Intelligent medical data processing method, system, device and medium based on cloud computing

Abstract

The present invention discloses a cloud computing-based intelligent medical data processing method, system, equipment and medium, which relates to the field of data processing technology, including: obtaining medical equipment data and patient treatment data; using high-frequency statistical methods and low-frequency statistical methods to obtain the equipment turnover cycle and equipment bottom line quantity of each medical equipment; marking medical equipment and anomaly annotation; the present invention is used to solve the problem that the prior art lacks an improved method for data processing of medical equipment, and is unable to supplement medical equipment and screen abnormal conditions under the premise of meeting actual needs, thereby causing the problem that medical equipment cannot meet actual patient needs.

Description

Technical Field

[0001] The present invention relates to the field of data processing technology, and specifically to a cloud computing-based smart medical data processing method, system, device and medium. Background Art

[0002] With the rapid development of Internet information technology and the establishment of regional intelligent medical service platforms, intelligent medical care will truly realize the interconnection and interoperability of medical information; intelligent medical engineering will be a multi-level data processing platform, which will comprehensively process and collaboratively utilize information related to various systems and multi-source data of the Internet of Things by associating, estimating and combining data from multiple information sources, and ultimately realize the integration of intelligent medical information; medical data processing, that is, the processing of statistical information, refers to the statistical calculation of the original data generated by the business system according to statistical themes, different dimensions and defined granularity to obtain information; the processing part completes the generation and storage of statistical information on the original data according to certain statistical methods.

[0003] Existing improvements in data processing for smart healthcare are usually improvements on defects in data transmission. For example, in a Chinese patent with application publication number CN117278333A, a smart medical data processing method, device and system based on a SaaS platform are disclosed. This solution is to solve the defect that hospitals in the prior art cannot control the operation and maintenance details of the medical SaaS platform, thereby reducing the security of data transmission within the hospital by encrypting the medical operation and maintenance data and the operation data. Other improvements in data processing for smart healthcare are usually improvements in the maintenance of security risks and the efficiency of policy allocation. There is a lack of improvements in data processing of medical equipment based on medical equipment data and patient treatment data. It is impossible to integrate and analyze the relevant data of medical equipment in combination with the remaining number of medical equipment and the use of medical equipment during patient treatment, so that it is impossible to supplement medical equipment and screen abnormal conditions on the premise of meeting actual needs, and it cannot meet the actual needs of patients. In view of this, it is necessary to improve the existing smart medical data processing method. Summary of the invention

[0004] The present invention aims to solve at least one of the technical problems in the prior art to a certain extent. By proposing a cloud computing-based intelligent medical data processing method, system, equipment and medium, the present invention is used to solve the problem that the prior art lacks improvements in data processing of medical equipment based on medical equipment data and patient treatment data, and is unable to integrate and analyze relevant data of medical equipment in combination with the remaining number of medical equipment and the use of medical equipment during patient treatment. It is also unable to supplement medical equipment and screen abnormal conditions under the premise of meeting actual needs, which leads to the problem that medical equipment cannot meet actual patient needs.

[0005] To achieve the above-mentioned purpose, in a first aspect, the present invention provides a smart medical data processing method based on cloud computing, comprising: obtaining all medical data to be processed and recording them as a medical database; obtaining medical equipment data and patient consultation data in the medical database, wherein the medical equipment data includes the types of medical equipment, the number of medical equipment and the usage of medical equipment, and the patient consultation data includes the patients who have been treated and the usage of medical equipment by the patients who have been treated during the consultation;

[0006] Based on medical device data and patient visit data, high-frequency and low-frequency statistical methods are used to obtain the equipment turnover cycle and equipment bottom line quantity of each medical device;

[0007] The number of unused medical devices in the medical database is obtained every common multiple of the rotation time, and the medical devices are marked and anomaly marked based on the number of unused medical devices.

[0008] Furthermore, based on the medical equipment data and patient visit data, high-frequency statistical methods and low-frequency statistical methods are used to obtain the equipment turnover period and equipment bottom line quantity of each medical equipment, including:

[0009] Different types of medical devices in the medical device data are recorded as medical device 1 to medical device M; for any medical device M1, the number of times the medical device M1 is used is obtained, which is recorded as the historical number of times the medical device M1 is used; and the historical number of times all medical devices are used is obtained;

[0010] The average of the historical usage times of all medical devices is recorded as the mean usage of the device; the medical devices with a historical usage time greater than or equal to the mean usage of the device from medical devices 1 to medical devices M are recorded as high-frequency medical devices; the medical devices with a historical usage time less than the mean usage of the device from medical devices 1 to medical devices M are recorded as low-frequency medical devices;

[0011] Use high-frequency statistical methods to analyze the medical equipment data and patient visit data of high-frequency medical equipment, and obtain the equipment turnover cycle and equipment bottom line quantity of all high-frequency medical data based on the analysis results;

[0012] Use low-frequency statistical methods to analyze the medical equipment data and patient visit data of low-frequency medical equipment, and obtain the equipment turnover cycle and equipment bottom line quantity of all low-frequency medical data based on the analysis results.

