel to be healthy is a forward difference predicted deviation or a reverse predicted deviation, sending the predicted deviation to the healthy index detection reminding to the service personnel to be healthy, and sending an alarm to the service personnel at the same time, and carrying out manual reminding by the service personnel;
the service personnel stores the information needing manual reminding and sends reminding within a set time; and acquiring the real-time refreshed time for detecting the health care data indexes of the to-be-health care service personnel before reminding, and reminding if the to-be-health care service personnel needing manual reminding still do not detect the health care data indexes.
Further, acquiring the health care data index detection information of the to-be-health care service personnel, and if the predicted deviation in the health care data index detection information is not larger than the set value and the proportion of the good predicted deviation is not qualified, sending a correction prompt to the expert group.
Further, the method further comprises the steps of: and acquiring living environment information of the to-be-cured service personnel, wherein the living environment information is related to-be-cured items of the to-be-cured personnel.
Further, in the step of matching Kang Yang items with proper health care services team:
if T > T 0 Then reject the manual scoring item M i The non-trusted manual scoring item is a scoring item given by a to-be-health maintenance service personnel, wherein the score of more than 90% of times in F health maintenance service teams is lower than an effective limit value of M or the score of more than 90% of times in F health maintenance service teams is higher than the effective limit value.
A big data based healthcare system comprising:
the storage module is used for storing the information of the service personnel to be cured and the information of the potential service personnel to be cured;
a standard curve generation module: the method comprises the steps of formulating a health care scheme according to a health care item of a person to be health care, and generating a health care curve of predicted health care data indexes and time of the health care item;
the prediction deviation judging module is used for acquiring the health data index information of the to-be-health service personnel at the designated time and comparing the health data index information with the prediction health index data corresponding to the designated time to obtain the prediction deviation; if the predicted deviation is greater than the set value, sending alarm information;
the prompting module is used for sending health prompting information to potential health service personnel;
the information receiving and transmitting and analyzing module is used for receiving feedback information of potential to-be-cured service personnel, classifying the feedback information to obtain second to-be-cured service personnel information, intention to-be-cured service personnel information and temporary unnecessary potential to-be-cured service personnel information; sending a health care case matched with a health care item of an intention to-be-maintained service person to the intention to-be-maintained service person; sending a questionnaire to a potential to-be-cured attendant which is not required temporarily, wherein the questionnaire comprises a non-curing willingness reason, and according to the non-curing reason matching solution, sending the matching solution to the potential to-be-cured attendant which is not required;
receiving response information of a potential to-be-cured service personnel to a matched solution, and analyzing the response information to obtain third to-be-cured service personnel information; combining the second to-be-cured service personnel information, the third to-be-cured service personnel information and the to-be-cured service personnel information to form first to-be-cured service personnel information, and replacing the stored to-be-cured service personnel information with the first to-be-cured service personnel information;
the health care service team screening module: for matching Kang Yang items to appropriate health care services teams:
scoring the whole health care service in the health care process of obtaining the health care service personnel to be health care, and generating a manual scoring item M i The method comprises the steps of carrying out a first treatment on the surface of the Said M i The effective limit value of (2) is M;
acquiring data information before rehabilitation, generating a first report, acquiring data information after rehabilitation, and generating a second report; the first report and the second report are sent to an expert group, and the expert group scores an expert for making a scheme according to the first report and the second report to obtain an expert group scoring item T; t has a locking value of T 0 ;
If T is less than or equal to T 0 Uploading the report to a decision-making team to request replacement of the health maintenance service team;
if T > T 0 ,Obtaining the health care service score according to the manual scoring item and the expert group scoring:
wherein, for randomly extracting the data information of the artificial scoring item with the number k from the total artificial scoring item, if Q is not less than Q Standard of Uploading the report to a health care services team; if Q is smaller than Q Standard of And uploading the report to a decision-making team to request replacement of the health-care service team.
The embodiment of the invention has the following beneficial effects:
the method and the system of the invention are based on the judgment of big data, specify the health care service team, and carry out secondary matching service team by scoring mechanism during health care service, thereby greatly improving the health care service level.
Drawings
FIG. 1 is a schematic diagram of determining a health care plan according to a predicted deviation value in an embodiment of the present invention.
Detailed Description
The present application is further described below with reference to examples.
