Medical self-service machine process optimization system and method based on interface-free data interaction

Abstract

The present invention discloses a medical self-service machine process optimization system and method based on interface-free data interaction, and relates to the field of medical information processing. The present invention updates and optimizes multiple parameters of the interface-free data interaction technology used for the synchronous update of the check-in data in the hospital's medical self-service machine and the patient information in the hospital information system from the two perspectives of offline and online check-in, thereby ensuring that the check-in data in the hospital's medical self-service machine and the patient information in the hospital information system are updated more synchronously; by collecting the current offline check-in data and the current online check-in data, a determination basis is provided for subsequent determination of whether it is necessary to update multiple parameters of the interface-free data interaction technology; by optimizing the hospital's interface-free data interaction parameter data, a setting basis is provided for subsequent single-update setting or secondary-update setting of multiple parameters of the current hospital's interface-free data interaction technology.

Description

Technical Field

[0001] The present invention belongs to the field of medical information processing, and in particular, relates to a medical self-service machine process optimization system and method based on interface-free data interaction. Background Art

[0002] Chinese patent CN117711594B discloses an intelligent medical guidance system based on machine learning and medical process optimization, which obtains the patient's current medical project related information; a subsystem for planning the medical treatment route; implements real-time outdoor and indoor navigation according to the optimal medical treatment route; based on the patient's current medical project information, pays on behalf of the patient and performs voice-synchronized medical guidance; stores the patient's current medical project information that has been completed as medical treatment record information, and the patient can choose to view these medical treatment records at will.

[0003] At present, the check-in information of patients in the medical self-service machines in hospitals cannot be synchronized with the patient information in the hospital's information system, which increases the waiting time for patients and the trouble of repeatedly filling in information, making the medical process cumbersome and redundant; among them, as the patient's check-in proceeds, the data between the medical self-service machine and the hospital's information system has high real-time performance, especially when checking in online, the data volume change rate of the check-in data is higher; if the relevant parameters for data interaction between the medical self-service machine and the hospital's information system cannot be reasonably set, such as the characteristic parameters of the transmission medium, signal strength and interference parameters, equipment processing capacity parameters, network congestion parameters and transmission distance parameters, etc., the synchronization between the patient's check-in data in the medical self-service machine and the hospital's information system will have a high delay or even cannot be synchronized, so that the doctor still cannot obtain the patient's information in time during the formal consultation, increasing the patient's waiting time and the trouble of repeatedly filling in information. Summary of the invention

[0004] In view of the problems in the related art, the present invention proposes a medical self-service machine process optimization system and method based on interface-free data interaction to overcome the above-mentioned technical problems existing in the existing related art.

[0005] In order to solve the above technical problems, the present invention is achieved through the following technical solutions:

[0006] The present invention is a medical self-service machine process optimization method based on non-interface data interaction, comprising the following steps:

[0007] S1. Collect the offline medical check-in time consumption data of patients who have signed in continuously in the past and the present, and obtain the offline medical check-in time consumption data set and the current check-in time consumption data set respectively; collect the time interval data of the completion of the update of the check-in information of the corresponding patients in the historical and current medical self-service machines and the hospital information system, and obtain the time interval data set and the current time interval data set respectively; collect the change rate data of the patient check-in data in the historical and current medical self-service machines and the hospital information system, and obtain the historical self-service machine check-in change rate data set, the information system check-in change rate data set, the current self-service machine check-in change rate data set and the current information system check-in change rate data set respectively;

[0008] S2. Optimize the hospital's non-interface data interaction parameter data according to the offline medical check-in time-consuming data set, the time interval data set, the historical self-service machine check-in change rate data set, and the information system check-in change rate data set to obtain a first final non-interface data interaction parameter data set and a second final non-interface data interaction parameter data set;

[0009] The data types in the first final non-interface data interaction parameter data set and the second final non-interface data interaction parameter data set both include characteristics of the transmission medium, signal strength and interference, processing capability of the device, network congestion level, and transmission distance;

[0010] S3, performing a primary update setting or a secondary update setting on the hospital's current non-interface data interaction parameters according to the current sign-in time-consuming data set, the current time interval data set, the current self-service machine sign-in change rate data set, and the current information system sign-in change rate data set;

[0011] When patients sign in at the hospital for medical treatment, there are two ways to sign in: online and offline. The online sign-in method means that patients can sign in through mobile devices such as mobile phones, such as scanning WeChat to sign in, etc.; and the offline sign-in method means that patients sign in at the hospital's medical self-service machine after arriving at the hospital. The sign-in rates of these two sign-in methods are different. The offline sign-in method can only sign in one patient at a time, and the next patient will sign in only after the previous patient has signed in; and the online sign-in method means that multiple patients sign in at the same time. Therefore, the update speed of the sign-in data corresponding to the two sign-in methods is different. Based on the above, this solution updates and optimizes multiple parameters of the interface-free data interaction technology used for the synchronous update of the sign-in data in the hospital's medical self-service machine and the patient information in the hospital information system from the two perspectives of offline and online sign-in. Ensure that the check-in data in the hospital's medical self-service machines is more synchronized with the update of patient information in the hospital information system, with better real-time performance, so as to better meet the needs of doctors' diagnosis and treatment; among them, by collecting multiple historical offline check-in data of medical self-service machines and historical online check-in data of medical self-service machines in multiple time periods, a data basis is provided for subsequent optimization operations on multiple parameters of non-interface data interaction technology; by collecting multiple current offline check-in data of medical self-service machines and current online check-in data of medical self-service machines in multiple time periods, a basis for determining whether it is necessary to update multiple parameters of non-interface data interaction technology is provided; by optimizing the hospital's non-interface data interaction parameter data, a basis for setting is provided for subsequent one-time update settings or secondary update settings of multiple parameters of the current hospital's non-interface data interaction technology.

