CN119724475B - Intelligent reminding method for nursing medication - Google Patents
Intelligent reminding method for nursing medication Download PDFInfo
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Abstract
The invention relates to the technical field of medication reminding, in particular to an intelligent reminding method for nursing medication. The method comprises the steps of obtaining medication compliance coefficients by combining the difference between medication time intervals of medication in a current time period of a patient and preset medication time intervals and the disturbance condition of medication time of the patient, obtaining medication behavior sensitivity coefficients according to the correlation condition between the medication time intervals of the patient medication and health indexes and the fluctuation condition of the medication time intervals, further determining the influence coefficients of medication compliance behaviors, and determining medication behavior deviation coefficients according to the difference between the proportion of the medication taken in the current time period of the patient and the preset proportion, the fluctuation condition of the proportion of each medication, the influence coefficients of the medication compliance coefficients and the medication compliance behaviors, and further adjusting medication automatic reminding frequency. The invention realizes the self-adaptive adjustment of the medication reminding frequency of the patient.
Description
Technical Field
The invention relates to the technical field of medication reminding, in particular to an intelligent reminding method for nursing medication.
Background
With aging population and increasing chronic diseases, the importance of drug treatment in nursing is increasing, but the problem of drug compliance (such as forgetting to take medicine, taking medicine by mistake, etc.) is more prominent especially in the elderly and chronic patients, affecting the treatment effect and increasing health risks. The nursing medicine bottle intelligent tag and the medicine management system can provide accurate medicine management and reminding service for patients or old people by utilizing the internet of things (IoT), a wireless communication technology and a data storage analysis technology, so that risks are reduced.
Existing care vial smart labels and medication management systems rely on preset medication information (e.g., medication name, dose, and time of use) to achieve automatic alerts. However, in practice, the health condition, the medication requirement and the living habit of each patient have certain differences, and the existing system cannot fully consider these individuation factors, so that the individuation medication reminding strategy cannot be provided simply by relying on preset medication information, and the management effect is affected.
Disclosure of Invention
In order to solve the problem that an individualized medication reminding strategy cannot be provided according to the individualized demands of patients in the prior art, the invention aims to provide an intelligent reminding method for nursing medication, which adopts the following technical scheme:
The invention provides an intelligent reminding method for nursing medication, which comprises the following steps:
acquiring the administration time, the dosage of the medicine and the health index of each administration in the current time period of the patient;
the medication compliance coefficient is obtained by combining the difference between the medication time interval of the medication in the current time period of the patient and the preset medication time interval and the disorder condition of the medication time of the patient; obtaining a drug action sensitivity coefficient according to the correlation condition between the drug time interval of the drug administration of the patient and the health index and the fluctuation condition of the drug time interval;
Determining a medication compliance coefficient according to the difference between the proportioning quantity of the medicines taken by the patient in the current time period and the preset proportioning quantity, the fluctuation condition of the proportioning quantity of each medicine, the medication compliance coefficient and the influence coefficient of the medication compliance;
And adjusting the automatic reminding frequency of the medication by using the medication behavior deviation coefficient.
Preferably, the obtaining the medication compliance coefficient by combining the difference between the medication time interval of the medication in the current time period of the patient and the preset medication time interval and the disorder condition of the medication time of the patient includes:
Calculating a medication time disorder coefficient according to the distribution condition of medication time of a patient in the current time period;
And combining the difference between the first average value and the preset medication time interval corresponding to each day in the current time period and the medication time disorder coefficient to obtain a medication compliance coefficient, wherein the difference between the first average value and the preset medication time interval and the medication time disorder coefficient are in negative correlation with the medication compliance coefficient.
Preferably, the calculating the medication time disorder coefficient according to the distribution condition of the medication time of the patient in the current time period includes:
for any day within the current time period, the medication times of all medications taken by the patient within the day form a medication time stamp sequence for the day;
All elements at the same position in all the medication time stamp sequences in the current time period form a subsequence; the variance of all elements in each subsequence is calculated respectively and is used as a first variance corresponding to each subsequence;
The mean of the first variances of all sub-sequences is determined as the medication time disorder coefficient.
