Patient rehabilitation monitoring method and system based on nursing data

Abstract

The invention discloses a patient rehabilitation monitoring method and system based on nursing data, and particularly relates to the technical field of rehabilitation monitoring. Core rehabilitation indexes are extracted by acquiring and classifying nursing data of a patient; analyzing the nursing data, identifying the current rehabilitation stage of the patient and evaluating the matching degree of the rehabilitation target and the core rehabilitation index; performing trend analysis on the time sequence of the nursing data, identifying abnormal data and evaluating the interference degree on the rehabilitation process; judging whether the rehabilitation progress of the patient meets the expectation or not according to the evaluation results of the matching degree and the interference degree; when the rehabilitation progress does not conform to the expectation, analyzing the demand change of the patient and evaluating the help effect of the nursing scheme; by comprehensively analyzing the matching degree, the interference degree and the nursing effect, the rehabilitation effect of the patient is evaluated, whether the nursing scheme needs to be adjusted or not is judged, individuation, accuracy and effectiveness of the nursing scheme are improved, the rehabilitation process of the patient can be accelerated, and the nursing quality is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of rehabilitation monitoring, and more specifically, to a patient rehabilitation monitoring method and system based on nursing data. Background Art

[0002] Traditional patient rehabilitation monitoring usually relies on traditional subjective evaluation methods and static monitoring data, which makes it difficult to dynamically and accurately evaluate the patient's rehabilitation progress, affecting the patient's rehabilitation effect. Especially when faced with complex rehabilitation needs and unstable rehabilitation progress, it is difficult for the nursing plan to quickly adapt to the patient's actual situation. In addition, existing technologies often ignore the time series changes of nursing data and the interference of abnormal data, and cannot accurately evaluate the patient's rehabilitation effect.

[0003] In order to solve the above problems, a technical solution is now provided. Summary of the invention

[0004] In order to overcome the above-mentioned defects of the prior art, an embodiment of the present invention provides a patient rehabilitation monitoring method and system based on nursing data to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solutions: A patient rehabilitation monitoring method based on nursing data comprises the following steps: Obtain the patient's nursing data, stratify and classify them according to the data source, and extract the core rehabilitation indicators; Analyze the patient's nursing data, identify the patient's current rehabilitation stage, and evaluate the degree of match between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators; Conduct trend analysis on time series changes of nursing data, identify abnormal data, and assess the degree of interference of abnormal data on the rehabilitation process; Based on the matching degree between the rehabilitation goals and core rehabilitation indicators of the current rehabilitation stage and the interference degree of abnormal data on the rehabilitation process, judge whether the patient's rehabilitation progress meets expectations; When the patient's rehabilitation progress does not meet expectations, analyze the changes in the patient's rehabilitation needs and evaluate the effectiveness of the current nursing plan in helping the rehabilitation process; Comprehensively analyze the degree of match between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators, the degree of interference of abnormal data on the rehabilitation process, and the effectiveness of the current nursing plan in helping the rehabilitation process, evaluate the patient's rehabilitation effect, and determine whether the current nursing plan needs to be adjusted.

[0006] In a preferred embodiment, the patient's nursing data is obtained, hierarchically classified according to the data source, and core rehabilitation indicators are extracted, specifically: Collect multi-source nursing data of patients and establish the corresponding relationship between data source and type; The hierarchical data were double classified by source and type to generate a multidimensional structure; Based on data content and time series characteristics, nursing data is subdivided; Define the judgment rules of core rehabilitation indicators and extract core rehabilitation indicators from classified data.

[0007] In a preferred embodiment, the patient's nursing data is analyzed to identify the patient's current rehabilitation stage and to evaluate the matching degree between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators, specifically: Extract key rehabilitation features based on patient care data and establish a stage feature set; Based on the stage feature set, the rehabilitation stage is identified and the current rehabilitation stage is calibrated; Match the corresponding rehabilitation goals according to the current rehabilitation stage and establish a rehabilitation goal feature set; Compare the matching degree between the core rehabilitation indicators and the rehabilitation target feature set to quantify the matching degree: take the weighted average of the matching scores of all core rehabilitation indicators to obtain the matching coefficient, which is expressed as: ;in, is the matching coefficient; The number of core rehabilitation indicators; represents the matching score; Indicates The weight of the core rehabilitation indicators.

[0008] In a preferred embodiment, trend analysis is performed on the time series changes of nursing data, abnormal data is identified, and the degree of interference of abnormal data on the rehabilitation process is evaluated, specifically: Collect the time series of nursing data and obtain the key indicator values ​​at each time point; Conduct trend analysis on nursing data time series to extract data change trends; Identify abnormal changes in time series data and define abnormal data points; Evaluate the degree of interference of abnormal data on the rehabilitation process: The calculation formula of the interference coefficient is: ;in, is the interference coefficient; For time point The amount of deviation; For time point Standard score of the upper data point; is the total number of time points.

