Bedside doctor-patient information interaction method, interaction terminal, medium and program product

Abstract

The invention discloses a bedside doctor-patient information interaction method, an interaction terminal, a medium and a program product, and the method comprises the steps: calling diagnosis and treatment data at the current time from a preset information base based on a patient identifier; extracting static cost items and dynamic cost items; classifying the medicine fees according to preset medication time periods to obtain cost distribution of the first time period, the second time period and the third time period; calculating a cost fluctuation coefficient of each time period; when it is determined that any cost fluctuation coefficient exceeds an early warning threshold value, cost abnormity checking information is sent to a checking terminal; receiving a checking result sent by the checking terminal; based on the abnormal cost information, generating diagnosis and treatment details including a cost abnormal description; integrating the diagnosis and treatment details, the static cost items and the dynamic cost items to generate a patient daily list; and displaying the patient daily list according to a preset layout rule. According to the invention, the efficiency and accuracy of synchronizing specific medical behaviors and cost information to the patient are improved, and the hysteresis and opaqueness of information synchronization are reduced.

Description

Technical Field

[0001] The present application belongs to the field of electronic digital data processing, and in particular relates to a bedside doctor-patient information interaction method, an interactive terminal, a medium and a program product. Background Art

[0002] In clinical medical practice, effective communication between doctors and patients is of great significance for the diagnosis, treatment and rehabilitation of patients. The traditional bedside doctor-patient interaction method mainly relies on the oral explanation of medical staff and paper materials. This method has problems such as non-intuitive information transmission, difficulty in controlling the patient's understanding, and low efficiency of doctor-patient communication, which is not conducive to patients' full understanding of their own conditions and treatment plans.

[0003] In related technologies, a display screen can be installed next to the bed to display the patient's examination results, diagnosis and treatment plan and other information in the form of pictures and texts, and provide a voice broadcast function, so that patients can understand their own conditions more intuitively. This system improves the problem of non-intuitive information transmission in traditional doctor-patient communication methods and improves patients' understanding of medical information.

[0004] However, although the existing bedside doctor-patient interaction system can display basic medical information, it lacks systematic display and management functions for the specific medical behaviors and cost information generated during the patient's daily diagnosis and treatment process. It is difficult for patients to grasp their hospitalization expenses and treatment progress in real time. In addition, the amount of data on the medicines used by patients every day and the corresponding price information is huge, which is difficult to synchronize to patients accurately and quickly, thereby increasing the lag and opacity of information synchronization, which is not conducive to building a harmonious doctor-patient relationship. Summary of the invention

[0005] The present application provides a bedside doctor-patient information interaction method, interactive terminal, medium and program product for improving the efficiency and accuracy of synchronizing specific medical behavior and cost information to patients, thereby reducing the lag and opacity of information synchronization.

[0006] In a first aspect, the present application provides a bedside doctor-patient information interaction method, wherein the interactive terminal responds to the patient clicking an information acquisition button, and retrieves the current time's diagnosis and treatment data from a preset information library based on the patient's patient identification, wherein the diagnosis and treatment data includes diagnosis and treatment records and expense records; The interactive terminal extracts static expense items and dynamic expense items from the expense records. The static expense items include bed fees and nursing fees, and the dynamic expense items include drug fees and examination fees. The interactive terminal classifies the drug expenses according to the preset drug use periods, and obtains the cost distribution of the first period, the second period, and the third period; The interactive terminal calculates the cost fluctuation coefficient of each time period based on the cost distribution of the first time period, the second time period and the third time period; When the interactive terminal determines that any cost fluctuation coefficient exceeds the warning threshold, it sends cost anomaly verification information to the verification terminal; The interactive terminal receives the verification result sent by the verification terminal, and the verification result includes abnormal fee information; The interactive terminal generates diagnosis and treatment details including an explanation of the abnormal cost based on the abnormal cost information; The interactive terminal integrates diagnosis and treatment details, static cost items, and dynamic cost items to generate a patient daily list; The interactive terminal displays the patient's daily list according to preset layout rules.

[0007] By adopting the above technical solution, static costs and dynamic costs are separated from the cost records through the interactive terminal, and the drug costs are finely classified and analyzed by time period, and the cost fluctuation coefficient of each time period is calculated, so that abnormal cost fluctuations can be discovered in time. When abnormal costs are found, the interactive terminal automatically sends verification information to the verification terminal and receives the verification results, and generates diagnosis and treatment details including abnormal descriptions. This dynamic monitoring and multi-party collaboration method enables abnormal costs to be quickly identified and explained. By integrating diagnosis and treatment details with cost items to form a patient's daily list, patients can clearly understand the daily cost composition and reasons for changes, which enhances the comprehensibility of cost information. This time-based cost analysis and abnormal verification mechanism can not only help medical institutions to discover and deal with abnormal costs in a timely manner, but also keep patients fully informed, thereby improving the efficiency and accuracy of synchronizing specific medical behaviors and cost information to patients, thereby reducing the lag and opacity of information synchronization.

[0008] In combination with some embodiments of the first aspect, in some embodiments, retrieving the diagnosis and treatment data at the current time from the preset information library based on the patient identification of the patient specifically includes: The interactive terminal obtains the hospitalization information corresponding to the patient identification, and the hospitalization information includes the admission time and ward information; The interactive terminal calculates the number of days of hospitalization based on the time of admission and compares the number of days of hospitalization with the preset hospitalization cycle; When the number of hospitalization days reaches a preset proportion of a preset hospitalization cycle, the interactive terminal extracts historical cost data from a preset information database; The interactive terminal calculates the average daily cost benchmark value based on historical cost data; The interactive terminal extracts the current diagnosis and treatment data from the preset information database, and associates the average daily cost benchmark with the current diagnosis and treatment data to obtain the diagnosis and treatment record and cost record.

[0009] By adopting the above technical solution, by obtaining the patient's hospitalization information and calculating the number of hospitalization days, when the number of hospitalization days reaches a preset proportion, the historical cost data is extracted to calculate the average daily cost benchmark value, and it is associated with the current diagnosis and treatment data. This dynamic benchmark value calculation method based on the hospitalization cycle enables the interactive terminal to evaluate the rationality of the cost according to the patient's specific hospitalization stage. Due to the differences in treatment plans and cost characteristics at different stages of hospitalization, the use of dynamic benchmark values ​​can better reflect the actual laws of cost changes than static standards. By correlating historical cost data with current data for analysis, the interactive terminal can more accurately determine whether the cost changes are within a reasonable range, thereby improving the accuracy and reliability of cost anomaly identification.

[0010] In combination with some embodiments of the first aspect, in some embodiments, the interactive terminal classifies the drug expenses according to the preset medication time periods to obtain the cost distribution of the first time period, the second time period, and the third time period, specifically including: The interactive terminal obtains the frequency of medication, which includes daily fixed-frequency medication and temporary medical prescription medication; The interactive terminal divides the daily fixed-frequency medication into corresponding time periods in the preset medication time periods according to the medication time, and the preset medication time periods include the first time period, the second time period and the third time period; The interactive terminal counts the medication time of temporary medical prescriptions and obtains statistical results; The interactive terminal allocates the temporary medical prescription medication to the closest time period based on the statistical results, and obtains the cost distribution of the first time period, the second time period and the third time period.

