Medical equipment management and evaluation platform, method and computer program product

Abstract

The invention discloses a medical equipment management and evaluation platform and method and a computer program product, and the platform comprises a data collection module which is used for obtaining the real-time data and information system data of medical equipment; the use efficiency analysis module is used for carrying out use efficiency analysis on the collected data to obtain a use efficiency analysis result of the medical equipment and storing the use efficiency analysis result to the platform database; the single-machine benefit analysis module is used for performing single-machine benefit analysis on the collected data to obtain a single-machine benefit analysis result and storing the single-machine benefit analysis result to the platform database; the performance evaluation module is used for performing performance evaluation on the data in the platform database by using a performance index evaluation system to obtain a performance evaluation result; and the simulation prediction module is used for performing simulation prediction according to the data in the platform database. According to the method and the system, fine management of the medical equipment is realized, the operation efficiency is improved, the rationality of resource allocation is enhanced, the equipment operation cost is reduced, and a powerful grasp is provided for management and monitoring of medical equipment assets.

Description

Technical Field

[0001] The present application relates to the technical field of integrated management of medical equipment, and in particular to a medical equipment management and evaluation platform, method and computer program product. Background Art

[0002] Medical equipment is one of the fastest growing assets of hospitals in recent years. Improving the efficiency of medical equipment use, avoiding idle equipment and rationally allocating equipment scale have become important ways to reduce hospital operating costs and improve hospital economic benefits. On the other hand, the management problems brought about by the influx of a large number of equipment into hospitals are becoming increasingly prominent.

[0003] Real-time supervision and dynamic scientific deployment of medical equipment will become increasingly important. The lagging, fixed, and static medical equipment management model can no longer meet the development requirements of modern hospitals. The early, full-process, and dynamic intervention management model can achieve cross-hospital medical equipment data resource sharing, thereby comprehensively and comprehensively evaluating the efficiency of medical equipment use and establishing industry standards for medical equipment supervision should be the direction of joint efforts of medical equipment management departments.

[0004] Medical equipment management is an important part of hospital management. It is not only related to the social and economic benefits of the hospital, but also closely related to the life safety of patients. The huge number and variety of medical equipment determine that medical equipment management is a complex and arduous system engineering. The traditional ledger-based, static, and lagging management model has long been unable to meet the requirements of hospitals. Improving operational efficiency, focusing on connotation-based development, and realizing refined management of medical equipment through information technology has become a general trend. Summary of the invention

[0005] The embodiments of the present application provide a medical equipment management and evaluation platform, method and computer program product to achieve refined management of medical equipment, improve operational efficiency, strengthen the rationality of resource allocation, enhance patient satisfaction with medical treatment, reduce equipment operating costs, and provide a handle for the management and monitoring of medical equipment assets.

[0006] The present application embodiment adopts the following technical solutions:

[0007] In a first aspect, an embodiment of the present application provides a medical device management and evaluation platform, wherein the medical device management and evaluation platform includes:

[0008] A data acquisition module, used to obtain real-time data of medical equipment and information system data, wherein the real-time data includes operation data and parameter data;

[0009] A usage efficiency analysis module, used to perform usage efficiency analysis on the real-time data and information system data of the medical device, obtain the usage efficiency analysis results of the medical device and store them in the platform database;

[0010] A stand-alone benefit analysis module is used to perform stand-alone benefit analysis on the real-time data and information system data of the medical device, obtain the stand-alone benefit analysis results of the medical device and store them in the platform database;

[0011] A performance evaluation module, used to perform performance evaluation based on the data in the platform database using a performance indicator evaluation system to obtain a performance evaluation result of the medical device;

[0012] The simulation prediction module is used to perform simulation prediction based on the data in the platform database to obtain simulation prediction results of medical equipment.

[0013] Optionally, the usage efficiency analysis module is further used to:

[0014] Analyzing the real-time data and information system data of the medical device using a first analysis algorithm to obtain a usage efficiency analysis result of the medical device;

[0015] Among them, the utilization efficiency analysis results of the medical equipment include at least one of the equipment power-on time, equipment working time, equipment service volume, equipment 24-hour workload, patient examination time and service volume distribution, part examination time and workload distribution, patient examination interval distribution, ultrasound equipment probe usage ratio, mirror usage times and usage time.

[0016] Optionally, the single-machine benefit analysis module is further used for:

[0017] Using a second analysis algorithm to perform a stand-alone benefit analysis on the real-time data and information system data of the medical device to obtain a stand-alone benefit analysis result of the medical device;

[0018] The single-machine benefit analysis results include at least one of the business income, operating cost, investment return rate, investment payback period, and the proportion of equipment with recoverable costs within a preset time of the medical equipment.

[0019] Optionally, the performance evaluation module is further used to:

[0020] Load unevaluated indicator data from the evaluation indicator data table of the platform database;

[0021] Load the evaluation index system information from the evaluation index system table of the platform database;

[0022] Calling an evaluation model function to calculate a performance evaluation score according to the unevaluated indicator data and the evaluation indicator system information;

[0023] The performance evaluation score is stored in the evaluation result table of the platform database.