[0009] In a preferred embodiment, based on the matching degree between the rehabilitation goal and the core rehabilitation index of the current rehabilitation stage and the interference degree of abnormal data on the rehabilitation process, it is judged whether the patient's rehabilitation progress meets expectations, specifically: Preset the matching coefficient threshold and compare the matching coefficient with the matching coefficient threshold: When the matching coefficient is greater than or equal to the matching coefficient threshold, it means that the rehabilitation goal of the current rehabilitation stage is highly matched with the patient's core rehabilitation indicators, and the patient's rehabilitation progress is in line with expectations; When the matching coefficient is less than the matching coefficient threshold, it means that the current patient's rehabilitation progress has not met expectations; Preset the interference coefficient threshold and compare the interference coefficient with the interference coefficient threshold: When the interference coefficient is greater than or equal to the interference coefficient threshold, it means that the abnormal data has a high degree of interference with the patient's rehabilitation process, and the patient's rehabilitation progress has not met expectations; When the interference coefficient is less than the interference coefficient threshold, it means that the abnormal data has little impact on the patient's rehabilitation process, and the current patient's rehabilitation progress meets expectations; When the matching coefficient is less than the matching coefficient threshold and the interference coefficient is greater than or equal to the interference coefficient threshold, it is determined that the patient's rehabilitation progress does not meet expectations.

[0010] In a preferred embodiment, when the patient's rehabilitation progress does not meet expectations, the patient's rehabilitation needs are analyzed and the effect of the current nursing program on the rehabilitation process is evaluated, specifically: Collect multi-stage rehabilitation data of patients, analyze rehabilitation data, and identify demand change trends and potential influencing factors; Evaluate the fit of the nursing plan to the patient's rehabilitation needs and the effect contribution rate: define the effect contribution rate coefficient to evaluate the effect of the nursing plan on the rehabilitation process. The expression is: ;in, is the effect contribution rate coefficient; is the total number of rehabilitation stages in the entire rehabilitation cycle; is the fit coefficient.

[0011] In a preferred embodiment, a comprehensive analysis is performed on the matching degree between the rehabilitation goal and the core rehabilitation index of the current rehabilitation stage, the interference degree of abnormal data on the rehabilitation process, and the effect of the current nursing plan on the rehabilitation process, specifically: The matching coefficient corresponding to the matching degree between the rehabilitation goal of the current rehabilitation stage and the core rehabilitation index, the interference coefficient corresponding to the interference degree of abnormal data on the rehabilitation process, and the effect contribution rate coefficient corresponding to the helping effect of the current nursing plan on the rehabilitation process are normalized, and the matching coefficient, interference coefficient and effect contribution rate coefficient obtained after normalization are calculated to obtain the patient rehabilitation effect coefficient. The calculation formula is: ;in, is the patient's rehabilitation effect coefficient; is the effect contribution rate coefficient; is the matching coefficient; is the interference coefficient; , , They are the weight factors of the matching coefficient, effect contribution coefficient and interference coefficient respectively.

[0012] In a preferred embodiment, the patient rehabilitation effect is evaluated according to the calculated patient rehabilitation effect coefficient, and it is determined whether the current nursing plan needs to be adjusted, specifically: Preset the patient rehabilitation effect coefficient threshold, and compare the patient rehabilitation effect coefficient with the patient rehabilitation effect coefficient threshold: When the patient rehabilitation effect coefficient is greater than or equal to the patient rehabilitation effect coefficient threshold, it means that the patient's rehabilitation effect is good at this time and there is no need to adjust the current nursing plan; When the patient rehabilitation effect coefficient is less than the patient rehabilitation effect coefficient threshold, it indicates that the patient's rehabilitation effect is poor at this time and the current nursing plan needs to be adjusted.

[0013] On the other hand, the present invention provides a patient rehabilitation monitoring system based on nursing data, including a data classification module, a rehabilitation stage identification module, an abnormality identification module, a rehabilitation progress judgment module, a help effect evaluation module, and a rehabilitation effect evaluation module; The data classification module is used to obtain the patient's nursing data, classify them according to the data source, and extract the core rehabilitation indicators; The rehabilitation stage identification module is used to analyze the patient's nursing data, identify the patient's current rehabilitation stage, and evaluate the matching degree between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators; The anomaly identification module is used to perform trend analysis on the time series changes of nursing data, identify abnormal data, and evaluate the degree of interference of abnormal data on the rehabilitation process; The rehabilitation progress judgment module determines whether the patient's rehabilitation progress meets expectations based on the matching degree between the rehabilitation goals and core rehabilitation indicators of the current rehabilitation stage and the degree of interference of abnormal data on the rehabilitation process; The help effect evaluation module is used to analyze the changes in the patient's rehabilitation needs when the patient's rehabilitation progress does not meet expectations, and to evaluate the help effect of the current nursing plan on the rehabilitation process; The rehabilitation effect evaluation module is used to comprehensively analyze the degree of matching between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators, the degree of interference of abnormal data on the rehabilitation process, and the effectiveness of the current nursing plan in helping the rehabilitation process, evaluate the patient's rehabilitation effect, and determine whether the current nursing plan needs to be adjusted.

[0014] Technical effects and advantages of a patient rehabilitation monitoring method and system based on nursing data of the present invention: By obtaining the patient's nursing data and classifying and analyzing it, and performing trend analysis on the nursing data to find abnormal data, combined with the matching degree between the rehabilitation goals and the core rehabilitation indicators and the interference effect of abnormal data, it is possible to evaluate in real time whether the patient's rehabilitation progress meets expectations. When the rehabilitation progress does not meet expectations, the changes in the patient's rehabilitation needs are analyzed to evaluate the effectiveness of the nursing plan. By comprehensively analyzing the matching degree between the rehabilitation goals and the core rehabilitation indicators, the interference effect of abnormal data, and the effectiveness of the nursing plan, the personalization and accuracy of the nursing plan can be effectively improved. It can not only promote the personalized adjustment of the patient's rehabilitation process, but also provide data support for nursing decisions, ensuring that each patient receives the most suitable nursing plan during the rehabilitation process. BRIEF DESCRIPTION OF THE DRAWINGS

