Nursing unit risk level assessment method and device and processing equipment

Abstract

The invention provides a nursing unit risk level assessment method, a nursing unit risk level assessment device and processing equipment, which are used for introducing an automatic online system to efficiently complete risk level assessment of a nursing unit and providing a three-dimensional five-degree index based on clinical data driving in details. Therefore, the risk level assessment of the nursing unit can be comprehensively, objectively, fairly and visually realized, a high-precision risk level assessment effect can be promoted, safe and quick-response nursing unit management work can be further realized, high-quality clinical nursing quality and high-efficiency human resource utilization are promoted, and the method has a better application value.

Description

Technical Field

[0001] The present application relates to the field of medical technology, and in particular to a method, device and processing equipment for assessing the risk level of a nursing unit. Background Art

[0002] Ensuring the maximum utilization of nurse human resources in nursing human resource management and ensuring patient safety and improving nursing quality in clinical nursing have become important goals of major medical institutions. Nursing units (nursing units are basic nursing units composed of doctors, nurses, care workers, several patient beds, related diagnosis and treatment, and attached medical, living, management, transportation and other rooms, which are existing concepts in themselves) are key areas for patient care. Therefore, the effectiveness of risk management of nursing units can directly affect the health and quality of care of patients.

[0003] The inventors of this application have discovered that traditional risk assessment schemes for nursing units usually rely on manual records and subjective judgments, which are not only prone to delays in information processing, but may also lead to insufficient accuracy in risk identification, resulting in low effectiveness of nursing unit risk management. Summary of the invention

[0004] The present application provides a nursing unit risk level assessment method, device and processing equipment, which are used to introduce an automated online system to efficiently complete the risk level assessment of the nursing unit. At the same time, a three-dimensional five-dimensional indicator driven by clinical data is proposed in detail. This can not only comprehensively, objectively, fairly and visually realize the risk level assessment of the nursing unit, but also promote high-precision risk level assessment effects, thereby realizing safe and fast-response nursing unit management, promoting high-quality clinical nursing quality and efficient human resource utilization, and having better application value.

[0005] In a first aspect, the present application provides a method for assessing the risk level of a nursing unit, the method comprising:

[0006] With the triggering of the current monitoring time point, clinical data including doctor's orders and medical contents are obtained from the pre-connected online business system of the relevant hospital through the preset data transmission channel, so as to achieve the purpose of integrating information from various clinical data sources;

[0007] Based on clinical data, the risk levels of different nursing units involved in the current situation are determined in accordance with the pre-configured three-dimensional five-dimensional indicators. The three-dimensional five-dimensional indicators specifically involve the three dimensions of nursing workload, nursing work difficulty and nursing practice risk. The nursing workload dimension specifically involves the indicator of correction workload, the nursing work difficulty dimension specifically involves the three indicators of graded nursing RIDIT value, critical patient RIDIT value and specialist CMI value, and the nursing practice risk dimension specifically involves the indicator of practice risk.

[0008] Obtain the risk levels of different nursing units under historical circumstances previously determined at historical monitoring time points;

[0009] Based on the risk level in the current situation and the risk levels of different nursing units in historical situations, the risk changes of different nursing units are dynamically monitored.

[0010] In combination with the first aspect of the present application, in a first possible implementation method of the first aspect of the present application, the relevant hospital online business system specifically includes an HIS system, a medical technology workstation, a nurse workstation and a charging system.

[0011] In combination with the first aspect of the present application, in a second possible implementation of the first aspect of the present application, after dynamically monitoring the risk changes of different nursing units in combination with the risk level in the current situation and the risk levels of different nursing units in historical situations, the method further includes:

[0012] Push or display dynamic monitoring results to relevant users to prompt timely response and human resource adjustments.

[0013] In combination with the first aspect of the present application, in a third possible implementation of the first aspect of the present application, after dynamically monitoring the risk changes of different nursing units in combination with the risk level in the current situation and the risk levels of different nursing units in historical situations, the method further includes:

[0014] The dynamic monitoring results are pushed to the preset hospital night shift performance management system, human resources management system and nursing quality management system.

[0015] In combination with the first aspect of the present application, in a fourth possible implementation of the first aspect of the present application, the current monitoring time point and the historical monitoring time point are specifically preset time points with a period of 1 day.

[0016] In combination with the first aspect of the present application, in a fifth possible implementation of the first aspect of the present application, for different nursing units, the three-dimensional five-dimensional indicators have the following processing contents:

[0017] The workload of correction is the sum of the difficulty coefficient of each nursing technique and the corresponding frequency of medical advice;

[0018] RIDIT value of graded nursing = (third-level nursing weight × number of third-level nursing bed days + second-level nursing weight × number of second-level nursing bed days + first-level nursing weight × number of first-level nursing bed days + special-level nursing weight × number of special-level nursing bed days) / first total bed days;

[0019] RIDIT value of critically ill patients = (normal weight × total number of days for normal patients + severe weight × total number of days for severe patients + critical weight × total number of days for critical patients) / total number of days for the second;

[0020] Specialist CMI values ​​are reported regularly by the Medical Department;

[0021] The practice risk takes a fixed value.