[0012] Preferably, the S1 comprises the following steps:

[0013] S11, collecting multiple historical patients who have signed in continuously at offline medical self-service machines and the corresponding offline check-in time consumption, to obtain an offline check-in patient set and an offline check-in time consumption data set;

[0014] S12, setting multiple historical online sign-in data collection time periods to obtain a historical collection time period set; collecting the number of change data of historical online medical self-service machine visit sign-in information multiple times according to the historical collection time period set to obtain a patient sign-in change data set;

[0015] Calculate the patient sign-in data change rate data for each historical online sign-in data collection time period according to the patient sign-in change data set and the historical collection time period set, and obtain the historical self-service machine sign-in change rate data set;

[0016] S13, the medical self-service machine adopts the interface-free data interaction technology and updates the corresponding patient information in the hospital information system according to the check-in information of each patient in the offline check-in patient set; during the updating process, the time interval data between the update of the offline check-in information of the patient in the medical self-service machine and the update of the corresponding patient information in the hospital information system is collected according to the offline check-in patient set to obtain the time interval data set;

[0017] The patient's online sign-in data is synchronized to the medical self-service machine, and the medical self-service machine then uses the interface-free data interaction technology to update the corresponding patient information in the hospital information system according to the patient's online sign-in data; during the update process, the update rate data of the patient information in each historical online sign-in data collection time period in the hospital information system is obtained according to the historical collection time period set, and the information system sign-in change rate data set is obtained;

[0018] S14, collecting multiple current offline sign-in data of medical self-service machines and current online sign-in data of medical self-service machines in multiple time periods;

[0019] Since it takes a certain amount of time for each patient to sign in through the medical self-service machine when signing in offline, the sign-in time provides time for synchronization of patient information between the medical self-service machine and the hospital information system; when the time required for synchronization of patient information between the medical self-service machine and the hospital information system is greater than the sign-in time of the corresponding patient, that is, the synchronization rate is lower than the sign-in update rate, this will result in the sign-in information not being updated to the hospital information system in a timely manner. When more and more data accumulates, it will affect the final doctor's diagnosis and treatment; and when signing in online, if the update rate of the patient sign-in information in the medical self-service machine is greater than the update rate of the patient information in the hospital information system, it will also affect the final doctor's diagnosis and treatment; based on this, this solution collects the offline medical check-in time of historical patients, the update rate of the patient sign-in information in the medical self-service machine when signing in online, and the update rate of the patient information in the hospital information system. According to these data, the parameters of the current hospital's non-interface data interaction can be optimized in a targeted manner.

[0020] Preferably, the S14 comprises the following steps:

[0021] S141, collecting the check-in time data corresponding to patients who have signed in consecutively at multiple offline medical self-service machines in the current hospital and the time interval data between the update of the offline check-in information of the patient in the medical self-service machine and the update of the corresponding patient information in the hospital information system, to obtain the current check-in time data set and the current time interval data set;

[0022] S142, setting multiple time periods for collecting online check-in data to obtain a current collection time period set;

[0023] According to the current collection time period set, the rate of change data of the current online medical self-service machine visit check-in information and the update rate data of the online check-in data in the current hospital information system are collected to obtain the current self-service machine check-in change rate data set and the current information system check-in change rate data set;

[0024] Preferably, S2 comprises the following steps:

[0025] S21, setting a non-interface data interaction parameter type set; collecting data values ​​of various parameters of the hospital during non-interface data interaction according to the non-interface data interaction parameter type set to obtain an initial non-interface data interaction parameter data set;

[0026] S22, when the number of patients who sign in for online medical consultation is 0, optimizing each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set according to the offline medical consultation sign-in time-consuming data set and the time interval data set, to obtain a first final non-interface data interaction parameter data set;

[0027] Otherwise, each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set is optimized according to the offline medical check-in time-consuming data set, the time interval data set, the historical self-service machine check-in change rate data set, and the information system check-in change rate data set to obtain a second final non-interface data interaction parameter data set;

[0028] The types of interfaceless data interaction parameters include the characteristics of the transmission medium, signal strength and interference, equipment processing capabilities, network congestion level, and transmission distance. Since the requirements for the hospital's interfaceless interaction rate are different when there is only offline sign-in and when offline sign-in and online sign-in coexist, the two situations are analyzed separately when the number of patients who sign in online is 0 and when the number of patients who sign in online is not 0.