[0024] Optionally, the simulation prediction module is further used for:

[0025] Obtaining device usage data within a preset time range from the platform database, the device usage data including the average daily working hours of a single device, the average daily workload of a single device, the average number of days for patient appointments, and the percentage of advanced function usage;

[0026] Perform simulation prediction based on the equipment usage data to obtain simulation prediction results, wherein the simulation calculation results include the relationship between the average daily workload of a single device, the average number of appointment days for patients, and the number of devices;

[0027] Determine whether new medical equipment is needed and whether new medical equipment with advanced functions is needed based on the simulation prediction results, existing medical equipment and expected goals;

[0028] When new medical devices and / or new medical devices with advanced functions are needed, existing medical devices are recommended and displayed using preset recommendation strategies.

[0029] Optionally, the simulation prediction module is further used for:

[0030] In the case where a new medical device with advanced functions is needed, the existing medical device with advanced functions is determined based on the device characteristic information of the existing medical device;

[0031] Obtain the unit benefit index value of existing advanced medical equipment;

[0032] According to the stand-alone benefit index values ​​of the existing advanced medical devices, the existing advanced medical devices are ranked and displayed;

[0033] When new medical equipment is needed, obtain the unit benefit index values ​​of all existing medical equipment;

[0034] All existing medical equipment are sorted and displayed according to their stand-alone efficiency index values.

[0035] Optionally, the medical equipment management and evaluation platform further includes:

[0036] The parameter monitoring module is used to monitor the operating data and parameter data of medical equipment.

[0037] Optionally, the medical equipment management and evaluation platform further includes:

[0038] The early warning module is used to use preset early warning rules to determine whether the operating data and parameter data of the monitored medical equipment trigger alarm conditions, and to issue an alarm reminder when the alarm conditions are triggered.

[0039] In a second aspect, an embodiment of the present application further provides a medical device management and evaluation method, wherein the medical device management and evaluation method is executed by a medical device management and evaluation platform, and the medical device management and evaluation method includes:

[0040] Acquire real-time data and information system data of medical equipment, wherein the real-time data includes operation data and parameter data;

[0041] Performing a utilization efficiency analysis on the real-time data and information system data of the medical device, obtaining the utilization efficiency analysis results of the medical device and storing them in the platform database;

[0042] Performing stand-alone benefit analysis on the real-time data and information system data of the medical equipment, obtaining stand-alone benefit analysis results of the medical equipment and storing them in the platform database;

[0043] Based on the data in the platform database, a performance evaluation is performed using a performance indicator evaluation system to obtain a performance evaluation result of the medical equipment;

[0044] A simulation prediction is performed based on the data in the platform database to obtain a simulation prediction result of the medical device.

[0045] In a third aspect, an embodiment of the present application further provides a computer program product, including a computer program or instructions, which, when executed by a processor, implements any of the aforementioned medical device management and evaluation methods.

[0046] At least one of the above technical solutions adopted in the embodiment of the present application can achieve the following beneficial effects: the medical equipment management and evaluation platform of the embodiment of the present application includes: a data acquisition module, which is used to obtain real-time data and information system data of medical equipment, and the real-time data includes operation data and parameter data; an efficiency analysis module, which is used to analyze the efficiency of the real-time data and information system data of medical equipment, obtain the efficiency analysis results of the use of medical equipment and store them in the platform database; a stand-alone benefit analysis module, which is used to analyze the real-time data and information system data of medical equipment, obtain the stand-alone benefit analysis results of medical equipment and store them in the platform database; a performance evaluation module, which is used to perform performance evaluation based on the data in the platform database using the performance indicator evaluation system, and obtain the performance evaluation results of medical equipment; a simulation prediction module, which is used to perform simulation prediction based on the data in the platform database, and obtain the simulation prediction results of medical equipment. The information-based medical equipment management and evaluation platform adopted in the embodiment of the present application realizes the refined management of medical equipment, improves operational efficiency, strengthens the rationality of resource allocation, improves patient satisfaction with medical treatment, reduces equipment operating costs, and provides a powerful grip for the management and monitoring of medical equipment assets. BRIEF DESCRIPTION OF THE DRAWINGS

[0047] The drawings described herein are used to provide a further understanding of the present application and constitute a part of the present application. The illustrative embodiments of the present application and their descriptions are used to explain the present application and do not constitute an improper limitation on the present application. In the drawings:

[0048] Figure 1 This is a schematic diagram of the structure of a medical device management and evaluation platform in an embodiment of the present application;

[0049] Figure 2 A complete flow chart of a medical device performance evaluation in an embodiment of the present application;

[0050] Figure 3 A schematic diagram of a complete process of simulation prediction of a medical device in an embodiment of the present application;

[0051] Figure 4 This is a flow chart of a medical equipment management and evaluation method in an embodiment of the present application. DETAILED DESCRIPTION

[0052] In order to make the purpose, technical solution and advantages of the present application clearer, the technical solution of the present application will be clearly and completely described below in combination with the specific embodiments of the present application and the corresponding drawings. 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 ordinary technicians in this field without making creative work are within the scope of protection of the present application.

[0053] The technical solutions provided by various embodiments of the present application are described in detail below in conjunction with the accompanying drawings.