[0013] Furthermore, the high-frequency statistical method includes:

[0014] For any high-frequency medical device A, the time when the high-frequency medical device A is used for the first time is recorded as the device start time, and the time when the high-frequency medical device A is used for the last time is recorded as the device end time;

[0015] The time period between the equipment start time and the equipment end time is evenly divided into T segments, and recorded in sequence as usage time period 1 to usage time period T based on the time sequence;

[0016] For any one usage time period T1 from usage time period 1 to usage time period T, based on the patient consultation data, the patients who use the high-frequency medical device A in usage time period T1 are recorded as consultation patient T1~1 to consultation patient T1~K in sequence;

[0017] For any patient T1~K1 from the patients T1~1 to the patients T1~K, the duration of the high-frequency medical device A used by the patient T1~K1 is recorded as the device usage duration of the patient T1~K1; the device usage duration of all the patients is obtained and recorded in sequence as device usage duration 1 to device usage duration K;

[0018] Obtain the visiting time differences of adjacent visiting patients from visiting patient T1~1 to visiting patient T1~K, and record them as visiting time difference 1 to visiting time difference K-1, respectively.

[0019] Furthermore, the high-frequency statistical method also includes:

[0020] For any equipment usage time K1 from equipment usage time 1 to equipment usage time K-1, when equipment usage time K1 is less than the consultation time difference K1, the patients T1~K1+1 are marked as repeatable patients; when equipment usage time K1 is greater than or equal to the consultation time difference K1, the patients T1~K1+1 are marked as waiting patients, and 1 is recorded as the waiting number of patients T1~K1+1; when equipment usage time K1 is greater than or equal to the sum of the consultation time difference K1 plus the consultation time difference K1+1, the waiting number of patients T1~K1+1 is increased by 1, and so on. When equipment usage time K1 is greater than or equal to the sum of the consultation time difference K1 and the consultation time difference K-1, the waiting number of patients T1~K1+1 is (K-1)-K1+1.

[0021] Obtain the marking status of patients T1~2 to T1~K. When all patients are marked as repeatable patients, record the use time period T1 as a generous time period. When at least one of all patients is not marked as a repeatable patient, obtain the waiting number of all patients marked as waiting patients, and obtain the maximum value of all waiting numbers, record it as the bottom line number of equipment in the use time period T1, and record the equipment usage time corresponding to the maximum value of all waiting numbers as the maximum turnaround time of the use time period T1.

[0022] Get the maximum rotation time and equipment bottom line quantity of all usage time periods;

[0023] The time interval consisting of the minimum and maximum values ​​of the maximum rotation time of all use time periods is recorded as the equipment rotation period of high-frequency medical equipment A, and the equipment bottom line quantity of all use time periods is recorded as the equipment bottom line quantity of high-frequency medical equipment A;

[0024] Based on the above method, the equipment turnover period and equipment bottom line quantity of all high-frequency medical equipment are obtained.

[0025] Furthermore, the low-frequency statistical method includes:

[0026] The number of low-frequency medical devices is recorded as J, and all low-frequency medical devices are recorded as low-frequency medical device 1 to low-frequency medical device J in sequence;

[0027] For any low-frequency medical device J1 from low-frequency medical device 1 to low-frequency medical device J, obtain the maximum number of low-frequency medical devices J1 used at the same time in the medical device data corresponding to the low-frequency medical device J1, and record it as the equipment bottom line number of the low-frequency medical device J1;

[0028] A plane rectangular coordinate system is established, recorded as the low-frequency analysis coordinate system, wherein the coordinate points to the right of the coordinate origin in the X-axis of the low-frequency analysis coordinate system are low-frequency medical equipment 1 to low-frequency medical equipment J, and the unit of the Y-axis of the low-frequency analysis coordinate system is the usage time.

[0029] Furthermore, the low-frequency statistical method also includes:

[0030] For any low-frequency medical device J1 from low-frequency medical devices 1 to low-frequency medical devices J, based on the medical device data corresponding to the low-frequency medical device J1, the duration of each use of the low-frequency medical device J1 is recorded as the usage duration J1~1 to the usage duration J1~L, and the minimum and maximum values ​​among the usage duration J1~1 to the usage duration J1~L are recorded as the usage duration L1~MIN and the usage duration L1~MAX, respectively; the straight line parallel to the Y axis corresponding to the low-frequency medical device L1 with the X-axis coordinate in the low-frequency analysis coordinate system is recorded as the vertical reference line, and the time interval corresponding to the area with the Y-axis coordinate in the vertical reference line between the usage duration L1~MIN and the usage duration L1~MAX is recorded as the device rotation period of the low-frequency medical device L1;

[0031] Based on the above method, the equipment turnover period and equipment bottom line quantity of all low-frequency medical equipment are obtained.

[0032] Furthermore, obtaining the number of unused medical devices in the medical database every common multiple of the rotation time, and marking the medical devices and abnormal marking based on the number of unused medical devices include:

[0033] Place the time intervals corresponding to the equipment rotation periods of all low-frequency medical equipment and all high-frequency medical equipment on the same time axis, and record the time interval with the most overlaps of equipment rotation periods in the time axis as the common multiple rotation period;

[0034] The unused quantity of all medical devices in the medical database is obtained every common multiple rotation time. For any medical device A, the unused quantity of medical device A is recorded as the real-time remaining quantity. When the real-time remaining quantity is less than the bottom line quantity of medical device A, medical device A is marked as equipment to be replenished. When medical device A is marked as equipment to be replenished for P consecutive times, the quantity of medical device A is marked as abnormal, wherein the common multiple rotation time is within the common multiple rotation period.