[0015] Figure 1 A schematic diagram of a patient rehabilitation monitoring method based on nursing data according to the present invention; Figure 2 The present invention is a structural schematic diagram of a patient rehabilitation monitoring system based on nursing data. DETAILED DESCRIPTION

[0016] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0017] Example 1

[0018] Figure 1 The present invention provides a patient rehabilitation monitoring method based on nursing data, which comprises the following steps: Obtain the patient's nursing data, stratify and classify them according to the data source, and extract the core rehabilitation indicators; Analyze the patient's nursing data, identify the patient's current rehabilitation stage, and evaluate the degree of match between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators; Conduct trend analysis on time series changes of nursing data, identify abnormal data, and assess the degree of interference of abnormal data on the rehabilitation process; Based on the matching degree between the rehabilitation goals and core rehabilitation indicators of the current rehabilitation stage and the interference degree of abnormal data on the rehabilitation process, judge whether the patient's rehabilitation progress meets expectations; When the patient's rehabilitation progress does not meet expectations, analyze the changes in the patient's rehabilitation needs and evaluate the effectiveness of the current nursing plan in helping the rehabilitation process; Comprehensively analyze the degree of match between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators, the degree of interference of abnormal data on the rehabilitation process, and the effectiveness of the current nursing plan in helping the rehabilitation process, evaluate the patient's rehabilitation effect, and determine whether the current nursing plan needs to be adjusted.

[0019] Obtain the patient's nursing data, classify them according to the data source, and extract the core rehabilitation indicators, specifically: Collect multi-source nursing data of patients and establish a correspondence between data sources and types, specifically: obtain medical history records and daily nursing records from the electronic medical record system, obtain real-time physiological data recorded by the device from the nursing recorder, collect patient activity information from wearable devices, and extract subjective description information from patient self-report data.

[0020] Data from different sources are classified according to the data content, for example: physiological indicators include blood pressure, heart rate, and body temperature; behavioral data include activity level and sleep time; subjective descriptions include patients' pain scores and self-reported emotions.

[0021] Create corresponding relationships based on the characteristics of the source and data types. For example, the collection results of wearable devices are mostly behavioral data, and the data in the electronic medical record system involves multiple types.

[0022] The nursing data are preliminarily stratified according to the data source to generate a multidimensional hierarchical structure. Specifically, the data are divided into several layers according to the collection source of the nursing data. For example, the data from the electronic medical record system is one layer, and the data from wearable devices is another layer.

[0023] Extract data from each data source separately and classify them by data type. For example, in the electronic medical record system data layer, distinguish between medical history records, nursing records, etc.; in the wearable device data layer, distinguish between activity data, sleep data, etc.

[0024] Hierarchical data is doubly classified by source and type to generate a multidimensional structure. For example, the first dimension is the data source layer; the second dimension is the type classification within the source layer.

[0025] Based on the data content and time series characteristics, the nursing data is subclassified. Specifically, content analysis is performed on each type of data to extract its static and dynamic features. For example, static features include average, minimum and maximum values; dynamic features include fluctuation range, change trend, etc.

[0026] Perform time series analysis on time series data and calculate the characteristics of key time points, such as extracting the peak value, change rate and key node data of the time series; identify abnormal points or mutation points by analyzing the continuity of time series data.

[0027] According to the data characteristics, nursing data is further classified into: static data includes blood pressure average and heart rate stability; dynamic data includes daily change trend of sleep duration; abnormal data includes extreme points or mutation points in activity data.

[0028] Define the judgment rules for core rehabilitation indicators and extract core rehabilitation indicators from classified data. Specifically, formulate judgment criteria for core rehabilitation indicators for different data types. For example, physiological indicators are used to determine whether they are within the normal range, such as blood pressure values ​​within a certain reference range; behavioral data are used to determine whether the target value is reached, such as whether the daily activity volume meets the expected standard; subjective descriptions are used to analyze high-frequency words or key trends that appear in the description.

[0029] Calculate the classified data and extract the core rehabilitation indicators. For example, calculate the basic statistics such as mean and variance for static data; extract key features such as change trend and change rate for dynamic data.

[0030] The core rehabilitation indicators include physiological indicators such as heart rate average and blood pressure stability; behavioral indicators include total daily activity and sleep duration.

[0031] Analyze the patient's nursing data, identify the patient's current rehabilitation stage, and evaluate the degree of match between the rehabilitation goals and core rehabilitation indicators in the current rehabilitation stage, specifically: Based on the patient care data, key rehabilitation features are extracted and a stage feature set is established. Specifically, key rehabilitation features are extracted based on the collected patient care data. For example, heart rate and blood pressure fluctuations may reflect the patient's physiological recovery process; changes in gait and activity can reflect the recovery of motor function; pain scores and emotional states reflect the patient's subjective recovery experience. Each feature represents a different dimension of rehabilitation progress.

[0032] All the extracted key features are classified according to their performance in different rehabilitation stages to form a stage feature set.

[0033] Based on the stage feature set, the rehabilitation stage is identified and the current rehabilitation stage is calibrated. Specifically, the patient's rehabilitation process is divided into different stages, such as acute recovery stage, functional recovery stage, stable stage, etc. Each rehabilitation stage has different rehabilitation goals and requirements.