In order to more clearly describe embodiments of the present invention or technical solutions in the prior art, in the following description, different "an embodiment" or "an embodiment" does not necessarily refer to the same embodiment. Various embodiments may be substituted or combined, and other implementations may be obtained from these embodiments by those of ordinary skill in the art without undue burden.
A health method based on big data comprises the following steps:
storing information of service personnel to be cured and information of potential service personnel to be cured; the personnel to be supported are the personnel who have determined to be supported, and the potential personnel to be supported are the personnel who need supported on the basis of the current physical indexes, but do not temporarily put forward the support requirement for some reasons, such as economy, time and the like;
formulating a health care scheme according to the health care items of the personnel to be health care, and generating a health care curve of predicted health care data indexes and time of the health care items; it is to be noted that, when the health care service is started, a large number of formulated health care schemes are stored in the system, and big data are selected according to Kang Yangxiang, health care strength and other proper health care schemes; for example, people with leg pain can be screened out a leg health care scheme, the leg pain grade is also divided into a plurality of grades, further screening schemes can be carried out according to the leg pain grade, and the like, and the screening schemes are only exemplified herein, and do not represent the screening standard;
acquiring the health care data index information of the to-be-health care service personnel at the appointed time, and comparing the health care data index information with the predicted health care index data corresponding to the appointed time to obtain a predicted deviation; if the predicted deviation is greater than the set value, sending alarm information; in the process of performing the health care service, the health care item index needs to be detected in a staged manner, and the effect of the staged detection can be measured by predicting deviation; the purpose of monitoring the health and maintenance effect in real time can be achieved; the prediction deviation can judge whether the health effect exceeds the reasonable range of the health effect.
Sending health maintenance prompt information to potential health maintenance service personnel;
receiving feedback information of potential to-be-cured service personnel, and classifying the feedback information to obtain second to-be-cured service personnel information, intention to-be-cured service personnel information and temporary unnecessary potential to-be-cured service personnel information; sending a health care case matched with a health care item of an intention to-be-maintained service person to the intention to-be-maintained service person; sending a questionnaire to a potential to-be-cured attendant which is not required temporarily, wherein the questionnaire comprises a non-curing willingness reason, and according to the non-curing reason matching solution, sending the matching solution to the potential to-be-cured attendant which is not required;
receiving response information of a potential to-be-cured service personnel to a matched solution, and analyzing the response information to obtain third to-be-cured service personnel information; combining the second to-be-cured service personnel information, the third to-be-cured service personnel information and the to-be-cured service personnel information to form first to-be-cured service personnel information, and replacing the stored to-be-cured service personnel information with the first to-be-cured service personnel information;
it will be appreciated that many people who need healthcare services do not actually wish to have their body better themselves, as it is readily appreciated that everyone wants to get more and more healthy, but always have some reasons, such as economic reasons, time reasons, choose to give up the mental and other reasons for the rejection of the healthcare services, the system finds the appropriate solution according to the feedback information, such as economic problems, can provide some simple and affordable solutions, or provide some fund or some policy of relief of the relevant departments, such as time problems, can provide time-staggered services, etc.
Matching Kang Yang with appropriate health care services team:
scoring the whole health care service in the health care process of obtaining the health care service personnel to be health care, and generating a manual scoring item M i The method comprises the steps of carrying out a first treatment on the surface of the Said M i The effective limit value of (2) is M;
acquiring data information before rehabilitation, generating a first report, acquiring data information after rehabilitation, and generating a second report; the first report and the second report are sent to an expert group, and the expert group scores an expert for making a scheme according to the first report and the second report to obtain an expert group scoring item T; t has a locking value of T 0 ;
If T is less than or equal to T 0 Uploading the report to a decision-making team to request replacement of the health maintenance service team;
if T > T 0 ,Obtaining the health care service score according to the manual scoring item and the expert group scoring:
wherein, for randomly extracting the data information of the artificial scoring item with the number k from the total artificial scoring item, if Q is not less than Q Standard of Uploading the report to a health care services team; if Q is smaller than Q Standard of And uploading the report to a decision-making team to request replacement of the health-care service team.
Whether the team is professional or not is the key of the trust and health maintenance service of people, the application divides the professional of the team into two parts, namely service and scheme professionals, and the service aspect comprises prompt, attitude quality and the like; the scheme specialty is mainly judged from the health care effect; the judgment of M is actually the judgment of the effect of the health and maintenance scheme, and the judgment of T is basically the judgment of the effect of the health and maintenance scheme.