[0035] In a second aspect, the present invention also provides a cloud computing-based smart medical data processing system, including a data acquisition module, an equipment data analysis module, and an equipment data processing module;

[0036] The data acquisition module is used to acquire all medical data for data processing and record them as a medical database; acquire medical equipment data and patient consultation data in the medical database, wherein the medical equipment data includes the types of medical equipment, the number of medical equipment and the usage of medical equipment, and the patient consultation data includes the patients who have been treated and the usage of medical equipment by the patients who have been treated during the treatment;

[0037] The equipment data analysis module is used to obtain the equipment turnover cycle and equipment bottom line quantity of each medical equipment based on medical equipment data and patient visit data using high-frequency statistical methods and low-frequency statistical methods;

[0038] The equipment data processing module is used to obtain the unused quantity of medical equipment in the medical database every common multiple of the rotation time, and mark and annotate the medical equipment as abnormal based on the unused quantity of the medical equipment.

[0039] In a third aspect, the present invention provides a storage medium having a computer program stored thereon, wherein when the computer program is executed by a processor, the steps in the above method are performed.

[0040] In a fourth aspect, the present invention provides an electronic device, comprising a processor and a memory, wherein the memory stores computer-readable instructions, and when the computer-readable instructions are executed by the processor, the steps in the above method are performed.

[0041] Beneficial effects of the present invention: The present invention first obtains medical equipment data and patient visit data;

[0042] Then, based on the medical equipment data and the patient's medical treatment data, high-frequency statistical methods and low-frequency statistical methods are used to obtain the equipment turnover cycle and the equipment bottom line quantity of each medical equipment; finally, the number of unused medical equipment in the medical database is obtained every common multiple of the turnover time, and the medical equipment is marked and anomaly marked based on the unused number of medical equipment. The advantage of this is that by using high-frequency statistical methods and low-frequency statistical methods based on the medical equipment data and the patient's medical treatment data to obtain the equipment turnover cycle and the equipment bottom line quantity of each medical equipment, the obtained equipment turnover cycle and equipment bottom line quantity can be made to conform to the actual use of medical equipment. When the medical equipment is subsequently marked and anomaly marked, it can better meet the actual use needs of medical equipment, and by obtaining the equipment turnover cycle, the cycle of repeated use of medical equipment can be obtained, and by obtaining the equipment bottom line quantity, the minimum number of medical equipment that needs to be provided when there are more patients can be obtained, thereby providing data support for the replenishment and abnormal marking of medical equipment, ensuring that medical equipment can be replenished and abnormalities can be checked in a timely manner in actual situations. BRIEF DESCRIPTION OF THE DRAWINGS

[0043] Figure 1 is a functional block diagram of the system of the present invention;

[0044] Figure 2 is a flow chart of the steps of the method of the present invention;

[0045] Figure 3 is a schematic diagram of a low-frequency analysis coordinate system of the present invention;

[0046] Figure 4 Schematic diagram of an electronic device of the present invention. DETAILED DESCRIPTION

[0047] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0048] Example 1, please refer to Figure 1 As shown, in the first aspect, the present application provides a smart medical data processing system based on cloud computing, including a data acquisition module, an equipment data analysis module and an equipment data processing module;

[0049] The data acquisition module is used to acquire all medical data for data processing and record them as a medical database; acquire medical equipment data and patient consultation data in the medical database, wherein the medical equipment data includes the types of medical equipment, the number of medical equipment and the usage of medical equipment, and the patient consultation data includes the patients who have been treated and the usage of medical equipment by the patients who have been treated during the treatment;

[0050] The equipment data analysis module is used to obtain the equipment turnover period and equipment bottom line quantity of each medical equipment based on medical equipment data and patient visit data using high-frequency statistical methods and low-frequency statistical methods; the equipment data analysis module is configured with an overall analysis strategy, which includes:

[0051] Different types of medical devices in the medical device data are recorded as medical device 1 to medical device M; for any medical device M1, the number of times the medical device M1 is used is obtained, which is recorded as the historical number of times the medical device M1 is used; and the historical number of times all medical devices are used is obtained;

[0052] The average of the historical usage times of all medical devices is recorded as the mean usage of the device; the medical devices with a historical usage time greater than or equal to the mean usage of the device from medical devices 1 to medical devices M are recorded as high-frequency medical devices; the medical devices with a historical usage time less than the mean usage of the device from medical devices 1 to medical devices M are recorded as low-frequency medical devices;

[0053] When the calculated mean equipment usage value is not an integer, the mean equipment usage value is rounded down. For example, in a data processing, the historical usage times of all medical devices are 100, 1, 32, 544, 0, 5, 43 and 432 respectively. Through calculation, the mean equipment usage value is 144.625, and the mean equipment usage value obtained after rounding down is 144.

[0054] Use the high-frequency analysis sub-strategy to analyze the medical device data and patient visit data of high-frequency medical devices, and obtain the device turnover period and device bottom line quantity of all high-frequency medical data based on the analysis results;

[0055] The high-frequency analysis sub-strategy includes: for any high-frequency medical device A, the time when the high-frequency medical device A is used for the first time is recorded as the device start time, and the time when the high-frequency medical device A is used for the last time is recorded as the device end time;

[0056] The time period between the equipment start time and the equipment end time is evenly divided into T segments, and recorded as use time period 1 to use time period T in sequence based on time. The value of T can be adjusted based on the length of the time period between the equipment start time and the equipment end time. When the time period between the equipment start time and the equipment end time is longer, the value of T can be increased. When the time period between the equipment start time and the equipment end time is shorter, the value of T can be reduced. In this embodiment, T is set to 5. For example, in a data processing, the equipment start time of high-frequency medical equipment A is May 10, and the equipment end time of high-frequency medical equipment A is May 25 of the same year. Then the length of each use time period is 5 days.