[0054] The present application embodiment provides a medical equipment management and evaluation platform, such as Figure 1 As shown, a schematic diagram of the structure of a medical equipment management and evaluation platform in an embodiment of the present application is provided, wherein the medical equipment management and evaluation platform 100 includes: a data acquisition module 110, a usage efficiency analysis module 120, a stand-alone benefit analysis module 130, a performance evaluation module 140 and a simulation prediction module 150, wherein:

[0055] A data acquisition module 110 is used to obtain real-time data and information system data of medical equipment, wherein the real-time data includes operation data and parameter data;

[0056] The utilization efficiency analysis module 120 is used to perform utilization efficiency analysis on the real-time data and information system data of the medical device, obtain the utilization efficiency analysis results of the medical device and store them in the platform database;

[0057] The stand-alone benefit analysis module 130 is used to perform stand-alone benefit analysis on the real-time data and information system data of the medical device, obtain the stand-alone benefit analysis results of the medical device and store them in the platform database;

[0058] The performance evaluation module 140 is used to perform performance evaluation based on the data in the platform database using a performance indicator evaluation system to obtain a performance evaluation result of the medical device;

[0059] The simulation prediction module 150 is used to perform simulation prediction based on the data in the platform database to obtain simulation prediction results of medical equipment.

[0060] The medical equipment management and evaluation platform of the embodiment of the present application mainly includes a data acquisition module, a usage efficiency analysis module, a single-machine benefit analysis module, a performance evaluation module and a simulation prediction module.

[0061] The data acquisition module mainly uses IoT acquisition devices to obtain real-time data of equipment through video analysis, image processing, deep learning, protocol analysis, DICOM file analysis and other technologies, including equipment operation data, equipment physiological parameters, equipment alarm parameters, waveform parameters, key component parameters, etc. Using system fusion methods, through views, WebService, ETL extraction and other technologies, data from hospital information systems such as HIS, LIS, PACS, RIS, HRP, including charge item data, examination-related data, cost-income data, disease diagnosis data, etc.

[0062] The usage efficiency analysis module is mainly used to conduct multi-dimensional analysis of usage efficiency data such as equipment working hours, service volume, 24-hour workload distribution, and patient examination interval distribution.

[0063] The single-machine benefit analysis module is mainly used to comprehensively analyze the equipment's business income, cost, investment return rate, investment payback period, break-even point and other equipment benefit data.

[0064] The performance evaluation module is mainly used to build a performance evaluation index system for equipment usage, and use system data to conduct performance evaluation of equipment, including performance evaluation in different dimensions such as equipment, department, and brand.

[0065] The simulation prediction module is mainly used to simulate and calculate the relationship between workload, appointment time and number of equipment according to equipment usage, such as equipment quantity, workload, appointment time, etc., as a basis for decision-making by medical equipment managers.

[0066] The information-based medical equipment management and evaluation platform adopted in the embodiment of the present application realizes the refined management of medical equipment, improves operational efficiency, strengthens the rationality of resource allocation, enhances patient satisfaction with medical treatment, reduces equipment operating costs, and provides a powerful grip for the management and monitoring of medical equipment assets.

[0067] In some embodiments of the present application, the usage efficiency analysis module 120 is also used to: use a first analysis algorithm to analyze the real-time data and information system data of the medical device to obtain a usage efficiency analysis result of the medical device; wherein the usage efficiency analysis result of the medical device includes at least one of the equipment power-on time, equipment working time, equipment service volume, equipment 24-hour workload, patient examination time and service volume distribution, site examination time and workload distribution, patient examination interval distribution, ultrasound equipment probe usage ratio, mirror usage times and usage time.

[0068] The usage efficiency analysis module of the embodiment of the present application can use statistical analysis, correlation analysis and other techniques to analyze the data obtained by the Internet of Things acquisition device to obtain indicator data related to the usage efficiency of medical equipment, such as equipment power-on time, equipment working time, equipment service volume, equipment 24-hour workload, patient examination time and service volume distribution, part examination time and workload distribution, patient examination interval distribution, ultrasound equipment probe usage ratio, mirror usage times and usage time, etc.

[0069] In addition, the efficiency analysis results can be displayed and ranked in multiple dimensions by equipment, department, brand, model, etc. according to actual needs.

[0070] In some embodiments of the present application, the stand-alone benefit analysis module 130 is also used to: use a second analysis algorithm to perform a stand-alone benefit analysis on the real-time data and information system data of the medical device to obtain a stand-alone benefit analysis result of the medical device; wherein the stand-alone benefit analysis result includes at least one of the medical device's business income, operating costs, investment return rate, investment payback period, and the proportion of equipment with recoverable costs within a preset time.

[0071] The stand-alone benefit analysis module of the embodiment of the present application is mainly used to comprehensively analyze the operation data and information system data of the equipment, and analyze the equipment's business income, cost (including equipment depreciation, staff wages, repair costs, maintenance costs, quality control costs, metering costs, consumables costs, energy costs, etc.), investment rate of return, investment payback period, the proportion of equipment with recoverable costs within six years, and other equipment benefit data. For example, annualized investment rate of return = equipment contract amount / (equipment annual income - annual operating cost), where the equipment annual income is the income of the charging record of a single device that can be queried in the HIS within a year; the annual operating cost is the annual cost of a single device during its use, including equipment depreciation, staff wages, repair costs, maintenance costs, quality control costs, metering costs, consumables costs, energy costs, etc.; annualized investment payback period = 1 / annualized investment rate of return.

[0072] In addition, the results of single-machine benefit analysis can be displayed and ranked in multiple dimensions according to actual needs by equipment, department, brand, model, etc.

[0073] In some embodiments of the present application, the performance evaluation module 140 is also used to: load unevaluated indicator data from the evaluation indicator data table of the platform database; load evaluation indicator system information from the evaluation indicator system table of the platform database; call the evaluation model function to calculate the performance evaluation score based on the unevaluated indicator data and the evaluation indicator system information; and store the performance evaluation score in the evaluation result table of the platform database.