The timely finishing scheme and the replacement team show the expertise and responsibility of the service organization; if T is less than or equal to T 0 Uploading the report to a decision-making team to request replacement of the health maintenance service team; the expert group is explained to carry out very low evaluation on the scheme, and no matter how good the service is, the expert group can not change the health effect, and the team needs to be replaced;
the judgment here considers that the service and the scheme are qualified, and the detailed report is sent to the original service team, and the original team improves the detail according to the report;
if T > T 0 ,Then according to the manual dividing of the items and the specialitiesScoring the home group to obtain a health care service score:
this decision is based on the fact that if the solution has no problem with its professionals, and there is a certain defect in the service, further analysis is required:
wherein, for randomly extracting the data information of the artificial scoring item with the number k from the total artificial scoring item, if Q is not less than Q Standard of Uploading the report to a health care services team; if Q is smaller than Q Standard of And uploading the report to a decision-making team to request replacement of the health-care service team.
The explanation of this analysis is as follows: because the expert group is a judgment item with strong objectivity according to the report, the scoring of the service personnel to be supported is complex in practice, and the comprehensive evaluation of the scheme, the service attitude and the like is included, and the influence of factors such as the mood factor of the scoring personnel, the self requirement, the character and the like is also received, a large number of samples are needed to determine whether to replace the team or improve the service, and in the judgment, besides all the scoring personnel, the scoring of the random lottery part scoring personnel is weighted secondarily, so that the reliability of the data is ensured. The reason is that there is a bias score that must occur in the overall score, but not necessarily in the random decimation or in a smaller proportion, since the bias itself is small.
The method and the system of the invention are based on the judgment of big data, specify the health care service team, and carry out secondary matching service team by scoring mechanism during health care service, thereby greatly improving the health care service level.
In some embodiments of the present invention, in conjunction with fig. 1, in the coordinate space of fig. 1, four lines from top to bottom are a normal index 1, an upper prediction limit 2, a predicted health index data 3, and a lower prediction limit 4, respectively; the line divides the coordinate system into four blocks from top to bottom, namely, a good prediction bias 5, a normal healthy maintenance 6, a bad prediction bias 7 and a reverse prediction bias 8; if the predicted deviation is larger than the set value, the method comprises the following steps of: classifying the prediction deviation to obtain a good prediction deviation, a bad prediction deviation and a reverse prediction deviation; if the predicted deviation is good, archiving the predicted deviation to a database to be observed; if the deviation is the deviation of the forward error prediction, sending information for adjusting the health and maintenance scheme to service personnel; and if the deviation is the reverse prediction deviation, sending information for changing the health and maintenance scheme to service personnel.
In some embodiments of the invention, the method further comprises the steps of: collecting the time for the health maintenance service personnel to detect the health maintenance data indexes, and if the time interval for the health maintenance service personnel to detect the health maintenance data indexes exceeds a threshold value, then:
if the predicted deviation of the last detection of the healthy data index of the service personnel to be healthy is not more than 40% of the set value; sending a health index detection prompt to the to-be-cured service personnel; if the time interval of the detection of the health care data index of the service personnel to be health care exceeds N times of the threshold value, an alarm is sent to the service personnel to carry out manual reminding; the n=0.25 set value/predicted deviation value;
if the predicted deviation of the last detection of the healthy data index of the service personnel to be healthy is more than 40% of the set value; sending a health index detection prompt to the service personnel to be cured, and sending an alarm to the service personnel at the same time, wherein the service personnel carry out manual prompt;
if the predicted deviation of the last time of the healthy data index detection of the service personnel to be healthy is a forward difference predicted deviation or a reverse predicted deviation, sending the predicted deviation to the healthy index detection reminding to the service personnel to be healthy, and sending an alarm to the service personnel at the same time, and carrying out manual reminding by the service personnel;
the service personnel stores the information needing manual reminding and sends reminding within a set time; and acquiring the real-time refreshed time for detecting the health care data indexes of the to-be-health care service personnel before reminding, and reminding if the to-be-health care service personnel needing manual reminding still do not detect the health care data indexes.
In some embodiments of the present invention, the health data index detection information of the service personnel to be health maintained is obtained, and if the predicted deviation in the health data index detection information is not greater than the set value and the proportion of the good predicted deviation is not qualified, a rectification prompt is sent to the expert group.