[0057] For any one usage time period T1 from usage time period 1 to usage time period T, based on the patient consultation data, the patients who use the high-frequency medical device A in usage time period T1 are recorded as consultation patient T1~1 to consultation patient T1~K in sequence;

[0058] For any patient T1~K1 from the patients T1~1 to the patients T1~K, the duration of the high-frequency medical device A used by the patient T1~K1 is recorded as the device usage duration of the patient T1~K1; the device usage duration of all the patients is obtained and recorded in sequence as device usage duration 1 to device usage duration K;

[0059] Obtain the visiting time differences of adjacent visiting patients from visiting patient T1~1 to visiting patient T1~K, and record them as visiting time difference 1 to visiting time difference K-1;

[0060] In the specific implementation process, for example, in a data processing, the visit times of patients T1~1 to T1~5 are May 1, May 10, May 11, May 14, and May 20 in the same year, respectively. Then the visit time difference 1 to visit time difference 4 are 9 days, 1 day, 3 days, and 6 days respectively;

[0061] The high-frequency analysis sub-strategy also includes: for any equipment usage time K1 from equipment usage time 1 to equipment usage time K-1, when the equipment usage time K1 is less than the consultation time difference K1, the visiting patients T1~K1+1 are marked as repeatable patients; when the equipment usage time K1 is greater than or equal to the consultation time difference K1, the visiting patients T1~K1+1 are marked as waiting patients, and 1 is recorded as the waiting number of the visiting patients T1~K1+1; when the equipment usage time K1 is greater than or equal to the sum of the consultation time difference K1 plus the consultation time difference K1+1, the waiting number of the visiting patients T1~K1+1 is increased by 1, and so on, when the equipment usage time K1 is greater than or equal to the sum of the consultation time difference K1 and the consultation time difference K-1, the waiting number of the visiting patients T1~K1+1 is (K-1)-K1+1;

[0062] In the specific implementation process, for example, in a data processing, K is 5, the equipment usage time 2 is 9 days; the time difference from visit time 2 to visit time 4 is 1 day, 1 day and 2 days respectively, and the equipment usage time 2 is greater than the sum of the time difference from visit time 2 to visit time 4, then the patient 3 should be marked as a waiting patient, and the waiting number is 3;

[0063] Obtain the marking status of patients T1~2 to T1~K. When all patients are marked as repeatable patients, record the use time period T1 as a generous time period. When at least one of all patients is not marked as a repeatable patient, obtain the waiting number of all patients marked as waiting patients, and obtain the maximum value of all waiting numbers, record it as the bottom line number of equipment in the use time period T1, and record the equipment usage time corresponding to the maximum value of all waiting numbers as the maximum turnaround time of the use time period T1.

[0064] Get the maximum rotation time and equipment bottom line quantity of all usage time periods;

[0065] The time interval consisting of the minimum and maximum values ​​of the maximum rotation time of all usage time periods is recorded as the equipment rotation cycle of high-frequency medical equipment A, and the equipment bottom line quantity of all usage time periods is recorded as the equipment bottom line quantity of high-frequency medical equipment A.

[0066] Based on the above method, the equipment turnover cycle and equipment bottom line number of all high-frequency medical devices are obtained; the equipment bottom line number obtained through the above analysis can represent that when the medical device is used, there are at most the equipment bottom line number of patients waiting to use the medical device, so there should still be at least the equipment bottom line number of the medical devices at this time to meet the needs of the patients; by obtaining the maximum turnover time, the longest time that the medical device can be reused after one use can be obtained, so that when the data of the medical device is regularly extracted later, the time of regularly extracted data can be associated with the time when the medical device can be reused, so that the extracted data can better reflect the usage of the medical device.

[0067] Use the low-frequency analysis sub-strategy to analyze the medical device data and patient visit data of low-frequency medical devices, and obtain the device turnover period and device bottom line quantity of all low-frequency medical data based on the analysis results;

[0068] The low-frequency analysis sub-strategy includes: recording the number of low-frequency medical devices as J, and recording all low-frequency medical devices as low-frequency medical device 1 to low-frequency medical device J in sequence;

[0069] For any low-frequency medical device J1 from low-frequency medical device 1 to low-frequency medical device J, obtain the maximum number of low-frequency medical devices J1 used at the same time in the medical device data corresponding to the low-frequency medical device J1, and record it as the equipment bottom line number of the low-frequency medical device J1;

[0070] Establish a plane rectangular coordinate system, recorded as a low-frequency analysis coordinate system, wherein the coordinate points to the right of the coordinate origin in the X-axis of the low-frequency analysis coordinate system are low-frequency medical equipment 1 to low-frequency medical equipment J, and the unit of the Y-axis of the low-frequency analysis coordinate system is the usage time;

[0071] See also Figure 3 As shown, the time interval RR3 to RR4 corresponding to the area between point RR1 and point RR2 is the device rotation period of the low-frequency medical device 2.

