An intelligent reminder method for nursing medications

Abstract

The present invention relates to the technical field of medication reminder, and particularly relates to an intelligent reminder method for nursing medication. The method includes: obtaining a medication compliance coefficient by combining the difference between the medication time interval of the patient within the current time period and the preset medication time interval and the disorder condition of the patient's medication time; obtaining a medication behavior sensitivity coefficient according to the correlation between the medication time interval of the patient's medication and the health indicators and the fluctuation condition of the medication time interval, and further determining the influence coefficient of the medication compliance behavior. According to the difference between the proportion amount of the medication taken by the patient within the current time period and the preset proportion amount, the fluctuation condition of the proportion amount of each medication, the medication compliance coefficient and the influence coefficient of the medication compliance behavior, a medication behavior deviation coefficient is determined, and then the automatic medication reminder frequency is adjusted. The present invention realizes the adaptive adjustment of the medication reminder frequency for patients.

Description

Technical Field

[0001] The present invention relates to the technical field of medication reminder, and particularly to an intelligent reminder method for nursing medication. Background Art

[0002] With the aging of the population and the increase in chronic diseases, the importance of drug treatment in nursing is increasing continuously. However, problems of drug compliance (such as forgetting to take medicine, taking the wrong medicine, etc.) are particularly prominent among the elderly and patients with chronic diseases, affecting the treatment effect and increasing health risks. The intelligent label for nursing medicine bottles and the medication management system can use the Internet of Things (IoT), wireless communication technology, and data storage and analysis technology to provide accurate medication management and reminder services for patients or the elderly, reducing risks.

[0003] Existing intelligent labels for nursing medicine bottles and medication management systems rely on preset drug information (such as drug name, dosage, and usage time) to achieve automatic reminders. However, in practice, there are certain differences in the health status, medication needs, and living habits of each patient. The existing systems fail to fully consider these individualized factors. Therefore, simply relying on preset drug information cannot provide personalized medication reminder strategies, affecting the management effect. Summary of the Invention

[0004] In order to solve the problem that the existing system cannot provide personalized medication reminder strategies according to the individualized needs of patients, the purpose of the present invention is to provide an intelligent reminder method for nursing medication, and the specific technical solutions adopted are as follows:

[0005] The present invention provides an intelligent reminder method for nursing medication, which includes the following steps:

[0006] Obtain the medication time, the proportion of the drug, and the health indicators for each medication of the patient in the current time period;

[0007] Combining the difference between the medication time interval of the patient's medication in the current time period and the preset medication time interval and the disorder of the patient's medication time, obtain the medication compliance coefficient; according to the correlation between the medication time interval of the patient's medication and the health indicators, as well as the fluctuation of the medication time interval, obtain the medication behavior sensitivity coefficient;

[0008] Based on the medication compliance coefficient and the medication behavior sensitivity coefficient, determine the influence coefficient of the medication compliance behavior; according to the difference between the proportion of the drug taken by the patient in the current time period and the preset proportion, the fluctuation of the proportion of each drug, the medication compliance coefficient, and the influence coefficient of the medication compliance behavior, determine the medication behavior deviation coefficient;

[0009] Use the medication behavior deviation coefficient to adjust the automatic medication reminder frequency.

[0010] Preferably, obtaining a medication compliance coefficient by combining the difference between the medication time intervals of the patient's medications during the current time period and the preset medication time intervals and the disorder condition of the patient's medication time includes:

[0011] Calculating a medication time disorder coefficient according to the distribution of the medication times of the patient's medications during the current time period;

[0012] Calculating a first average value of the medication time intervals between all adjacent two medications of the patient each day during the current time period; combining the difference between the first average value corresponding to each day during the current time period and the preset medication time interval and the medication time disorder coefficient to obtain a medication compliance coefficient, and both the difference between the first average value and the preset medication time interval and the medication time disorder coefficient are negatively correlated with the medication compliance coefficient.

[0013] Preferably, calculating the medication time disorder coefficient according to the distribution of the medication times of the patient's medications during the current time period includes:

[0014] For any day during the current time period, the medication times of all the patient's medications on that day form a medication time stamp sequence for that day;

[0015] All the elements at the same position in all the medication time stamp sequences during the current time period form a subsequence; calculating the variance of all the elements in each subsequence as the first variance corresponding to each subsequence;

[0016] Determining the average value of the first variances of all the subsequences as the medication time disorder coefficient.

[0017] Preferably, obtaining a medication behavior sensitivity coefficient according to the correlation between the medication time intervals of the patient's medications and the health indicators and the fluctuation condition of the medication time intervals includes:

[0018] The medication time intervals between all adjacent two medications during the current time period form a time interval sequence; the health indicators between all adjacent two medications during the current time period form a health indicator sequence;

[0019] Calculating the Spearman correlation coefficient between the time interval sequence and the health indicator sequence; calculating the second variance of all the elements in the time interval sequence;

[0020] Obtaining a medication behavior sensitivity coefficient according to the Spearman correlation coefficient and the second variance, the Spearman correlation coefficient is positively correlated with the medication behavior sensitivity coefficient, and the second variance is negatively correlated with the medication behavior sensitivity coefficient.