[0022] In combination with the fifth possible implementation of the first aspect of the present application, in a sixth possible implementation of the first aspect of the present application, for different nursing units, the risk levels in the current situation have the following processing contents:

[0023] Obtain the values ​​of each indicator of the three-dimensional five-dimensional indicators;

[0024] Rank the values ​​of each indicator vertically, with high-quality indicators ranked from low to high;

[0025] On the basis of the ranking results, the rank of each indicator is multiplied by the indicator weight to calculate the weighted rank value of each indicator, and then the weighted rank values ​​of each indicator are added together to obtain the total weighted rank value;

[0026] The total rank values ​​of different nursing units are converted into corresponding probability values ​​in the probability distribution, and the different nursing units are classified according to the corresponding probability values. The corresponding 6 grades from high to low specifically include extremely high-risk nursing units, high-risk nursing units, relatively high-risk nursing units, medium-risk nursing units, low-risk nursing units and relatively low-risk nursing units.

[0027] In a second aspect, the present application provides a nursing unit risk level assessment device, the device comprising:

[0028] The acquisition unit is used to acquire clinical data including doctor's orders and medical contents from the pre-connected online business system of the relevant hospital through the preset data transmission channel as triggered by the current monitoring time point, so as to achieve the purpose of integrating information from various clinical data sources;

[0029] A determination unit is used to determine the risk level of different nursing units involved in the current situation based on clinical data and in accordance with pre-configured three-dimensional five-dimensional indicators, wherein the three-dimensional five-dimensional indicators specifically involve three dimensions: nursing workload dimension, nursing work difficulty dimension and nursing practice risk dimension. The nursing workload dimension specifically involves an indicator of correction workload, the nursing work difficulty dimension specifically involves three indicators of graded nursing RIDIT value, critical patient RIDIT value and specialist CMI value, and the nursing practice risk dimension specifically involves an indicator of practice risk;

[0030] The acquisition unit is also used to obtain the risk levels of different nursing units under historical circumstances previously determined at historical monitoring time points;

[0031] The monitoring unit is used to dynamically monitor the risk changes of different nursing units by combining the risk level under current circumstances and the risk levels of different nursing units under historical circumstances.

[0032] In combination with the second aspect of the present application, in a first possible implementation method of the second aspect of the present application, the relevant hospital online business system specifically includes a HIS system, a medical technology workstation, a nurse workstation and a charging system.

[0033] In conjunction with the second aspect of the present application, in a second possible implementation manner of the second aspect of the present application, the apparatus further includes an application unit, configured to:

[0034] Push or display dynamic monitoring results to relevant users to prompt timely response and human resource adjustments.

[0035] In combination with the second aspect of the present application, in a third possible implementation manner of the second aspect of the present application, the apparatus further includes an application unit, configured to:

[0036] The dynamic monitoring results are pushed to the preset hospital night shift performance management system, human resources management system and nursing quality management system.

[0037] In combination with the second aspect of the present application, in a fourth possible implementation of the second aspect of the present application, the current monitoring time point and the historical monitoring time point are specifically preset time points with a period of 1 day.

[0038] In combination with the second aspect of the present application, in a fifth possible implementation of the second aspect of the present application, for different nursing units, the three-dimensional five-dimensional indicators have the following processing contents:

[0039] The workload of correction is the sum of the difficulty coefficient of each nursing technique and the corresponding frequency of medical advice;

[0040] RIDIT value of graded nursing = (third-level nursing weight × number of third-level nursing bed days + second-level nursing weight × number of second-level nursing bed days + first-level nursing weight × number of first-level nursing bed days + special-level nursing weight × number of special-level nursing bed days) / first total bed days;

[0041] RIDIT value of critically ill patients = (normal weight × total number of days for normal patients + severe weight × total number of days for severe patients + critical weight × total number of days for critical patients) / total number of days for the second;

[0042] Specialist CMI values ​​are reported regularly by the Medical Department;

[0043] The practice risk takes a fixed value.

[0044] In combination with the fifth possible implementation of the second aspect of the present application, in a sixth possible implementation of the second aspect of the present application, for different nursing units, the risk levels in the current situation have the following processing contents:

[0045] Obtain the values ​​of each indicator of the three-dimensional five-dimensional indicators;

[0046] Rank the values ​​of each indicator vertically, with high-quality indicators ranked from low to high;

[0047] On the basis of the ranking results, the rank of each indicator is multiplied by the indicator weight to calculate the weighted rank value of each indicator, and then the weighted rank values ​​of each indicator are added together to obtain the total weighted rank value;

[0048] The total rank values ​​of different nursing units are converted into corresponding probability values ​​in the probability distribution, and the different nursing units are classified according to the corresponding probability values. The corresponding 6 grades from high to low specifically include extremely high-risk nursing units, high-risk nursing units, relatively high-risk nursing units, medium-risk nursing units, low-risk nursing units and relatively low-risk nursing units.

[0049] In a third aspect, the present application provides a processing device, including a processor and a memory, wherein a computer program is stored in the memory, and when the processor calls the computer program in the memory, the method provided in the first aspect of the present application or any possible implementation method of the first aspect of the present application is executed.

[0050] In a fourth aspect, the present application provides a computer-readable storage medium, which stores multiple instructions, and the instructions are suitable for a processor to load to execute the method provided by the first aspect of the present application or any possible implementation of the first aspect of the present application.