[0034] The rule-based classification method identifies the patient's current rehabilitation stage according to the key rehabilitation features in the stage feature set. Perform a weighted analysis on each key rehabilitation feature and judge whether the patient meets the conditions of a certain rehabilitation stage based on these features. For example: Acute recovery period: The patient may have more obvious physiological changes, such as unstable body temperature, abnormal heart rate, etc. Functional recovery period: The patient's physiological indicators of recovery gradually stabilize, but they may need to strengthen exercise and functional training. Stable period: The patient's physiological and behavioral indicators tend to be normal, and the rehabilitation goals are gradually achieved.

[0035] According to the current rehabilitation stage, the corresponding rehabilitation goal is matched, and a rehabilitation goal feature set is established, specifically: define each rehabilitation stage Corresponding rehabilitation target feature set ;in, Indicates the stage of recovery No. The goal characteristics of rehabilitation are: for example, in the acute recovery phase, the goal characteristics include stabilizing heart rate and controlling blood pressure.

[0036] According to the current stage of recovery , extract the corresponding rehabilitation target feature set ;in, A set of rehabilitation goal features representing the current rehabilitation stage; Represents the set of rehabilitation goal features of the current rehabilitation stage, and It is an equivalence relationship.

[0037] Compare the matching degree between the core rehabilitation indicators and the rehabilitation target feature set, and quantify the matching degree, specifically: The core set of rehabilitation indicators extracted from the nursing data is: , each Represents a core rehabilitation indicator.

[0038] For each core rehabilitation indicator and rehabilitation goal characteristics , calculate the matching score , the calculation formula is: ;in, represents the matching score; Indicates core rehabilitation indicators; Indicates The weight of the core rehabilitation indicators; Indicates target value for each rehabilitation goal feature; Indicates Normal value ranges for the rehabilitation target characteristics.

[0039] The matching scores of all core rehabilitation indicators are weighted averaged to obtain the matching coefficient, which is expressed as: ;in, is the matching coefficient, which is used to evaluate the matching degree between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators; The number of core rehabilitation indicators.

[0040] The larger the matching coefficient, the higher the matching degree between the rehabilitation goal and the core rehabilitation index in the current rehabilitation stage, and the closer the patient's rehabilitation status is to the preset target status. It indicates that the patient's core rehabilitation index is consistent with the target requirements of the current rehabilitation stage, the patient's rehabilitation progress is smooth, the patient's treatment and nursing plan is effective, and the patient's health status is gradually recovering.

[0041] Conduct trend analysis on the time series changes of nursing data, identify abnormal data, and evaluate the degree of interference of abnormal data on the rehabilitation process, specifically: Collect the time series of nursing data and obtain the key indicator values ​​at each time point. Specifically, obtain time series data from the patient care data source, including physiological indicators (such as blood pressure, heart rate), behavioral data (such as activity level, sleep duration), etc. Each time point corresponds to a data value.

[0042] From the time point Get each time point The data value of the dataset is represented as: ;in, Indicates at a point in time For each data point , contains multiple features.

[0043] Conduct trend analysis on the nursing data time series and extract the changing trend of the data. Specifically, conduct trend analysis on the collected time series data and identify the normal fluctuation range and data pattern by analyzing the overall changing trend of the data.

[0044] Apply the sliding average algorithm to the time series data to smooth out high-frequency fluctuations and calculate the time points The sliding average The sliding average value calculated by the sliding average algorithm As the current time point The trend of the data.

[0045] Identify abnormal changes in the time series and define abnormal data points. Specifically, identify abnormal data points by calculating the deviation between the actual data and the trend line. Abnormal data points refer to data that are significantly different from the normal change trend, which may interfere with the patient's recovery process.

[0046] Use standardized methods to identify outliers and calculate time points Standard score , represents the standard deviation of the data point from the mean. Upper data point Standard score When the standard score is greater than the preset threshold, Defined as 1, otherwise the standard score Defined as 0. When the standard score When defined as 1, it means that the data point This is abnormal data.

[0047] Evaluate the degree of interference of abnormal data on the recovery process, specifically: by calculating each abnormal data point The deviation is defined as the difference between the actual data and the expected data: ;in, It's time point The amount of deviation; It's time point The sliding average of .

[0048] According to the deviation, the interference coefficient is calculated to quantify the degree of interference with the rehabilitation process. The calculation formula of the interference coefficient is: ;in, is the interference coefficient; For time point The amount of deviation; For time point Standard score of the upper data point; is the total number of time points.

[0049] The larger the interference coefficient, the higher the degree of interference of abnormal data on the rehabilitation process, and the greater the negative impact on the patient's rehabilitation status. A larger interference coefficient usually indicates that there is a deviation between the abnormal change data in the patient's care data and the expected rehabilitation goal or normal physiological range, which may cause a delay in the rehabilitation progress. Abnormal data usually reflects abnormal fluctuations in physiological, behavioral or psychological states, which may interfere with the implementation of the rehabilitation plan and even affect the patient's long-term recovery effect. A higher interference coefficient indicates that abnormal data may indicate that the patient's physical condition has deteriorated and the treatment effect is not ideal.

[0050] Based on the matching degree between the rehabilitation goals and core rehabilitation indicators of the current rehabilitation stage and the interference degree of abnormal data on the rehabilitation process, it is judged whether the patient's rehabilitation progress meets expectations, specifically: Preset the matching coefficient threshold and compare the matching coefficient with the matching coefficient threshold: When the matching coefficient is greater than or equal to the matching coefficient threshold, it means that the rehabilitation goal of the current rehabilitation stage is highly matched with the patient's core rehabilitation indicators, and the patient's rehabilitation progress is in line with expectations. This means that the patient has already or is close to reaching the set rehabilitation goal, and the current treatment, care and lifestyle program has effectively promoted the rehabilitation process; When the matching coefficient is less than the matching coefficient threshold, it indicates that there is a gap between the patient's rehabilitation status and the preset rehabilitation goal, and the patient's current rehabilitation progress has not met expectations.