[0021] Preferably, obtaining the medication behavior sensitivity coefficient according to the Spearman correlation coefficient and the second variance includes:

[0022] Calculate the first sum of the second variance and a preset adjustment parameter, and determine the ratio between the Spearman correlation coefficient and the first sum as the drug-taking behavior sensitivity coefficient, where the preset adjustment parameter is a value greater than 0.

[0023] Preferably, determining the influence coefficient of drug-taking compliance behavior based on the drug-taking compliance coefficient and the drug-taking behavior sensitivity coefficient includes:

[0024] Calculate the second sum of the drug-taking behavior sensitivity coefficient and a preset adjustment parameter; determine the ratio between the drug-taking compliance coefficient and the second sum as the influence coefficient of drug-taking compliance behavior.

[0025] Preferably, determining the drug-taking behavior deviation coefficient according to the difference between the dosage ratio of the drugs taken by the patient in the current time period and the preset dosage ratio, the fluctuation of the dosage ratio of each drug, the drug-taking compliance coefficient, and the influence coefficient of drug-taking compliance behavior includes:

[0026] Denote the standard deviation of the dosage ratio of each drug taken by the patient in the current time period as the fluctuation degree of the dosage ratio of each drug;

[0027] According to the difference between the dosage ratio of each drug taken by the patient in the current time period and the preset dosage ratio and the corresponding fluctuation degree of the dosage ratio, obtain the drug dosage deviation coefficient of each drug, and both the difference between the dosage ratio of each drug and the preset dosage ratio and the fluctuation degree of the dosage ratio are positively correlated with the drug dosage deviation coefficient;

[0028] Evaluate the overall deviation of drug dosage based on the drug dosage deviation coefficients of all drugs;

[0029] Obtain the drug-taking behavior deviation coefficient by comprehensively considering the drug-taking compliance coefficient, the influence coefficient of drug-taking compliance behavior, and the overall deviation of drug dosage.

[0030] Preferably, evaluating the overall deviation of drug dosage based on the drug dosage deviation coefficients of all drugs includes: taking the average value of the drug dosage deviation coefficients of all drugs as the overall deviation of drug dosage.

[0031] Preferably, obtaining the drug-taking behavior deviation coefficient by comprehensively considering the drug-taking compliance coefficient, the influence coefficient of drug-taking compliance behavior, and the overall deviation of drug dosage includes:

[0032] Determine the product of the negative correlation normalization result of the drug-taking compliance coefficient, the influence coefficient of drug-taking compliance behavior, and the overall deviation of drug dosage as the drug-taking behavior deviation coefficient.

[0033] Preferably, adjusting the automatic medication reminder frequency using the medication behavior deviation coefficient includes:

[0034] Calculating the ceiling result of the product between the medication behavior deviation coefficient and the preset reminder frequency, and taking the ceiling result as the adjusted automatic medication reminder frequency.

[0035] The present invention has at least the following beneficial effects:

[0036] The present invention first evaluates the medication compliance of a patient by combining the difference between the medication time interval of the patient within the current time period and the preset medication time interval and the disorder of the patient's medication time, and obtains a medication compliance coefficient. Then, according to the correlation between the medication time interval of the patient's medication and the health indicators and the fluctuation of the medication time interval, a medication behavior sensitivity coefficient is obtained. The medication compliance of the patient and its influencing factors can be comprehensively measured through the medication compliance coefficient and the medication behavior sensitivity coefficient, and the influence coefficient of the medication compliance behavior is determined. The possible dose deviation behavior during the patient's medication process is also considered, and the medication behavior deviation coefficient of the patient is evaluated accordingly, and then the automatic medication reminder frequency of the patient is determined to achieve an adaptive adjustment of the reminder frequency, so as to ensure that the personalized nursing reminder can accurately meet the actual needs of the patient, improve their medication compliance, and achieve a better management effect. BRIEF DESCRIPTION OF THE DRAWINGS

[0037] In order to more clearly illustrate the technical solutions and advantages in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings required for the description of the embodiments or the prior art. Obviously, the drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, other drawings can be obtained based on these drawings without creative efforts.

[0038] Figure 1 It is a flowchart of a nursing medication intelligent reminder method provided by an embodiment of the present invention;

[0039] Figure 2 It is a structural block diagram of a nursing medication intelligent reminder system provided by an embodiment of the present invention. DETAILED DESCRIPTION OF THE EMBODIMENTS

[0040] In order to further elaborate on the technical means and effects adopted by the present invention to achieve the predetermined invention purpose, the following will describe in detail a nursing medication intelligent reminder method proposed according to the present invention in combination with the accompanying drawings and preferred embodiments.