[0029] Preferably, in S22, each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set is optimized according to the offline medical check-in time-consuming data set and the time interval data set to obtain the first final non-interface data interaction parameter data set, including the following steps:

[0030] S2211, constructing a first mayfly population; setting the maximum number of iterations of the first mayfly population to , the current number of iterations is , respectively recorded as the first maximum number of iterations and the first current number of iterations;

[0031] S2212, setting a value interval of a parameter corresponding to each non-interface data interaction parameter type in the non-interface data interaction parameter type set to obtain a value interval set; setting an initial position of each mayfly in the first mayfly population according to the value interval set to obtain a first initial position matrix;

[0032] S2213, constructing a fitness function of the first mayfly population according to the offline medical check-in time-consuming data set and the time interval data set;

[0033] S2214, start iteration, and set the first current iteration number to 1 before iteration; during the first round of iteration, use the fitness function of the first mayfly population to calculate the fitness value of the initial position of each mayfly in the first initial position matrix to obtain a first fitness value set; use the maximum fitness value in the first fitness value set and the initial position of the corresponding mayfly as the first global optimal fitness and the first global optimal position respectively; update the initial position of each mayfly in the first initial position matrix according to the first global optimal fitness and the first global optimal position; after the update is completed, add 1 to the first current iteration number and enter the next round of iteration;

[0034] In each other round of iteration, the fitness function of the first mayfly population is used to calculate the fitness value of each mayfly position updated in the previous round of iteration to obtain a second fitness value set; the maximum fitness value in the second fitness value set and the position of the corresponding mayfly are respectively used as the second global optimal fitness and the second global optimal position; the position of each mayfly updated in the previous round of iteration is updated again according to the second global optimal fitness and the second global optimal position; after the update is completed, the first current iteration number is increased by 1 and the next round of iteration is entered;

[0035] S2215, when When , the iteration is stopped to obtain the first final global optimal position; the first final global optimal position is used as the first final non-interface data interaction parameter data set;

[0036] Preferably, in S22, each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set is optimized according to the offline medical check-in time-consuming data set, the time interval data set, the historical self-service machine check-in change rate data set, and the information system check-in change rate data set to obtain the second final non-interface data interaction parameter data set, including the following steps:

[0037] S2221: Construct a second mayfly population; set the maximum number of iterations of the second mayfly population to , the current number of iterations is , respectively recorded as the second maximum number of iterations and the second current number of iterations;

[0038] S2222, setting the initial position of each mayfly in the second mayfly population according to the value interval set to obtain a second initial position matrix;

[0039] S2223, constructing a fitness function of the second mayfly population according to the offline medical check-in time-consuming data set and the time interval data set, the historical self-service machine check-in change rate data set, and the information system check-in change rate data set;

[0040] S2224, start iteration, and set the second current iteration number to 1 before iteration; during the first round of iteration, use the fitness function of the second mayfly population to calculate the fitness value of the initial position of each mayfly in the second initial position matrix to obtain a third fitness value set; use the maximum fitness value in the third fitness value set and the initial position of the corresponding mayfly as the third global optimal fitness and the third global optimal position respectively; update the initial position of each mayfly in the second initial position matrix according to the third global optimal fitness and the third global optimal position; after the update is completed, add 1 to the second current iteration number and enter the next round of iteration;

[0041] In each other round of iteration, the fitness function of the second mayfly population is used to calculate the fitness value of each mayfly position updated in the previous round of iteration to obtain a fourth fitness value set; the maximum fitness value in the fourth fitness value set and the position of the corresponding mayfly are respectively used as the fourth global optimal fitness and the fourth global optimal position; the position of each mayfly updated in the previous round of iteration is updated again according to the fourth global optimal fitness and the fourth global optimal position; after the update is completed, the second current iteration number is increased by 1 and the next round of iteration is entered;

[0042] S2225, when When , the iteration is stopped to obtain a second final global optimal position; the second final global optimal position is used as a second final non-interface data interaction parameter data set;

[0043] By simulating the social behavior and mating process of mayflies, the mayfly optimization algorithm can effectively find the optimal solution in the search space, maintain a good balance between exploring new solutions and utilizing existing information, help to escape from the local optimal solution, and improve the global search capability. Based on this, this scheme uses the mayfly optimization algorithm to iterate and optimize multiple parameters during the hospital's interface-free data interaction, so that the real-time requirements can be met when data synchronization is performed through interface-free interaction technology.

[0044] Preferably, S3 comprises the following steps:

[0045] S31, predicting the sign-in time consumption data and time interval data at future moments according to the current sign-in time consumption data set and the current time interval data set, to obtain a future sign-in time consumption data set and a future time interval data set;

[0046] Predicting the self-service machine sign-in change rate data and the information system sign-in change rate data at future times according to the current self-service machine sign-in change rate data set and the current information system sign-in change rate data set, to obtain a future self-service machine sign-in change rate data set and a future information system sign-in change rate data set;

[0047] S32, updating and setting the parameters for the current hospital's non-interface data interaction according to the current sign-in time-consuming data set, the current time interval data set, the current self-service machine sign-in change rate data set, and the current information system sign-in change rate data set;

[0048] S33. When the first update setting is not performed, the parameters for the current hospital to perform non-interface data interaction are updated for a second time according to the future sign-in time-consuming data set, the future time interval data set, the future self-service machine sign-in change rate data set, and the future information system sign-in change rate data set; otherwise, there is no need to perform a second update setting on the parameters for the current hospital to perform non-interface data interaction;

[0049] Through prediction, we can obtain the sign-in time consumption data, time interval data, self-service machine sign-in change rate data set and information system sign-in change rate data at future moments, and judge whether the current interface-free data interaction parameters meet the requirements at both the current moment and the future moment. If not, we can make timely adjustments.