[0051] From the above content, it can be concluded that the present application has the following beneficial effects:

[0052] With regard to the management objectives of the nursing units, this application, triggered by the current monitoring time point, obtains clinical data including medical orders and medical contents from the pre-connected online business system of the relevant hospital through a preset data transmission channel. On the basis of the clinical data, the pre-configured three-dimensional five-dimensional indicators are followed to determine the risk levels of the different nursing units involved in the current situation. Combined with the risk level in the current situation and the risk level of different nursing units in historical situations, the risk changes of different nursing units are dynamically monitored. While introducing an automated online system to efficiently complete the risk level assessment of the nursing unit, a three-dimensional five-dimensional indicator driven by clinical data is proposed in detail, which can not only realize the risk level assessment of the nursing unit in a comprehensive, objective, fair and visual manner, but also promote high-precision risk level assessment results, thereby achieving safe and rapid response nursing unit management, promoting high-quality clinical nursing quality and efficient utilization of human resources, and having better application value. BRIEF DESCRIPTION OF THE DRAWINGS

[0053] In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings required for use in the description of the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the present application. For those skilled in the art, other drawings can be obtained based on these drawings without creative work.

[0054] Figure 1 A flowchart of the method for assessing the risk level of a nursing unit in this application;

[0055] Figure 2 A structural schematic diagram of a nursing unit risk level assessment method device of the present application;

[0056] Figure 3 A schematic diagram of the structure of the processing equipment of this application. DETAILED DESCRIPTION

[0057] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0058] The terms "first", "second", etc. in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects, and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described here can be implemented in an order other than that illustrated or described here. In addition, the terms "including" and "having" and any of their variations are intended to cover non-exclusive inclusions, for example, a process, method, system, product or device that includes a series of steps or modules is not necessarily limited to those steps or modules clearly listed, but may include other steps or modules that are not clearly listed or inherent to these processes, methods, products or devices. The naming or numbering of steps in this application does not mean that the steps in the method flow must be executed in the time / logical sequence indicated by the naming or numbering. The process steps that have been named or numbered can change the execution order according to the technical purpose to be achieved, as long as the same or similar technical effects can be achieved.

[0059] The division of modules in this application is a logical division. There may be other division methods when it is implemented in actual applications. For example, multiple modules can be combined or integrated into another system, or some features can be ignored or not executed. In addition, the mutual coupling or direct coupling or communication connection shown or discussed can be through some interfaces, and the indirect coupling or communication connection between modules can be electrical or other similar forms, which are not limited in this application. In addition, the modules or submodules described as separate components may or may not be physically separated, may or may not be physical modules, or may be distributed in multiple circuit modules, and some or all of the modules may be selected according to actual needs to achieve the purpose of the present application.

[0060] Before introducing the nursing unit risk level assessment method provided in this application, the background content involved in this application is first introduced.

[0061] The nursing unit risk level assessment method, device and computer-readable storage medium provided in the present application can be applied to processing equipment to efficiently complete the risk level assessment of the nursing unit while introducing an automated online system. In addition, a three-dimensional five-dimensional indicator driven by clinical data is proposed in detail. This can not only comprehensively, objectively, fairly and visually realize the risk level assessment of the nursing unit, but also promote high-precision risk level assessment results, thereby realizing safe and fast-response nursing unit management, promoting high-quality clinical nursing quality and efficient utilization of human resources, and having better application value.

[0062] The nursing unit risk level assessment method mentioned in this application can be executed by a nursing unit risk level assessment device, or a server, physical host or user equipment (UE) and other different types of processing devices integrated with the nursing unit risk level assessment device. Among them, the nursing unit risk level assessment device can be implemented in hardware or software, and the UE can be a terminal device such as a smart phone, tablet computer, laptop computer, desktop computer or personal digital assistant (PDA), and the processing device can be set in the form of a device cluster.

[0063] It can be understood that in specific applications, the nursing unit risk level assessment method provided by the present application can be configured through the application program / functional service of the nursing unit risk level assessment system, and the processing equipment that executes the nursing unit risk level assessment method of the present application, or the processing equipment equipped with the corresponding application service of the nursing unit risk level assessment method of the present application, considering that the present application is a data processing carried out on the basis of existing data, therefore generally speaking, its specific equipment type and equipment deployment form are relatively flexible, and can meet the required data processing capabilities.

[0064] As for the data acquisition (non-collection) stage and the use of risk assessment results, further adaptive adjustments can be made to the equipment type and equipment deployment form of the processing equipment based on actual conditions.

[0065] Next, we will introduce the nursing unit risk level assessment method provided by this application.

[0066] First, see Figure 1 , Figure 1 A flow chart of the nursing unit risk level assessment method of the present application is shown. The nursing unit risk level assessment method provided by the present application may specifically include the following steps S101 to S104:

[0067] Step S101, triggered by the current monitoring time point, obtains clinical data including doctor's orders and medical contents from the pre-connected online business system of the relevant hospital through a preset data transmission channel, so as to achieve the purpose of integrating information from various clinical data sources;

[0068] It can be understood that the nursing unit risk level assessment method provided by the present application, or the nursing unit risk level assessment system configured by the present application, is based on the consideration of convenient application, and uses the monitoring time point as a trigger condition to initiate the assessment process of the risk level of the nursing unit.

[0069] The monitoring time point can be preset or determined in real time, and may also involve the setting of the monitoring cycle.

[0070] The determination strategy behind determining the monitoring time point is relatively flexible. It can be determined manually or automatically according to the corresponding strategy to determine the best time point that matches the actual situation.

[0071] Furthermore, in some cases, the monitoring time point is not necessarily fixed and can be adjusted to suit different actual situations and application requirements.

[0072] It can be seen that in the data acquisition link here, this application specifically links the hospital's original online systems, namely the hospital's online business systems related to the nursing unit, and obtains clinical data including medical orders and medical content from them, so as to achieve the purpose of integrating information from various clinical data sources.