Preferably, the obtaining the drug administration behavior sensitivity coefficient according to the correlation condition between the drug administration time interval and the health index of the patient and the fluctuation condition of the drug administration time interval includes:
The medicine time intervals of all adjacent twice medicines in the current time period form a time interval sequence, and the health indexes between all adjacent twice medicines in the current time period form a health index sequence;
Calculating a spearman correlation coefficient between the time interval sequence and the health index sequence;
And obtaining a drug administration behavior sensitivity coefficient according to the spearman correlation coefficient and the second variance, wherein the spearman correlation coefficient and the drug administration behavior sensitivity coefficient are in positive correlation, and the second variance and the drug administration behavior sensitivity coefficient are in negative correlation.
Preferably, the obtaining the drug administration behavior sensitivity coefficient according to the spearman correlation coefficient and the second variance includes:
and calculating a first sum value of the second variance and a preset adjustment parameter, determining the ratio between the Speermann correlation coefficient and the first sum value as a drug administration behavior sensitivity coefficient, wherein the preset adjustment parameter is a numerical value larger than 0.
Preferably, the determining the influence coefficient of the medication compliance based on the medication compliance coefficient and the medication compliance coefficient of sensitivity includes:
And determining the ratio of the medication compliance coefficient to the second sum value as an influence coefficient of the medication compliance.
Preferably, the determining the deviation coefficient of medication behavior according to the difference between the ratio of the medicines taken by the patient in the current time period and the preset ratio, the fluctuation condition of the ratio of each medicine, the medication compliance coefficient and the influence coefficient of medication compliance behavior includes:
Recording standard deviation of the proportioning amount of each medicine taken by a patient in the current time period as the fluctuation degree of the proportioning amount of each medicine;
Obtaining a medicine dosage deviation coefficient of each medicine according to the difference between the proportioning quantity of each medicine taken by a patient in the current time period and the preset proportioning quantity and the corresponding proportioning quantity fluctuation degree, wherein the difference between the proportioning quantity of each medicine and the preset proportioning quantity and the proportioning quantity fluctuation degree are in positive correlation with the medicine dosage deviation coefficient;
evaluating the overall deviation of the dosage of the drug based on the coefficient of deviation of the dosage of the drug;
and integrating the medication compliance coefficient, the influence coefficient of the medication compliance behavior and the integral deviation of the medication dosage to obtain a medication behavior deviation coefficient.
Preferably, the evaluating the overall deviation of the dosage of the drug based on the coefficient of deviation of the dosage of the drug includes taking the average value of the coefficient of deviation of the dosage of the drug as the overall deviation of the dosage of the drug.
Preferably, the step of obtaining the medication compliance coefficient, the influence coefficient of the medication compliance behavior and the overall deviation of the medication dosage to obtain the medication behavior deviation coefficient includes:
and determining the product of the negative correlation normalization result of the medication compliance coefficient, the influence coefficient of the medication compliance behavior and the integral deviation of the medication dosage as a medication behavior deviation coefficient.
Preferably, the adjusting the automatic reminding frequency of the medication by using the deviation coefficient of the medication behavior includes:
And calculating an upward rounding result of the product between the medication behavior deviation coefficient and the preset reminding frequency, and taking the upward rounding result as the adjusted medication automatic reminding frequency.
The invention has at least the following beneficial effects:
According to the invention, firstly, the difference between the medication time interval of medication in the current time period of a patient and the preset medication time interval and the disorder condition of the medication time of the patient are combined, the medication compliance of the patient is evaluated, the medication compliance coefficient is obtained, then, the medication behavior sensitivity coefficient is obtained according to the correlation condition between the medication time interval of the patient medication and the health index and the fluctuation condition of the medication time interval, the medication compliance of the patient and the influence factors thereof can be comprehensively measured through the medication compliance coefficient and the medication behavior sensitivity coefficient, the influence coefficient of the medication compliance behavior is determined, the dose deviation behavior possibly occurring in the medication process of the patient is considered, the medication behavior deviation coefficient of the patient is evaluated according to the dose deviation behavior, the medication automatic reminding frequency of the patient is determined, and the self-adaptive adjustment of the reminding frequency is realized, so that the personalized nursing reminding can accurately meet the actual demands of the patient, the medication compliance of the patient is improved, and the better management effect is achieved.