[0011] By adopting the above technical solution, the time periods are divided and allocated by distinguishing between fixed-frequency medication and temporary medication. For fixed-frequency medication, it is directly divided according to the time of administration, and for temporary medication, the closest time period is determined through statistical analysis. This differentiated time period division method takes into account the time characteristics of different types of medication, so that the cost distribution is more in line with the actual medication rules. By accurately counting and classifying the medication time, the interactive terminal can accurately reflect the actual drug cost structure of each time period, reducing the deviation that may be caused by simply dividing it evenly by time. This time period division method based on medication characteristics improves the accuracy of cost distribution and provides a more reliable data basis for subsequent cost fluctuation analysis.

[0012] In combination with some embodiments of the first aspect, in some embodiments, after the interactive terminal displays the patient's daily list according to the preset layout rule, the method further includes: The interactive terminal detects whether there is associated medical advice information in the diagnosis and treatment details, and the associated medical advice information includes medical advice fees; When the associated medical advice information is detected, the interactive terminal extracts the execution time series data corresponding to the associated medical advice information, and the execution time series data includes the medical advice issuance time, execution time and execution order; The interactive terminal identifies a medical order combination with a causal relationship based on the execution time series data and the preset medical order association rule, the preset medical order association rule is that the time interval between medical order issuance is less than the first preset time length and the time interval between executions is less than the second preset time length, and the medical order combination includes at least two pieces of associated medical order information connected in execution order; The interactive terminal calculates the cost association strength for the medical order combination, where the cost association strength is the degree of correlation between each associated medical order information in the medical order combination and the medical order cost; When the cost correlation intensity exceeds the preset threshold, the interactive terminal marks the medical order combination as a key monitoring object.

[0013] By adopting the above technical solution, the related medical order information is detected and the execution time series data is extracted, the medical order combinations with causal relationships are identified, the cost correlation strength is calculated, and the medical order combinations with high correlation strength are monitored. This cost monitoring method based on the correlation of medical orders can discover the correlation patterns between cost items that are apparently independent but actually have causal relationships. By tracking the cost change trends of key monitored objects in real time, the interactive terminal can identify potential cost anomalies from the perspective of the logical relationship of medical order execution. This cost monitoring method based on the correlation of medical orders reduces the limitations of monitoring a single cost item, can more comprehensively grasp the medical logic behind cost changes, and improves the depth and accuracy of cost monitoring.

[0014] In conjunction with some embodiments of the first aspect, in some embodiments, the interactive terminal identifies a combination of medical orders having a causal relationship based on execution time series data and preset medical order association rules, specifically including: The interactive terminal extracts the start and end time points of the execution time corresponding to each associated medical order information; The interactive terminal calculates the time overlap between the associated medical order information adjacent in execution order based on the start and end time points; The interactive terminal determines the associated medical order information with a time overlap greater than a preset time overlap threshold as a candidate medical order combination; The interactive terminal determines the candidate medical order combination that meets the preset medical order association rule as the medical order combination.

[0015] By adopting the above technical solution, the start and end time points of the execution of medical orders are extracted and the time overlap between different medical orders is calculated, and a quantitative evaluation mechanism for the timing of medical order execution is established. By statistically analyzing the sequence characteristics of medical order execution and combining them with time overlap analysis, the potential causal relationship between medical orders can be captured from the time dimension. The type of association between medical orders is determined based on the time overlap and sequence characteristics, and an accurate characterization of the medical order association relationship is achieved. The process of aggregating highly associated medical orders into medical order combinations enables the interactive terminal to identify a set of diagnostic and treatment behaviors with intrinsic connections from discrete medical order information. Through the overall analysis of the medical order execution process, the accuracy of medical order association identification is improved.

[0016] In combination with some embodiments of the first aspect, in some embodiments, after the interactive terminal marks the medical order combination as a key monitoring object, the method further includes: The interactive terminal obtains the historical cost data of the key monitored object, and the historical cost data is the accumulated cost amount of each medical order combination within a preset period; The interactive terminal establishes a fee benchmark interval based on the average and standard deviation of the accumulated fee amount; The interactive terminal obtains the current fee and calculates the degree of deviation between the current fee and the fee benchmark range; The interactive terminal generates a cost risk level based on the degree of deviation.

[0017] By adopting the above technical solution, the historical cost data of key monitoring objects are obtained and the cost benchmark interval is established, forming a dynamic cost assessment standard. The deviation degree of the current cost is calculated based on the cost benchmark interval, realizing the quantitative judgment of cost anomalies. The mechanism of generating cost risk level according to the degree of deviation converts continuous cost deviation into discrete risk level, making cost risk easier to understand and manage. This cost risk assessment method based on historical data takes into account the cost differences of different patients and different treatment plans, and reduces the judgment bias caused by the use of unified standards. By establishing a corresponding relationship between cost and risk level, the interactive terminal can promptly detect cost anomalies and issue risk warnings, enhancing the pertinence and effectiveness of medical cost management.

[0018] In conjunction with some embodiments of the first aspect, in some embodiments, calculating the degree of deviation between the current fee and the fee benchmark interval specifically includes: The interactive terminal extracts the cost data of several billing cycles from the current time; The interactive terminal removes abnormal fluctuation points in the cost data to obtain cleaning cost data; The interactive terminal compares the cleaning cost data with the cost benchmark range to obtain the degree of deviation.

[0019] By adopting the above technical solution, the cost data of the recent billing cycles are extracted and the abnormal fluctuation points are eliminated, which improves the timeliness and data quality of cost assessment. The standard deviation of cost changes is calculated and the normal fluctuation range is determined accordingly, and a statistical cost fluctuation assessment method is established. The process of comparing the current cost with the normal fluctuation range to obtain the degree of deviation realizes the objective quantification of cost anomalies. By combining data cleaning and statistical analysis, the accuracy and reliability of cost anomaly judgment are improved.

[0020] In a second aspect, an embodiment of the present application provides a bedside medical and patient information interaction terminal, which includes: one or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and one or more processors call the computer instructions to enable the interactive terminal to execute the method described in the first aspect and any possible implementation method of the first aspect.

[0021] In a third aspect, an embodiment of the present application provides a computer-readable storage medium, comprising instructions, which, when executed on an interactive terminal, enable the interactive terminal to execute the method described in the first aspect and any possible implementation manner of the first aspect.

[0022] In a fourth aspect, an embodiment of the present application provides a computer program product, characterized in that when the computer program product is run on an interactive terminal, the interactive terminal executes the method described in any possible implementation manner in the first aspect.

[0023] One or more technical solutions provided in the embodiments of the present application have at least the following technical effects or advantages: 1. The present application provides a bedside medical and patient information interaction method, which separates static costs and dynamic costs from the cost records through an interactive terminal, and performs refined classification analysis of drug costs by time period, calculates the cost fluctuation coefficient of each time period, and can promptly discover abnormal cost fluctuations. When abnormal costs are found, the interactive terminal automatically sends verification information to the verification terminal and receives the verification results, and generates diagnosis and treatment details including abnormal descriptions. This dynamic monitoring and multi-party collaboration method enables abnormal costs to be quickly identified and explained. By integrating diagnosis and treatment details with cost items to form a patient's daily list, patients can clearly understand the daily cost composition and reasons for changes, enhancing the comprehensibility of cost information. This time-based cost analysis and abnormal verification mechanism can not only help medical institutions to promptly discover and handle cost anomalies, but also keep patients fully informed, thereby improving the efficiency and accuracy of synchronizing specific medical behaviors and cost information to patients, thereby reducing the lag and opacity of information synchronization.