[0050] Preferably, the S32 comprises the following steps:

[0051] S321, performing a difference operation between the current time interval data set and the current sign-in time-consuming data set to obtain a first current difference data set; then performing a difference operation between the current self-service machine sign-in change rate data set and the current information system sign-in change rate data set to obtain a second current difference data set;

[0052] S322. When the number of patients who have signed in for online medical consultation at the hospital is 0 and there is difference data less than 0 in the first current difference data set, the first final non-interface data interaction parameter data set is used to update and set the parameters for the current hospital when performing non-interface data interaction; when the number of patients who have signed in for online medical consultation at the hospital is 0 and there is no difference data less than 0 in the first current difference data set, there is no need to update and set the parameters for the current hospital when performing non-interface data interaction;

[0053] When the number of patients who have signed in for online medical treatment at the hospital is not 0, there is difference data less than 0 in the first current difference data set, or there is difference data less than 0 in the second current difference data set, the second final non-interface data interaction parameter data set is used to update the parameters for non-interface data interaction of the current hospital; when the number of patients who have signed in for online medical treatment at the hospital is not 0, there is no difference data less than 0 in the first current difference data set, and there is no difference data less than 0 in the second current difference data set, there is no need to update the parameters for non-interface data interaction of the current hospital;

[0054] Collect the online and offline check-in data of the current patients in the hospital, and provide a data basis for the subsequent update and setting of parameters for the current hospital during interface-free data interaction.

[0055] Preferably, the S33 comprises the following steps:

[0056] S331, performing a difference operation between the future sign-in time-consuming data set and the future time interval data set to obtain a first future difference data set; then performing a difference operation between the future self-service machine sign-in change rate data set and the future information system sign-in change rate data set to obtain a second future difference data set;

[0057] S332. When the number of patients who have signed in for online medical consultation at the hospital is not 0, there is difference data less than 0 in the first future difference data set, or there is difference data less than 0 in the second future difference data set, the second final non-interface data interaction parameter data set is used to perform a secondary update setting on the parameters for non-interface data interaction at the current hospital; when the number of patients who have signed in for online medical consultation at the hospital is not 0, there is no difference data less than 0 in the first current difference data set, and there is no difference data less than 0 in the second current difference data set, there is no need to perform a secondary update setting on the parameters for non-interface data interaction at the current hospital;

[0058] The medical self-service machine process optimization system based on non-interface data interaction includes a historical sign-in data collection module, a current sign-in data collection module, a non-interface data interaction parameter data optimization module and a current non-interface data interaction parameter update setting module.

[0059] The present invention combines the patient's check-in and medical consultation process in the hospital into the self-service machine, and then uses the interface-free technology to change the hospital's HIS information through the check-in and provide feedback on the medical consultation. That is, the check-in information in the medical self-service machine is synchronized with the hospital's HIS system through the interface-free data interaction technology. When the patient is consulted, the doctor obtains the patient's changed information through the HIS system.

[0060] The present invention has the following beneficial effects: 1. In the present invention, multiple parameters of the interfaceless data interaction technology used for the synchronous update of the sign-in data in the hospital's medical self-service machine and the patient information in the hospital information system are updated and optimized from the two perspectives of offline and online sign-in, ensuring that the sign-in data in the hospital's medical self-service machine and the patient information in the hospital information system are updated more synchronously and in a more real-time manner, thereby better meeting the needs of doctors' diagnosis and treatment; wherein; by collecting multiple current offline sign-in data of the medical self-service machine and the current online sign-in data of the medical self-service machine in multiple time periods, a basis for determining whether it is necessary to update multiple parameters of the interfaceless data interaction technology is provided for subsequent determination; by optimizing the hospital's interfaceless data interaction parameter data, a basis for setting is provided for subsequent one-time update setting or secondary update setting of multiple parameters of the current hospital's interfaceless data interaction technology.

[0061] 2. In the present invention, by separately analyzing the two situations when the number of patients who sign in for online medical treatment is 0 and when the number of patients who sign in for online medical treatment is not 0, the analysis is made more comprehensive and accurate, thereby making the subsequent optimization effect of the parameters without interface data interaction better.

[0062] 3. In the present invention, the mayfly optimization algorithm is used to iterate and optimize multiple parameters when the hospital performs interface-free data interaction multiple times, so that the real-time requirements can be met when data synchronization is performed through the interface-free interaction technology.

[0063] Of course, any product implementing the present invention does not necessarily need to achieve all of the advantages described above at the same time. BRIEF DESCRIPTION OF THE DRAWINGS

[0064] In order to more clearly illustrate the technical solutions of the embodiments of the invention, the drawings required for describing the embodiments will be briefly introduced below. Obviously, the drawings described below are only some embodiments of the invention. For ordinary technicians in this field, they can also obtain drawings based on these drawings without paying creative work.