In some embodiments of the invention, the method further comprises the steps of: and acquiring living environment information of the to-be-cured service personnel, wherein the living environment information is related to-be-cured items of the to-be-cured personnel.
In some embodiments of the invention, the appropriate health services team step is matched for Kang Yang:
if T > T 0 Then reject the manual scoring item M i The non-trusted manual scoring item is a scoring item given by a to-be-health maintenance service personnel, wherein the score of more than 90% of times in F health maintenance service teams is lower than an effective limit value of M or the score of more than 90% of times in F health maintenance service teams is higher than the effective limit value.
Here, an explanation will be made: conventional scoring generally adopts a mode of removing the highest score and the lowest score in order to ensure notarization, but the mode has defects, the highest score and the lowest score are not necessarily objective, and the embodiment of the application adopts the mode of deleting scores which are obtained under the statistics of big data and are mostly given to differences or mostly given to people with high scores, so that the scores can be more fair.
A big data based healthcare system comprising:
the storage module is used for storing the information of the service personnel to be cured and the information of the potential service personnel to be cured;
a standard curve generation module: the method comprises the steps of formulating a health care scheme according to a health care item of a person to be health care, and generating a health care curve of predicted health care data indexes and time of the health care item;
the prediction deviation judging module is used for acquiring the health data index information of the to-be-health service personnel at the designated time and comparing the health data index information with the prediction health index data corresponding to the designated time to obtain the prediction deviation; if the predicted deviation is greater than the set value, sending alarm information;
the prompting module is used for sending health prompting information to potential health service personnel;
the information receiving and transmitting and analyzing module is used for receiving feedback information of potential to-be-cured service personnel, classifying the feedback information to obtain second to-be-cured service personnel information, intention to-be-cured service personnel information and temporary unnecessary potential to-be-cured service personnel information; sending a health care case matched with a health care item of an intention to-be-maintained service person to the intention to-be-maintained service person; sending a questionnaire to a potential to-be-cured attendant which is not required temporarily, wherein the questionnaire comprises a non-curing willingness reason, and according to the non-curing reason matching solution, sending the matching solution to the potential to-be-cured attendant which is not required;
receiving response information of a potential to-be-cured service personnel to a matched solution, and analyzing the response information to obtain third to-be-cured service personnel information; combining the second to-be-cured service personnel information, the third to-be-cured service personnel information and the to-be-cured service personnel information to form first to-be-cured service personnel information, and replacing the stored to-be-cured service personnel information with the first to-be-cured service personnel information;
the health care service team screening module: for matching Kang Yang items to appropriate health care services teams:
scoring the whole health care service in the health care process of obtaining the health care service personnel to be health care, and generating a manual scoring item M i The method comprises the steps of carrying out a first treatment on the surface of the Said M i The effective limit value of (2) is M;
acquiring data information before rehabilitation, generating a first report, acquiring data information after rehabilitation, and generating a second report; the first report and the second report are sent to an expert group, and the expert group scores an expert for making a scheme according to the first report and the second report to obtain an expert group scoring item T; t has a locking value of T 0 ;
If T is less than or equal to T 0 Uploading the report to a decision-making team to request replacement of the health maintenance service team;
if T > T 0 ,Obtaining the health care service score according to the manual scoring item and the expert group scoring:
wherein, for randomly extracting the data information of the artificial scoring item with the number k from the total artificial scoring item, if Q is not less than Q Standard of Uploading the report to a health care services team; if Q is smaller than Q Standard of And uploading the report to a decision-making team to request replacement of the health-care service team.