Drawings
In order to more clearly illustrate the embodiments of the invention or the technical solutions and advantages of the prior art, the following description will briefly explain the drawings used in the embodiments or the description of the prior art, and it is obvious that the drawings in the following description are only some embodiments of the invention, and other drawings can be obtained according to the drawings without inventive effort for a person skilled in the art.
Fig. 1 is a flowchart of a nursing medication intelligent reminding method according to an embodiment of the present invention;
Fig. 2 is a block diagram of a nursing medication intelligent reminding system according to an embodiment of the invention.
Detailed Description
In order to further describe the technical means and effects adopted by the invention to achieve the preset aim, the following describes an intelligent reminding method for nursing medication according to the invention in detail with reference to the attached drawings and the preferred embodiment.
Unless defined otherwise, all technical and scientific terms used herein have the same meaning as commonly understood by one of ordinary skill in the art to which this invention belongs.
The following specifically describes a specific scheme of the intelligent reminding method for nursing medication provided by the invention with reference to the accompanying drawings.
An embodiment of a nursing medication intelligent reminding method comprises the following steps:
the specific scene aimed at by the embodiment is that in the process of reminding the patient of medication, medication time data of the patient history are analyzed, the medication compliance of the patient is evaluated by combining personalized life habits of the patient, the medication behavior sensitivity coefficient of the patient is determined by combining the correlation between the health index of the patient and the medication data, the influence coefficient of the medication compliance behavior is further determined, and the medication reminding frequency of the patient is adaptively adjusted by combining the difference between the proportion of the medicines taken in the patient history data and the preset proportion and the fluctuation condition of the proportion of each medicine.
The embodiment provides an intelligent reminding method for nursing medication, as shown in fig. 1, the intelligent reminding method for nursing medication of the embodiment comprises the following steps:
step S1, acquiring the administration time of each administration, the proportion of the medicines and the health index of the patient in the current time period.
The intelligent label system of the traditional nursing medicine bottle mainly comprises an intelligent label module, a health record platform, a central processing unit, a cloud platform and a remote monitoring module, wherein the intelligent label in the system is small electronic equipment which can be attached to the outside of the medicine bottle, a built-in chip is used for storing medicine related information such as preset proportioning amount, preset taking time and other known data, and the system adopts a Radio Frequency Identification (RFID) technology to display medicine related information through different color areas or patterns, including taking time, dosage, medicine type, whether taking along with meals is needed or not and the like. The intelligent label module is also provided with a built-in clock and an infrared sensor, and is used for automatically recording the opening and closing state of the medicine bottle cap and the time of each opening and closing. The health record platform monitors the physiological index of the patient through the infrared thermometer, the intelligent bracelet and other devices, inputs the data into the trained convolutional neural network model for analysis, generates a score of 0 to 10, reflects the health condition of the patient, and takes the score as the health index of the patient in the embodiment. The system monitors the proportioning amount of each medicine by installing an integrated sensor on the inner wall of the nursing medicine bottle, and uploads the acquired medicine time, the acquired proportioning amount of the medicine and the health index of the patient to the cloud for storage in real time so as to ensure the timely updating and backup of data. In addition, the system also supports the storage of data in the local equipment, so that a user can conveniently check the historical medication records at any time. In this embodiment, the time for opening the cap of the medicine bottle when the patient takes the medicine every time is taken as the medicine taking time of the patient every time.
The intelligent label system of the nursing medicine bottle is used for collecting the medicine taking time of each medicine taking in the current time period of a patient, the proportion of each medicine taking each time and health indexes of the patient between every two adjacent medicines, wherein the current time period is a set formed by all historical moments, the time interval between the current time period and the current moment is smaller than or equal to the preset time length, the preset time length is 14 days in the embodiment, and in specific application, an implementer can set according to specific conditions.