[0072] The low-frequency analysis sub-strategy also includes: for any low-frequency medical device J1 from low-frequency medical device 1 to low-frequency medical device J, based on the medical device data corresponding to the low-frequency medical device J1, the duration of each use of the low-frequency medical device J1 is recorded in sequence as usage duration J1~1 to usage duration J1~L, and the minimum and maximum values ​​among usage duration J1~1 to usage duration J1~L are recorded as usage duration L1~MIN and usage duration L1~MAX, respectively; the straight line parallel to the Y axis corresponding to the low-frequency medical device L1 with the X-axis coordinate in the low-frequency analysis coordinate system is recorded as a vertical reference line, and the time interval corresponding to the area between the Y-axis coordinate of the vertical reference line with the usage duration L1~MIN to the usage duration L1~MAX is recorded as the equipment turnover cycle of the low-frequency medical device L1; by establishing a low-frequency analysis coordinate system, the equipment turnover cycle of the low-frequency medical device can be visualized, so that the analysis can be more concise and clear.

[0073] Based on the above method, the equipment turnover period and equipment bottom line quantity of all low-frequency medical equipment are obtained; the equipment data processing module is used to obtain the unused quantity of medical equipment in the medical database every common multiple of the turnover time, and mark and annotate the medical equipment based on the unused quantity of medical equipment.

[0074] The equipment data processing module is configured with a real-time equipment processing strategy, which includes: placing the time intervals corresponding to the equipment rotation cycles of all low-frequency medical equipment and all high-frequency medical equipment in the same time axis, and recording the time interval with the most overlaps of equipment rotation cycles in the time axis as the common multiple rotation cycle;

[0075] The unused quantity of all medical equipment in the medical database is obtained every common multiple rotation time. For any medical equipment A, the unused quantity of medical equipment A is recorded as the real-time remaining quantity. When the real-time remaining quantity is less than the equipment bottom line quantity of medical equipment A, medical equipment A is marked as equipment to be replenished; when medical equipment A is marked as equipment to be replenished for P consecutive times, the quantity of medical equipment A is marked as abnormal, wherein the common multiple rotation time is within the common multiple rotation period;

[0076] In the specific implementation process, for example, if the common multiple rotation period is 3 to 5 days, the common multiple rotation time can be 3.5 days, 4 days, 4.5 days, etc.

[0077] Example 2, please refer to Figure 2 As shown, in a second aspect, the present invention provides a smart medical data processing method based on cloud computing, comprising:

[0078] Step S1, obtain all medical data for data processing and record them as a medical database; obtain medical equipment data and patient consultation data in the medical database, wherein the medical equipment data includes the types of medical equipment, the number of medical equipment and the usage of medical equipment, and the patient consultation data includes the patients who have been treated and the usage of medical equipment by the patients who have been treated during the treatment.

[0079] Step S2, obtaining the equipment turnover period and equipment bottom line quantity of each medical equipment using high-frequency statistical method and low-frequency statistical method based on medical equipment data and patient consultation data;

[0080] Step S2 includes: step S201, recording different types of medical devices in the medical device data as medical devices 1 to medical devices M; for any medical device M1, obtaining the number of times the medical device M1 has been used, recorded as the historical number of times the medical device M1 has been used; obtaining the historical number of times all medical devices have been used;

[0081] Step S202, record the average of the historical usage times of all medical devices as the device usage average; record the medical devices with the historical usage times greater than or equal to the device usage average among medical devices 1 to medical devices M as high-frequency medical devices; record the medical devices with the historical usage times less than the device usage average among medical devices 1 to medical devices M as low-frequency medical devices;

[0082] Step S203, using a high-frequency statistical method to analyze the medical equipment data of high-frequency medical equipment and the patient consultation data, and obtaining the equipment turnover period and equipment bottom line quantity of all high-frequency medical data based on the analysis results.

[0083] The high-frequency statistical method includes: for any high-frequency medical device A, the time when the high-frequency medical device A is used for the first time is recorded as the device start time, and the time when the high-frequency medical device A is used for the last time is recorded as the device end time;

[0084] The time period between the equipment start time and the equipment end time is evenly divided into T segments, and recorded in sequence as usage time period 1 to usage time period T based on the time sequence;

[0085] For any one usage time period T1 from usage time period 1 to usage time period T, based on the patient consultation data, the patients who use the high-frequency medical device A in usage time period T1 are recorded as consultation patient T1~1 to consultation patient T1~K in sequence;

[0086] For any patient T1~K1 from the patients T1~1 to the patients T1~K, the duration of the high-frequency medical device A used by the patient T1~K1 is recorded as the device usage duration of the patient T1~K1; the device usage duration of all the patients is obtained and recorded in sequence as device usage duration 1 to device usage duration K;

[0087] Obtain the visiting time differences of adjacent visiting patients from visiting patient T1~1 to visiting patient T1~K, and record them as visiting time difference 1 to visiting time difference K-1;

[0088] The high-frequency statistical method also includes: for any equipment usage time K1 from equipment usage time 1 to equipment usage time K-1, when the equipment usage time K1 is less than the consultation time difference K1, the patient T1~K1+1 is marked as a repeatable patient; when the equipment usage time K1 is greater than or equal to the consultation time difference K1, the patient T1~K1+1 is marked as a waiting patient, and 1 is recorded as the waiting number of the patient T1~K1+1; when the equipment usage time K1 is greater than or equal to the sum of the consultation time difference K1 plus the consultation time difference K1+1, the waiting number of the patient T1~K1+1 is increased by 1, and so on, when the equipment usage time K1 is greater than or equal to the sum of the consultation time difference K1 and the consultation time difference K-1, the waiting number of the patient T1~K1+1 is (K-1)-K1+1;

[0089] Obtain the marking status of patients T1~2 to T1~K. When all patients are marked as repeatable patients, record the use time period T1 as a generous time period. When at least one of all patients is not marked as a repeatable patient, obtain the waiting number of all patients marked as waiting patients, and obtain the maximum value of all waiting numbers, record it as the bottom line number of equipment in the use time period T1, and record the equipment usage time corresponding to the maximum value of all waiting numbers as the maximum turnaround time of the use time period T1.