[0024] 2. The present application provides a bedside medical-patient information interaction method, which detects related medical order information and extracts execution time series data, identifies medical order combinations with causal relationships, calculates the cost correlation strength, and focuses on monitoring medical order combinations with high correlation strength. This cost monitoring method based on the correlation of medical orders can discover the correlation patterns between cost items that are apparently independent but actually have causal relationships. By tracking the cost change trends of key monitored objects in real time, the interactive terminal can identify potential cost anomalies from the perspective of the logical relationship of medical order execution. This cost monitoring method based on the correlation of medical orders reduces the limitations of monitoring a single cost item, can more comprehensively grasp the medical logic behind cost changes, and improves the depth and accuracy of cost monitoring.

[0025] 3. The present application provides a bedside medical and patient information interaction method to obtain historical cost data of key monitored objects and establish a cost benchmark interval, forming a dynamic cost assessment standard. The degree of deviation of the current cost is calculated based on the cost benchmark interval, and quantitative judgment of cost anomalies is achieved. A mechanism for generating cost risk levels based on the degree of deviation converts continuous cost deviations into discrete risk levels, making cost risks easier to understand and manage. This cost risk assessment method based on historical data takes into account the cost differences between different patients and different treatment plans, and reduces the judgment bias caused by the use of a unified standard. By establishing a corresponding relationship between costs and risk levels, the interactive terminal can promptly detect cost anomalies and provide risk warnings, thereby enhancing the pertinence and effectiveness of medical cost management. BRIEF DESCRIPTION OF THE DRAWINGS

[0026] Figure 1 It is a flow chart of a bedside doctor-patient information interaction method in an embodiment of the present application.

[0027] Figure 2 It is a flow chart of a cost monitoring method based on medical order association analysis in an embodiment of the present application.

[0028] Figure 3 It is a schematic diagram of the physical device structure of a bedside doctor-patient information interaction terminal provided in an embodiment of the present application. DETAILED DESCRIPTION

[0029] The terms used in the following embodiments of the present application are only for the purpose of describing specific embodiments, and are not intended to be used as limitations to the present application. As used in the specification and appended claims of the present application, the singular expressions "one", "a kind of", "said", "above", "the" and "this" are intended to also include plural expressions, unless there is a clear indication to the contrary in the context. It should also be understood that the term "and / or" used in the present application refers to any or all possible combinations comprising one or more listed items.

[0030] In the following, the terms "first" and "second" are used for descriptive purposes only and are not to be understood as suggesting or implying relative importance or implicitly indicating the number of the indicated technical features. Thus, a feature defined as "first" or "second" may explicitly or implicitly include one or more of the features, and in the description of the embodiments of the present application, unless otherwise specified, "plurality" means two or more.

[0031] The following uses an embodiment and combines Figure 1 , a bedside doctor-patient information interaction method in an embodiment of the present application is described: See also Figure 1 , which is a flow chart of a bedside doctor-patient information interaction method in an embodiment of the present application.

[0032] S101, in response to a patient clicking an information acquisition button, the interactive terminal retrieves current diagnosis and treatment data from a preset information database based on the patient's patient identification; In response to the patient clicking the information acquisition button, the interactive terminal retrieves the current diagnosis and treatment data from the preset information library based on the patient's patient identification, and the diagnosis and treatment data includes diagnosis and treatment records and cost records. Specifically: the interactive terminal obtains the hospitalization information corresponding to the patient identification, and the hospitalization information includes the admission time and ward information; the interactive terminal calculates the number of hospitalization days based on the admission time, and compares the number of hospitalization days with the preset hospitalization cycle; when the number of hospitalization days reaches the preset proportion of the preset hospitalization cycle, the interactive terminal extracts the historical cost data from the preset information library; the interactive terminal calculates the average daily cost benchmark value based on the historical cost data; the interactive terminal associates the average daily cost benchmark value with the current diagnosis and treatment data to obtain the diagnosis and treatment records and cost records.

[0033] In this step, the interactive terminal needs to respond to the patient's active operation and provide real-time medical information query services. When the patient clicks the information acquisition button, the interactive terminal can capture the action and use it as a trigger condition for the information acquisition request. At the same time, in order to accurately locate the patient's medical information, the interactive terminal also needs to obtain the patient's unique identifier, such as patient ID, hospitalization number, etc., as an index for retrieving data from the information database.

[0034] In specific implementation, the interactive terminal can use a variety of methods such as touch screens and buttons to set information acquisition buttons for patients to operate conveniently. At the same time, in order to improve patient privacy protection and data security, after receiving a patient's request, the interactive terminal can also require the patient to perform identity authentication, such as entering a password, biometrics, etc., to ensure that only legitimate users can access their medical information. In addition, when the interactive terminal retrieves data from the preset information library, it can dynamically obtain the latest medical records and cost data based on the current system time to ensure the real-time and accuracy of the information.

[0035] When obtaining diagnosis and treatment data, the interactive terminal can also perform necessary preprocessing and conversion on the original data to improve the readability and usability of the data. For example, the interactive terminal can automatically calculate the patient's hospitalization days based on the patient's admission time, and compare it with the preset hospitalization period to determine the patient's current hospitalization stage; the interactive terminal can also use data mining, machine learning and other technologies to analyze the patient's historical cost data, calculate statistical indicators such as average daily costs and cost growth trends, and provide a reference for subsequent cost analysis.

[0036] S102, the interactive terminal extracts static expense items and dynamic expense items from the expense record; The interactive terminal extracts static expense items and dynamic expense items from the expense records. The static expense items include bed fees and nursing fees, and the dynamic expense items include drug fees and examination fees.

[0037] In this step, the interactive terminal needs to further process and classify the expense record data obtained in the previous step. Usually, the medical expenses of a patient are composed of multiple items, and the billing methods and change rules of different items are different. In order to better analyze and present the patient's expense situation, the interactive terminal can divide these expense items into two categories: static expenses and dynamic expenses.

[0038] Specifically, static costs refer to cost items that remain relatively fixed and have little change during the patient's hospitalization, such as bed fees, nursing fees, etc. These costs are usually calculated according to fixed standards and cycles and have little to do with the patient's actual diagnosis and treatment. Therefore, the interactive terminal can directly extract the amount data of these items from the cost records and list them separately as basic costs in subsequent cost statistics and displays.

[0039] In contrast, dynamic costs refer to cost items that change dynamically with the patient's condition and treatment process, such as drug costs, examination fees, and surgery fees. These costs are closely related to the patient's actual treatment behavior, reflecting changes in the patient's condition and the doctor's treatment decisions. In order to accurately grasp the changing trend of patient costs, the interactive terminal needs to track and extract these dynamic cost data in real time, and conduct a comprehensive analysis in combination with the patient's treatment information.

[0040] When extracting dynamic expense items, the interactive terminal can use a rule-based approach to predefine some keywords or templates, such as "drugs" and "examinations", and then match and extract them from the expense records. At the same time, the interactive terminal can also use natural language processing, text mining and other technologies to perform semantic analysis on the text description of the expense record, and automatically identify and classify different expense items. For some complex combination items, the interactive terminal can also use algorithms such as association rule mining and frequent pattern mining to discover the implicit relationships and co-occurrence patterns, and achieve more refined expense classification.