Thus, the embodiment collects the administration time of each administration, the proportion of each administration and the health index between two adjacent administrations in the current period of the patient. It should be noted that, in this embodiment, one patient is taken as an example, and other patients can be treated by the method provided in this embodiment.
And S2, obtaining a medication compliance coefficient by combining the difference between the medication time interval of the medication in the current time period of the patient and the preset medication time interval and the disorder condition of the medication time of the patient, and obtaining a medication behavior sensitivity coefficient according to the correlation condition between the medication time interval of the medication of the patient and the health index and the fluctuation condition of the medication time interval.
The administration time of the medicine is usually fixed, such as before meals, after meals or before sleeping. However, due to different living habits of some patients, the dining time is irregular, so that the taking of medicines on time is difficult, and the medication compliance is affected, so that the reminding of the intelligent label cannot be matched with the actual dining time, and the reminding effect is reduced.
The method is used for analyzing 24 hours a day as a time length unit, specifically, for any day in the current time period, the medication time of all medications taken by a patient in the day forms a medication time stamp sequence of the day according to the time sequence, and the medication time stamp sequence of each day in the current time period can be obtained, namely a plurality of medication time stamp sequences corresponding to the current time period are obtained. All elements at the same position in all medication time stamp sequences in the current time period form a subsequence, namely, the 1 st element in all medication time stamp sequences forms the 1 st subsequence, the 2 nd element in all medication time stamp sequences forms the 2 nd subsequence, the 3 rd element in all medication time stamp sequences forms the 3 rd subsequence, and so on, so that a plurality of subsequences are obtained. And respectively calculating variances of all elements in each subsequence, wherein the variances are used as first variances corresponding to each subsequence, the first variances are used for reflecting fluctuation conditions of the elements in the subsequences, and the larger the variances are, the larger the fluctuation degree of the elements in the corresponding subsequences is. The mean of the first variances of all sub-sequences is determined as the medication time disorder coefficient.
According to the medication time of every two adjacent medications in the current time period of the patient, calculating the average value of the medication time intervals of every two adjacent medications in the current time period of the patient, and recording the average value as a first average value, wherein a corresponding first average value exists in every day in the current time period. And combining the difference between the first average value and the preset medication time interval corresponding to each day in the current time period and the medication time disorder coefficient to obtain a medication compliance coefficient, wherein the difference between the first average value and the preset medication time interval and the medication time disorder coefficient are in negative correlation with the medication compliance coefficient.
The negative correlation represents that the dependent variable decreases with increasing independent variable, and the dependent variable increases with decreasing independent variable, and may be a subtraction relationship, a division relationship, or the like, which is determined by practical application.
In this embodiment, a specific calculation formula of the medication compliance coefficient is given, and the medication compliance coefficient may be expressed as:
Wherein, Represents the medication compliance coefficient, S represents the medication time disorder coefficient, N represents the number of days in the current period,Indicating a preset medication time interval,Represents the average value of the medication time intervals of all the two adjacent medications on the nth day in the current period of the patient, namely the first average value corresponding to the nth day in the current period of the patient, exp () represents an exponential function based on a natural constant,Representing taking absolute value symbols.
The difference between the first average value corresponding to the nth day and the preset medicine taking time interval is shown, and the larger the absolute value is, the larger the difference between the first average value and the preset medicine taking time interval is shown, and the preset medicine taking time interval is shown to be set by a doctor according to the condition of a patient and the type of medicine taken.
When the medication time disorder coefficient is smaller and the difference between the corresponding first average value and the preset medication time interval is smaller, the patient is indicated to take the medicine according to the preset flow, and the medication compliance is stronger, namely the medication compliance coefficient is larger.
In the actual taking process, different medicines have different pharmacological characteristics, such as half-life and absorption speed difference, part of medicines need to be taken strictly according to fixed time to ensure curative effect and safety, and other medicines have loose requirements on taking time. For example, aspirin and antihypertensive agents (e.g., enalapril) are administered on time to maintain stable blood levels, whereas antacid agents (e.g., aluminum hydroxide) and a portion of vitamin supplements (e.g., vitamin C) may be administered before or after meals with less effect.