[0074] The performance evaluation module of the embodiment of the present application is mainly used to determine the performance evaluation index system for the use of the equipment according to the expert consultation method, expert seminar, etc., and to perform performance evaluation on the equipment according to the data obtained by the system, which may include performance evaluation of different dimensions such as equipment, department, brand, model, etc. The system supports the construction of the index system, the selection of the dimensionless method of the index, the setting and modification of the weight, the setting and modification of the benchmarking parameters, and the calculation and ranking of the evaluation index.

[0075] For example, a performance evaluation index system is constructed for large medical equipment such as CT, MR, PET-CT, and LA, including first-level evaluation indicators such as utilization efficiency, cost control, and operation guarantee, and second-level evaluation indicators such as average daily service volume per unit, average daily working hours per unit, average daily startup time per unit, average monthly income per unit, and average monthly main cost per unit. For example, a performance evaluation index system is constructed for thoracoscopy, including first-level evaluation indicators such as utilization efficiency, clinical effect, and clinical service, and second-level evaluation indicators such as average daily surgical service volume of equipment, average use time of equipment per surgery, average daily income of equipment, proportion of level 4 surgeries served by equipment, proportion of patients discharged within 0-48 hours after surgery served by equipment, number of surgical types served by equipment, number of departments served by equipment, and number of surgical tables served by equipment.

[0076] In order to facilitate the understanding of the above embodiments, Figure 2 As shown, a complete process diagram of a medical device performance evaluation in an embodiment of the present application is provided, which mainly includes the following steps:

[0077] Step 201: Determine an indicator set.

[0078] The platform has built-in indicator set knowledge base and indicator set parameter knowledge base. The indicators in the indicator set knowledge base are the largest set of indicators for which data can be obtained in the platform. The indicator set knowledge base contains key field information such as the indicator name, definition, unit, attribute (high priority, low priority), data source, and update frequency. The indicator set parameter knowledge base contains information on indicator description statistics parameters such as time (such as year), statistical period, minimum indicator value, maximum indicator value, mean indicator value, median indicator value, standard deviation indicator value, upper quartile indicator value, and lower quartile indicator value.

[0079] When determining the indicator set, the evaluation indicator system can be determined through expert consultation or expert seminars, and the evaluation indicator system contains information such as evaluation dimensions, indicator levels, indicator names, indicator benchmarking methods, and indicator weights. The importance of indicators and indicator weights can be quantified using multiple levels (level-score: extremely unimportant-1, very unimportant-2, unimportant-3, less important-4, general-5, more important-6, important-7, very important-8, extremely important-9). Of course, the number of levels can be flexibly set by technicians in this field according to actual needs, and no specific limitation is made here.

[0080] Step 202: Obtain indicator data.

[0081] The indicator data in the indicator set determined for equipment evaluation is extracted from the platform database through SQL statements, and the extracted data is data within a preset time range or historical data up to the current date.

[0082] Step 203: Establish an evaluation index system and save the evaluation model.

[0083] The determined indicator set is modeled using the comprehensive evaluation software EISQMS. The model contains scenario information, scoring range and evaluation indicator system information. The evaluation indicator system information includes key information such as indicator name, level (primary indicator, secondary indicator, tertiary indicator, etc.), indicator definition, indicator unit, indicator attribute (high priority, low priority), indicator dimensionless method (standardization, positive, normalization, etc.), indicator weight, indicator scoring threshold, indicator average value, etc.

[0084] After the evaluation indicator set is initially modeled using the tool software EISQMS, a simulation sample is generated, and the data of the obtained indicator set is organized into sample data based on real-world data in the format of the simulation sample. The sample data based on real-world data is imported into the tool EISQMS, and the descriptive parameter data (such as mean value, median, etc.) of the indicator is calculated using the tool. The descriptive parameter data calculated based on the sample data of real-world data is used to update the relevant parameters in the initial model, and the updated model is used as the evaluation model. The model is exported and stored using the tool EISQMS.

[0085] Step 204: Load the evaluation model.

[0086] In the performance evaluation module of the platform, the evaluation model is loaded through the DLL dynamic library to support the business application of equipment performance evaluation. The evaluation model supports the modification and update of benchmarking parameters and weight parameters. The pre-work for calling the evaluation model is as follows: 1) Establish an evaluation index system table in the platform database. The table building operation only needs to be performed once. The table contains key fields such as index system ID, index system name, index ID, index level, index name, index definition, index unit, index attribute, index benchmarking method, index benchmarking parameter, and index weight; 2) Import the index system of the determined evaluation model into the corresponding evaluation index system table in the platform database in Excel mode. When the performance evaluation module in the platform changes the benchmarking parameter or weight parameter, the relevant content in the evaluation index system table will be updated synchronously; 3) Establish an evaluation index data table in the platform database. The table building operation only needs to be performed once. The table contains key fields such as data ID, index ID, index level, index name, and index value; 4) Establish an evaluation result table in the platform database. The table building operation only needs to be performed once. The table contains key fields such as data ID, evaluation index name, and evaluation index score; 5) Write an SQL statement in the platform database and store it as a function Func. The function of this function is to extract the index data in the evaluation index system from the platform according to the specified time range and store the extraction results in the evaluation index data table.