[0090] Get the maximum rotation time and equipment bottom line quantity of all usage time periods;

[0091] The time interval consisting of the minimum and maximum values ​​of the maximum rotation time of all use time periods is recorded as the equipment rotation period of high-frequency medical equipment A, and the equipment bottom line quantity of all use time periods is recorded as the equipment bottom line quantity of high-frequency medical equipment A;

[0092] Based on the above method, the equipment turnover period and equipment bottom line quantity of all high-frequency medical equipment are obtained.

[0093] Step S204, using a low-frequency statistical method to analyze the medical equipment data of low-frequency medical equipment and the patient consultation data, and obtaining the equipment turnover period and equipment bottom line quantity of all low-frequency medical data based on the analysis results;

[0094] The low-frequency statistical method includes: recording the number of low-frequency medical devices as J, and recording all low-frequency medical devices as low-frequency medical devices 1 to low-frequency medical devices J in sequence;

[0095] For any low-frequency medical device J1 from low-frequency medical device 1 to low-frequency medical device J, obtain the maximum number of low-frequency medical devices J1 used at the same time in the medical device data corresponding to the low-frequency medical device J1, and record it as the equipment bottom line number of the low-frequency medical device J1;

[0096] Establish a plane rectangular coordinate system, recorded as a low-frequency analysis coordinate system, wherein the coordinate points to the right of the coordinate origin in the X-axis of the low-frequency analysis coordinate system are low-frequency medical equipment 1 to low-frequency medical equipment J, and the unit of the Y-axis of the low-frequency analysis coordinate system is the usage time;

[0097] The low-frequency statistical method also includes: for any low-frequency medical device J1 from low-frequency medical devices 1 to low-frequency medical devices J, based on the medical device data corresponding to the low-frequency medical device J1, recording the duration of each use of the low-frequency medical device J1 as the usage duration J1~1 to the usage duration J1~L in sequence, recording the minimum value and the maximum value among the usage duration J1~1 to the usage duration J1~L as the usage duration L1~MIN and the usage duration L1~MAX respectively; recording the straight line parallel to the Y axis corresponding to the low-frequency medical device L1 with the X-axis coordinate in the low-frequency analysis coordinate system as the vertical reference line, and recording the time interval corresponding to the area with the Y-axis coordinate in the vertical reference line between the usage duration L1~MIN and the usage duration L1~MAX as the equipment rotation period of the low-frequency medical device L1;

[0098] Based on the above method, the equipment turnover period and equipment bottom line quantity of all low-frequency medical equipment are obtained.

[0099] Step S3, obtaining the number of unused medical devices in the medical database every common multiple of the rotation time, and marking and abnormally annotating the medical devices based on the number of unused medical devices.

[0100] Step S3 includes: Step S301, placing the time intervals corresponding to the equipment rotation periods of all low-frequency medical equipment and all high-frequency medical equipment in the same time axis, and recording the time interval with the largest number of overlaps of equipment rotation periods in the time axis as the common multiple rotation period;

[0101] Step S302, obtaining the unused quantity of all medical devices in the medical database every common multiple rotation time, for any medical device A, recording the unused quantity of medical device A as the real-time remaining quantity, when the real-time remaining quantity is less than the equipment bottom line quantity of medical device A, marking medical device A as equipment to be replenished; when medical device A is marked as equipment to be replenished for P consecutive times, marking the quantity of medical device A as abnormal, wherein the common multiple rotation time is within the common multiple rotation period.

[0102] Embodiment 3, in a third aspect, the present application provides an electronic device, including a processor 401 and a memory 402, wherein the memory 402 stores computer-readable instructions, and when the computer-readable instructions are executed by the processor 401, the steps in the above method are executed. Through the above technical solution, the processor 401 and the memory 402 are interconnected and communicate with each other through a communication bus and / or other forms of connection mechanisms (not marked), and the memory 402 stores a computer program executable by the processor 401. When the electronic device 40 is running, the processor 401 executes the computer program to execute the method in any optional implementation of the above embodiment to achieve the following functions: obtain all medical data for data processing and record them as a medical database; obtain medical equipment data and patient visit data in the medical database, wherein the medical equipment data includes the type of medical equipment, the number of medical equipment and the usage of medical equipment, and the patient visit data includes the patients who have been treated and the usage of medical equipment of the patients who have been treated during the treatment; based on the medical equipment data and the patient visit data, use high-frequency statistical methods and low-frequency statistical methods to obtain the equipment turnover period and equipment bottom line quantity of each medical equipment; obtain the unused number of medical equipment in the medical database every common multiple of the rotation time, and mark and annotate the medical equipment based on the unused number of medical equipment.