[0041] S103, the interactive terminal classifies the drug expenses according to the preset drug use periods, and obtains the cost distribution of the first period, the second period, and the third period; The interactive terminal classifies the drug expenses according to the preset medication time periods, and obtains the cost distribution of the first time period, the second time period and the third time period. Specifically: the interactive terminal obtains the frequency of medication, which includes daily fixed-frequency medication and temporary medical prescription medication; the interactive terminal divides the daily fixed-frequency medication into corresponding time periods according to the medication time; the interactive terminal counts the medication time of temporary medical prescription medication and obtains the statistical results; the interactive terminal allocates the temporary medical prescription medication to the closest time period based on the statistical results, and obtains the cost distribution of the first time period, the second time period and the third time period.

[0042] In this step, the interactive terminal needs to further analyze the extracted drug cost data in the time dimension. Since patients usually need to take different drugs at different time periods according to doctor's orders during hospitalization, and the cost difference of different drugs may be large. Therefore, classifying and counting drug costs according to the medication period can help patients more clearly understand their medication usage and cost distribution in a day, so as to better cooperate with the doctor's diagnosis and treatment and reasonably control drug costs.

[0043] In specific implementation, the interactive terminal can pre-set several fixed medication time periods, such as morning, afternoon, evening, etc., as the basis for classification. Then, the interactive terminal can automatically obtain the medication time information of each drug expense item, and classify it into the corresponding category according to which time period the time falls. For some temporary medical prescription medications, the time may not be fixed. The interactive terminal can classify them into the time period with the closest time span according to the proximity of the medication time to the midpoint of each time period.

[0044] While classifying the time periods, the interactive terminal can also automatically count the total drug cost, the number of drugs used, the cost ratio and other indicators in each time period to form an intuitive time period cost distribution chart. Through the chart display, patients can clearly see their peak drug use period and cost concentration period in a day, which helps them to arrange their daily life and work schedule reasonably and communicate with doctors about the medication plan in a timely manner. In the case of abnormal fluctuations in cost distribution, the interactive terminal can also give obvious color identification or prompt information to guide patients to promptly discover and verify drug cost issues.

[0045] In some cases, it may be difficult to completely fix the medication time period for patients, or there may be overlaps in the medication time of different drugs. In response to this situation, the interactive terminal can adopt a more flexible classification method, such as dynamically dividing the drug into different time period combinations based on its type of action, frequency of use and other characteristics. For example, some long-term fixed medications can be separately classified as "common medications", and some short-term targeted medications can be classified as "stage medications". The interactive terminal can also support custom time period settings, allowing patients or medical staff to flexibly adjust the time period division plan according to the actual medication situation.

[0046] S104, the interactive terminal calculates the cost fluctuation coefficient of each time period based on the cost distribution of the first time period, the second time period and the third time period; In this step, the interactive terminal needs to further analyze the fluctuation of drug costs in different time periods, that is, the degree of dispersion or variability of costs. By introducing the cost fluctuation coefficient, the interactive terminal can quantitatively evaluate the stability of drug costs in each time period, quickly discover abnormal cost fluctuations, and provide a basis for subsequent cost verification and early warning.

[0047] In specific implementation, the interactive terminal can use a variety of statistical methods to calculate the cost fluctuation coefficient, and the commonly used methods include the coefficient of variation method and the coefficient of dispersion method. Taking the coefficient of variation method as an example, the interactive terminal first needs to calculate the cost mean and standard deviation in each time period, and then divide the standard deviation by the mean to obtain the coefficient of variation. The larger the coefficient of variation, the higher the degree of dispersion of the cost in the time period, and the greater the fluctuation; conversely, the smaller the coefficient of variation, the more concentrated the cost distribution in the time period, and the smaller the fluctuation.

[0048] S105. When the interactive terminal determines that any cost fluctuation coefficient exceeds the warning threshold, the interactive terminal sends cost abnormality verification information to the verification terminal; In this step, the interactive terminal needs to determine whether there is an abnormal cost fluctuation based on the cost fluctuation coefficient calculated in the previous step, and promptly issue an early warning and verification request to the relevant parties. By setting an early warning threshold, the interactive terminal can automatically identify those periods when the cost fluctuation is too large and exceeds the normal range, and prompt the management staff to verify and intervene, thereby reducing the economic losses of patients and improving the quality of medical services.

[0049] In specific implementation, the interactive terminal first needs to set a reasonable cost fluctuation warning threshold based on historical data and expert experience. The threshold can be a fixed upper limit of the coefficient of variation, such as 0.5, 0.8, etc., or a dynamic interval, which is adjusted in real time according to factors such as the patient's condition and the type of medicine. When the cost fluctuation coefficient of a certain period exceeds the warning threshold, the interactive terminal can determine that the drug cost in that period has fluctuated abnormally, which needs to be paid attention to and verified.

[0050] S106, the interactive terminal receives the verification result sent by the verification terminal, and generates diagnosis and treatment details including an explanation of the abnormal cost based on the abnormal cost information; The interactive terminal receives the verification result sent by the verification terminal, and generates the diagnosis and treatment details including the explanation of the abnormal cost based on the abnormal cost information. The verification result includes the abnormal cost information.

[0051] In this step, the interactive terminal needs to receive and process the cost verification results returned by the verification terminal, and integrate the abnormal cost information found in the verification into the patient's diagnosis and treatment details to form a complete and accurate diagnosis and treatment cost report. In this way, the interactive terminal can help patients fully understand their diagnosis and treatment conditions and cost structure, and improve the transparency and credibility of medical services.

[0052] In the specific implementation, the interactive terminal first needs to establish a stable and secure data transmission channel with the verification terminal to ensure that the verification results can be delivered in a timely and accurate manner. Here, the interactive terminal can use technologies such as encrypted transmission and digital signatures to protect the confidentiality and integrity of the data. At the same time, the interactive terminal also needs to design a standardized verification result format, such as JSON, XML, etc., to facilitate the parsing and processing of the result data.

[0053] After receiving the verification results, the interactive terminal needs to automatically extract the abnormal cost information, such as the time when the abnormality occurred, the name of the drug, the type of abnormality, the amount involved, etc., and compare and associate it with the original medical expense records. For the cost items confirmed as abnormal, the interactive terminal needs to clearly mark them in the medical details and generate a brief abnormal description, such as "drug duplication", "self-paid drugs not informed to patients", etc., to remind patients to pay attention.

[0054] When generating an exception explanation, the interactive terminal can refer to the abnormal cause analysis and handling opinions provided by the verification terminal, and provide more specific and reasonable explanations and suggestions in combination with the hospital's management regulations and the patient's actual situation. For example, for abnormal expenses caused by the wrong drug delivery, the interactive terminal can tell the patient how to apply for a refund or replacement; for abnormal expenses caused by system failures, the interactive terminal can tell the patient how to negotiate with the hospital to resolve the problem.

[0055] At the same time, in order to help patients better understand the impact of abnormal expenses and subsequent processing, the interactive terminal can also provide some intuitive visualization elements when generating diagnosis and treatment details, such as a pie chart showing the proportion of abnormal expenses in total expenses, a time trend chart of abnormal expenses, etc., so that patients can understand their abnormal expenses at a glance. For some complex medical terms and processing procedures, the interactive terminal can also provide pop-up explanations, or link to authoritative medical knowledge bases, to facilitate patient inquiries and understanding.