Based on the characteristics, firstly, the medication time intervals of every two adjacent medications in the current time period are calculated respectively, the medication time intervals of all the two adjacent medications in the current time period form a time interval sequence, health indexes between all the two adjacent medications in the current time period form a health index sequence, and the time interval sequence and the health index sequence are arranged according to time sequence. The calculation method of the spearman correlation coefficient between the time interval sequence and the health index sequence is the prior art, and will not be repeated here. The variance of all elements in the time interval sequence is calculated from all elements in the time interval sequence and is noted as the second variance. And obtaining a drug administration behavior sensitivity coefficient according to the spearman correlation coefficient and the second variance, wherein the spearman correlation coefficient and the drug administration behavior sensitivity coefficient are in positive correlation, and the second variance and the drug administration behavior sensitivity coefficient are in negative correlation.
The positive correlation relationship indicates that the dependent variable increases with the increase of the independent variable, and the dependent variable decreases with the decrease of the independent variable, and may be determined by an addition relationship, a multiplication relationship, or the like, and the negative correlation relationship indicates that the dependent variable decreases with the increase of the independent variable, and the dependent variable increases with the decrease of the independent variable, and may be determined by a subtraction relationship, a division relationship, or the like, and the dependent variable is determined by the actual application.
In this embodiment, a first sum of the second variance and a preset adjustment parameter is calculated, a ratio between the spearman correlation coefficient and the first sum is determined as a drug administration behavior sensitivity coefficient, and the preset adjustment parameter is a value greater than 0. The drug administration susceptibility can be expressed as:
wherein E represents a drug action sensitivity coefficient, U represents a time interval sequence, P represents a health index sequence, Representing the spearman correlation coefficient between the time interval sequence and the health index sequence,Representing the variance, i.e. the second variance,Indicating the preset adjustment parameters of the device,Representing a first sum value.
The preset adjustment parameter is introduced into the calculation formula of the drug administration behavior sensitivity coefficient to prevent the denominator from being 0, in this embodiment, the preset adjustment parameter is 0.01, and in specific applications, an implementer can set according to specific situations. The larger the spearman correlation coefficient between the time interval sequence and the health index sequence is, the stronger the correlation between the two sequences is, which means that the change of the health index is closely related to the medication time interval, and the larger the medication behavior sensitivity coefficient of the medicine is, the reflection of the patient on the medicine is highly dependent on the medication time and the medication frequency. The variance of all elements in the time interval sequence is used for reflecting the fluctuation condition of the element values in the time interval sequence, and the larger the variance is, the more discrete the element values are, and the smaller the fluctuation of the medication time interval is. If the fluctuation of the time interval of the medicine taking of the patient in the current time period is small, and even a tiny time interval change can significantly influence the health index of the patient in the time period, the health condition of the patient is highly dependent on the time interval and the frequency of the medicine taking, and therefore, the medicine taking behavior sensitivity coefficient of the medicine is large. The larger the spearman correlation coefficient between the time interval sequence and the health index sequence, the smaller the second variance, the larger the medication behavior sensitivity coefficient.
And step S3, determining an influence coefficient of medication compliance based on the medication compliance coefficient and the medication behavior sensitivity coefficient, and determining a medication behavior deviation coefficient according to the difference between the proportioning amount of the medicines taken by the patient in the current time period and the preset proportioning amount, the fluctuation condition of the proportioning amount of each medicine, the medication compliance coefficient and the influence coefficient of medication compliance.
When the patient uses the medicine with a larger medicine behavior sensitivity coefficient, the influence of the daily medicine compliance of the patient is aggravated, so the embodiment combines the medicine compliance coefficient and the medicine behavior sensitivity coefficient to determine the influence coefficient of the medicine compliance.
The method comprises the steps of calculating a second sum value of a drug administration behavior sensitivity coefficient and a preset adjustment parameter, and determining a ratio of the drug administration compliance coefficient to the second sum value as an influence coefficient of the drug administration compliance.
In this embodiment, a specific calculation formula for the influence coefficient of the medication compliance behavior is given, and the influence coefficient of the medication compliance behavior may be expressed as:
Wherein F is the influence coefficient of medication compliance, R is the medication compliance coefficient, E is the medication compliance sensitivity coefficient, Indicating the preset adjustment parameters of the device,Representing a second sum.