[0103] Embodiment 4, in a fourth aspect, the present application provides a storage medium on which a computer program is stored, and when the computer program is executed by a processor, the steps in the above method are executed. Through the above technical solution, when the computer program is executed by the processor, the method in any optional implementation of the above embodiment is executed to achieve the following functions: obtain all medical data for data processing and record them as a medical database; obtain medical equipment data and patient visit data in the medical database, wherein the medical equipment data includes the type of medical equipment, the number of medical equipment and the use of medical equipment, and the patient visit data includes the use of medical equipment by the patients who have been treated and the use of medical equipment by the patients who have been treated during the treatment; based on the medical equipment data and the patient visit data, use high-frequency statistical methods and low-frequency statistical methods to obtain the equipment turnover cycle and equipment bottom line quantity of each medical equipment; obtain the unused quantity of medical equipment in the medical database every common multiple of the turnover time, and mark and annotate the medical equipment based on the unused quantity of medical equipment.

[0104] In the above embodiments of the present application, the description of each embodiment has its own emphasis. For parts that are not described in detail in a certain embodiment, please refer to the relevant description of other embodiments.

[0105] It should be understood by those skilled in the art that the 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 aspects. Moreover, the present invention may take the form of a computer program product implemented on one or more computer-usable storage media containing computer-usable program codes. Among them, the storage medium may be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as static random access memory (Static Random Access Memory, referred to as SRAM), electrically erasable programmable read-only memory (Electrically Erasable Programmable Read-Only Memory, referred to as EEPROM), erasable programmable read-only memory (Erasable Programmable Read Only Memory, referred to as EPROM), programmable read-only memory (Programmable Read-Only Memory, referred to as PROM), read-only memory (Read-Only Memory, referred to as ROM), magnetic memory, flash memory, magnetic disk or optical disk. 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.

[0106] In the embodiments provided in the present application, it should be understood that the disclosed devices and methods can be implemented in other ways. The device embodiments described above are merely schematic. For example, the division of the units is only a logical function division. There may be other division methods in actual implementation. For example, multiple units or components can be combined or integrated into another system, or some features can be ignored or not executed. Another point is that the mutual coupling or direct coupling or communication connection shown or discussed can be through some communication interfaces, and the indirect coupling or communication connection of devices or units can be electrical, mechanical or other forms.