[0041] Unless otherwise defined, all technical and scientific terms used herein have the same meaning as commonly understood by those skilled in the technical field to which the present invention belongs.

[0042] The following specifically describes the specific solution of an intelligent reminder method for nursing medications provided by the present invention in conjunction with the accompanying drawings.

[0043] An embodiment of an intelligent reminder method for nursing medications:

[0044] The specific scenario targeted by this embodiment is as follows: During the process of reminding patients to take medications, analyze the historical medication time data of the patients, combine their personalized living habits, evaluate the patients' medication compliance, combine the correlation between the patients' health indicators and medication data, determine the medication behavior sensitivity coefficient of the patients, and then determine the influence coefficient of the medication compliance behavior. Also, combine the difference between the dosage ratio of the medications taken in the patients' historical data and the preset dosage ratio, as well as the fluctuation of the dosage ratio of each medication, to adaptively adjust the medication reminder frequency for the patients.

[0045] This embodiment proposes an intelligent reminder method for nursing medications, as Figure 1 shown, an intelligent reminder method for nursing medications in this embodiment includes the following steps:

[0046] Step S1, obtain the medication time, dosage ratio of the medication, and health indicators for each medication taken by the patient within the current time period.

[0047] The existing intelligent label system for nursing medication bottles mainly includes an intelligent label module, a health record platform, a central processing unit, and a cloud platform and remote monitoring module. The intelligent label in this system is a small electronic device that can be attached to the outside of the medicine bottle. The built-in chip is used to store public-known data related to the medicine, such as the preset dosage ratio, scheduled taking time, etc. The system uses radio frequency identification (RFID) technology to display medication-related information through different color areas or patterns, including taking time, dosage, medicine type, and whether it needs to be taken with meals, etc. The intelligent label module is also equipped with a built-in clock and an infrared sensor, which are used to automatically record the opening and closing status of the medicine bottle cap and the time of each opening and closing. The health record platform monitors the physiological indicators of the patients through devices such as infrared thermometers and smart bracelets, and inputs these data into a trained convolutional neural network model for analysis to generate a score from 0 to 10, which reflects the health status of the patients. In this embodiment, this score is used as the health indicator of the patients. The system monitors the dosage ratio of each medicine by installing an integrated sensor on the inner wall of the nursing medication bottle. The system uploads the collected medication time, dosage ratio of the medication, and the health indicators of the patients to the cloud for storage in real time to ensure the timely update and backup of the data. In addition, the system also supports storing the data in a local device for the user to view the historical medication records at any time. It should be noted that in this embodiment, the time when the medicine bottle cap is opened each time the patient takes the medicine is used as the medication time for each time of the patient.

[0048] In this embodiment, a smart label system for nursing medicine bottles is used to collect the medication time for each medication of a patient within the current time period, the proportion of each drug for each medication, and the health indicators of the patient between every two adjacent medications; wherein, the current time period is a set composed of all historical moments whose time interval from the current moment is less than or equal to a preset duration. In this embodiment, the preset duration is 14 days, and in specific applications, the implementer can set it according to specific circumstances.

[0049] So far, this embodiment has collected the medication time for each medication of the patient within the current time period, the proportion of each drug taken each time, and the health indicators between two adjacent medications. It should be noted that: this embodiment is described with one patient as an example, and the method provided in this embodiment can be used to process other patients.

[0050] Step S2: Combine the difference between the medication time interval of the patient within the current time period and the preset medication time interval, and the disorder situation of the patient's medication time to obtain a medication compliance coefficient; according to the correlation between the medication time interval of the patient's medication and the health indicators, as well as the fluctuation situation of the medication time interval, obtain a medication behavior sensitivity coefficient.

[0051] The taking time of drugs is usually fixed, such as before meals, after meals, or before bedtime. However, due to the different living habits of some patients and irregular meal times, it is difficult to take medicine on time, which affects medication compliance. This makes the reminder of the smart label unable to match the actual meal time, reducing the reminder effect.

[0052] Taking 24 hours a day as a time unit for analysis, specifically, for any day within the current time period, in chronological order, the medication times of all medications of the patient on that day form the medication time stamp sequence of that day; using this method, the medication time stamp sequences of each day within the current time period can be obtained, that is, multiple medication time stamp sequences corresponding to the current time period are obtained. All elements at the same position in all the medication time stamp sequences within the current time period form a subsequence, that is, the first element in all the medication time stamp sequences forms the first subsequence, the second element in all the medication time stamp sequences forms the second subsequence, the third element in all the medication time stamp sequences forms the third subsequence, and so on, obtaining multiple subsequences. Calculate the variance of all elements in each subsequence respectively as the first variance corresponding to each subsequence. The first variance is used to reflect the fluctuation of the elements in the subsequence. The larger the variance, the greater the degree of fluctuation of the elements in the corresponding subsequence. Determine the average value of the first variances of all subsequences as the medication time disorder coefficient.