It should be noted that the above embodiments can be freely combined as needed. The above description is only of the preferred embodiments of the present invention and is not intended to limit the present invention, but various modifications and variations can be made to the present invention by those skilled in the art. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
1. The health method based on big data is characterized by comprising the following steps:
storing information of service personnel to be cured and information of potential service personnel to be cured;
formulating a health care scheme according to the health care items of the personnel to be health care, and generating a health care curve of predicted health care data indexes and time of the health care items;
acquiring the health care data index information of the to-be-health care service personnel at the appointed time, and comparing the health care data index information with the predicted health care index data corresponding to the appointed time to obtain a predicted deviation; if the predicted deviation is greater than the set value, sending alarm information;
sending health maintenance prompt information to potential health maintenance service personnel;
receiving feedback information of potential to-be-cured service personnel, and classifying the feedback information to obtain second to-be-cured service personnel information, intention to-be-cured service personnel information and temporary unnecessary potential to-be-cured service personnel information; sending a health care case matched with a health care item of an intention to-be-maintained service person to the intention to-be-maintained service person; sending a questionnaire to a potential to-be-cured attendant which is not required temporarily, wherein the questionnaire comprises a non-curing willingness reason, and according to the non-curing reason matching solution, sending the matching solution to the potential to-be-cured attendant which is not required;
receiving response information of a potential to-be-cured service personnel to a matched solution, and analyzing the response information to obtain third to-be-cured service personnel information; combining the second to-be-cured service personnel information, the third to-be-cured service personnel information and the to-be-cured service personnel information to form first to-be-cured service personnel information, and replacing the stored to-be-cured service personnel information with the first to-be-cured service personnel information;
matching Kang Yang with appropriate health care services team:
scoring the whole health care service in the health care process of obtaining the health care service personnel to be health care, and generating a manual scoring item M i The method comprises the steps of carrying out a first treatment on the surface of the Said M i The effective limit value of (2) is M;
acquiring data information before rehabilitation, generating a first report, acquiring data information after rehabilitation, and generating a second report; the first report and the second report are sent to an expert group, and the expert group scores an expert for making a scheme according to the first report and the second report to obtain an expert group scoring item T; t has a locking value of T 0 ;
If T is less than or equal to T 0 Uploading the report to a decision-making team to request replacement of the health maintenance service team;
if T > T 0 ,Root of the Chinese characterObtaining the health care service score according to the manual scoring item and the expert group scoring:
wherein, for randomly extracting the data information of the artificial scoring item with the number k from the total artificial scoring item, if Q is not less than Q Standard of Uploading the report to a health care services team; if Q is smaller than Q Standard of And uploading the report to a decision-making team to request replacement of the health-care service team.
2. The big data based health method of claim 1, wherein after sending the alarm information if the predicted deviation is greater than the set value, comprising the steps of: classifying the prediction deviation to obtain a good prediction deviation, a bad prediction deviation and a reverse prediction deviation; if the predicted deviation is good, archiving the predicted deviation to a database to be observed; if the deviation is the deviation of the forward error prediction, sending information for adjusting the health and maintenance scheme to service personnel; and if the deviation is the reverse prediction deviation, sending information for changing the health and maintenance scheme to service personnel.
3. The big data based healthcare method of claim 2, further comprising the steps of: collecting the time for the health maintenance service personnel to detect the health maintenance data indexes, and if the time interval for the health maintenance service personnel to detect the health maintenance data indexes exceeds a threshold value, then:
if the predicted deviation of the last detection of the healthy data index of the service personnel to be healthy is not more than 40% of the set value; sending a health index detection prompt to the to-be-cured service personnel; if the time interval of the detection of the health care data index of the service personnel to be health care exceeds N times of the threshold value, an alarm is sent to the service personnel to carry out manual reminding; the n=0.25 set value/predicted deviation value;
if the predicted deviation of the last detection of the healthy data index of the service personnel to be healthy is more than 40% of the set value; sending a health index detection prompt to the service personnel to be cured, and sending an alarm to the service personnel at the same time, wherein the service personnel carry out manual prompt;
if the predicted deviation of the last time of the healthy data index detection of the service personnel to be healthy is a forward difference predicted deviation or a reverse predicted deviation, sending the predicted deviation to the healthy index detection reminding to the service personnel to be healthy, and sending an alarm to the service personnel at the same time, and carrying out manual reminding by the service personnel;
the service personnel stores the information needing manual reminding and sends reminding within a set time; and acquiring the real-time refreshed time for detecting the health care data indexes of the to-be-health care service personnel before reminding, and reminding if the to-be-health care service personnel needing manual reminding still do not detect the health care data indexes.
4. The method for health care based on big data according to claim 3, wherein health care data index detection information of the service personnel to be health care is obtained, and if the predicted deviation in the health care data index detection information is not greater than the set value and the proportion of the good predicted deviation is not qualified, a correction prompt is sent to the expert group.
5. The big data based healthcare method of claim 4, further comprising the steps of: and acquiring living environment information of the to-be-cured service personnel, wherein the living environment information is related to-be-cured items of the to-be-cured personnel.