[0056] S107. The interactive terminal integrates the diagnosis and treatment details, static expense items, and dynamic expense items to generate a patient daily list, and displays the patient daily list according to a preset layout rule.

[0057] In this step, the interactive terminal needs to summarize and organize all the cost information obtained and analyzed previously, generate an intuitive and complete patient daily list, and present the list content to the patient according to the preset display layout rules. The patient daily list is an important basis for patients to understand and manage daily medical expenses. Through standardized and beautiful list design, the readability and interactivity of the cost information can be improved, helping patients to view their cost details more conveniently and pleasantly.

[0058] When integrating cost information, the interactive terminal needs to classify and summarize the patient's diagnosis and treatment details, static cost items, dynamic cost items, etc., extract key cost indicators and description information, and organize them in a certain order and format. For example, at the top of the daily list, the interactive terminal can display the patient's basic information, such as name, hospitalization number, ward, etc.; in the main part of the list, the interactive terminal can list the cost amount and details of each major item according to static costs, drug costs, examination costs, etc.; at the bottom of the list, the interactive terminal can summarize the total cost of the day and compare it with the cost of the previous day to indicate the increase or decrease in costs.

[0059] When designing the display layout of the daily list, the interactive terminal can fully consider the patient's reading habits and visual experience, adopt a clear and beautiful table or card design, reasonably arrange the position and size of different expense items, and highlight key information. For example, for expense items with large amounts or abnormalities, the interactive terminal can use eye-catching colors or icons to mark them, so that patients can quickly locate them; for some professional terms or abbreviations, the interactive terminal can provide floating prompts or annotations to facilitate patient understanding.

[0060] At the same time, in order to cater to the reading preferences of different patients, the interactive terminal can provide a variety of display layout templates, such as concise, detailed, and chart types, allowing patients to choose and switch independently. For some patients with poor vision or inflexible finger operation, the interactive terminal can also provide barrier-free access modes such as large fonts and voice broadcasts to improve the accessibility of list information.

[0061] When displaying the patient's daily list, the interactive terminal can also provide some intelligent interactive functions, such as supporting the screening, sorting, and searching of expense items, so that patients can quickly find and locate specific expense information; supporting the zooming in, zooming out, and turning pages of the list content, so that patients can flexibly adjust the display mode of the list; supporting the addition of marks or annotations to the expense items of interest, so that patients can record and track expense changes, etc. In addition, the interactive terminal can also automatically optimize the display layout and interactive mode of the list based on the patient's viewing behavior and feedback, and continuously improve the patient's user experience.

[0062] In the above embodiment, static costs and dynamic costs are separated from the cost records through the interactive terminal, and the drug costs are finely classified and analyzed by time period, and the cost fluctuation coefficient of each time period is calculated, so that abnormal cost fluctuations can be discovered in time. When abnormal costs are found, the interactive terminal automatically sends verification information to the verification terminal and receives the verification results, and generates diagnosis and treatment details including abnormal descriptions. This dynamic monitoring and multi-party collaboration method enables abnormal costs to be quickly identified and explained. By integrating diagnosis and treatment details with cost items to form a patient's daily list, patients can clearly understand the daily cost composition and reasons for changes, which enhances the comprehensibility of cost information. This time-based cost analysis and abnormal verification mechanism can not only help medical institutions to discover and handle abnormal costs in a timely manner, but also keep patients fully informed, thereby improving the efficiency and accuracy of synchronizing specific medical behaviors and cost information to patients, thereby reducing the lag and opacity of information synchronization.

[0063] The implementation process of the above embodiment mainly involves the classification analysis and abnormal identification of expenses, but does not conduct an in-depth analysis of the relationship between medical orders. Given that medical expenses are often generated by the combined implementation of multiple medical orders, monitoring expenses only from the perspective of a single medical order may not fully reflect the actual reasons for the change in expenses. Therefore, it is necessary to establish a cost monitoring mechanism based on the relationship between medical orders to more comprehensively grasp the law of cost changes. Figure 2 , a cost monitoring method based on medical advice association analysis in an embodiment of the present application is described: See also Figure 2 , which is a flow chart of a cost monitoring method based on medical order association analysis in an embodiment of the present application.

[0064] S201, the interactive terminal detects whether there is related medical advice information in the diagnosis and treatment details; The interactive terminal detects whether there is associated medical advice information in the diagnosis and treatment details, and the associated medical advice information includes medical advice fees.

[0065] In this step, the interactive terminal needs to analyze and process the diagnosis and treatment details data to identify whether it contains association information between multiple medical orders. Medical order association information reflects the logical dependency and temporal constraint relationship between different medical behaviors, which is of great significance for understanding the causes and changing patterns of medical expenses. Associated medical order information usually includes various expense data related to the execution of medical orders, such as drug fees, examination fees, and surgical fees. The correlation and combination characteristics of these expense data are important bases for subsequent cost analysis and abnormal monitoring.

[0066] In specific implementation, the interactive terminal can use rule-based pattern matching technology to predefine a series of identification rules and extraction templates for related medical orders, such as keywords in the name of medical order items, consistency of execution departments, time difference range, etc., and then use these rules to match and filter the diagnosis and treatment details data to find those medical order combinations that may be related and their corresponding cost information. At the same time, the interactive terminal can also use external knowledge sources such as medical knowledge graphs and medical order standard libraries to infer and judge the semantic relationship between medical orders, discover those implicit and indirect associations, and expand the coverage of related information.

[0067] S202, when the associated medical advice information is detected, the interactive terminal extracts the execution time series data corresponding to the associated medical advice information; When the associated medical order information is detected, the interactive terminal extracts the execution timing data corresponding to the associated medical order information, and the execution timing data includes the medical order issuance time, execution time and execution order.

[0068] In this step, when the interactive terminal recognizes that there is related medical order information in the diagnosis and treatment details, it is necessary to further extract the execution time series data of these related medical orders to provide data support for the subsequent cost correlation analysis. The medical order execution time series data records the execution process of each medical order on the timeline, including the specific time points of each link such as medical order issuance, review, execution, and stop, as well as the execution sequence between each medical order, reflecting the whole process and dynamic changes of medical order execution, and is an important basis for judging the causal relationship of medical orders.

[0069] In specific implementation, the interactive terminal can obtain the execution time series data of the associated medical orders in real time by connecting with clinical data platforms such as hospital information systems (HIS) and electronic medical record systems. In the process of data extraction, in order to ensure the accuracy and completeness of the time series data, the interactive terminal also needs to perform necessary preprocessing on the acquired raw data, such as data cleaning, format conversion, timestamp verification, etc., to improve data quality and availability. For some cases where time series data is missing or inconsistent, the interactive terminal can use data repair techniques such as interpolation and estimation to reasonably complete the missing values. In addition, the interactive terminal can also use technologies such as time series databases and time series indexes to optimize the storage and retrieval performance of time series data, providing efficient support for subsequent real-time analysis and display.