[0053] According to the medication time of each two adjacent medications of the patient in the current time period, the average of the medication time intervals of all two adjacent medications of the patient in the current time period is calculated, and the average is recorded as the first average; there is a corresponding first average for each day in the current time period. The medication compliance coefficient is obtained by combining the difference between the first average and the preset medication time interval corresponding to each day in the current time period and the medication time disorder coefficient, and the difference between the first average and the preset medication time interval and the medication time disorder coefficient are both negatively correlated with the medication compliance coefficient.

[0054] Among them, the negative correlation relationship means that the dependent variable will decrease as the independent variable increases, and the dependent variable will increase as the independent variable decreases. It can be a subtraction relationship, a division relationship, etc., which is determined by practical applications.

[0055] In this embodiment, a specific calculation formula for the medication compliance coefficient is given, and the medication compliance coefficient can be expressed as:

[0056]

[0057] in, represents the medication compliance coefficient, S represents the medication time disorder coefficient, and N represents the number of days in the current time period. Indicates the preset medication time interval. represents the average of the time intervals between two consecutive medications taken on the nth day of the patient's current time period, that is, the first average corresponding to the nth day of the patient's current time period; exp() represents an exponential function with a natural constant as the base, Indicates the absolute value sign.

[0058] It represents the difference between the first average value corresponding to the nth day and the preset medication time interval. The larger the absolute value, the greater the difference between the two. It should be noted that the preset medication time interval is set by the doctor according to the patient's condition and the type of medication taken.

[0059] When the medication time disorder coefficient is smaller and the difference between the first average value corresponding to each day and the preset medication time interval is smaller, it means that the patient takes the medicine according to the predetermined process and has a stronger medication compliance, that is, the larger the medication compliance coefficient is.

[0060] During the actual medication process, different drugs have different pharmacological properties, such as differences in half-life and absorption rate. Some drugs need to be taken strictly at fixed times to ensure efficacy and safety, while others have more flexible requirements for the time of administration. For example, aspirin and antihypertensive drugs (such as enalapril) need to be taken on time to maintain a stable blood drug concentration, while antacid drugs (such as aluminum hydroxide) and some vitamin supplements (such as vitamin C) can be taken before or after meals with less impact on the effect.

[0061] Based on the above characteristics, first, calculate the time intervals between every two adjacent drug administrations within the current time period. The time intervals between all adjacent drug administrations within the current time period form a time interval sequence, and the health indicators between all adjacent drug administrations within the current time period form a health indicator sequence. It should be noted that both the time interval sequence and the health indicator sequence are arranged in chronological order. Calculate the Spearman correlation coefficient between the time interval sequence and the health indicator sequence. The calculation method of the Spearman correlation coefficient is prior art and will not be elaborated here. According to all the elements in the time interval sequence, calculate the variance of all the elements in the time interval sequence, and denote this variance as the second variance. Based on the Spearman correlation coefficient and the second variance, obtain the medication behavior sensitivity coefficient. The Spearman correlation coefficient has a positive correlation with the medication behavior sensitivity coefficient, and the second variance has a negative correlation with the medication behavior sensitivity coefficient.

[0062] Among them, the positive correlation means that the dependent variable increases as the independent variable increases and decreases as the independent variable decreases. It can be an additive relationship, a multiplicative relationship, etc., which is determined by the actual application. The negative correlation means that the dependent variable decreases as the independent variable increases and increases as the independent variable decreases. It can be a subtractive relationship, a divisive relationship, etc., which is determined by the actual application.

[0063] In this embodiment, calculate the first sum value of the second variance and the preset adjustment parameter, and determine the ratio between the Spearman correlation coefficient and the first sum value as the medication behavior sensitivity coefficient. The preset adjustment parameter is a value greater than 0. The medication behavior sensitivity coefficient can be expressed as:

[0064]

[0065] Among them, E represents the medication behavior sensitivity coefficient, U represents the time interval sequence, P represents the health indicator sequence, represents the Spearman correlation coefficient between the time interval sequence and the health indicator sequence, represents the variance of all the elements in the time interval sequence, that is, the second variance, represents the preset adjustment parameter, represents the first sum value.