6. The big data based healthcare method of claim 4, wherein the step of matching Kang Yang items with appropriate healthcare team is performed by:
if T > T 0 Then reject the manual scoring item M i The non-trusted manual scoring item is a scoring item given by a to-be-health maintenance service personnel, wherein the score of more than 90% of times in F health maintenance service teams is lower than an effective limit value of M or the score of more than 90% of times in F health maintenance service teams is higher than the effective limit value.
7. A big data based healthcare system comprising:
the storage module is used for storing the information of the service personnel to be cured and the information of the potential service personnel to be cured;
a standard curve generation module: the method comprises the steps of formulating a health care scheme according to a health care item of a person to be health care, and generating a health care curve of predicted health care data indexes and time of the health care item;
the prediction deviation judging module is used for acquiring the health data index information of the to-be-health service personnel at the designated time and comparing the health data index information with the prediction health index data corresponding to the designated time to obtain the prediction deviation; if the predicted deviation is greater than the set value, sending alarm information;
the prompting module is used for sending health prompting information to potential health service personnel;
the information receiving and transmitting and analyzing module is used for receiving feedback information of potential to-be-cured service personnel, classifying the feedback information to obtain second to-be-cured service personnel information, intention to-be-cured service personnel information and temporary unnecessary potential to-be-cured service personnel information; sending a health care case matched with a health care item of an intention to-be-maintained service person to the intention to-be-maintained service person; sending a questionnaire to a potential to-be-cured attendant which is not required temporarily, wherein the questionnaire comprises a non-curing willingness reason, and according to the non-curing reason matching solution, sending the matching solution to the potential to-be-cured attendant which is not required;
receiving response information of a potential to-be-cured service personnel to a matched solution, and analyzing the response information to obtain third to-be-cured service personnel information; combining the second to-be-cured service personnel information, the third to-be-cured service personnel information and the to-be-cured service personnel information to form first to-be-cured service personnel information, and replacing the stored to-be-cured service personnel information with the first to-be-cured service personnel information;
the health care service team screening module: for matching Kang Yang items to appropriate health care services teams:
scoring the whole health care service in the health care process of obtaining the health care service personnel to be health care, and generating a manual scoring item M i The method comprises the steps of carrying out a first treatment on the surface of the Said M i The effective limit value of (2) is M;
acquiring data information before rehabilitation, generating a first report, acquiring data information after rehabilitation, and generating a second report; the first report and the second report are sent to an expert group, and the expert group scores an expert for making a scheme according to the first report and the second report to obtain an expert group scoring item T; t has a locking value of T 0 ;
If T is less than or equal to T 0 Uploading the report to a decision-making team to request replacement of the health maintenance service team;
if T > T 0 ,Obtaining the health care service score according to the manual scoring item and the expert group scoring:
wherein, for randomly extracting the data information of the artificial scoring item with the number k from the total artificial scoring item, if Q is not less than Q Standard of Uploading the report to a health care services team; if Q is smaller than Q Standard of And uploading the report to a decision-making team to request replacement of the health-care service team.
Priority Applications (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202310262761.3A CN116307890B (en) | 2023-03-17 | 2023-03-17 | Health maintenance method and system based on big data |
Applications Claiming Priority (1)
Application Number | Priority Date | Filing Date | Title |
---|---|---|---|
CN202310262761.3A CN116307890B (en) | 2023-03-17 | 2023-03-17 | Health maintenance method and system based on big data |
Publications (2)
Publication Number | Publication Date |
---|---|
CN116307890A true CN116307890A (en) | 2023-06-23 |
CN116307890B CN116307890B (en) | 2023-10-27 |
Family
ID=86799168
Family Applications (1)
Application Number | Title | Priority Date | Filing Date |
---|---|---|---|
CN202310262761.3A Active CN116307890B (en) | 2023-03-17 | 2023-03-17 | Health maintenance method and system based on big data |