[0065] Figure 1 It is a flow chart of a medical self-service machine process optimization method based on non-interface data interaction of the present invention;

[0066] Figure 2 This is a flow chart of synchronizing the check-in information of the medical self-service machine process with the hospital HIS system of the present invention. DETAILED DESCRIPTION

[0067] The following will be combined with the drawings in the embodiments of the invention to clearly and completely describe the technical solutions in the embodiments of the invention. Obviously, the described embodiments are only part of the embodiments of the invention, not all of the embodiments. Based on the embodiments in the invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the invention.

[0068] In the description of the present invention, it is necessary to understand that the terms "opening", "upper", "lower", "top", "middle", "inside" and the like indicating orientation or positional relationship are only for the convenience of describing the invention and simplifying the description, and do not indicate or imply that the components or elements referred to must have a specific orientation, be constructed and operate in a specific orientation, and therefore cannot be understood as limiting the invention.

[0069] Embodiment 1

[0070] This embodiment is a medical self-service machine process optimization method based on non-interface data interaction, including the following steps:

[0071] S1. Collect multiple historical patients who have signed in continuously at offline medical self-service machines and the corresponding offline medical sign-in time consumption to obtain an offline medical sign-in time consumption data set; the medical self-service machine adopts a non-interface data interaction technology and updates the corresponding patient information in the hospital information system according to the sign-in information of each patient in the offline medical sign-in patient set, and collects the time interval data between the update of the patient's offline medical sign-in information in the medical self-service machine and the update of the corresponding patient information in the hospital information system, to obtain a time interval data set; collect the number of change data of historical online medical self-service machine medical sign-in information for multiple times and the patient sign-in data change rate data for each historical online sign-in data collection time period, to obtain the historical self-service machine sign-in change rate data data set; obtain the update rate data of patient information in each historical online sign-in data collection time period in the hospital information system, and obtain the information system sign-in change rate data set; collect the sign-in time consumption data corresponding to patients who sign in continuously at multiple offline medical self-service machines in the current hospital, and the time interval data between the update of the offline sign-in information of the patient in the medical self-service machine and the update of the corresponding patient information in the hospital information system, and obtain the current sign-in time consumption data set and the current time interval data set; collect the rate of change data of the current online medical self-service machine sign-in information and the update rate data of the online sign-in data in the current hospital information system, and obtain the current self-service machine sign-in change rate data set and the current information system sign-in change rate data set;

[0072] The S1 comprises the following steps:

[0073] S11. Collect multiple patients who have signed in continuously at offline medical self-service machines and the corresponding offline check-in time consumption to obtain a set of offline check-in patients. And offline medical check-in time consumption dataset , a 1i , a 2i Respectively represent the collected i The historical data of patients who have signed in at offline medical self-service machines and the corresponding offline medical sign-in time consumption, Indicates the total number of patients who have signed in at offline medical self-service machines in history;

[0074] S12. Set multiple historical online sign-in data collection time periods to obtain a historical collection time period set. , Indicates the setting i Historical online check-in data collection time period, Indicates the total number of historical online sign-in data collection time periods set; according to the number of changes in historical online medical self-service machine sign-in information collected multiple times in the historical collection time period set, the patient sign-in change data set is obtained , a 3i Indicated in i Patient sign-in change data within the historical online sign-in data collection period;

[0075] According to the patient sign-in change data set and the historical collection time period set, calculate the patient sign-in data change rate data for each historical online sign-in data collection time period to obtain the historical self-service machine sign-in change rate data set , a 4i Indicates i The change rate of patient check-in data during the historical online check-in data collection period; the calculation formula is as follows: ;

[0076] In the formula, Indicates the setting i The length of the historical online check-in data collection period;

[0077] S13. The medical self-service machine adopts the interface-free data interaction technology and updates the corresponding patient information in the hospital information system according to the check-in information of each patient in the offline check-in patient set; during the update process, the time interval data between the update of the offline check-in information of the patient in the medical self-service machine and the update of the corresponding patient information in the hospital information system is collected according to the offline check-in patient set to obtain the time interval data set. ,a 5i Indicates that offline check-in patients are concentrated in the first i The time interval between when the offline check-in information of a patient is updated in the medical self-service machine and when the information in the hospital information system is updated;

[0078] The patient's online sign-in data is synchronized to the medical self-service machine, and the medical self-service machine then uses the interface-free data interaction technology to update the corresponding patient information in the hospital information system according to the patient's online sign-in data; during the update process, the update rate data of the patient information in each historical online sign-in data collection time period in the hospital information system is obtained according to the historical collection time period set, and the information system sign-in change rate data set is obtained , a 6i Indicates i Update rate data of patient information in the hospital information system during the historical online check-in data collection period;

[0079] S14, collecting multiple current offline sign-in data of medical self-service machines and current online sign-in data of medical self-service machines in multiple time periods;

[0080] The S14 comprises the following steps:

[0081] S141. Collect the check-in time consumption data corresponding to patients who have signed in continuously at multiple offline medical self-service machines in the current hospital, and the time interval data between the update of the offline check-in information of the patient in the medical self-service machine and the update of the corresponding patient information in the hospital information system, and obtain the current check-in time consumption data set and the current time interval dataset , , Respectively represent the collected i The check-in time data corresponding to the current patient who has signed in continuously at the offline medical self-service machine and the i The time interval between the offline check-in information of the current patient being updated in the medical self-service machine and the information being updated in the hospital information system. Indicates the total number of patients who signed in consecutively at offline medical self-service machines;