[0051] The matching coefficient threshold is set based on clinical experience, historical data analysis, the importance of rehabilitation goals and actual conditions. The matching coefficient threshold is set according to the individual rehabilitation needs of the patient, taking into account multiple factors such as the patient's age, condition, and rehabilitation stage.

[0052] Preset the interference coefficient threshold and compare the interference coefficient with the interference coefficient threshold: When the interference coefficient is greater than or equal to the interference coefficient threshold, it means that the abnormal data has a high degree of interference with the patient's rehabilitation process, and the rehabilitation plan may be affected. At this time, the patient's rehabilitation status is negatively affected by the abnormal data, which may lead to a delay in the rehabilitation progress, and the patient's rehabilitation progress does not meet expectations; When the interference coefficient is less than the interference coefficient threshold, it means that the abnormal data has little impact on the patient's rehabilitation process, and the current patient's rehabilitation progress meets expectations.

[0053] The setting of the interference coefficient threshold is determined based on the individual needs of the patient, the treatment goals, and the possible interference factors during the rehabilitation process. First, the setting of the threshold will take into account the patient's rehabilitation stage, such as the acute recovery period, the functional recovery period, and the stable period. In the acute stage, the patient's physiological state changes greatly, and the threshold of the interference coefficient may be set lower to allow for early detection of potential abnormal effects. In the functional recovery period or the stable period, the patient's physiological and behavioral indicators tend to be stable, and the threshold can be appropriately increased to reduce overreaction to small fluctuations. In addition, the threshold setting also needs to take into account the individual differences of patients, such as age, disease type, chronic disease history, etc., which may need to be further optimized through data analysis and historical rehabilitation data.

[0054] When the matching coefficient is less than the matching coefficient threshold and the interference coefficient is greater than or equal to the interference coefficient threshold, it is determined that the patient's rehabilitation progress does not meet expectations.

[0055] When the patient's rehabilitation progress does not meet expectations, it means that there is a large gap between the patient's core rehabilitation indicators and the set rehabilitation goals, and the abnormal data interferes with the rehabilitation process to a high degree, indicating that the rehabilitation plan may be insufficient and the patient has failed to achieve the ideal recovery state. The patient's rehabilitation progress does not meet expectations and reflects problems in many aspects, such as the ineffectiveness of the treatment plan and individual differences among patients. At this time, the treatment plan needs to be adjusted, including changing medications, changing drug dosages, changing the intensity of rehabilitation training, etc. In addition, factors such as the patient's mental state, emotional problems, or lifestyle may also have an impact on rehabilitation, and these factors also need to receive appropriate attention and intervention. In order to avoid worsening of the disease, the treatment team should make personalized adjustments to the rehabilitation plan to ensure that the rehabilitation goals are more in line with the patient's actual needs and reduce the impact of interfering factors.

[0056] When the patient's rehabilitation progress does not meet expectations, analyze the changes in the patient's rehabilitation needs and evaluate the effectiveness of the current nursing plan in helping the rehabilitation process, specifically: Collect multi-stage rehabilitation data of patients, specifically: the collected rehabilitation data include changes in patients' basic symptoms, quality of life scores, daily activity abilities, motor function recovery, and emotional states, etc.

[0057] During the collection of rehabilitation data, the following variables were defined: Indicates that the patient Symptom scores at each recovery stage; Indicates that the patient Activity score of each rehabilitation stage; Indicates that the patient Quality of life scores during the recovery period.

[0058] Analyze rehabilitation data to identify trends in demand changes and potential influencing factors. Specifically, by analyzing the collected multi-stage rehabilitation data, it is possible to identify trends in patient demand changes during the rehabilitation process. These trends not only involve the patient's symptoms and mobility, but also include potential influencing factors such as the patient's emotions, social support, and drug reactions.

[0059] definition For the A multidimensional rehabilitation data set for each rehabilitation stage; is the increment of the patient's rehabilitation needs, expressed in The changes in rehabilitation needs in each rehabilitation stage relative to the previous stage.

[0060] Evaluate the fit of the nursing plan to the patient's rehabilitation needs and the contribution rate of the effect, specifically: define the fit coefficient, which means The degree of fit between the nursing plan in each rehabilitation stage and the patient's needs is calculated as follows: ;in, is the fit coefficient; For the The weight of the rehabilitation data; For the The first stage of rehabilitation Items of rehabilitation data; is the total number of rehabilitation data.

[0061] The effect contribution rate coefficient is defined to evaluate the effect of the nursing program on the rehabilitation process. Its expression is: ;in, is the effect contribution rate coefficient; is the total number of rehabilitation stages in the entire rehabilitation cycle; is the fit coefficient.

[0062] The larger the effect contribution rate coefficient, the more obvious the current nursing plan is in helping the patient's rehabilitation process, and the nursing measures can more effectively meet the patient's rehabilitation needs. A larger effect contribution rate coefficient reflects that the nursing measures can more accurately meet the patient's rehabilitation needs at each stage. This means that nursing intervention has a significant effect on improving patients' symptoms, restoring their mobility, and improving their quality of life, and can dynamically adapt to the changing trends of patients' needs. It can also help the medical team evaluate the effectiveness of different nursing strategies, thereby optimizing resource allocation, further improving rehabilitation effects, and helping to develop more targeted and efficient intervention measures.