[0073] Behind this, it is understandable that medical institutions have a wide range of data sources, including electronic medical record systems, monitoring equipment, nursing records, etc. These data are often scattered in different systems. Traditional technologies lack effective integration and analysis methods, which makes it difficult to comprehensively assess the risk status of nursing units. After this application specifically configures this data integration setting, in-depth analysis and modeling of clinical data from different data sources will help achieve a comprehensive, objective, fair and visual assessment of nursing unit risk levels.

[0074] Specifically, as an exemplary embodiment, the relevant hospital online business system involved here may specifically include systems such as HIS system, medical technology workstation, nurse workstation and charging system.

[0075] Among them, HIS stands for Hospital Information System.

[0076] Step S102, based on the clinical data, following the pre-configured three-dimensional five-dimensional indicators, determine the risk level of the different nursing units involved in the current situation, wherein the three-dimensional five-dimensional indicators specifically involve three dimensions: nursing workload dimension, nursing work difficulty dimension and nursing practice risk dimension. The nursing workload dimension specifically involves the indicator of correction workload, the nursing work difficulty dimension specifically involves the three indicators of graded nursing RIDIT value, critical patient RIDIT value and specialist CMI value, and the nursing practice risk dimension specifically involves the indicator of practice risk;

[0077] It can be seen that in the face of the need to assess the risk level of the nursing unit, this application does not simply or broadly stay at the level of risk assessment based on the clinical data obtained previously. In specific operations, this application has conceived a novel assessment framework and carried out specific risk assessment work with specially set three-dimensional five-dimensional indicators as the core.

[0078] It is understandable that unified standards and specifications are provided for these indicators, which can avoid the problem that the risk assessment results are difficult to compare and standardize due to reliance on manual records and subjective judgments as in the prior art, thus affecting the scientificity and reliability of decision-making.

[0079] Here, RIDIT, namely, relative to an identified distribution unit, is a unit relative to a specific distribution. The RIDIT value is a quantitative value obtained by RIDIT analysis. RIDIT analysis is an existing non-parametric verification analysis method, so it is not described in detail.

[0080] CMI stands for Case Mix Index. The CMI value is also an existing indicator in clinical work.

[0081] The above-mentioned three-dimensional five-dimensional index is a new index system summarized by the inventor of this application from the complicated clinical nursing work. It covers multiple aspects such as nursing quality, workload, practice environment and compliance of the nursing process, ensuring the comprehensiveness and fairness of subsequent risk assessment.

[0082] Specifically, you can refer to Table 1 below to understand the indicator connotation, data source and calculation method involved in the three-dimensional five-dimensional index proposed in this application.

[0083] Table 1 - Content, data source and calculation method of each indicator

[0084]

[0085] Based on the contents shown in Table 1, it can be understood that, as an exemplary embodiment, the present application may have the following processing contents for the three-dimensional and five-dimensional indicators for different nursing units:

[0086] (1) The corrected workload is the sum of the difficulty coefficient of each nursing technique and the corresponding frequency of medical orders (i.e., cumulative);

[0087] All nursing work-related medical orders and their issuance / execution frequency of the nursing unit (based on the specific execution department involved) retrieved from the medical order system are accumulated / summed up by calculating the medical order frequency × the corresponding nursing technology difficulty coefficient to calculate the overall workload of the nursing unit.

[0088] In terms of details, inpatient department medical orders can use execution frequency, and outpatient department medical orders can use issuance frequency. If there are special circumstances, they can be marked in the system and specially handled.

[0089] (2) RIDIT value of graded nursing care = (third-level nursing weight × number of third-level nursing bed days + second-level nursing weight × number of second-level nursing bed days + first-level nursing weight × number of first-level nursing bed days + special-level nursing weight × number of special-level nursing bed days) / first total bed days;

[0090] Extract the number of bed days of "special care", "level I (first level) care", "level II (second level) care" and "level III (third level) care" of the nursing units, and calculate the weight of each level of care based on the total number of bed days in the hospital;

[0091] The RIDIT value of the nursing unit = (third-level nursing weight × third-level nursing bed days + second-level nursing weight × second-level nursing bed days + first-level nursing weight × first-level nursing bed days + special-level nursing weight × special-level nursing bed days) / total bed days.

[0092] Among them, some special nursing units without graded nursing bed days can use fixed values, which will be determined by the core group of the Nursing Department through discussion.

[0093] (3) RIDIT value for critically ill patients = (normal weight × total number of days for normal patients + severe weight × total number of days for severe patients + critical weight × total number of days for critical patients) / total number of days for the second time;

[0094] The medical order system assists in retrieving the number of bed days reported as "critically ill" and "seriously ill" in the nursing unit, and calculates the weight of each type of critical condition based on the total number of bed days in the hospital.

[0095] The RIDIT value of the nursing unit = (normal weight × total number of days for normal patients + serious illness weight × total number of days for serious patients + critical illness weight × total number of days for critical patients) / total number of days.

[0096] Some special nursing units have fixed RIDIT values ​​for patients without critical illness, and the fixed values ​​are determined through discussion by the core group of the Nursing Department.

[0097] (4) Specialty CMI values ​​are reported regularly by the Medical Department;

[0098] The original value of specialist CMI shall be reported regularly / periodically by the Medical Department.

[0099] (5) The practice risk takes a fixed value.

[0100] The practice risk is determined by experts and takes a fixed value.

[0101] Based on the specific indicator values ​​of the three-dimensional and five-dimensional indicators, this application also provides a more specific implementation plan on how to quantify the corresponding risk levels.