The preset adjustment parameter is introduced into the calculation formula of the influence coefficient of the medication compliance behavior in the present embodiment to prevent the denominator from being 0. The larger the medication compliance coefficient, the smaller the medication behavior sensitivity coefficient, the larger the coefficient of influence of the medication compliance behavior.
The effect of a drug on the health of a patient is closely related to the behavior of the patient. Even slight compliance fluctuations may have a significant impact on the efficacy if the patient's health is very sensitive to the time and frequency of administration.
Based on this, in subsequent analysis, for patients with higher drug administration susceptibility, despite their better drug compliance, it is still necessary to set higher system alert strengths to ensure that the effects of the drug are not negatively affected by compliance fluctuations.
In the nursing process, patients often need to use multiple medicines for combined treatment, and the dosage and proportion difference of different medicines can significantly influence the final curative effect. The dosage proportion of the medicines is strictly required, and if the patients use the medicines improperly, the incorrect dosage can seriously influence the effect of the medicines.
According to the ratio of each medicine taken in the current time period of the patient, calculating the standard deviation of the ratio of each medicine taken in the current time period of the patient, and recording the standard deviation of the ratio of each medicine taken in the current time period of the patient as the fluctuation degree of the ratio of each medicine, wherein the larger the value is, the larger the fluctuation of the actual ratio of each medicine in the historical medicine taking process of the patient is, the inconsistency of the ratio possibly exists, so that the patient is difficult to accurately determine the medicine ratio of each time. Therefore, according to the difference between the proportioning quantity and the preset proportioning quantity of each medicament taken by a patient in the current time period and the corresponding proportioning quantity fluctuation degree, the medicament dosage deviation coefficient of each medicament is obtained, and the difference between the proportioning quantity and the preset proportioning quantity of each medicament and the proportioning quantity fluctuation degree are in positive correlation with the medicament dosage deviation coefficient.
The positive correlation represents that the dependent variable increases with the increase of the independent variable, and the dependent variable decreases with the decrease of the independent variable, and may be determined by practical application, such as addition relationship and multiplication relationship.
In this embodiment, given a specific calculation formula of the medication dose deviation coefficient, the medication dose deviation coefficient of the i-th medicine may be expressed as:
Wherein, Represents the dosage deviation coefficient of the i-th drug,Represents the standard deviation of the proportionality amount of the ith medicine taken by the patient in the current time period,Represents the proportioning quantity of the ith medicine when the ith medicine is taken for the u time in the current time period,Represents the preset dosage of the ith medicine, U represents the times of taking the medicine in the current time period,Representing taking absolute value symbols.
The absolute value is used for representing the difference between the ratio of the ith medicine and the preset ratio when the patient takes the medicine for the u-th time in the current time period, and the larger the absolute value is, the larger the difference between the ratio and the preset ratio is.For reflecting the overall difference between the proportionality of the ith drug taken by the patient during the current time period and the preset proportionality, the larger the value, the larger the overall difference. In the embodiment, the fluctuation degree of the medicine proportioning quantity and the average value of the deviation between the actual medicine consumption and the preset proportioning quantity are combined to form a comprehensive index, the fluctuation and deviation condition of the medicine proportioning quantity are reflected, and the comprehensive index is helpful for revealing whether a patient has obvious proportioning error and instability in the actual medicine consumption process. When the standard deviation of the ratio of the ith medicine taken by the patient in the current time period is larger and the overall difference between the ratio of the ith medicine taken by the patient in the current time period and the preset ratio is also larger, the dosage deviation of the ith medicine taken by the patient in the current time period is larger, namely the dosage deviation coefficient of the ith medicine is larger.
By adopting the method, the dosage deviation coefficient of each medicine can be obtained, and the average value of the dosage deviation coefficients of all medicines is taken as the integral deviation of the dosage. It should be noted that the preset dosage of each drug is set by a doctor according to the condition of the patient.