[0066] In the calculation formula of the drug use behavior sensitivity coefficient, a preset adjustment parameter is introduced to prevent the denominator from being zero. In this embodiment, the preset adjustment parameter is 0.01. In specific applications, the implementer can set it according to specific circumstances. The larger the Spearman correlation coefficient between the time interval sequence and the health index sequence, the stronger the correlation between these two sequences, which means that the change of the health index is closely related to the drug use time interval, indicating that the patient's response to the drug is highly dependent on the medication time and frequency, and the drug use behavior sensitivity coefficient of the drug is larger. The variance of all elements in the time interval sequence is used to reflect the fluctuation of the element values in the time interval sequence. The larger the variance, the more discrete the element values, and the smaller the fluctuation of the drug use time interval. If the fluctuation of the drug use time interval of the patient is small in the current time period, and even a small change in the time interval can significantly affect the patient's health index in this time period, this indicates that the patient's health status is highly dependent on the drug use time interval and frequency. Therefore, the drug use behavior sensitivity coefficient of this drug is larger. When the Spearman correlation coefficient between the time interval sequence and the health index sequence is larger and the second variance is smaller, the drug use behavior sensitivity coefficient is larger.

[0067] Step S3, determining the influence coefficient of the medication compliance behavior based on the medication compliance coefficient and the medication behavior sensitivity coefficient; determining the medication behavior deviation coefficient according to the difference between the dosage ratio of the drugs taken by the patient in the current time period and the preset dosage ratio, the fluctuation of the dosage ratio of each drug, the medication compliance coefficient, and the influence coefficient of the medication compliance behavior.

[0068] When the patient uses a drug with a large drug use behavior sensitivity coefficient, it will exacerbate the impact on the patient's daily medication compliance. Therefore, in this embodiment, the influence coefficient of the medication compliance behavior will be determined by combining the medication compliance coefficient and the medication behavior sensitivity coefficient.

[0069] Specifically, calculate the second sum value of the drug use behavior sensitivity coefficient and the preset adjustment parameter; determine the ratio between the medication compliance coefficient and the second sum value as the influence coefficient of the medication compliance behavior.

[0070] In this embodiment, a specific calculation formula for the influence coefficient of the medication compliance behavior is given. The influence coefficient of the medication compliance behavior can be expressed as:

[0071]

[0072] where F is the influence coefficient of the medication compliance behavior, R represents the medication compliance coefficient, E represents the medication behavior sensitivity coefficient, represents the preset adjustment parameter, represents the second sum value.

[0073] In the formula for calculating the influence coefficient of medication compliance behavior in this embodiment, a preset adjustment parameter is introduced to prevent the denominator from being zero. When the medication compliance coefficient is larger and the medication behavior sensitivity coefficient is smaller, the influence coefficient of medication compliance behavior is larger.

[0074] The impact of drugs on a patient's health is closely related to the patient's medication behavior. If the patient's health status is very sensitive to the timing and frequency of medication, then even minor fluctuations in compliance may have a significant impact on the efficacy.

[0075] Based on this, in subsequent analyses, for patients with a relatively high medication behavior sensitivity coefficient, even though their medication compliance is good, a relatively high system reminder intensity still needs to be set to ensure that the effect of the drug is not negatively affected by compliance fluctuations.

[0076] During the nursing process, patients usually need to use multiple medications for combination therapy, and the differences in the dosages and ratios of different medications can significantly affect the final efficacy. There are strict requirements for the dosage ratios between some medications. If the patient uses them improperly, the wrong dosage may seriously affect the effect of the drug.

[0077] According to the ratio amounts of each drug taken by the patient each time within the current time period, calculate the standard deviation of the ratio amounts of each drug taken by the patient within the current time period. Denote the standard deviation of the ratio amounts of each drug taken by the patient within the current time period as the degree of ratio amount fluctuation of each drug. The larger this value is, the greater the fluctuation of the actual ratio amount of the drug each time during the patient's historical medication process, and there may be inconsistencies in the ratio amounts, resulting in the patient having difficulty accurately determining the medication ratio each time. By using this method, the degree of ratio amount fluctuation of each drug can be obtained, and one drug flavor corresponds to one degree of ratio amount fluctuation. Therefore, according to the difference between the ratio amount of each drug taken by the patient within the current time period and the preset ratio amount and the corresponding degree of ratio amount fluctuation, the medication dosage deviation coefficient of each drug is obtained. The difference between the ratio amount of each drug and the preset ratio amount and the degree of ratio amount fluctuation are both positively correlated with the medication dosage deviation coefficient.

[0078] Among them, the positive correlation means that the dependent variable will increase as the independent variable increases, and the dependent variable will decrease as the independent variable decreases. It can be an additive relationship, a multiplicative relationship, etc., which is determined by the actual application.