[0102] Specifically, as an exemplary embodiment, for different nursing units, the risk level in the current situation may include the following processing contents:

[0103] (1) Obtain the values ​​of each index of the three-dimensional five-dimensional index;

[0104] After the specific values ​​of the three-dimensional and five-dimensional indicators have been processed, the values ​​of each indicator can be extracted for use in quantifying the risk level here.

[0105] (2) Rank the values ​​of each indicator vertically, with high-quality indicators ranked from low to high (low-quality indicators ranked from high to low, and all indicators in this paper are high-quality indicators, ranked from low to high);

[0106] (3) Based on the ranking results (the results of the processing of the longitudinal partial ranking in the previous step), the rank of each indicator is multiplied by the indicator weight to calculate the weighted rank value of each indicator, and then the weighted rank values ​​of each indicator are added together to obtain the total weighted rank value (the higher the total weighted rank value, the higher the risk of the nursing unit);

[0107] As an example, the indicator weights of the indicators may be as shown in Table 2 below.

[0108] Table 2- Weight of each indicator

[0109]

[0110] It can be understood that the content shown in Table 2 above is an example, and the weights of each indicator of the three-dimensional five-dimensional indicators can be adaptively adjusted according to actual conditions in actual situations.

[0111] (4) (Combined with probability distribution) the total rank values ​​of different nursing units are converted into corresponding probability values ​​(probit values) in the probability distribution, and different nursing units are classified according to the corresponding probability values. The corresponding six grades from high to low specifically include extremely high-risk nursing units, high-risk nursing units, relatively high-risk nursing units, medium-risk nursing units, low-risk nursing units and relatively low-risk nursing units.

[0112] Among them, it can be understood that the grading result is the risk level assessment result.

[0113] As an example, the classification results of different nursing units can be summarized as shown in Table 3 below:

[0114] Table 3 - Example of binning results

[0115]

[0116] It can be understood that for the above classification results (risk level assessment results), different levels (risk levels) can be distinguished by different colors, for example, "1A"-"3B" can be displayed in different colors.

[0117] Step S103, obtaining the risk levels of different nursing units under historical circumstances previously determined at historical monitoring time points;

[0118] It can be understood that the present application also involves dynamic monitoring of risks. In this regard, in addition to determining the risk level of different care units under current circumstances, the risk level of different care units under historical circumstances previously determined at historical monitoring time points recorded on the system can also be obtained.

[0119] The risk levels of different nursing units under historical circumstances previously determined at historical monitoring time points are consistent with the previous determination process of the risk levels of different nursing units under current circumstances.

[0120] In addition, as an exemplary embodiment, the current monitoring time point and historical monitoring time point involved in the present application can specifically be preset time points with a period of 1 day, that is, the risk level is updated and calculated on a daily basis. In this way, the risk assessment process involved in the present application can take into account the operating cost, assessment accuracy and subsequent response efficiency under actual circumstances.

[0121] Of course, in specific applications, the monitoring period may also span a time period other than 1 day (24 hours), and, as mentioned earlier, the monitoring time point itself may also be adaptively adjusted according to actual needs.

[0122] Furthermore, continuing to focus on the monitoring time point, it can be understood that the present application believes that, assuming that the monitoring period (such as 1 day) remains unchanged, although the data is usually collected / aggregated in a post-aggregation manner, in some details, the data may still be updated after the data collection time point, which may lead to slight deviations in the exposed risk changes.

[0123] In this regard, compared with conventional settings or conventional thinking that only focuses on the monitoring period, this application can introduce a dynamic adjustment mechanism for the monitoring time point while keeping the monitoring period unchanged, so as to take into account both data collection cost and data accuracy in details.

[0124] On the one hand, under the premise that the monitoring cycle remains unchanged, the specific monitoring time point can be adjusted and adapted in combination with the data update situation of the original data after the monitoring time point in the past, so as to make the adjusted specific monitoring time point as later as possible than the data update time point corresponding to the data update situation. This setting takes into account the deviation of the optimal data collection time point due to human and objective reasons in actual situations as much as possible, so as to avoid the continued data update of the original data after the monitoring time point as much as possible.

[0125] On the other hand, under the premise that the monitoring cycle remains unchanged, the monitoring time points can be randomly or manually adjusted within the observation period, based on the risk changes of different nursing units at different monitoring time points after multiple adjustments (the risk changes here are obtained by following the data processing involved in the subsequent step S104), to observe whether there are target monitoring time points that will expose more risk situations, and use the target monitoring time points as the specific monitoring time points to be adopted subsequently.

[0126] In addition, it should be noted that step S103 here is independent of the previous step S101 and step S102 in terms of execution timing.

[0127] Step S104 , dynamically monitoring the risk changes of different nursing units in combination with the risk level in the current situation and the risk levels of different nursing units in the past situation.

[0128] In this way, after obtaining the risk level assessment results of both the current risk level and the historical risk level of different nursing units, it is possible to update the risk level assessment results of different nursing units and dynamically monitor the risk changes of different nursing units from a time dimension, which can be used for recording and analysis to meet the management needs of the nursing units.

[0129] In this case, based on the dynamic monitoring results, corresponding to the subsequent data usage link, as an exemplary embodiment, after dynamically monitoring the risk changes of different nursing units in combination with the risk level in the current situation and the risk level of different nursing units in historical situations, the method of the present application may also include:

[0130] Push or display dynamic monitoring results to relevant users to prompt timely response and human resource adjustments.