When the patient takes medicines in daily nursing and taking processes, the medicine taking process is strictly fixed, the lower the influence of the medicine compliance on the treatment effect is, the final nursing and treating effect can be obviously influenced by the low compliance of the current stage of the patient, and meanwhile, when the medicine consumption deviation coefficient of the patient in each taking process is considered to be larger, the medicine taking behavior deviation of the current stage of the patient can be further aggravated, so that the accuracy and the curative effect of the treatment effect are influenced.
Based on the analysis, the product of the negative correlation normalization result of the medication compliance coefficient, the influence coefficient of the medication compliance behavior and the integral deviation of the medication dosage is determined as a medication behavior deviation coefficient.
In this embodiment, a specific calculation formula of the medication behavior deviation coefficient is given, and the medication behavior deviation coefficient may be expressed as:
wherein Q represents a deviation coefficient of medication behavior, F represents an influence coefficient of medication compliance behavior, R represents a medication compliance coefficient, e represents a natural constant, Indicating the overall deviation of the dosage.
Negative correlation normalization results of medication compliance coefficients are represented. When the medication compliance coefficient is smaller, the influence coefficient of medication compliance behavior is larger, and the overall deviation of medication dosage is also larger, the patient is indicated to have larger deviation of medication dosage in the current time period, so that the medication behavior deviation coefficient is larger.
Thus, the present embodiment acquires the medication behavior deviation coefficient of the patient.
And S4, adjusting the automatic reminding frequency of the medication by using the medication behavior deviation coefficient.
In conventional medication automatic reminder systems, automatic reminder of patient care medication is typically achieved by setting a fixed reminder frequency. However, due to the personalized living habits of the patient, the patient may have inconsistent medication time in the daily care process, and the traditional method cannot provide a personalized medication reminding strategy according to the personalized needs of the patient.
In this embodiment, a deviation coefficient of medication behavior is obtained in step S3, and the larger the deviation coefficient of medication behavior is, the more serious the patient has medication dosage deviation behavior in the nursing medication process, and when the automatic reminding logic of the system is optimized subsequently, stronger automatic reminding strength needs to be set for the patient, so as to ensure medication accuracy.
Specifically, an upward rounding result of the product between the medication behavior deviation coefficient and a preset reminding frequency is calculated, the upward rounding result is used as an adjusted medication automatic reminding frequency, the reminding frequency of the system is set to be the adjusted medication automatic reminding frequency, and the time system automatically reminds a patient of medication. It should be noted that the preset reminding frequency is set manually. The system monitors and determines the deviation coefficient of the medication behavior in real time according to the actual medication behavior of the patient. The frequency of the reminder is dynamically adjusted by tracking the patient's medication time, compliance and response to the reminder. For example, if the patient does not take the medication on time, the system will increase the frequency of alerts, whereas if the patient follows the medication plan, the system will decrease the frequency of alerts.
In addition, the system can customize personalized reminding contents according to the medication records and life habits of patients. The reminding is not only limited to the notification of the medication time, but also different reminding modes such as voice reminding, vibration reminding or short message reminding can be provided according to the preference of the patient, so that the reminding mode is ensured to be more in line with the requirements of the patient, and the medication compliance of the patient is improved.
According to the method, firstly, the difference between the medication time interval of medication in the current time period of a patient and the preset medication time interval and the disorder condition of the medication time of the patient are combined, medication compliance of the patient is evaluated, medication compliance coefficients are obtained, then medication behavior sensitivity coefficients are obtained according to the correlation condition between the medication time interval of medication of the patient and health indexes and the fluctuation condition of the medication time interval, the medication compliance of the patient and influence factors thereof can be comprehensively measured through the medication compliance coefficients and the medication behavior sensitivity coefficients, the influence coefficients of the medication compliance behaviors are determined, the dose deviation behaviors possibly occurring in the medication process of the patient are considered, the medication behavior deviation coefficients of the patient are evaluated according to the dose deviation behaviors, and then the medication automatic reminding frequency of the patient is determined, so that self-adaptive adjustment of reminding frequency is realized, and therefore personalized nursing reminding can accurately meet the actual demands of the patient, the medication compliance of the patient is improved, and a better management effect is achieved.