[0070] S203, the interactive terminal identifies a combination of medical orders having a causal relationship based on the execution time series data and the preset medical order association rules; The interactive terminal identifies a combination of medical orders with a causal relationship based on execution time series data and preset medical order association rules. The preset medical order association rules are that the time interval between medical order issuance is less than the first preset time length and the time interval between executions is less than the second preset time length. The medical order combination includes at least two related medical order information connected in execution order. Specifically: the interactive terminal extracts the start and end time points of the execution time corresponding to each related medical order information; the interactive terminal calculates the time overlap between the related medical order information adjacent in execution order based on the start and end time points; the interactive terminal determines the related medical order information with a time overlap greater than the preset time overlap threshold as an alternative medical order combination; the interactive terminal determines the alternative medical order combination that meets the preset medical order association rules as the medical order combination.

[0071] In this step, the interactive terminal needs to extract the time series data of the execution of medical orders and use the preset association rules to intelligently identify those medical order combinations with close causal relationships. The combination of medical orders reflects the mutual influence and constraint relationship between multiple medical behaviors in the clinical diagnosis and treatment process, which is of great significance for analyzing and predicting the evolution of medical expenses. The automatic discovery of causal relationships guided by association rules can help the interactive terminal grasp the internal logic of cost changes more comprehensively and accurately.

[0072] In the specific implementation, the interactive terminal first needs to summarize and preset a series of rules for judging the causal relationship of medical orders based on the practical experience of hospital management and clinical diagnosis and treatment. The formulation of rules needs to fully consider the time factors, logical factors and medical factors of medical order execution, and establish sensitive and effective identification conditions for strongly related medical order combinations. For example, the rules can set the maximum time interval between related medical orders and the time interval between execution, and give higher relevance to those medical orders that are highly adjacent in time; the rules can also set logically strong dependent medical order patterns such as medication compatibility, test packages, and preoperative preparations as important references for determining causal relationships; the rules can also use medical knowledge such as disease clinical pathways and diagnosis and treatment specifications to define and constrain key medical order combinations at different diagnosis and treatment stages of the same disease, thereby assisting the reasoning of causal relationships.

[0073] Based on the preset association rules, the interactive terminal can comprehensively scan and compare the time series data of medical order execution, and identify those combinations of medical orders that are close in time, logically related, and clinically reasonable, as the key research objects of causal analysis. In the process of causal analysis, the interactive terminal needs to further refine the feature extraction and rule matching of time series data. On the one hand, the interactive terminal can calculate the overlap of execution time windows, the mean and variance of time intervals in the time series data, and quantitatively characterize the temporal relationship of medical orders; on the other hand, the interactive terminal can also use regular expressions, semantic parsing and other technologies to deeply match the text content of medical orders, extract association clues and verify rule conditions.

[0074] For the identified alternative medical order combinations, the interactive terminal also needs to combine statistical methods and medical knowledge to further screen and confirm the causal relationship. For example, the interactive terminal can use correlation tests, causal inference and other methods to analyze the necessity of executing the medical orders in the combination, and eliminate those combinations with insignificant correlation. The interactive terminal can also use professional knowledge such as pharmacological action mechanisms and physiological and pathological principles to deduce the causal logic of medical orders from the perspectives of drug efficacy mechanisms and disease etiology to improve the accuracy of combination screening. After completing the screening, the interactive terminal can output a series of credible and highly causally related medical order combinations, providing key research directions for subsequent cost correlation analysis.

[0075] It should be noted that due to the complexity and diversity of disease conditions and diagnosis and treatment methods, the association pattern of medical order combinations may show the characteristics of dynamic changes, and the preset static association rules may have the risk of omission or misjudgment. Therefore, the interactive terminal also needs to establish a continuous optimization mechanism for association rules, and continuously mine the diagnosis and treatment data through big data analysis and machine learning technology, and continuously learn new association pattern features from them to correct and expand the original rules. At the same time, the interactive terminal can also introduce an active learning mechanism, actively obtain human experience and guidance through expert feedback and interactive verification, and correct and reinforce the association hypothesis automatically discovered by the machine, so as to continuously improve the accuracy and comprehensiveness of causal analysis. In short, based on fine-grained time series feature extraction and flexible dynamic association rule mining, and continuous iterative optimization under the guidance of machine intelligence and human experience, the interactive terminal can more intelligently, comprehensively and accurately realize the causal relationship identification of medical order combinations, thereby providing a solid foundation for in-depth understanding of the law of cost changes.

[0076] S204, the interactive terminal calculates the cost association strength for the medical order combination; The interactive terminal calculates the cost association strength for the medical order combination, where the cost association strength is the degree of correlation between each associated medical order information in the medical order combination and the medical order cost.

[0077] In this step, the interactive terminal needs to further quantitatively evaluate the strength of the correlation between the various medical order costs in the medical order combination after identifying the medical order combination with a causal relationship. The cost correlation strength reflects the degree of influence of the cost change of one medical order on the cost change of other related medical orders, and intuitively reflects the close connection and restrictive effect of each link of the medical order combination. By depicting the linkage characteristics between related medical order costs, the interactive terminal can accurately grasp the sensitive nodes and risk units of the medical order combination costs, laying the foundation for targeted implementation of key monitoring.

[0078] In specific implementation, the interactive terminal can use a variety of correlation analysis and statistical modeling methods to quantitatively examine the linear or nonlinear relationship between the medical order cost elements in the medical order combination, and then obtain a comprehensive indicator that describes the overall correlation strength. Common analysis methods include Pearson correlation coefficient, Spearman rank correlation coefficient, mutual information, maximum information coefficient, etc. These methods describe the similarity, monotonicity, dependence and other characteristics between variables from different perspectives. The interactive terminal can select one or more analysis methods according to the distribution characteristics of the data and the purpose of analysis to calculate the correlation strength of the cost data matrix of the medical order combination.

[0079] After selecting the appropriate association measurement method, the interactive terminal needs to further optimize the feature representation and computational efficiency of the data. On the one hand, since the cost data of the medical order combination usually presents non-stationary and high-dimensional characteristics, the interactive terminal needs to perform necessary preprocessing on the data before calculating the association strength, such as stabilization, dimensionality reduction, and normalization, to improve the discoverability of the association pattern. For example, the interactive terminal can use the difference method to eliminate the trend item of the cost sequence and highlight the driving factors of cost changes; for another example, the interactive terminal can use dimensionality reduction algorithms such as principal component analysis to extract the low-dimensional dense features of the cost data and calculate the association strength on this basis.

[0080] On the other hand, when the number of medical orders is large, the amount of calculation for calculating the correlation between each order in the combination will show a combinatorial explosion trend, which will bring great pressure to real-time analysis and response. In order to improve the efficiency of correlation strength analysis, the interactive terminal can use some fast approximate algorithms to obtain the estimated value of the correlation with an acceptable loss of accuracy. For example, the interactive terminal can use the local sensitive hashing technology to map the original high-dimensional cost data to a low-dimensional hash space through random projection transformation, and obtain the approximate correlation strength of the cost elements in the hash space through fast metrics such as Hamming distance.

[0081] After obtaining the pairwise correlation strength of each cost element of the medical order combination, the interactive terminal also needs to design a comprehensive strength evaluation index, taking into account each pairwise correlation degree, and quantitatively characterizing the overall cost correlation level of the entire medical order combination. When designing the evaluation index, it is necessary to reasonably consider factors such as the importance differences of different medical order items and the typical patterns of correlation relationships. For example, the interactive terminal can use a weighted average method to assign weight coefficients to each pairwise correlation degree to highlight the contribution of the core medical order items; the interactive terminal can also introduce a network model to map the correlation degree to the connection strength of the network, and use certain topological feature measurements of the network, such as average degree, clustering coefficient, etc., to characterize the overall correlation complexity.