[0082] S142, set the time periods for collecting the current online sign-in data, and obtain the current collection time period set. , e i Indicates the setting i The time period for collecting online sign-in data. Indicates the total number of time periods set for collecting online check-in data;

[0083] According to the current collection time period set, the rate of change data of the current online medical self-service machine visit check-in information and the update rate data of the online check-in data in the current hospital information system are collected, and the current self-service machine check-in change rate data set is obtained. And the current information system check-in change rate data set , , Respectively expressed in i The rate of change of the current online medical self-service machine visit sign-in information collected during the time period of the current online sign-in data collection and the update rate of the online sign-in data in the current hospital information system;

[0084] S2. Optimize the hospital's non-interface data interaction parameter data according to the offline medical check-in time-consuming data set, the time interval data set, the historical self-service machine check-in change rate data set, and the information system check-in change rate data set to obtain a first final non-interface data interaction parameter data set and a second final non-interface data interaction parameter data set;

[0085] The S2 comprises the following steps:

[0086] S21. Set the non-interface data interaction parameter type set , b i Indicates the setting i There are no interface data interaction parameter types, Indicates the total number of set non-interface data interaction parameter types; collects data values ​​of various parameters of the hospital's non-interface data interaction according to the non-interface data interaction parameter type set to obtain an initial non-interface data interaction parameter data set;

[0087] S22, when the number of patients who sign in for online medical consultation is 0, optimizing each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set according to the offline medical consultation sign-in time-consuming data set and the time interval data set, to obtain a first final non-interface data interaction parameter data set;

[0088] Otherwise, each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set is optimized according to the offline medical check-in time-consuming data set, the time interval data set, the historical self-service machine check-in change rate data set, and the information system check-in change rate data set to obtain a second final non-interface data interaction parameter data set;

[0089] In S22, each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set is optimized according to the offline medical check-in time-consuming data set and the time interval data set to obtain the first final non-interface data interaction parameter data set, including the following steps:

[0090] S2211. Constructing the first mayfly population , c 1i Indicates the first mayfly population i Only mayflies, represents the size of the first mayfly population; sets the maximum number of iterations of the first mayfly population to , the current number of iterations is , respectively recorded as the first maximum number of iterations and the first current number of iterations; the search space dimension of the first mayfly population is ;

[0091] S2212: Set the value range of the parameter corresponding to each non-interface data interaction parameter type in the non-interface data interaction parameter type set to obtain a value range set. ;as follows, ;

[0092] in, , Respectively represent the first i The lower limit and upper limit of the value of the parameter corresponding to the non-interface data interaction parameter type;

[0093] According to the value interval set Set the initial position of each mayfly in the first mayfly population to obtain the first initial position matrix d 1 ;as follows, ;in, d 1ij Indicates the first mayfly population i The initial position of the mayfly is the first j The components of the data dimension of the non-interface data interaction parameter of the type; the calculation formula is as follows, ;

[0094] In the formula, rand 1ij Indicates for d 1ij Generate a random number between 0 and 1;

[0095] S2213, based on the offline medical check-in time-consuming data set and the time interval dataset Constructing the fitness function of the first mayfly population ;as follows, ;

[0096] in, a 2(i-1) Indicates the number of offline medical check-in time-consuming data sets i- 1 offline medical check-in time consumption data; β represents a sufficiently large positive number;

[0097] S2214, start iteration, before iteration, set the first current iteration number Set to 1; the fitness function of the first mayfly population is used in the first iteration Calculate the fitness value of the initial position of each mayfly in the first initial position matrix to obtain a first fitness value set; use the maximum fitness value in the first fitness value set and the initial position of the corresponding mayfly as the first global optimal fitness and the first global optimal position respectively; update the initial position of each mayfly in the first initial position matrix according to the first global optimal fitness and the first global optimal position; after the update is completed, update the first current iteration number Add 1 and enter the next iteration;

[0098] In each other iteration, the fitness function of the first mayfly population is used Calculate the fitness value of each mayfly position updated in the previous round of iterations to obtain a second fitness value set; use the maximum fitness value in the second fitness value set and the position of the corresponding mayfly as the second global optimal fitness and the second global optimal position respectively; update the position of each mayfly updated in the previous round of iterations according to the second global optimal fitness and the second global optimal position; after the update is completed, update the first current iteration number Add 1 and enter the next iteration;

[0099] S2215, when When , the iteration is stopped to obtain the first final global optimal position; the first final global optimal position is used as the first final non-interface data interaction parameter data set;

[0100] In S22, each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set is optimized according to the offline medical check-in time-consuming data set, the time interval data set, the historical self-service machine check-in change rate data set, and the information system check-in change rate data set to obtain the second final non-interface data interaction parameter data set, including the following steps:

[0101] S2221; Construct the second mayfly population , c2i Indicates the second mayfly population i Only mayflies, represents the size of the second mayfly population; sets the maximum number of iterations of the second mayfly population to , the current number of iterations is , respectively recorded as the second maximum number of iterations and the second current number of iterations; the search space dimension of the second mayfly population is ;

[0102] S2222, according to the value interval set Set the initial position of each mayfly in the second mayfly population to obtain the second initial position matrix d 2 ;as follows, ;