An embodiment of a nursing medication intelligent reminding system comprises:
As shown in fig. 2, the figure shows a block diagram of a nursing medication intelligent reminding system, which includes a data acquisition module, a first calculation module, a second calculation module and a frequency adjustment module.
The data acquisition module is used for acquiring the administration time of each administration, the proportion of the medicines and the health index of the patient in the current time period;
The first calculation module is used for obtaining a medication compliance coefficient by combining the difference between the medication time interval of medication in the current time period of a patient and the preset medication time interval and the disturbance condition of the medication time of the patient;
The second calculation module is used for determining an influence coefficient of medication compliance based on the medication compliance coefficient and the medication behavior sensitivity coefficient, and determining a medication behavior deviation coefficient according to the difference between the proportioning quantity of the medicines taken by the patient in the current time period and the preset proportioning quantity, the fluctuation condition of the proportioning quantity of each medicine, the medication compliance coefficient and the influence coefficient of the medication compliance behavior;
and the frequency adjustment module is used for adjusting the automatic reminding frequency of the medication by utilizing the medication behavior deviation coefficient.
It should be understood that the block diagram of a nursing medicative intelligent reminding system and its modules shown in fig. 2 can be implemented in various ways. For example, in some embodiments, the system and its modules may be implemented in hardware, software, or a combination of software and hardware. Where the hardware portions may be implemented using dedicated logic and the software portions may be stored in a memory for execution by a suitable instruction execution system, such as a microprocessor or dedicated design hardware. Those skilled in the art will appreciate that the methods and systems described above may be implemented using computer executable instructions and/or embodied in processor control code, such as provided on a carrier medium such as a magnetic disk, CD or DVD-ROM, a programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The system of the present specification and its modules may be implemented not only with hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, etc., or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., but also with software executed by various types of processors, for example, and with a combination of the above hardware circuits and software (e.g., firmware).
For further details on the above-mentioned respective modules, reference may be made to other locations in the present specification, and no further description is given here.
In other embodiments, a nursing medication intelligent reminding device is also provided and comprises a memory and a processor. The memory is used for storing executable program codes, and the processor is used for calling and running the executable program codes from the memory, so that the device executes the intelligent reminding method for nursing medicine. The device can be a chip, a component or a module, the chip can comprise a processor and a memory which are connected, wherein the memory is used for storing instructions, and when the processor calls and executes the instructions, the chip can be made to execute the intelligent reminding method for nursing medication provided by the embodiment.
In other embodiments, a computer program product is provided, which when run on a computer, causes the computer to perform the above-mentioned related steps to implement a nursing medication intelligent reminding method provided in the above-mentioned embodiments.
In other embodiments, a computer readable storage medium is provided, in which a computer program code is stored, which when run on a computer causes the computer to execute the above-mentioned related method steps to implement a nursing medication intelligent reminding method provided in the above-mentioned embodiments.
The system, the electronic device, the computer program product, and the computer readable storage medium are all configured to execute the corresponding methods provided above, so that the benefits achieved by the system, the electronic device, the computer program product, and the computer readable storage medium can refer to the benefits in the corresponding methods provided above, and are not described herein.
It should be noted that the above-mentioned embodiments are only preferred embodiments of the present invention, and are not intended to limit the present invention, and any modifications, equivalent substitutions, improvements, etc. within the principle of the present invention should be included in the protection scope of the present invention.
Claims (7)
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| CN108309791B (en) * | 2018-02-13 | 2021-01-08 | 南方医科大学南方医院 | Method for determining drug compliance through intelligent medicine box |
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| CN116543870B (en) * | 2023-07-06 | 2023-10-03 | 首都医科大学附属北京天坛医院 | Method, system, equipment and medium for analyzing drug compliance of hypertension patient |
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| CN119049642B (en) * | 2024-10-30 | 2025-01-24 | 长春中医药大学 | An intelligent auxiliary system and method for dermatological rehabilitation nursing |
| CN119314642A (en) * | 2024-11-29 | 2025-01-14 | 新能康技术有限公司 | An information management system and method for chronic disease patients based on intelligent AI |
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