[0082] S205. When the cost association strength exceeds a preset threshold, the interactive terminal marks the medical order combination as a key monitoring object.

[0083] In this step, the interactive terminal needs to determine whether the medical order combination meets the key monitoring standard based on the cost correlation strength index calculated in the previous step, and mark those that exceed the standard with early warning. When the cost linkage of the medical order combination exceeds a certain limit, it means that the overall cost risk of the combination is relatively high, and any abnormal fluctuation of the medical order in the combination may trigger a chain reaction, resulting in the total cost being out of control. Therefore, it is necessary to include highly correlated abnormal medical order combinations in the key monitoring category and adopt more stringent early warning measures and control methods.

[0084] In the specific implementation, the interactive terminal first needs to set an early warning threshold for the correlation strength of the medical order combination costs based on years of historical data and expert experience, as a judgment boundary for dividing the key monitoring objects. The setting of the threshold needs to take into account the sensitivity and accuracy of monitoring, that is, it is necessary to cover as many potential high-risk medical order combinations as possible to improve the detection rate of risk problems, and to avoid too many false alarms and reduce unnecessary manual investigation costs. Therefore, when determining the threshold, the interactive terminal can use a variety of statistical inference methods, such as hypothesis testing, confidence interval estimation, ROC curve analysis, etc., and combine the risk events of historical medical order combinations to evaluate the actual effect of the monitoring plan under different threshold conditions, and then find the optimal threshold that takes into account multiple goals.

[0085] In the above embodiment, the associated medical order information is detected and the execution time series data is extracted, the medical order combination with causal relationship is identified, the cost correlation strength is calculated and the medical order combination with high correlation strength is monitored. This cost monitoring method based on the correlation of medical orders can discover the correlation patterns between cost items that are apparently independent but actually have causal relationships. By tracking the cost change trends of key monitored objects in real time, the interactive terminal can identify potential cost anomalies from the perspective of the logical relationship of medical order execution. This cost monitoring method based on the correlation of medical orders reduces the limitations of monitoring a single cost item, can more comprehensively grasp the medical logic behind cost changes, and improves the depth and accuracy of cost monitoring.

[0086] Furthermore, in another embodiment, after the interactive terminal tracks the cost change trend of the key monitored object in real time, the method further includes: the interactive terminal obtains historical cost data of the key monitored object, the historical cost data being the accumulated cost amount of each medical order combination within a preset period; The interactive terminal establishes a fee benchmark interval based on the average and standard deviation of the accumulated fee amount; The interactive terminal obtains the current fee and calculates the degree of deviation between the current fee and the fee benchmark interval, and extracts the fee data of several billing cycles from the current moment; The interactive terminal removes abnormal fluctuation points in the cost data to obtain cleaning cost data; The interactive terminal compares the cleaning cost data with the cost benchmark interval to obtain the degree of deviation; The interactive terminal generates a cost risk level based on the degree of deviation.

[0087] In the above embodiment, historical cost data of key monitored objects are obtained and a cost benchmark interval is established, forming a dynamic cost assessment standard. The degree of deviation of the current cost is calculated based on the cost benchmark interval, and quantitative judgment of cost anomalies is achieved. The mechanism of generating cost risk levels according to the degree of deviation converts continuous cost deviations into discrete risk levels, making cost risks easier to understand and manage. This cost risk assessment method based on historical data takes into account the cost differences between different patients and different treatment plans, and reduces the judgment bias caused by the use of unified standards. By establishing a corresponding relationship between costs and risk levels, the interactive terminal can promptly detect cost anomalies and issue risk warnings, thereby enhancing the pertinence and effectiveness of medical cost management.

[0088] The following describes the interactive terminal in the embodiment of the present invention from the perspective of hardware processing. Figure 3 , which is a schematic diagram of the physical device structure of a bedside doctor-patient information interaction terminal provided in an embodiment of the present application.

[0089] It should be noted that Figure 3 The structure of the interactive terminal shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0090] like Figure 3 As shown, the interactive terminal includes a central processing unit (CPU) 301, which can perform various appropriate actions and processes according to the program stored in the read-only memory (ROM) 302 or the program loaded from the storage part 308 to the random access memory (RAM) 303, such as executing the method in the above embodiment. Various programs and data required for system operation are also stored in the RAM 303. The CPU 301, ROM 302 and RAM 303 are connected to each other through a bus 304. The input / output (I / O) interface 305 is also connected to the bus 304.

[0091] The following components are connected to the I / O interface 305: an input section 306 including a camera, an infrared sensor, etc.; an output section 307 including a liquid crystal display (LCD) and a speaker, etc.; a storage section 308 including a hard disk, etc.; and a communication section 309 including a network interface card such as a LAN (Local Area Network) card, a modem, etc. The communication section 309 performs communication processing via a network such as the Internet. A drive 310 is also connected to the I / O interface 305 as needed. A removable medium 311, such as a magnetic disk, an optical disk, a magneto-optical disk, a semiconductor memory, etc., is installed on the drive 310 as needed so that a computer program read therefrom is installed into the storage section 308 as needed.

[0092] In particular, according to an embodiment of the present invention, the process described above with reference to the flowchart can be implemented as a computer software program. For example, an embodiment of the present invention includes a computer program product, which includes a computer program carried on a computer-readable medium, and the computer program includes a computer program for executing the method shown in the flowchart. In such an embodiment, the computer program can be downloaded and installed from a network through the communication part 309, and / or installed from a removable medium 311. When the computer program is executed by the central processing unit (CPU) 301, various functions defined in the present invention are performed.

[0093] It should be noted that the computer-readable medium shown in the embodiment of the present invention may be a computer-readable signal medium or a computer-readable storage medium or any combination of the above two. The computer-readable storage medium may be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, device or device, or any combination of the above. More specific examples of computer-readable storage media may include, but are not limited to: an electrical connection with one or more wires, a portable computer disk, a hard disk, a random access memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM), a flash memory, an optical fiber, a portable compact disk read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the above. In the present invention, a computer-readable storage medium may be any tangible medium containing or storing a program, which may be used by or in combination with an instruction execution system, device or device. In the present invention, a computer-readable signal medium may include a data signal propagated in a baseband or as part of a carrier wave, which carries a computer-readable computer program. Such a propagated data signal may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing.

[0094] The flowcharts and block diagrams in the accompanying drawings illustrate the possible architecture, functions and operations of the systems, methods and computer program products according to various embodiments of the present invention. Among them, each box in the flowchart or block diagram can represent a module, a program segment, or a part of the code, and the above-mentioned module, program segment, or a part of the code contains one or more executable instructions for implementing the specified logical function. It should also be noted that in some alternative implementations, the functions marked in the box can also occur in a different order from the order marked in the accompanying drawings. For example, two boxes represented in succession can actually be executed substantially in parallel, and they can sometimes be executed in the opposite order, depending on the functions involved. It should also be noted that each box in the block diagram or flowchart, and the combination of boxes in the block diagram or flowchart, can be implemented with a dedicated hardware-based system that performs a specified function or operation, or can be implemented with a combination of dedicated hardware and computer instructions.

[0095] As another aspect, the present invention further provides a computer-readable storage medium, which may be included in the system described in the above embodiment; or may exist independently without being assembled into the system. The above storage medium carries one or more computer programs, and when the above one or more computer programs are executed by a processor of a system, the system implements the method provided in the above embodiment.