[0079] In this embodiment, a specific formula for calculating the medication dosage deviation coefficient is given. The medication dosage deviation coefficient of the i-th drug can be expressed as:

[0080]

[0081] Among them, represents the medication dosage deviation coefficient of the i-th drug, The standard deviation of the ratio of the \(i\)-th drug taken by the patient during the current time period The ratio of the \(i\)-th drug when the \(u\)-th dose of the drug is taken during the current time period The preset ratio of the \(i\)-th drug, and \(U\) represents the number of times the drug is taken during the current time period Represents the absolute value symbol

[0082] Used to characterize the difference between the ratio of the \(i\)-th drug when the \(u\)-th dose of the drug is taken by the patient during the current time period and the preset ratio. The larger the absolute value, the greater the difference between the two Used to reflect the overall difference between the ratio of the \(i\)-th drug taken by the patient during the current time period and the preset ratio. The larger this value, the greater the overall difference. In this embodiment, the fluctuation degree of the drug ratio and the average value of the deviation between each actual drug dosage and the preset ratio are combined to form a comprehensive index to reflect the volatility and deviation of the drug ratio. This comprehensive measure helps to reveal whether there are significant ratio errors and instabilities in the actual drug use process of the patient. When the standard deviation of the ratio of the \(i\)-th drug taken by the patient during the current time period is larger and the overall difference between the ratio of the \(i\)-th drug taken during the current time period and the preset ratio is also larger, it indicates that the dosage deviation of the \(i\)-th drug taken by the patient during the current time period is larger, that is, the drug dosage deviation coefficient of the \(i\)-th drug is larger

[0083] By using the above method, the drug dosage deviation coefficient of each drug can be obtained, and the average value of the drug dosage deviation coefficients of all drugs is used as the overall drug dosage deviation. It should be noted that: the preset ratio of each drug is set by the doctor according to the patient's condition

[0084] When the drug-taking process is strictly fixed during the daily care drug use of the patient, the greater the impact of medication compliance on the treatment effect, then the low compliance of the patient at the current stage may significantly affect the final nursing treatment effect; at the same time, considering that when the drug dosage deviation coefficient of the patient during each drug-taking process is relatively large, it may further exacerbate the drug-taking behavior deviation of the patient at the current stage, thereby affecting the accuracy and efficacy of the treatment effect

[0085] Based on the above analysis, the product of the negative correlation normalization result of the medication compliance coefficient, the influence coefficient of the medication compliance behavior, and the overall drug dosage deviation is determined as the drug-taking behavior deviation coefficient

[0086] In this embodiment, a specific calculation formula for the drug-taking behavior deviation coefficient is given. The drug-taking behavior deviation coefficient can be expressed as

[0087]

[0088] Among them, Q represents the medication behavior deviation coefficient, F represents the influence coefficient of medication compliance behavior, R represents the medication compliance coefficient, and e represents the natural constant. Indicates overall deviation in medication dosage.

[0089] It indicates the negative correlation normalization result of the medication compliance coefficient. When the medication compliance coefficient is smaller, the influence coefficient of medication compliance behavior is larger, and the overall deviation of medication dosage is larger, it means that the patient has a large deviation in medication dosage in the current time period, so the medication behavior deviation coefficient is larger.

[0090] So far, this embodiment has obtained the patient's medication behavior deviation coefficient.

[0091] Step S4, using the medication behavior deviation coefficient to adjust the frequency of automatic medication reminders.

[0092] In traditional automatic medication reminder systems, patients are usually reminded of their medication care by setting a fixed reminder frequency. However, due to the personalized living habits of patients, there may be inconsistencies in the medication time during daily care. Traditional methods cannot provide personalized medication reminder strategies based on the individual needs of patients.

[0093] In step S3 of this embodiment, the medication behavior deviation coefficient is obtained. The larger the medication behavior deviation coefficient is, the more serious the medication dosage deviation behavior of the patient in the nursing medication process is. When optimizing the automatic reminder logic of the system in the future, it is necessary to set a stronger automatic reminder intensity for the patient to ensure the accuracy of medication.

[0094] Specifically, the rounded-up result of the product of the medication behavior deviation coefficient and the preset reminder frequency is calculated, and the rounded-up result is used as the adjusted automatic medication reminder frequency, and the system reminder frequency is set to the adjusted automatic medication reminder frequency. When the time comes, the system will automatically remind the patient to take the medication. It should be noted that the preset reminder frequency is set manually. The system will monitor and determine the medication behavior deviation coefficient in real time based on the patient's actual medication behavior. The frequency of reminders is dynamically adjusted by tracking the patient's medication time, compliance behavior, and response to reminders. For example, if the patient does not take the medication on time, the system will increase the reminder frequency; conversely, if the patient follows the medication plan, the system will reduce the reminder frequency.

[0095] In addition, the system will also customize personalized reminder content based on the patient's medication records and living habits. These reminders are not limited to notifying the medication time, but can also provide different reminder methods according to the patient's preferences, such as voice reminders, vibration reminders, or text message reminders, etc., to ensure that the reminder method better meets the patient's needs and improves their medication compliance.