[0063] Comprehensively analyze the matching degree between the rehabilitation goals and core rehabilitation indicators of the current rehabilitation stage, the interference degree of abnormal data on the rehabilitation process, and the effect of the current nursing plan on the rehabilitation process, evaluate the patient's rehabilitation effect, and determine whether the current nursing plan needs to be adjusted. Specifically: The matching coefficient corresponding to the degree of matching between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators, the interference coefficient corresponding to the degree of interference of abnormal data on the rehabilitation process, and the effect contribution coefficient corresponding to the helping effect of the current nursing plan on the rehabilitation process are normalized, and the matching coefficient, interference coefficient and effect contribution coefficient obtained after normalization are calculated to obtain the patient rehabilitation effect coefficient. The patient rehabilitation effect is evaluated by the patient rehabilitation effect coefficient, and it is determined whether the current nursing plan needs to be adjusted.

[0064] The calculation formula of the patient rehabilitation effect coefficient is: ;in, is the patient's rehabilitation effect coefficient; is the effect contribution rate coefficient; is the matching coefficient; is the interference coefficient; , , They are the weight factors of the matching coefficient, effect contribution coefficient and interference coefficient respectively.

[0065] Preset the patient rehabilitation effect coefficient threshold, and compare the patient rehabilitation effect coefficient with the patient rehabilitation effect coefficient threshold: When the patient rehabilitation effect coefficient is greater than or equal to the patient rehabilitation effect coefficient threshold, it means that the patient's rehabilitation effect is good at this time and there is no need to adjust the current nursing plan; When the patient rehabilitation effect coefficient is less than the patient rehabilitation effect coefficient threshold, it indicates that the patient's rehabilitation effect is poor at this time and the current nursing plan needs to be adjusted.

[0066] The patient rehabilitation effect coefficient threshold is a comprehensive reference value set based on a large amount of historical rehabilitation data and medical research, taking into account factors such as the patient's basic health status, rehabilitation stage characteristics, target recovery level, and average rehabilitation progress. Through data modeling and expert evaluation, the patient rehabilitation effect coefficient threshold is ensured to be scientific and applicable, and can provide a reliable basis for judging the rehabilitation effect.

[0067] Adjustments to current care plans include: Reassess the patient's rehabilitation needs and adjust rehabilitation goals to make them more feasible and realistic; Develop personalized care plans based on the specific needs of patients. For example, increase the intensity of physical therapy for patients who need to improve their mobility; adjust the drug treatment plan or increase the frequency of rehabilitation training for patients whose symptoms are slow to improve; On the basis of the current nursing plan, effective intervention measures should be added, such as introducing new rehabilitation equipment, adopting a multidisciplinary joint diagnosis and treatment model, and expanding auxiliary support resources in the patient's rehabilitation environment (such as psychological counseling or home care training); In response to the interference caused by abnormal data, identify external interference factors (such as noise, environmental discomfort, etc.), optimize rehabilitation conditions by adjusting the rehabilitation environment and reducing adverse effects on patients' lives.

[0068] Example 2 The difference between Example 2 of the present invention and Example 1 is that this example introduces a patient rehabilitation monitoring system based on nursing data.

[0069] Figure 2 A structural schematic diagram of a patient rehabilitation monitoring system based on nursing data of the present invention is given, a patient rehabilitation monitoring system based on nursing data comprises a data classification module, a rehabilitation stage identification module, an abnormality identification module, a rehabilitation progress judgment module, a help effect evaluation module and a rehabilitation effect evaluation module; The data classification module is used to obtain the patient's nursing data, classify them according to the data source, and extract the core rehabilitation indicators; The rehabilitation stage identification module is used to analyze the patient's nursing data, identify the patient's current rehabilitation stage, and evaluate the matching degree between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators; The anomaly identification module is used to perform trend analysis on the time series changes of nursing data, identify abnormal data, and evaluate the degree of interference of abnormal data on the rehabilitation process; The rehabilitation progress judgment module determines whether the patient's rehabilitation progress meets expectations based on the matching degree between the rehabilitation goals and core rehabilitation indicators of the current rehabilitation stage and the degree of interference of abnormal data on the rehabilitation process; The help effect evaluation module is used to analyze the changes in the patient's rehabilitation needs when the patient's rehabilitation progress does not meet expectations, and to evaluate the help effect of the current nursing plan on the rehabilitation process; The rehabilitation effect evaluation module is used to comprehensively analyze the degree of matching between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators, the degree of interference of abnormal data on the rehabilitation process, and the effectiveness of the current nursing plan in helping the rehabilitation process, evaluate the patient's rehabilitation effect, and determine whether the current nursing plan needs to be adjusted.

[0070] The above embodiments may be implemented in whole or in part by software, hardware, firmware or any other combination thereof. When implemented by software, the above embodiments may be implemented in whole or in part in the form of a computer program product. The computer program product includes one or more computer instructions or computer programs. When the computer instructions or computer programs are loaded or executed on a computer, the process or function described in the embodiment of the present application is generated in whole or in part. The computer may be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The computer instructions may be stored in a computer-readable storage medium, or may be transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from one website, computer, server or data center to another website, computer, server or data center by wired (e.g., infrared, wireless, microwave, etc.) means. The computer-readable storage medium may be any available medium that a computer can access or a data storage device such as a server or data center that contains one or more available media sets. The available medium may be a magnetic medium (e.g., a floppy disk, a hard disk, a tape), an optical medium (e.g., a DVD), or a semiconductor medium. The semiconductor medium may be a solid-state hard disk.