[0096] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not cause the essence of the corresponding technical solutions to deviate from the scope of the technical solutions of the embodiments of the present application.

[0097] As used in the above embodiments, the term "when..." may be interpreted to mean "if..." or "after..." or "in response to determining..." or "in response to detecting...", depending on the context. Similarly, the phrases "upon determining..." or "if (the stated condition or event) is detected" may be interpreted to mean "if determining..." or "in response to determining..." or "upon detecting (the stated condition or event)" or "in response to detecting (the stated condition or event)", depending on the context.

[0098] In the above embodiments, it can be implemented in whole or in part by software, hardware, firmware or any combination thereof. When implemented using software, it can 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. When the computer program instructions are loaded and 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 transmitted from one computer-readable storage medium to another computer-readable storage medium. For example, the computer instructions may be transmitted from a website site, computer, server or data center to another website site, computer, server or data center by wired (e.g., coaxial cable, optical fiber, digital subscriber line) or wireless (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 includes one or more available media integrated. 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 (e.g., a solid-state hard disk), etc.

[0099] Those skilled in the art can understand that to implement all or part of the processes in the above-mentioned embodiments, the processes can be completed by computer programs to instruct related hardware, and the programs can be stored in computer-readable storage media. When the programs are executed, they can include the processes of the above-mentioned method embodiments. The aforementioned storage media include: ROM or random access memory RAM, magnetic disk or optical disk and other media that can store program codes.

Claims

1. A bedside doctor-patient information interaction method, characterized in that: include: The interactive terminal, in response to the patient clicking the information acquisition button, retrieves the current diagnosis and treatment data from the preset information library based on the patient identification of the patient, the diagnosis and treatment data including diagnosis and treatment records and expense records; The interactive terminal extracts static expense items and dynamic expense items from the expense record, wherein the static expense items include bed fees and nursing fees, and the dynamic expense items include drug fees and examination fees; The interactive terminal classifies the drug expenses according to the preset drug use periods to obtain the cost distribution of the first period, the second period and the third period; The interactive terminal calculates the cost fluctuation coefficient of each time period based on the cost distribution of the first time period, the second time period and the third time period; When the interactive terminal determines that any of the cost fluctuation coefficients exceeds the warning threshold, the interactive terminal sends cost anomaly verification information to the verification terminal; The interactive terminal receives the verification result sent by the verification terminal, wherein the verification result includes abnormal fee information; The interactive terminal generates diagnosis and treatment details including an explanation of the abnormal cost based on the abnormal cost information; The interactive terminal integrates the diagnosis and treatment details, the static expense items and the dynamic expense items to generate a patient daily list; The interactive terminal displays the patient daily list according to a preset layout rule.

2. The method according to claim 1, characterized in that The retrieving the diagnosis and treatment data of the current time from the preset information library based on the patient identification of the patient specifically includes: The interactive terminal obtains hospitalization information corresponding to the patient identifier, wherein the hospitalization information includes admission time and ward information; The interactive terminal calculates the number of hospitalization days based on the admission time, and compares the number of hospitalization days with a preset hospitalization cycle; When the number of hospitalization days reaches a preset proportion of the preset hospitalization period, the interactive terminal extracts historical expense data from a preset information database; The interactive terminal calculates an average daily cost benchmark value based on the historical cost data; The interactive terminal extracts the diagnosis and treatment data of the current time from the preset information library, and associates the average daily cost benchmark value with the diagnosis and treatment data to obtain a diagnosis and treatment record and a cost record.

3. The method according to claim 1, characterized in that The interactive terminal classifies the drug expenses according to the preset drug use periods to obtain the cost distribution of the first period, the second period and the third period, specifically including: The interactive terminal obtains the frequency of medication, which includes daily fixed frequency medication and temporary medical prescription medication; The interactive terminal divides the daily fixed-frequency medication into corresponding time periods in the preset medication time periods according to the medication time, and the preset medication time periods include a first time period, a second time period, and a third time period; The interactive terminal performs medication time statistics on the temporary medical prescription medication to obtain statistical results; The interactive terminal allocates the temporary medical prescription medication to the closest time period based on the statistical result, and obtains the cost distribution of the first time period, the second time period and the third time period.

4. The method according to claim 1, characterized in that After the interactive terminal displays the patient daily list according to the preset layout rule, the method further includes: The interactive terminal detects whether there is associated medical advice information in the diagnosis and treatment details, and the associated medical advice information includes medical advice fees; When the associated medical order information is detected, the interactive terminal extracts execution time sequence data corresponding to the associated medical order information, wherein the execution time sequence data includes the medical order issuance time, execution time and execution order; The interactive terminal identifies a medical order combination with a causal relationship based on the execution time series data and a preset medical order association rule, wherein the preset medical order association rule is that the time interval between the issuance of the medical order is less than a first preset time length and the time interval between the executions is less than a second preset time length, and the medical order combination includes at least two pieces of associated medical order information connected in the execution order; The interactive terminal calculates the cost association strength for the medical order combination, where the cost association strength is the degree of correlation between each associated medical order information in the medical order combination and the medical order cost; When the cost association strength exceeds a preset threshold, the interactive terminal marks the medical order combination as a key monitoring object.

5. The method according to claim 4, characterized in that The interactive terminal identifies a combination of medical orders having a causal relationship based on the execution time series data and the preset medical order association rules, specifically including: The interactive terminal extracts the start and end time points of the execution time corresponding to each of the associated medical advice information; The interactive terminal calculates the time overlap between the associated medical order information adjacent in the execution order based on the start and end time points; The interactive terminal determines the associated medical order information with a time overlap greater than a preset time overlap threshold as a candidate medical order combination; The interactive terminal determines the candidate medical order combination that meets the preset medical order association rule as the medical order combination.

6. The method according to claim 4, characterized in that After the interactive terminal marks the medical order combination as a key monitoring object, the method further includes: The interactive terminal obtains the historical cost data of the key monitored object, wherein the historical cost data is the accumulated cost amount of each medical order combination within a preset period; The interactive terminal establishes a fee reference interval based on the average value and standard deviation of the accumulated fee amount; The interactive terminal obtains the current fee and calculates the degree of deviation between the current fee and the fee reference interval; The interactive terminal generates a cost risk level according to the degree of deviation.

7. The method according to claim 6, characterized in that The calculating the degree of deviation between the current fee and the fee benchmark range specifically includes: The interactive terminal extracts cost data of several billing cycles from the current moment; The interactive terminal removes abnormal fluctuation points in the cost data to obtain cleaning cost data; The interactive terminal compares the cleaning fee data with the fee reference interval to obtain a degree of deviation.

8. A bedside doctor-patient information interaction terminal, characterized in that: The interactive terminal comprises: One or more processors and a memory; the memory is coupled to the one or more processors, the memory is used to store computer program code, the computer program code includes computer instructions, and the one or more processors call the computer instructions to enable the interactive terminal to execute the method as described in any one of claims 1-7.

9. A computer-readable storage medium comprising instructions, characterized in that: When the instruction is executed on the interactive terminal, the interactive terminal is caused to execute the method according to any one of claims 1 to 7.

10. A computer program product, characterized in that When the computer program product is executed on an interactive terminal, the interactive terminal is enabled to execute the method according to any one of claims 1 to 7.

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