[0087] Step 205: Set evaluation rules.

[0088] In the platform rule configuration, evaluation rule parameters such as evaluation model identifier, model scenario identifier, evaluation time, and evaluation cycle are set. According to the set evaluation rules, a stored procedure Proce is established in the platform database. The stored procedure executes the function Func in step 5) of step 204 according to the set evaluation time range. At the same time, a job is established in the platform database, and the execution rules of the job are set according to the set evaluation time and evaluation cycle.

[0089] Step 206: Evaluate according to preset rules.

[0090] The performance evaluation module in the platform evaluates the performance of the equipment according to the pre-loaded evaluation model and the set evaluation rule parameters, and synchronously updates the performance evaluation data of different dimensions such as department, brand, and model. The steps for using the evaluation model to evaluate the performance of the equipment are as follows: 1) Load the unevaluated indicator data from the evaluation indicator data table; 2) Load the relevant information of the evaluation indicator system from the evaluation indicator system table; 3) Calculate the evaluation score by calling the evaluation model function in the DLL dynamic library; 4) Store the evaluation score in the evaluation result table of the platform database.

[0091] In some embodiments of the present application, the simulation prediction module 150 is also used to: obtain equipment usage data within a preset time range from the platform database, the equipment usage data including the average daily working hours of a single device, the average daily workload of a single device, the average number of patient appointment days, and the proportion of advanced function usage; perform simulation prediction based on the equipment usage data to obtain simulation prediction results, and the simulation calculation results include the relationship between the average daily workload of a single device, the average number of patient appointment days, and the number of devices; determine whether new medical equipment is needed and whether new medical equipment with advanced functions is needed based on the simulation prediction results, existing medical equipment, and expected goals; and when new medical equipment and / or new medical equipment with advanced functions are needed, use preset recommendation strategies to recommend and display existing medical equipment.

[0092] The simulation prediction module of the embodiment of the present application is mainly used to simulate and calculate the relationship between workload, appointment duration and number of equipment according to the equipment usage. For example, according to the existing number of equipment, the average daily working hours of a single device, the average daily workload of a single device, the average number of patient appointment days, the use of advanced functions, the number of devices with advanced functions and other usage data, the patient appointment duration under different workloads under the existing number of equipment is calculated; or the number of equipment units and the number of equipment units with advanced functions required under different workloads under the expected patient appointment duration are calculated. For example, Hospital A currently has 13 MR devices, the average daily service volume of a single device is 44 people, and the average number of patient appointment days is 11 days. When the average daily service volume of a single device is optimized to 48 people, without increasing the number of equipment units, the estimated average number of patient appointment days is 8.35 days, which is consistent with the actual situation.

[0093] In order to facilitate the understanding of the above embodiments, Figure 3 As shown, a complete flow chart of a medical device simulation prediction in an embodiment of the present application is provided, which mainly includes the following steps:

[0094] 301: Get device usage data.

[0095] Through SQL statements, the device usage data within the preset time range is extracted from the platform database, such as the average daily working hours of a single device, the average daily workload of a single device, the average number of days for patient appointments, the proportion of advanced function usage, and other data.

[0096] 302: Simulate and measure the relationship between workload, appointment duration and number of devices.

[0097] According to the equipment usage, the relationship between workload, appointment time and number of equipment is simulated and calculated. For example, based on the real-world equipment usage data (such as the average daily working hours of a single device, the average daily workload of a single device, the average number of days for patient appointments, etc.), the total number of devices that need to be added and the number of devices with advanced functions that need to be added to achieve the expected goal (such as the expected appointment waiting time) are simulated and calculated through mathematical models. The calculation method is as follows:

[0098] 1) Assume the number of existing equipment is m;

[0099] 2) Let the average number of working days per month be t;

[0100] 3) Assume the average daily working time of a single machine is x1;

[0101] 4) Assume the average daily workload of a single machine is x2;

[0102] 5) Set the average number of days for patients to make appointments x3;

[0103] 6) Assume that the usage ratio of advanced functions is a1;

[0104] 7) Let the number of devices with advanced functions be m a ;

[0105] 8) Let the ratio of the average working hours of a single diagnosis and treatment of advanced functions and non-advanced functions be c1:

[0106]

[0107] 9) Let the average working time of non-advanced functions be d1;

[0108] 10) Let the growth rate of advanced function usage be e1;

[0109] 11) Assume the temporary variable new average daily workload per unit x′2:

[0110]

[0111] 12) Assume that the usage ratio of advanced functions of the device with advanced functions is f1: 0≤f1≤1. When f1=1, it means that the device with advanced functions only performs advanced functions.

[0112] 13) Assume that the expected average daily working time of a single device of the same type in hospitals is u1;

[0113] 14) Assume the expected average daily workload of a single device of the same type in hospitals is u2;

[0114] 15) Let the expected average number of days for patients with the same type of equipment in the same type of hospital be u3;

[0115] 16) Assume that the expected average daily workload of a single unit of this type of equipment in this hospital is

[0116] 17) Set the expected number of days for reservation generally

[0117] 18) Then the number of newly added equipment y:

[0118]

[0119] Among them, 0≤y≤20;

[0120] 19) The number of new high-end devices is n a :

[0121]

[0122] Among them, n a Round up.

[0123] It should be noted that 1)-15) above can be obtained based on statistical analysis of the original collected data, 16)-17) are the expected goals set, which can be flexibly set according to needs, and 18)-19) are the number of new devices and advanced devices required to achieve the expected goals.