[0131] It can be understood that pushing and / or displaying the dynamic monitoring results as soon as possible is conducive to timely capturing risk changes within the nursing unit, allowing medical institutions to respond and adjust human resources quickly. The adaptive measures made in this way can avoid the lag problem of existing technologies that limit immediate response and intervention capabilities due to poor real-time performance (this lag may cause potential risks to affect patients before they are discovered), which can effectively and efficiently reduce patient risks and ensure / improve the quality of clinical nursing work.

[0132] In addition, the dynamic monitoring results of risk situations can also be used to adjust business systems other than the nursing unit's work, providing new and accurate data support for the business processing of other business systems.

[0133] Correspondingly, as an exemplary embodiment, after dynamically monitoring the risk changes of different nursing units in combination with the risk level in the current situation and the risk levels of different nursing units in historical situations, the method of the present application may also include:

[0134] The dynamic monitoring results are pushed to the preset hospital night shift performance management system, human resources management system and nursing quality management system.

[0135] It can be understood that in specific applications, in addition to the three major systems listed in the embodiments here, namely the hospital night shift performance management system, the human resources management system and the nursing quality management system, other types of related business systems may also be involved. New business processing can be configured based on the dynamic monitoring results obtained by the present application scheme. In this way, the work value of clinical nursing work can be further guaranteed / enhanced from different aspects, and the user experience of patients can be guaranteed / enhanced.

[0136] For the above scheme content, including various exemplary embodiments, in general, for the management objectives of the nursing unit, this application is triggered by the current monitoring time point, and obtains clinical data including medical order content and medical content from the pre-connected online business system of the relevant hospital through a preset data transmission channel. On the basis of the clinical data, the pre-configured three-dimensional five-dimensional indicators are followed to determine the risk level of the different nursing units involved in the current situation. Combined with the risk level in the current situation and the risk level of different nursing units in historical situations, the risk changes of different nursing units are dynamically monitored. While introducing an automated online system to efficiently complete the risk level assessment of the nursing unit, a three-dimensional five-dimensional indicator driven by clinical data is proposed in detail, which can not only realize the risk level assessment of the nursing unit in a comprehensive, objective, fair and visual manner, but also promote high-precision risk level assessment effects, thereby realizing safe and fast-response nursing unit management work, promoting high-quality clinical nursing quality and efficient human resource utilization, and having better application value.

[0137] The above is an introduction to the nursing unit risk level assessment method provided in this application. In order to better implement the nursing unit risk level assessment method provided in this application, this application also provides a nursing unit risk level assessment device from the perspective of functional modules.

[0138] See also Figure 2 , Figure 2 This is a structural diagram of a nursing unit risk level assessment device of the present application. In the present application, the nursing unit risk level assessment device 200 may specifically include the following structure:

[0139] The acquisition unit 201 is used to acquire clinical data including doctor's order content and medical content from the pre-connected online business system of the relevant hospital through a preset data transmission channel as triggered by the current monitoring time point, so as to achieve the purpose of integrating information from various clinical data sources;

[0140] The determination unit 202 is used to determine the risk level of different nursing units involved in the current situation based on the clinical data and in accordance with the pre-configured three-dimensional five-dimensional indicators, wherein the three-dimensional five-dimensional indicators specifically involve three dimensions: nursing workload dimension, nursing work difficulty dimension and nursing practice risk dimension. The nursing workload dimension specifically involves an indicator of correction workload, the nursing work difficulty dimension specifically involves three indicators of graded nursing RIDIT value, critical patient RIDIT value and specialist CMI value, and the nursing practice risk dimension specifically involves an indicator of practice risk;

[0141] The acquisition unit 202 is also used to acquire the risk levels of different nursing units under historical circumstances previously determined at historical monitoring time points;

[0142] The monitoring unit 203 is used to dynamically monitor the risk changes of different nursing units by combining the risk level under the current situation and the risk levels of different nursing units under historical situations.

[0143] In an exemplary embodiment, the relevant hospital online business system specifically includes an HIS system, a medical technology workstation, a nurse workstation and a charging system.

[0144] In yet another exemplary embodiment, the apparatus further includes an application unit 204, configured to:

[0145] Push or display dynamic monitoring results to relevant users to prompt timely response and human resource adjustments.

[0146] In yet another exemplary embodiment, the apparatus further includes an application unit 204, configured to:

[0147] The dynamic monitoring results are pushed to the preset hospital night shift performance management system, human resources management system and nursing quality management system.

[0148] In another exemplary embodiment, the current monitoring time point and the historical monitoring time point are specifically preset time points with a period of 1 day.

[0149] In another exemplary embodiment, for different nursing units, the three-dimensional five-dimensional index has the following processing contents:

[0150] The workload of correction is the sum of the difficulty coefficient of each nursing technique and the corresponding frequency of medical advice;

[0151] RIDIT value of graded nursing = (third-level nursing weight × number of third-level nursing bed days + second-level nursing weight × number of second-level nursing bed days + first-level nursing weight × number of first-level nursing bed days + special-level nursing weight × number of special-level nursing bed days) / first total bed days;

[0152] RIDIT value of critically ill patients = (normal weight × total number of days for normal patients + severe weight × total number of days for severe patients + critical weight × total number of days for critical patients) / total number of days for the second;

[0153] Specialist CMI values ​​are reported regularly by the Medical Department;

[0154] The practice risk takes a fixed value.