[0071] Those of ordinary skill in the art will appreciate that the modules and algorithm steps of each example described in conjunction with the embodiments disclosed herein can be implemented in electronic hardware, or a combination of computer software and electronic hardware. Whether these functions are performed in hardware or software depends on the specific application and design constraints of the technical solution. Professional and technical personnel can use different methods to implement the described functions for each specific application, but such implementation should not be considered to be beyond the scope of this application.

[0072] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems, devices and modules described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0073] In the several embodiments provided in the present application, it should be understood that the disclosed systems, devices and methods can be implemented in other ways. For example, the device embodiments described above are only schematic. For example, the division of the modules is only a logical function division. There may be other division methods in actual implementation, such as multiple modules or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, indirect coupling or communication connection of devices or modules, which can be electrical, mechanical or other forms.

[0074] The modules described as separate components may or may not be physically separated, and the components shown as modules may or may not be physical modules, and may be located in one place or distributed on multiple network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment.

[0075] In addition, each functional module in each embodiment of the present application may be integrated into one processing module, or each module may exist physically separately, or two or more modules may be integrated into one module.

[0076] If the functions are implemented in the form of software function modules and sold or used as independent products, they can be stored in a computer-readable storage medium. Based on this understanding, the technical solution of the present application can be essentially or partly embodied in the form of a software product that contributes to the prior art. The computer software product is stored in a storage medium, including several instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to perform all or part of the steps of the methods described in the various embodiments of the present application. The aforementioned storage media include: U disk, mobile hard disk, read-only memory (ROM), random access memory (RAM), disk or optical disk, and other media that can store program codes.

[0077] The above is only a specific implementation of the present application, but the protection scope of the present application is not limited thereto. Any person skilled in the art who is familiar with the present technical field can easily think of changes or substitutions within the technical scope disclosed in the present application, which should be included in the protection scope of the present application. Therefore, the protection scope of the present application should be based on the protection scope of the claims.

[0078] Finally: The above description is only a preferred embodiment of the present invention and is not intended to limit the present invention. Any modifications, equivalent substitutions, improvements, etc. made within the spirit and principles of the present invention should be included in the protection scope of the present invention.

Claims

1. A patient rehabilitation monitoring method based on nursing data, characterized in that: The steps include: Obtain the patient's nursing data, stratify and classify them according to the data source, and extract the core rehabilitation indicators; Analyze the patient's nursing data, identify the patient's current rehabilitation stage, and evaluate the degree of match between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators; Conduct trend analysis on time series changes of nursing data, identify abnormal data, and assess the degree of interference of abnormal data on the rehabilitation process; Based on the matching degree between the rehabilitation goals and core rehabilitation indicators of the current rehabilitation stage and the interference degree of abnormal data on the rehabilitation process, judge whether the patient's rehabilitation progress meets expectations; When the patient's rehabilitation progress does not meet expectations, analyze the changes in the patient's rehabilitation needs and evaluate the effectiveness of the current nursing plan in helping the rehabilitation process; Comprehensively analyze the degree of match between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators, the degree of interference of abnormal data on the rehabilitation process, and the effectiveness of the current nursing plan in helping the rehabilitation process, evaluate the patient's rehabilitation effect, and determine whether the current nursing plan needs to be adjusted.

2. A patient rehabilitation monitoring method based on nursing data according to claim 1, characterized in that: Obtain the patient's nursing data, classify them according to the data source, and extract the core rehabilitation indicators, specifically: Collect multi-source nursing data of patients and establish the corresponding relationship between data source and type; The hierarchical data were double classified by source and type to generate a multidimensional structure; Sub-classify nursing data based on data content and time series characteristics; Define the judgment rules of core rehabilitation indicators and extract core rehabilitation indicators from classified data.

3. A patient rehabilitation monitoring method based on nursing data according to claim 2, characterized in that: Analyze the patient's nursing data, identify the patient's current rehabilitation stage, and evaluate the degree of match between the rehabilitation goals and core rehabilitation indicators in the current rehabilitation stage, specifically: Extract key rehabilitation features based on patient care data and establish a stage feature set; Based on the stage feature set, the rehabilitation stage is identified and the current rehabilitation stage is calibrated; Match the corresponding rehabilitation goals according to the current rehabilitation stage and establish a rehabilitation goal feature set; Compare the matching degree between the core rehabilitation indicators and the rehabilitation target feature set to quantify the matching degree: take the weighted average of the matching scores of all core rehabilitation indicators to obtain the matching coefficient, which is expressed as: ;in, is the matching coefficient; The number of core rehabilitation indicators; represents the matching score; Indicates The weight of the core rehabilitation indicators.

4. A patient rehabilitation monitoring method based on nursing data according to claim 3, characterized in that: Conduct trend analysis on the time series changes of nursing data, identify abnormal data, and evaluate the degree of interference of abnormal data on the rehabilitation process, specifically: Collect the time series of nursing data and obtain the key indicator values ​​at each time point; Conduct trend analysis on nursing data time series to extract data change trends; Identify abnormal changes in time series data and define abnormal data points; Evaluate the degree of interference of abnormal data on the rehabilitation process: The calculation formula of the interference coefficient is: ;in, is the interference coefficient; For time point The amount of deviation; For time point Standard score of the upper data point; is the total number of time points.