Country Status (1)
Country | Link |
---|---|
CN (1) | CN116307890B (en) |
Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20140123684A (en) * | 2013-04-15 | 2014-10-23 | 노영희 | Wellness Service and product certification System and the method thereof by using customer feed-back |
CN106846207A (en) * | 2017-01-19 | 2017-06-13 | 四川华迪信息技术有限公司 | Doctor supports combining information service and early warning platform and control method |
CN112184295A (en) * | 2020-09-22 | 2021-01-05 | 中国建设银行股份有限公司 | Health maintenance service determination method and device, electronic equipment and storage medium |
CN112565388A (en) * | 2020-12-01 | 2021-03-26 | 中盈优创资讯科技有限公司 | Distributed acquisition service scheduling system and method based on scoring system |
CN113781277A (en) * | 2021-08-05 | 2021-12-10 | 北京远盟普惠健康科技有限公司 | Terminal, system and data processing method for developing health maintenance service |
-
2023
- 2023-03-17 CN CN202310262761.3A patent/CN116307890B/en active Active
Patent Citations (5)
Publication number | Priority date | Publication date | Assignee | Title |
---|---|---|---|---|
KR20140123684A (en) * | 2013-04-15 | 2014-10-23 | 노영희 | Wellness Service and product certification System and the method thereof by using customer feed-back |
CN106846207A (en) * | 2017-01-19 | 2017-06-13 | 四川华迪信息技术有限公司 | Doctor supports combining information service and early warning platform and control method |
CN112184295A (en) * | 2020-09-22 | 2021-01-05 | 中国建设银行股份有限公司 | Health maintenance service determination method and device, electronic equipment and storage medium |
CN112565388A (en) * | 2020-12-01 | 2021-03-26 | 中盈优创资讯科技有限公司 | Distributed acquisition service scheduling system and method based on scoring system |
CN113781277A (en) * | 2021-08-05 | 2021-12-10 | 北京远盟普惠健康科技有限公司 | Terminal, system and data processing method for developing health maintenance service |
Also Published As
Publication number | Publication date |
---|---|
CN116307890B (en) | 2023-10-27 |
Similar Documents
Publication | Publication Date | Title |
---|---|---|
Olbert et al. | Meta-analysis of Black vs. White racial disparity in schizophrenia diagnosis in the United States: Do structured assessments attenuate racial disparities? | |
Ttofi et al. | School bullying and drug use later in life: A meta-analytic investigation. | |
Lopez et al. | Cognitive‐behavioural interventions for attention deficit hyperactivity disorder (ADHD) in adults | |
Cahill et al. | Implementation interventions to promote the uptake of evidence‐based practices in stroke rehabilitation | |
Holowka et al. | PTSD diagnostic validity in Veterans Affairs electronic records of Iraq and Afghanistan veterans. | |
Hu et al. | Automated detection of postoperative surgical site infections using supervised methods with electronic health record data | |
JP5547747B2 (en) | Automated assertion reuse for improved record linkage in distributed and autonomous medical environments with heterogeneous trust models | |
CN106845147B (en) | Method for building up, the device of medical practice summary model | |
Guaiana et al. | Cognitive behavioural therapy (group) for schizophrenia | |
Schreuders et al. | The relationship between nurse staffing and inpatient complications | |
CN116779190B (en) | Medical platform user follow-up management system and method based on Internet of things | |
US20070150314A1 (en) | Method for carrying out quality control of medical data records collected from different but comparable patient collectives within the bounds of a medical plan | |
Barrett et al. | A structural equation modeling analysis of influences on juvenile delinquency | |
CN107145715B (en) | Clinical medicine intelligence discriminating gear based on electing algorithm | |
Boyle et al. | A longitudinal analysis of nursing specialty certification by Magnet® status and patient unit type | |
Poly et al. | Artificial intelligence in diabetic retinopathy: Insights from a meta-analysis of deep learning | |
Ortiz-Orendain et al. | Modafinil for people with schizophrenia or related disorders | |
Sukanya | Validity of principal diagnoses in discharge summaries and ICD-10 coding assessments based on national health data of Thailand | |
Lin et al. | A case-finding clinical decision support system to identify subjects with chronic obstructive pulmonary disease based on public health data | |
CN116307890B (en) | Health maintenance method and system based on big data | |
Haugen et al. | The health management Information system in Malawi. Assessment of data quality and methods for improvement | |
Ghavidel et al. | Predicting the Need for Cardiovascular Surgery: A Comparative Study of Machine Learning Models | |
Randolph et al. | The competency screening test: A replication and extension | |
CN117423458A (en) | Human health state evaluation system and method | |
Bardsley et al. | Practical experiences in auditing patient outcomes. |
Legal Events
Date | Code | Title | Description |
---|---|---|---|
PB01 | Publication | ||
PB01 | Publication | ||
SE01 | Entry into force of request for substantive examination | ||
SE01 | Entry into force of request for substantive examination | ||
GR01 | Patent grant | ||
GR01 | Patent grant |