[0096] In this embodiment, first, the difference between the medication time interval of the patient's current period of medication and the preset medication time interval and the disorder of the patient's medication time are combined to evaluate the patient's medication compliance, and a medication compliance coefficient is obtained. Then, based on the correlation between the medication time interval of the patient's medication and the health indicators and the fluctuation of the medication time interval, a medication behavior sensitivity coefficient is obtained. The medication compliance coefficient and the medication behavior sensitivity coefficient can comprehensively measure the patient's medication compliance and its influencing factors, and the influencing coefficient of the medication compliance behavior is determined. The possible dose deviation behavior of the patient during the medication process is also considered, and based on this, the patient's medication behavior deviation coefficient is evaluated. Furthermore, the automatic reminder frequency of the patient's medication is determined to achieve an adaptive adjustment of the reminder frequency, so as to ensure that the personalized nursing reminder can accurately meet the actual needs of the patient, improve their medication compliance, and achieve a better management effect.

[0097] An embodiment of a smart reminder system for nursing medication:

[0098] As Figure 2 shown, the figure shows a structural block diagram of a smart reminder system for nursing medication. The system includes a data acquisition module, a first calculation module, a second calculation module, and a frequency adjustment module.

[0099] Among them, the data acquisition module is used to obtain the medication time, the proportion of the drug, and the health indicators of each medication of the patient in the current period.

[0100] The first calculation module is used to obtain the medication compliance coefficient by combining the difference between the medication time interval of the patient's current period of medication and the preset medication time interval and the disorder of the patient's medication time; and obtain the medication behavior sensitivity coefficient based on the correlation between the medication time interval of the patient's medication and the health indicators and the fluctuation of the medication time interval.

[0101] The second calculation module is used to determine the influencing coefficient of the medication compliance behavior based on the medication compliance coefficient and the medication behavior sensitivity coefficient; and determine the medication behavior deviation coefficient according to the difference between the proportion of the drug taken by the patient in the current period and the preset proportion, the fluctuation of the proportion of each drug, the medication compliance coefficient, and the influencing coefficient of the medication compliance behavior.

[0102] The frequency adjustment module is used to adjust the automatic reminder frequency of the medication by using the medication behavior deviation coefficient.

[0103] It should be understood that Figure 2 The structural block diagram and modules of the intelligent reminder system for nursing medications shown can be implemented in various ways. For example, in some embodiments, the system and its modules can be implemented through hardware, software, or a combination of software and hardware. Among them, the hardware part can be implemented using dedicated logic; the software part can be stored in a memory and executed by an appropriate instruction execution system, such as a microprocessor or dedicated designed hardware. Those skilled in the art can understand that the above methods and systems can be implemented using computer-executable instructions and / or included in processor control code. For example, such code is provided on a carrier medium such as a disk, CD, or DVD-ROM, a programmable memory such as a read-only memory (firmware), or a data carrier such as an optical or electronic signal carrier. The systems and modules of this specification can be implemented not only by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips and transistors, or programmable hardware devices such as field programmable gate arrays and programmable logic devices, but also by software executed by various types of processors, or by a combination of the above hardware circuits and software (e.g., firmware).

[0104] For more details about each of the above modules, reference can be made to other parts of this specification and will not be elaborated here.

[0105] In other embodiments, an intelligent reminder device for nursing medications is also provided, including a memory and a processor. The memory is used to store executable program code, and the processor is used to call and run the executable program code from the memory, so that the device executes the above intelligent reminder method for nursing medications. The device can specifically be a chip, component, or module. The chip can include a processor and a memory connected thereto; among them, the memory is used to store instructions, and when the processor calls and executes the instructions, the chip can execute the intelligent reminder method for nursing medications provided in the above embodiments.

[0106] In other embodiments, a computer program product is also provided. When the computer program product runs on a computer, it causes the computer to execute the above relevant steps to implement the intelligent reminder method for nursing medications provided in the above embodiments.

[0107] In other embodiments, a computer-readable storage medium is also provided. The computer-readable storage medium stores computer program code. When the computer program code runs on a computer, it causes the computer to execute the above relevant method steps to implement the intelligent reminder method for nursing medications provided in the above embodiments.

[0108] Among them, the provided system, electronic device, computer program product, and computer-readable storage medium are all used to execute the corresponding method provided above. Therefore, the beneficial effects that can be achieved can refer to the beneficial effects in the corresponding method provided above, and will not be elaborated here.

[0109] It should be noted that the above are only the preferred embodiments of the present invention and are not intended to limit the present invention. Any modifications, equivalent replacements, improvements, etc. made within the principles of the present invention shall be included within the protection scope of the present invention.