Claims

1. A smart medical data processing method based on cloud computing, characterized in that: include: Acquire all medical data for data processing and record them as a medical database; acquire medical equipment data and patient consultation data in the medical database, wherein the medical equipment data includes the types of medical equipment, the number of medical equipment and the usage of medical equipment, and the patient consultation data includes the patients who have been treated and the usage of medical equipment by the patients who have been treated during the treatment; Based on medical device data and patient visit data, high-frequency and low-frequency statistical methods are used to obtain the equipment turnover cycle and equipment bottom line quantity of each medical device; Obtaining the number of unused medical devices in the medical database every common multiple of the rotation time, and marking and abnormally annotating the medical devices based on the number of unused medical devices; Based on medical device data and patient visit data, high-frequency and low-frequency statistical methods are used to obtain the equipment turnover cycle and equipment bottom line quantity of each medical device, including: Different types of medical devices in the medical device data are recorded as medical device 1 to medical device M; for any medical device M1, the number of times the medical device M1 is used is obtained, which is recorded as the historical number of times the medical device M1 is used; and the historical number of times all medical devices are used is obtained; The average of the historical usage times of all medical devices is recorded as the mean usage of the device; the medical devices with a historical usage time greater than or equal to the mean usage of the device from medical devices 1 to medical devices M are recorded as high-frequency medical devices; the medical devices with a historical usage time less than the mean usage of the device from medical devices 1 to medical devices M are recorded as low-frequency medical devices; Use high-frequency statistical methods to analyze the medical equipment data and patient visit data of high-frequency medical equipment, and obtain the equipment turnover cycle and equipment bottom line quantity of all high-frequency medical data based on the analysis results; Use low-frequency statistical methods to analyze the medical equipment data and patient visit data of low-frequency medical equipment, and obtain the equipment turnover cycle and equipment bottom line quantity of all low-frequency medical data based on the analysis results; The high-frequency statistical methods include: For any high-frequency medical device A, the time when the high-frequency medical device A is used for the first time is recorded as the device start time, and the time when the high-frequency medical device A is used for the last time is recorded as the device end time; The time period between the equipment start time and the equipment end time is evenly divided into T segments, and recorded in sequence as usage time period 1 to usage time period T based on the time sequence; For any one usage time period T1 from usage time period 1 to usage time period T, based on the patient consultation data, the patients who use the high-frequency medical device A in usage time period T1 are recorded as consultation patient T1~1 to consultation patient T1~K in sequence; For any patient T1~K1 from the patients T1~1 to the patients T1~K, the duration of the high-frequency medical device A used by the patient T1~K1 is recorded as the device usage duration of the patient T1~K1; the device usage duration of all the patients is obtained and recorded in sequence as device usage duration 1 to device usage duration K; Obtain the visiting time differences of adjacent visiting patients from visiting patient T1~1 to visiting patient T1~K, and record them as visiting time difference 1 to visiting time difference K-1; The high-frequency statistical method also includes: For any equipment usage time K1 from equipment usage time 1 to equipment usage time K-1, when equipment usage time K1 is less than the consultation time difference K1, the patients T1~K1+1 are marked as repeatable patients; when equipment usage time K1 is greater than or equal to the consultation time difference K1, the patients T1~K1+1 are marked as waiting patients, and 1 is recorded as the waiting number of patients T1~K1+1; when equipment usage time K1 is greater than or equal to the sum of the consultation time difference K1 plus the consultation time difference K1+1, the waiting number of patients T1~K1+1 is increased by 1, and so on. When equipment usage time K1 is greater than or equal to the sum of the consultation time difference K1 and the consultation time difference K-1, the waiting number of patients T1~K1+1 is (K-1)-K1+1. Obtain the marking status of patients T1~2 to T1~K. When all patients are marked as repeatable patients, record the use time period T1 as a generous time period. When at least one of all patients is not marked as a repeatable patient, obtain the waiting number of all patients marked as waiting patients, and obtain the maximum value of all waiting numbers, record it as the bottom line number of equipment in the use time period T1, and record the equipment usage time corresponding to the maximum value of all waiting numbers as the maximum turnaround time of the use time period T1. Get the maximum rotation time and equipment bottom line quantity of all usage time periods; The time interval consisting of the minimum and maximum values ​​of the maximum rotation time of all use time periods is recorded as the equipment rotation period of high-frequency medical equipment A, and the equipment bottom line quantity of all use time periods is recorded as the equipment bottom line quantity of high-frequency medical equipment A; Based on the above method, the equipment turnover period and equipment bottom line quantity of all high-frequency medical equipment are obtained; The low-frequency statistical method comprises: The number of low-frequency medical devices is recorded as J, and all low-frequency medical devices are recorded as low-frequency medical device 1 to low-frequency medical device J in sequence; For any low-frequency medical device J1 from low-frequency medical device 1 to low-frequency medical device J, obtain the maximum number of low-frequency medical devices J1 used at the same time in the medical device data corresponding to the low-frequency medical device J1, and record it as the equipment bottom line number of the low-frequency medical device J1; Establish a plane rectangular coordinate system, recorded as a low-frequency analysis coordinate system, wherein the coordinate points to the right of the coordinate origin in the X-axis of the low-frequency analysis coordinate system are low-frequency medical equipment 1 to low-frequency medical equipment J, and the unit of the Y-axis of the low-frequency analysis coordinate system is the usage time; The low-frequency statistical method also includes: For any low-frequency medical device J1 from low-frequency medical devices 1 to low-frequency medical devices J, based on the medical device data corresponding to the low-frequency medical device J1, the duration of each use of the low-frequency medical device J1 is recorded as the usage duration J1~1 to the usage duration J1~L, and the minimum and maximum values ​​among the usage duration J1~1 to the usage duration J1~L are recorded as the usage duration L1~MIN and the usage duration L1~MAX, respectively; the straight line parallel to the Y axis corresponding to the low-frequency medical device L1 with the X-axis coordinate in the low-frequency analysis coordinate system is recorded as the vertical reference line, and the time interval corresponding to the area with the Y-axis coordinate in the vertical reference line between the usage duration L1~MIN and the usage duration L1~MAX is recorded as the device rotation period of the low-frequency medical device L1; Based on the above method, the equipment turnover period and equipment bottom line quantity of all low-frequency medical equipment are obtained.

2. The cloud computing-based intelligent medical data processing method according to claim 1, characterized in that: Obtaining the unused quantity of medical devices in the medical database every common multiple of the rotation time, and marking and abnormally annotating the medical devices based on the unused quantity of the medical devices includes: Place the time intervals corresponding to the equipment rotation periods of all low-frequency medical equipment and all high-frequency medical equipment on the same time axis, and record the time interval with the most overlaps of equipment rotation periods in the time axis as the common multiple rotation period; The unused quantity of all medical devices in the medical database is obtained every common multiple rotation time. For any medical device A, the unused quantity of medical device A is recorded as the real-time remaining quantity. When the real-time remaining quantity is less than the bottom line quantity of medical device A, medical device A is marked as equipment to be replenished. When medical device A is marked as equipment to be replenished for P consecutive times, the quantity of medical device A is marked as abnormal, wherein the common multiple rotation time is within the common multiple rotation period.

3. A cloud computing-based smart medical data processing system, applicable to the cloud computing-based smart medical data processing method according to any one of claims 1-2, characterized in that: It includes a data acquisition module, an equipment data analysis module and an equipment data processing module; The data acquisition module is used to acquire all medical data for data processing and record them as a medical database; acquire medical equipment data and patient consultation data in the medical database, wherein the medical equipment data includes the types of medical equipment, the number of medical equipment and the usage of medical equipment, and the patient consultation data includes the patients who have been treated and the usage of medical equipment by the patients who have been treated during the treatment; The equipment data analysis module is used to obtain the equipment turnover cycle and equipment bottom line quantity of each medical equipment based on medical equipment data and patient visit data using high-frequency statistical methods and low-frequency statistical methods; The equipment data processing module is used to obtain the unused quantity of medical equipment in the medical database every common multiple of the rotation time, and mark and annotate the medical equipment as abnormal based on the unused quantity of the medical equipment.

4. An electronic device, characterized in that: The method comprises a processor and a memory, wherein the memory stores computer-readable instructions. When the computer-readable instructions are executed by the processor, the steps in the method according to any one of claims 1 to 2 are executed.

5. A storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 2 are performed.

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