[0124] In some embodiments of the present application, the simulation prediction module 150 is also used for: when it is necessary to add new medical equipment with advanced functions, determining the existing medical equipment with advanced functions according to the equipment characteristic information of the existing medical equipment; obtaining the stand-alone benefit index values ​​of the existing medical equipment with advanced functions; sorting and displaying the existing medical equipment with advanced functions according to the stand-alone benefit index values ​​of the existing medical equipment with advanced functions; when it is necessary to add new medical equipment, obtaining the stand-alone benefit index values ​​of all existing medical equipment; sorting and displaying all existing medical equipment according to the stand-alone benefit index values ​​of all existing medical equipment.

[0125] Based on the real-world device usage data, the total number of devices that need to be added and the number of devices with advanced functions that need to be added are calculated through mathematical model simulation to achieve the expected goal (such as the expected waiting time for appointments). The existing devices of this type in the platform are classified by specifications and models, and the stand-alone benefit indicators of devices of different specifications and models, such as the payback period, and parameters such as device characteristics (including parameters used to identify whether they have advanced functions) are counted. First, the devices with specifications and models of device characteristics with advanced functions are arranged in ascending order according to the payback period, and their ranking is used as the priority number. In this candidate list, devices with advanced functions are recommended according to the priority number, and devices with advanced functions that need to be added are recommended according to the device priority number in this candidate list. All devices with different specifications and models of device characteristics are arranged in ascending order according to the payback period, and their ranking is used as the priority number. In this candidate list, devices are recommended according to the priority number, and devices that need to be added (excluding devices with advanced functions that need to be added) are recommended according to the device priority number in this candidate list.

[0126] In the embodiment of the present application, when determining the need for new equipment and new advanced equipment based on simulation prediction results and the user's expected goals, the above-mentioned recommendation priority method can facilitate the user to efficiently and intuitively select the specific new equipment models, while fully considering the benefits brought by the new equipment while meeting the expected goals.

[0127] In some embodiments of the present application, the medical device management and evaluation platform 100 further includes: a parameter monitoring module for monitoring the operation data and parameter data of the medical device.

[0128] A parameter monitoring module can also be set in the medical equipment management and evaluation platform of the embodiment of the present application, which is mainly used for real-time monitoring of the equipment's operating status (such as standby, working, shutdown, fault, etc.), physiological parameters (such as ventilation mode, expiratory tidal volume, minute expiratory volume, respiratory rate, etc.), alarm parameters (such as high airway pressure alarm, apnea alarm, low battery voltage alarm, etc.), waveform parameters (such as flow rate, pressure, capacity, etc.) and key component parameters (such as tube exposure times, tube voltage, tube current, CTDI, etc.).

[0129] In some embodiments of the present application, the medical device management and evaluation platform 100 also includes: an early warning module, which is used to use preset early warning rules to determine whether the operating data and parameter data of the monitored medical device trigger an alarm condition, and to issue an alarm reminder when the alarm condition is triggered.

[0130] An early warning module can also be set up in the medical equipment management and evaluation platform of the embodiment of the present application, which is mainly used to issue alarm reminders for the equipment operating status, equipment physiological parameters, equipment alarm parameters, equipment life, equipment key component parameters, etc. according to preset alarm rules such as alarm trigger conditions, alarm thresholds, alarm frequencies, alarm durations, alarm methods, etc.

[0131] For example, in the case of the RRT (rapid response team) critical value alarm, when the monitored parameters are found to have reached the preset abnormal range, and the total number of abnormalities within a certain period reaches the preset alarm frequency threshold or the continuous alarm time reaches the preset alarm duration threshold, the parameter alarm data will be sent to the rapid response team for verification and confirmation through the preset alarm method (such as SMS, APP, etc.), so that relevant processing can be made in a timely manner when necessary. The RRT critical value alarm supports alarm threshold setting, real-time viewing of alarm data, real-time query of alarm sending status, and timely notification of team response status. Taking the monitor RRT alarm as an example, there are two modes: system self-alarm and preset alarm. In the system self-alarm mechanism, the upper and lower limits of the parameters are set on the monitor. If the upper limit is greater than the upper limit or less than the lower limit, the system will alarm; in the preset alarm mechanism, the upper and lower limits of the parameters are manually set on the system. If the upper limit is greater than the upper limit or less than the lower limit for X minutes, the system will alarm.

[0132] Of course, the specific method of setting the alarm rules can be flexibly set by those skilled in the art according to actual needs, and no specific limitation is made here.

[0133] The present application also provides a medical equipment management and evaluation method, such as Figure 4 As shown, a flow chart of a medical device management and evaluation method in an embodiment of the present application is provided. The medical device management and evaluation method is executed by a medical device management and evaluation platform. The medical device management and evaluation method includes at least the following steps S410 to S450:

[0134] Step S410, acquiring real-time data and information system data of the medical device, wherein the real-time data includes operation data and parameter data;

[0135] Step S420, performing a usage efficiency analysis on the real-time data and information system data of the medical device, obtaining the usage efficiency analysis result of the medical device and storing it in the platform database;

[0136] Step S430, performing a stand-alone benefit analysis on the real-time data and information system data of the medical device, obtaining a stand-alone benefit analysis result of the medical device and storing it in a platform database;

[0137] Step S440, performing performance evaluation using a performance indicator evaluation system based on the data in the platform database to obtain a performance evaluation result of the medical device;

[0138] Step S450, performing simulation prediction based on the data in the platform database to obtain simulation prediction results of the medical equipment.