Claims

1. A nursing medication intelligent reminder method, characterized in that: The method comprises the following steps: Obtain the medication time, medication ratio and health indicators of each medication taken by the patient in the current time period; The medication compliance coefficient is obtained by combining the difference between the medication time interval of the patient in the current time period and the preset medication time interval and the disorder of the patient's medication time; the medication behavior sensitivity coefficient is obtained according to the correlation between the medication time interval of the patient and the health index, as well as the fluctuation of the medication time interval; Determine the influence coefficient of medication compliance behavior based on the medication compliance coefficient and the medication behavior sensitivity coefficient; determine the medication behavior deviation coefficient according to the difference between the proportion of the medicine taken by the patient in the current time period and the preset proportion, the fluctuation of the proportion of each medicine, the medication compliance coefficient and the influence coefficient of medication compliance behavior; Using the medication behavior deviation coefficient to adjust the frequency of automatic medication reminders; The medication compliance coefficient is obtained by combining the difference between the medication time interval of the patient's medication in the current time period and the preset medication time interval and the disorder of the patient's medication time, including: According to the distribution of medication time of the patient in the current time period, the medication time disorder coefficient is calculated; Calculate the first average value of the medication time intervals between all two adjacent medications taken by the patient every day in the current time period; combine 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 both negatively correlated with the medication compliance coefficient; The medication behavior sensitivity coefficient is obtained based on the correlation between the medication time interval of the patient and the health index, as well as the fluctuation of the medication time interval, including: The time intervals between all two consecutive medications in the current time period constitute a time interval sequence; the health indicators between all two consecutive medications in the current time period constitute a health indicator sequence; Calculating the Spearman correlation coefficient between the time interval sequence and the health indicator sequence; calculating the second variance of all elements in the time interval sequence; According to the Spearman correlation coefficient and the second variance, a medication behavior sensitivity coefficient is obtained, wherein the Spearman correlation coefficient is positively correlated with the medication behavior sensitivity coefficient, and the second variance is negatively correlated with the medication behavior sensitivity coefficient; The calculation of the medication time disorder coefficient includes: For any day in the current time period, the medication times of all medications taken by the patient on that day constitute the medication timestamp sequence of that day; All elements at the same position in all medication timestamp sequences in the current time period constitute a subsequence; the variance of all elements in each subsequence is calculated as the first variance corresponding to each subsequence; The average value of the first variance of all subsequences is determined as the medication time disorder coefficient.

2. According to claim 1, a nursing medication intelligent reminder method is characterized in that: The method of obtaining a medication behavior sensitivity coefficient based on the Spearman correlation coefficient and the second variance includes: The first sum of the second variance and a preset adjustment parameter is calculated, and the ratio between the Spearman correlation coefficient and the first sum is determined as a medication behavior sensitivity coefficient, wherein the preset adjustment parameter is a value greater than 0.

3. According to claim 1, a nursing medication intelligent reminder method is characterized in that: The determining the influence coefficient of medication compliance behavior based on the medication compliance coefficient and the medication behavior sensitivity coefficient includes: Calculate the second sum of the medication behavior sensitivity coefficient and the preset adjustment parameter; and determine the ratio between the medication compliance coefficient and the second sum as the influence coefficient of the medication compliance behavior.

4. The method for intelligently reminding nursing medication according to claim 1, characterized in that: Determining the medication behavior deviation coefficient based on the difference between the ratio of the medication taken by the patient in the current time period and the preset ratio, the fluctuation of the ratio of each medication, the medication compliance coefficient and the influence coefficient of medication compliance behavior includes: The standard deviation of the proportion of each drug taken by the patient in the current time period is recorded as the fluctuation degree of the proportion of each drug; According to the difference between the ratio of each drug taken by the patient in the current time period and the preset ratio and the corresponding fluctuation degree of the ratio, the dosage deviation coefficient of each drug is obtained, and the difference between the ratio of each drug and the preset ratio and the fluctuation degree of the ratio are both positively correlated with the dosage deviation coefficient; Based on the dosage deviation coefficient of all drugs, the overall deviation of the dosage is evaluated; The medication compliance coefficient, the influence coefficient of the medication compliance behavior and the overall deviation of the medication dosage are comprehensively considered to obtain the medication behavior deviation coefficient.

5. The method for intelligently reminding nursing medication according to claim 4, characterized in that: The evaluating the overall deviation of the dosage based on the dosage deviation coefficient of all drugs includes: taking the average value of the dosage deviation coefficients of all drugs as the overall deviation of the dosage.

6. The method for intelligently reminding nursing medication according to claim 4, characterized in that: The comprehensive medication compliance coefficient, the influence coefficient of the medication compliance behavior and the overall deviation of the medication dosage are used to obtain the medication behavior deviation coefficient, including: The product of the negative correlation normalized result of the medication compliance coefficient, the influence coefficient of the medication compliance behavior and the overall deviation of the medication dosage is determined as the medication behavior deviation coefficient.

7. The method for intelligently reminding nursing medication according to claim 1, characterized in that: The method of adjusting the automatic medication reminder frequency by using the medication behavior deviation coefficient includes: The rounded-up result of the product of the medication behavior deviation coefficient and the preset reminder frequency is calculated, and the rounded-up result is used as the adjusted medication automatic reminder frequency.

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