[0155] In yet another exemplary embodiment, for different nursing units, the risk levels in the current situation have the following processing contents:

[0156] Obtain the values ​​of each indicator of the three-dimensional five-dimensional indicators;

[0157] Rank the values ​​of each indicator vertically, with high-quality indicators ranked from low to high;

[0158] On the basis of the ranking results, the rank of each indicator is multiplied by the indicator weight to calculate the weighted rank value of each indicator, and then the weighted rank values ​​of each indicator are added together to obtain the total weighted rank value;

[0159] The total rank values ​​of different nursing units are converted into corresponding probability values ​​in the probability distribution, and the different nursing units are classified according to the corresponding probability values. The corresponding 6 grades from high to low specifically include extremely high-risk nursing units, high-risk nursing units, relatively high-risk nursing units, medium-risk nursing units, low-risk nursing units and relatively low-risk nursing units.

[0160] This application also provides a processing device from the perspective of hardware structure, see Figure 3 , Figure 3 301, a memory 302, and an input / output device 303. The processor 301 is used to execute the computer program stored in the memory 302 to implement the following Figure 1 The steps of the nursing unit risk level assessment method in the corresponding embodiment; or, the processor 301 is used to execute the computer program stored in the memory 302 to implement the following Figure 2 Corresponding to the functions of each unit in the embodiment, the memory 302 is used to store the processor 301 executing the above Figure 1 The computer program required by the nursing unit risk level assessment method in the corresponding embodiment.

[0161] Exemplarily, the computer program may be divided into one or more modules / units, one or more modules / units are stored in the memory 302, and executed by the processor 301 to complete the present application. One or more modules / units may be a series of computer program instruction segments capable of completing specific functions, and the instruction segments are used to describe the execution process of the computer program in the computer device.

[0162] The processing device may include, but is not limited to, a processor 301, a memory 302, and an input / output device 303. Those skilled in the art will appreciate that the illustration is merely an example of a processing device and does not constitute a limitation on the processing device, and may include more or fewer components than shown in the illustration, or a combination of certain components, or different components. For example, the processing device may also include a network access device, a bus, etc., and the processor 301, the memory 302, the input / output device 303, etc. are connected via a bus.

[0163] The processor 301 may be a central processing unit (CPU), or other general-purpose processors, digital signal processors (DSP), application-specific integrated circuits (ASIC), field-programmable gate arrays (FPGA) or other programmable logic devices, discrete gate or transistor logic devices, discrete hardware components, etc. A general-purpose processor may be a microprocessor or any conventional processor, etc. The processor is the control center of the processing device, and uses various interfaces and lines to connect various parts of the entire device.

[0164] The memory 302 can be used to store computer programs and / or modules. The processor 301 implements various functions of the computer device by running or executing the computer programs and / or modules stored in the memory 302 and calling the data stored in the memory 302. The memory 302 can mainly include a program storage area and a data storage area, wherein the program storage area can store an operating system, at least one application required for a function, etc.; the data storage area can store data created according to the use of the processing device, etc. In addition, the memory can include a high-speed random access memory, and can also include a non-volatile memory, such as a hard disk, a memory, a plug-in hard disk, a smart memory card (Smart Media Card, SMC), a secure digital (SecureDigital, SD) card, a flash card (Flash Card), at least one disk storage device, a flash memory device, or other volatile solid-state storage devices.

[0165] When the processor 301 is used to execute the computer program stored in the memory 302, the following functions can be implemented:

[0166] With the triggering of the current monitoring time point, clinical data including doctor's orders and medical contents are obtained from the pre-connected online business system of the relevant hospital through the preset data transmission channel, so as to achieve the purpose of integrating information from various clinical data sources;

[0167] Based on clinical data, the risk levels of different nursing units involved in the current situation are determined in accordance with the pre-configured three-dimensional five-dimensional indicators. The three-dimensional five-dimensional indicators specifically involve the three dimensions of nursing workload, nursing work difficulty and nursing practice risk. The nursing workload dimension specifically involves the indicator of correction workload, the nursing work difficulty dimension specifically involves the three indicators of graded nursing RIDIT value, critical patient RIDIT value and specialist CMI value, and the nursing practice risk dimension specifically involves the indicator of practice risk.

[0168] Obtain the risk levels of different nursing units under historical circumstances previously determined at historical monitoring time points;

[0169] Based on the risk level in the current situation and the risk levels of different nursing units in historical situations, the risk changes of different nursing units are dynamically monitored.

[0170] Those skilled in the art can clearly understand that for the convenience and simplicity of description, the specific working process of the nursing unit risk level assessment device, processing equipment and its corresponding units described above can refer to the following. Figure 1 The description of the nursing unit risk level assessment method in the corresponding embodiment will not be repeated here.

[0171] A person of ordinary skill in the art will appreciate that all or part of the steps in the various methods of the above embodiments may be completed by instructions, or by controlling related hardware through instructions. The instructions may be stored in a computer-readable storage medium and loaded and executed by a processor.

[0172] To this end, the present application provides a computer-readable storage medium, in which a plurality of instructions are stored, and the instructions can be loaded by a processor to execute the present application as follows: Figure 1 The steps of the nursing unit risk level assessment method in the corresponding embodiment, the specific operation can refer to the following Figure 1 The description of the nursing unit risk level assessment method in the corresponding embodiment will not be repeated here.

[0173] The computer-readable storage medium may include: a read-only memory (ROM), a random access memory (RAM), a magnetic disk or an optical disk, etc.

[0174] Due to the instructions stored in the computer-readable storage medium, the present application can be executed. Figure 1 Corresponding to the steps of the nursing unit risk level assessment method in the embodiment, therefore, the present application can be implemented as follows Figure 1The beneficial effects that can be achieved by the nursing unit risk level assessment method in the corresponding embodiment are detailed in the previous description and will not be repeated here.