[0139] The medical device management and evaluation method of the embodiment of the present application is executed by the medical device management and evaluation platform of the aforementioned embodiment. It can be understood that each step of the above-mentioned medical device management and evaluation method can be implemented based on the medical device management and evaluation platform provided in the aforementioned embodiment, and the relevant explanations about the medical device management and evaluation platform are applicable to the medical device management and evaluation method, which will not be repeated here.

[0140] The medical equipment management and evaluation platform of this application is composed of system software and IoT front-end device terminals. It adopts a combination of software and hardware, utilizes core technologies such as real-time statistics and analysis of the use process and equipment status of medical equipment, and integrates basic data from systems such as HIS and HRP. It realizes refined management of the hospital's medical equipment use efficiency, single-machine benefits, parameter monitoring, early warning, performance evaluation, etc., provides an effective basis for the hospital to comprehensively evaluate the use of medical equipment, provides accurate evaluation data for the purchase of medical equipment, and realizes scientific and standardized management of medical equipment.

[0141] The present application also provides a computer program product, which stores one or more programs, wherein the one or more programs include instructions, which, when executed by an electronic device including multiple application programs, enable the electronic device to execute Figure 1 The method performed by the medical equipment management and evaluation device in the illustrated embodiment is specifically used to perform:

[0142] Acquire real-time data and information system data of medical equipment, wherein the real-time data includes operation data and parameter data;

[0143] Performing a utilization efficiency analysis on the real-time data and information system data of the medical device, obtaining the utilization efficiency analysis results of the medical device and storing them in the platform database;

[0144] Performing stand-alone benefit analysis on the real-time data and information system data of the medical equipment, obtaining stand-alone benefit analysis results of the medical equipment and storing them in the platform database;

[0145] Based on the data in the platform database, a performance evaluation is performed using a performance indicator evaluation system to obtain a performance evaluation result of the medical equipment;

[0146] A simulation prediction is performed based on the data in the platform database to obtain a simulation prediction result of the medical equipment.

[0147] Those skilled in the art will appreciate that embodiments of the present invention may be provided as methods, systems, or computer program products. Therefore, the present invention may take the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) containing computer-usable program code.

[0148] The present invention is described with reference to flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to embodiments of the present invention. It should be understood that each process and / or block in the flowchart and / or block diagram, as well as the combination of processes and / or blocks in the flowchart and / or block diagram, can be implemented by computer program instructions. These computer program instructions can be provided to a processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing device to produce a machine, so that the instructions executed by the processor of the computer or other programmable data processing device generate instructions for implementing the processes in the flowchart and / or block diagram. Figure 1 A process or multiple processes and / or boxes Figure 1 A device that provides the functions specified in a block or multiple blocks.

[0149] These computer program instructions may also be stored in a computer-readable memory capable of directing a computer or other programmable data processing device to operate in a specific manner, so that the instructions stored in the computer-readable memory produce an article of manufacture comprising an instruction device, which implements the process Figure 1 A process or multiple processes and / or boxes Figure 1 A function specified in one or more boxes.

[0150] These computer program instructions can also be loaded onto a computer or other programmable data processing device so that a series of operating steps are executed on the computer or other programmable device to produce a computer-implemented process, thereby providing instructions for implementing the process. Figure 1 A process or multiple processes and / or boxes Figure 1 The steps for the functions specified in one or more boxes.

[0151] In a typical configuration, a computing device includes one or more processors (CPU), input / output interfaces, network interfaces, and memory.

[0152] The memory may include non-permanent storage in a computer-readable medium, random access memory (RAM) and / or non-volatile memory in the form of read-only memory (ROM) or flash RAM. The memory is an example of a computer-readable medium.

[0153] Computer readable media include permanent and non-permanent, removable and non-removable media that can be implemented by any method or technology to store information. Information can be computer readable instructions, data structures, program modules or other data. Examples of computer storage media include, but are not limited to, phase change memory (PRAM), static random access memory (SRAM), dynamic random access memory (DRAM), other types of random access memory (RAM), read-only memory (ROM), electrically erasable programmable read-only memory (EEPROM), flash memory or other memory technology, compact disk read-only memory (CD-ROM), digital versatile disk (DVD) or other optical storage, magnetic cassettes, magnetic tape magnetic disk storage or other magnetic storage devices or any other non-transmission media that can be used to store information that can be accessed by a computing device. As defined herein, computer readable media does not include temporary computer readable media (transitory media), such as modulated data signals and carrier waves.

[0154] It should also be noted that the terms "include", "comprises" or any other variations thereof are intended to cover non-exclusive inclusion, so that a process, method, commodity or device including a series of elements includes not only those elements, but also other elements not explicitly listed, or also includes elements inherent to such process, method, commodity or device. In the absence of more restrictions, the elements defined by the sentence "comprises a ..." do not exclude the existence of other identical elements in the process, method, commodity or device including the elements.

[0155] Those skilled in the art will appreciate that the embodiments of the present application may be provided as methods, systems or computer program products. Therefore, the present application may adopt the form of a complete hardware embodiment, a complete software embodiment or an embodiment in combination with software and hardware. Moreover, the present application may adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk storage, CD-ROM, optical storage, etc.) that contain computer-usable program code.