5. A patient rehabilitation monitoring method based on nursing data according to claim 4, characterized in that: Based on the matching degree between the rehabilitation goals and core rehabilitation indicators of the current rehabilitation stage and the interference degree of abnormal data on the rehabilitation process, it is judged whether the patient's rehabilitation progress meets expectations, specifically: Preset the matching coefficient threshold and compare the matching coefficient with the matching coefficient threshold: When the matching coefficient is greater than or equal to the matching coefficient threshold, it means that the rehabilitation goal of the current rehabilitation stage is highly matched with the patient's core rehabilitation indicators, and the patient's rehabilitation progress is in line with expectations; When the matching coefficient is less than the matching coefficient threshold, it means that the current patient's rehabilitation progress has not met expectations; Preset the interference coefficient threshold and compare the interference coefficient with the interference coefficient threshold: When the interference coefficient is greater than or equal to the interference coefficient threshold, it means that the abnormal data has a high degree of interference with the patient's rehabilitation process, and the patient's rehabilitation progress has not met expectations; When the interference coefficient is less than the interference coefficient threshold, it means that the abnormal data has little impact on the patient's rehabilitation process, and the current patient's rehabilitation progress meets expectations; When the matching coefficient is less than the matching coefficient threshold and the interference coefficient is greater than or equal to the interference coefficient threshold, it is determined that the patient's rehabilitation progress does not meet expectations.

6. A patient rehabilitation monitoring method based on nursing data according to claim 5, characterized in that: When the patient's rehabilitation progress does not meet expectations, analyze the changes in the patient's rehabilitation needs and evaluate the effectiveness of the current nursing plan in helping the rehabilitation process, specifically: Collect multi-stage rehabilitation data of patients, analyze rehabilitation data, and identify demand change trends and potential influencing factors; Evaluate the fit of the nursing plan to the patient's rehabilitation needs and the effect contribution rate: define the effect contribution rate coefficient to evaluate the effect of the nursing plan on the rehabilitation process. The expression is: ;in, is the effect contribution rate coefficient; is the total number of rehabilitation stages in the entire rehabilitation cycle; is the fit coefficient.

7. A patient rehabilitation monitoring method based on nursing data according to claim 6, characterized in that: A comprehensive analysis is conducted on the matching degree between the rehabilitation goals and core rehabilitation indicators of the current rehabilitation stage, the interference degree of abnormal data on the rehabilitation process, and the effect of the current nursing program on the rehabilitation process. Specifically: The matching coefficient corresponding to the matching degree between the rehabilitation goal of the current rehabilitation stage and the core rehabilitation index, the interference coefficient corresponding to the interference degree of abnormal data on the rehabilitation process, and the effect contribution rate coefficient corresponding to the helping effect of the current nursing plan on the rehabilitation process are normalized, and the matching coefficient, interference coefficient and effect contribution rate coefficient obtained after normalization are calculated to obtain the patient rehabilitation effect coefficient. The calculation formula is: ;in, is the patient recovery effect coefficient; is the effect contribution rate coefficient; is the matching coefficient; is the interference coefficient; , , They are the weight factors of the matching coefficient, effect contribution coefficient and interference coefficient respectively.

8. A patient rehabilitation monitoring method based on nursing data according to claim 7, characterized in that: The patient rehabilitation effect is evaluated based on the calculated patient rehabilitation effect coefficient, and it is determined whether the current nursing plan needs to be adjusted, specifically: Preset the patient rehabilitation effect coefficient threshold, and compare the patient rehabilitation effect coefficient with the patient rehabilitation effect coefficient threshold: When the patient rehabilitation effect coefficient is greater than or equal to the patient rehabilitation effect coefficient threshold, it means that the patient's rehabilitation effect is good at this time and there is no need to adjust the current nursing plan; When the patient rehabilitation effect coefficient is less than the patient rehabilitation effect coefficient threshold, it indicates that the patient's rehabilitation effect is poor at this time and the current nursing plan needs to be adjusted.

9. A patient rehabilitation monitoring system based on nursing data, used to implement a patient rehabilitation monitoring method based on nursing data according to any one of claims 1 to 8, characterized in that: It includes a data classification module, a rehabilitation stage identification module, an abnormality identification module, a rehabilitation progress judgment module, an assistance effect evaluation module, and a rehabilitation effect evaluation module; The data classification module is used to obtain the patient's nursing data, classify them according to the data source, and extract the core rehabilitation indicators; The rehabilitation stage identification module is used to analyze the patient's nursing data, identify the patient's current rehabilitation stage, and evaluate the matching degree between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators; The anomaly identification module is used to perform trend analysis on the time series changes of nursing data, identify abnormal data, and evaluate the degree of interference of abnormal data on the rehabilitation process; The rehabilitation progress judgment module determines whether the patient's rehabilitation progress meets expectations based on the matching degree between the rehabilitation goals and core rehabilitation indicators of the current rehabilitation stage and the degree of interference of abnormal data on the rehabilitation process; The help effect evaluation module is used to analyze the changes in the patient's rehabilitation needs when the patient's rehabilitation progress does not meet expectations, and to evaluate the help effect of the current nursing plan on the rehabilitation process; The rehabilitation effect evaluation module is used to comprehensively analyze the degree of matching between the rehabilitation goals of the current rehabilitation stage and the core rehabilitation indicators, the degree of interference of abnormal data on the rehabilitation process, and the effectiveness of the current nursing plan in helping the rehabilitation process, evaluate the patient's rehabilitation effect, and determine whether the current nursing plan needs to be adjusted.

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