[0103] in, d 2ij Indicates the second mayfly population i The initial position of the mayfly is the first j The components of the data dimension of the non-interface data interaction parameter of the type; the calculation formula is as follows, In the formula, rand 2ij Indicates for d 2ij Generate a random number between 0 and 1;

[0104] S2223, based on the offline medical check-in time-consuming data set and the time interval dataset , Historical self-service machine sign-in change rate dataset And the information system check-in change rate data set Constructing the fitness function of the second mayfly population ;as follows, ;

[0105] in, a 2(i-1) represents the number of the offline medical check-in time-consuming dataset i- 1 offline medical check-in time consumption data; , Both represent sufficiently large positive numbers;

[0106] S2224, start iteration, before iteration, set the second current iteration number Set to 1; the fitness function of the second mayfly population is used in the first iteration Calculate the fitness value of the initial position of each mayfly in the second initial position matrix to obtain a third fitness value set; use the maximum fitness value in the third fitness value set and the initial position of the corresponding mayfly as the third global optimal fitness and the third global optimal position respectively; update the initial position of each mayfly in the second initial position matrix according to the third global optimal fitness and the third global optimal position; after the update is completed, the second current iteration number is Add 1 and enter the next iteration;

[0107] In each other iteration, the fitness function of the second mayfly population is used Calculate the fitness value of each mayfly position updated in the previous round of iteration to obtain a fourth fitness value set; use the maximum fitness value in the fourth fitness value set and the position of the corresponding mayfly as the fourth global optimal fitness and the fourth global optimal position respectively; update the position of each mayfly updated in the previous round of iteration again according to the fourth global optimal fitness and the fourth global optimal position; after the update is completed, the second current iteration number Add 1 and enter the next iteration;

[0108] S2225, when When , the iteration is stopped to obtain a second final global optimal position; the second final global optimal position is used as a second final non-interface data interaction parameter data set;

[0109] S3, performing a primary update setting or a secondary update setting on the hospital's current non-interface data interaction parameters according to the current sign-in time-consuming data set, the current time interval data set, the current self-service machine sign-in change rate data set, and the current information system sign-in change rate data set;

[0110] The S3 comprises the following steps:

[0111] S31, predicting the sign-in time consumption data and time interval data at future moments according to the current sign-in time consumption data set and the current time interval data set, to obtain a future sign-in time consumption data set and a future time interval data set;

[0112] Predicting the self-service machine sign-in change rate data and the information system sign-in change rate data at future times according to the current self-service machine sign-in change rate data set and the current information system sign-in change rate data set, to obtain a future self-service machine sign-in change rate data set and a future information system sign-in change rate data set;

[0113] S32, updating and setting the parameters for the current hospital's non-interface data interaction according to the current sign-in time-consuming data set, the current time interval data set, the current self-service machine sign-in change rate data set, and the current information system sign-in change rate data set;

[0114] The S32 comprises the following steps:

[0115] S321, performing a difference operation between the current time interval dataset and the current sign-in time dataset to obtain a first current difference dataset , Indicates the first i The current time interval data and the current check-in time consumption data set i -1 the difference between the current sign-in time-consuming data; then perform a difference operation between the current self-service machine sign-in change rate data set and the current information system sign-in change rate data set to obtain a second current difference data set , Indicates the number of the current information system check-in change rate data set i The check-in change rate data is compared with the current self-service machine check-in change rate data set. i The difference between the check-in change rate data;

[0116] S322. When the number of patients who have signed in for online medical consultation at the hospital is 0 and there is difference data less than 0 in the first current difference data set, the first final non-interface data interaction parameter data set is used to update and set the parameters for the current hospital when performing non-interface data interaction; when the number of patients who have signed in for online medical consultation at the hospital is 0 and there is no difference data less than 0 in the first current difference data set, there is no need to update and set the parameters for the current hospital when performing non-interface data interaction;

[0117] When the number of patients who have signed in for online medical treatment at the hospital is not 0, there is difference data less than 0 in the first current difference data set, or there is difference data less than 0 in the second current difference data set, the second final non-interface data interaction parameter data set is used to update the parameters for non-interface data interaction of the current hospital; when the number of patients who have signed in for online medical treatment at the hospital is not 0, there is no difference data less than 0 in the first current difference data set, and there is no difference data less than 0 in the second current difference data set, there is no need to update the parameters for non-interface data interaction of the current hospital;

[0118] S33. When the first update setting is not performed, the parameters for the current hospital to perform non-interface data interaction are updated for a second time according to the future sign-in time-consuming data set, the future time interval data set, the future self-service machine sign-in change rate data set, and the future information system sign-in change rate data set; otherwise, there is no need to perform a second update setting on the parameters for the current hospital to perform non-interface data interaction;

[0119] The S33 comprises the following steps:

[0120] S331, performing a difference operation between the future check-in time-consuming data set and the future time interval data set to obtain a first future difference data set , represents the first i The future time interval data and the future check-in time consumption data set i -1 The difference between the time consumption of future check-in data, f represents the total number of future sign-in time-consuming data in the future sign-in time-consuming data set; then the future self-service machine sign-in change rate data set and the future information system sign-in change rate data set are subtracted to obtain a second future difference data set , represents the number of the future information system check-in change rate data set i The check-in change rate data and the future self-service machine check-in change rate data set i The difference between the check-in change rate data, Indicates the total number of check-in change rate data in the future information system check-in change rate data set;

[0121] S332. When the number of patients who have signed in for online medical treatment at the hospital is not 0, there is difference data less than 0 in the first future difference data set, or there is difference data less than 0 in the second future difference data set, the second final non-interface data interaction parameter data set is used to perform a second update setting of the parameters for the current hospital when performing non-interface data interaction; when the number of patients who have signed in for online medical treatment at the hospital is not 0, there is no difference data less than 0 in the first current difference data set, and there is no difference data less than 0 in the second current difference data set, there is no need to perform a second update setting of the parameters for the current hospital when performing non-interface data interaction.