[0175] The above is a detailed introduction to the nursing unit risk level assessment method, device, processing equipment and computer-readable storage medium provided by the present application. Specific examples are used in this article to illustrate the principles and implementation methods of the present application. The description of the above embodiments is only used to help understand the method of the present application and its core idea; at the same time, for technical personnel in this field, according to the ideas of the present application, there will be changes in the specific implementation methods and application scope. In summary, the content of this specification should not be understood as a limitation on the present application.

Claims

1. A nursing unit risk level assessment method, characterized in that: The method comprises: With the triggering of the current monitoring time point, clinical data including doctor's orders and medical contents are obtained from the pre-connected online business system of the relevant hospital through the preset data transmission channel, so as to achieve the purpose of integrating information from various clinical data sources; Based on the clinical data, the risk levels of the different nursing units involved in the current situation are determined in accordance with the pre-configured three-dimensional five-dimensional indicators, wherein the three-dimensional five-dimensional indicators specifically involve three dimensions: nursing workload dimension, nursing work difficulty dimension and nursing practice risk dimension. The nursing workload dimension specifically involves an indicator of correction workload, the nursing work difficulty dimension specifically involves three indicators: graded nursing RIDIT value, critical patient RIDIT value and specialist CMI value, and the nursing practice risk dimension specifically involves an indicator of practice risk; Obtaining risk levels of the different nursing units under historical circumstances previously determined at historical monitoring time points; The risk level in the current situation and the risk levels of the different nursing units in historical situations are combined to dynamically monitor the risk changes of the different nursing units.

2. The method according to claim 1, characterized in that: The relevant hospital online business systems specifically include HIS system, medical technology workstation, nurse workstation and charging system.

3. The method according to claim 1, characterized in that After dynamically monitoring the risk changes of the different nursing units by combining the risk level in the current situation and the risk levels of the different nursing units in historical situations, the method further includes: Push or display dynamic monitoring results to relevant users to prompt timely response and human resource adjustments.

4. The method according to claim 1, characterized in that: After dynamically monitoring the risk changes of the different nursing units by combining the risk level in the current situation and the risk levels of the different nursing units in historical situations, the method further includes: The dynamic monitoring results are pushed to the preset hospital night shift performance management system, human resources management system and nursing quality management system.

5. The method according to claim 1, characterized in that The current monitoring time point and the historical monitoring time point are specifically preset time points with a period of 1 day.

6. The method according to claim 1, characterized in that For the different nursing units, the three-dimensional and five-dimensional indicators have the following processing contents: The correction workload is the sum of the difficulty coefficient of each nursing technique and the corresponding frequency of medical advice; The graded nursing RIDIT value = (third-level nursing weight × third-level nursing bed days + second-level nursing weight × second-level nursing bed days + first-level nursing weight × first-level nursing bed days + special nursing weight × special nursing bed days) / first total bed days; The RIDIT value of the critically ill patient = (normal weight × total number of days for normal patients + severe weight × total number of days for severe patients + critical weight × total number of days for critical patients) / second total number of days; The specialist CMI values ​​are reported regularly by the Medical Department; The practice risk takes a fixed value.

7. The method according to claim 6, characterized in that For the different care units, the risk levels in the current situation have the following treatment contents: Obtaining the values ​​of the three-dimensional and five-dimensional indices; The values ​​of the above indicators are ranked vertically, and the high-quality indicators are ranked from low to high; On the basis of the ranking results, the rank of each indicator is multiplied by the indicator weight to calculate the weighted rank value of each indicator, and then the weighted rank values ​​of each indicator are added together to obtain the total weighted rank value; The total rank values ​​of the different nursing units are converted into corresponding probability values ​​in the probability distribution, and the different nursing units are graded according to the corresponding probability values. The corresponding 6 grades from high to low specifically include extremely high-risk nursing units, high-risk nursing units, relatively high-risk nursing units, medium-risk nursing units, low-risk nursing units and relatively low-risk nursing units.

8. A nursing unit risk level assessment device, characterized in that: The device comprises: The acquisition unit is used to acquire clinical data including doctor's orders and medical contents from the online business system of the relevant hospital connected in advance through the preset data transmission channel as triggered by the current monitoring time point, so as to achieve the purpose of integrating information from various clinical data sources; A determination unit is used to determine the risk level of different nursing units involved in the current situation based on the clinical data and in accordance with pre-configured three-dimensional five-dimensional indicators, wherein the three-dimensional five-dimensional indicators specifically involve three dimensions: nursing workload dimension, nursing work difficulty dimension and nursing practice risk dimension; the nursing workload dimension specifically involves an indicator of correction workload; the nursing work difficulty dimension specifically involves three indicators of graded nursing RIDIT value, critical patient RIDIT value and specialist CMI value; and the nursing practice risk dimension specifically involves an indicator of practice risk; The acquisition unit is further used to acquire the risk levels of the different nursing units under historical circumstances previously determined at historical monitoring time points; The monitoring unit is used to dynamically monitor the risk changes of the different nursing units by combining the risk level in the current situation and the risk levels of the different nursing units in historical situations.

9. A processing device, characterized in that: The method comprises a processor and a memory, wherein the memory stores a computer program, and the processor executes the method according to any one of claims 1 to 7 when calling the computer program in the memory.

10. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a plurality of instructions, and the instructions are suitable for being loaded by a processor to execute the method according to any one of claims 1 to 7.

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