[0156] The above is only an embodiment of the present application and is not intended to limit the present application. For those skilled in the art, the present application may have various changes and variations. Any modification, equivalent replacement, improvement, etc. made within the spirit and principle of the present application should be included in the scope of the claims of the present application.

Claims

1. A medical equipment management and evaluation platform, wherein: The medical equipment management and evaluation platform includes: A data acquisition module, used to obtain real-time data of medical equipment and information system data, wherein the real-time data includes operation data and parameter data; A usage efficiency analysis module, used to perform usage efficiency analysis on the real-time data and information system data of the medical device, obtain the usage efficiency analysis results of the medical device and store them in the platform database; A stand-alone benefit analysis module is used to perform stand-alone benefit analysis on the real-time data and information system data of the medical device, obtain the stand-alone benefit analysis results of the medical device and store them in the platform database; A performance evaluation module, used to perform performance evaluation based on the data in the platform database using a performance indicator evaluation system to obtain a performance evaluation result of the medical device; The simulation prediction module is used to perform simulation prediction based on the data in the platform database to obtain simulation prediction results of medical equipment.

2. The medical equipment management and evaluation platform as claimed in claim 1, wherein: The usage efficiency analysis module is also used for: Analyzing the real-time data and information system data of the medical device using a first analysis algorithm to obtain a usage efficiency analysis result of the medical device; Among them, the utilization efficiency analysis results of the medical equipment include at least one of the equipment power-on time, equipment working time, equipment service volume, equipment 24-hour workload, patient examination time and service volume distribution, part examination time and workload distribution, patient examination interval distribution, ultrasound equipment probe usage ratio, mirror usage times and usage time.

3. The medical equipment management and evaluation platform as claimed in claim 1, wherein: The stand-alone benefit analysis module is also used for: Using a second analysis algorithm to perform a stand-alone benefit analysis on the real-time data and information system data of the medical device to obtain a stand-alone benefit analysis result of the medical device; The single-machine benefit analysis results include at least one of the business income, operating cost, investment return rate, investment payback period, and the proportion of equipment with recoverable costs within a preset time of the medical equipment.

4. The medical device management and evaluation platform as claimed in claim 1, wherein: The performance evaluation module is also used to: Load unevaluated indicator data from the evaluation indicator data table of the platform database; Load the evaluation index system information from the evaluation index system table of the platform database; Calling an evaluation model function to calculate a performance evaluation score according to the unevaluated indicator data and the evaluation indicator system information; The performance evaluation score is stored in the evaluation result table of the platform database.

5. The medical equipment management and evaluation platform as claimed in claim 1, wherein: The simulation prediction module is also used for: Obtaining device usage data within a preset time range from the platform database, the device usage data including the average daily working hours of a single device, the average daily workload of a single device, the average number of days for patient appointments, and the percentage of advanced function usage; Perform simulation prediction based on the equipment usage data to obtain simulation prediction results, wherein the simulation calculation results include the relationship between the average daily workload of a single device, the average number of appointment days for patients, and the number of devices; Determine whether new medical equipment is needed and whether new medical equipment with advanced functions is needed based on the simulation prediction results, existing medical equipment and expected goals; When new medical devices and / or new medical devices with advanced functions are needed, existing medical devices are recommended and displayed using preset recommendation strategies.

6. The medical equipment management and evaluation platform as claimed in claim 5, wherein: The simulation prediction module is also used for: In the case where a new medical device with advanced functions is needed, the existing medical device with advanced functions is determined based on the device characteristic information of the existing medical device; Obtain the unit benefit index value of existing advanced medical equipment; According to the stand-alone benefit index values ​​of the existing advanced medical devices, the existing advanced medical devices are ranked and displayed; When new medical equipment is needed, obtain the unit benefit index values ​​of all existing medical equipment; All existing medical equipment are sorted and displayed according to their stand-alone efficiency index values.

7. The medical equipment management and evaluation platform as claimed in claim 1, wherein: The medical equipment management and evaluation platform also includes: The parameter monitoring module is used to monitor the operating data and parameter data of medical equipment.

8. The medical equipment management and evaluation platform as claimed in claim 7, wherein: The medical equipment management and evaluation platform also includes: The early warning module is used to use preset early warning rules to determine whether the operating data and parameter data of the monitored medical equipment trigger alarm conditions, and to issue an alarm reminder when the alarm conditions are triggered.

9. A medical equipment management and evaluation method, wherein: The medical equipment management and evaluation method is executed by a medical equipment management and evaluation platform, and the medical equipment management and evaluation method includes: Acquire real-time data and information system data of medical equipment, wherein the real-time data includes operation data and parameter data; Performing a utilization efficiency analysis on the real-time data and information system data of the medical device, obtaining the utilization efficiency analysis results of the medical device and storing them in the platform database; Performing stand-alone benefit analysis on the real-time data and information system data of the medical equipment, obtaining stand-alone benefit analysis results of the medical equipment and storing them in the platform database; Based on the data in the platform database, a performance evaluation is performed using a performance indicator evaluation system to obtain a performance evaluation result of the medical equipment; A simulation prediction is performed based on the data in the platform database to obtain a simulation prediction result of the medical equipment.

10. A computer program product, comprising a computer program or instructions, wherein when the computer program or instructions are executed by a processor, the medical device management and evaluation method according to claim 9 is implemented.

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