[0122] Embodiment 2

[0123] This embodiment discloses a medical self-service machine process optimization system based on non-interface data interaction, and the system can implement the method of the above embodiment, including a historical sign-in data collection module, a current sign-in data collection module, a non-interface data interaction parameter data optimization module, and a current non-interface data interaction parameter update setting module;

[0124] The historical sign-in data collection module is used to collect multiple historical offline sign-in data of medical self-service machines and historical online sign-in data of medical self-service machines in multiple time periods, and obtain offline medical sign-in time consumption data set, time interval data set, historical self-service machine sign-in change rate data set and information system sign-in change rate data set;

[0125] The current sign-in data collection module is used to collect multiple current offline sign-in data of medical self-service machines and current online sign-in data of medical self-service machines in multiple time periods, and obtain a current sign-in time-consuming data set, a current time interval data set, a current self-service machine sign-in change rate data set, and a current information system sign-in change rate data set;

[0126] The non-interface data interaction parameter data optimization module is used to optimize the hospital's non-interface data interaction parameter data according to the offline medical check-in time-consuming data set, the time interval data set, the historical self-service machine check-in change rate data set, and the information system check-in change rate data set to obtain a first final non-interface data interaction parameter data set and a second final non-interface data interaction parameter data set;

[0127] The current non-interface data interaction parameter update setting module is used to perform a primary update setting or a secondary update setting of the hospital's current non-interface data interaction parameters according to the current sign-in time consumption data set, the current time interval data set, the current self-service machine sign-in change rate data set, and the current information system sign-in change rate data set.

[0128] In the description of this specification, the description with reference to the terms "one embodiment", "example", "specific example", etc. means that the specific features, structures, materials or characteristics described in conjunction with the embodiment or example are included in at least one embodiment or example of the invention. In this specification, the schematic representation of the above terms does not necessarily refer to the same embodiment or example. Moreover, the specific features, structures, materials or characteristics described can be combined in any one or more embodiments or examples in a suitable manner.

[0129] The preferred embodiments of the invention disclosed above are only used to help explain the invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to the specific implementation methods described. Obviously, many modifications and changes can be made according to the content of this specification. This specification selects and specifically describes these embodiments in order to better explain the principles and practical applications of the invention, so that those skilled in the art can understand and use the invention well.

Claims

1. A medical self-service machine process optimization method based on non-interface data interaction, characterized in that: The following steps are involved: S1. Collect the offline medical check-in time consumption data of patients who have signed in continuously in the past and the present, and obtain the offline medical check-in time consumption data set and the current check-in time consumption data set respectively; collect the time interval data of the completion of the update of the check-in information of the corresponding patients in the historical and current medical self-service machines and the hospital information system, and obtain the time interval data set and the current time interval data set respectively; collect the change rate data of the patient check-in data in the historical and current medical self-service machines and the hospital information system, and obtain the historical self-service machine check-in change rate data set, the information system check-in change rate data set, the current self-service machine check-in change rate data set and the current information system check-in change rate data set respectively; S2. Optimize the hospital's non-interface data interaction parameter data according to the offline medical check-in time-consuming data set, the time interval data set, the historical self-service machine check-in change rate data set, and the information system check-in change rate data set to obtain a first final non-interface data interaction parameter data set and a second final non-interface data interaction parameter data set; The data types in the first final non-interface data interaction parameter data set and the second final non-interface data interaction parameter data set both include characteristics of the transmission medium, signal strength and interference, processing capability of the device, network congestion level, and transmission distance; S3. Perform a primary update or secondary update on the hospital's current non-interface data interaction parameters based on the current sign-in time dataset, the current time interval dataset, the current self-service machine sign-in change rate dataset, and the current information system sign-in change rate dataset.

2. The medical self-service machine process optimization method based on non-interface data interaction according to claim 1 is characterized in that: The S1 comprises the following steps: S11, collecting multiple historical patients who have signed in continuously at offline medical self-service machines and the corresponding offline check-in time consumption, to obtain an offline check-in patient set and an offline check-in time consumption data set; S12, repeatedly collecting the number of change data of historical online medical self-service machine visit sign-in information to obtain a patient sign-in change data set; calculating the patient sign-in data change rate data for each historical online sign-in data collection period according to the patient sign-in change data set, to obtain a historical self-service machine sign-in change rate data set; S13, the medical self-service machine adopts the interface-free data interaction technology and updates the corresponding patient information in the hospital information system according to the check-in information of each patient in the offline check-in patient set; in the updating process, the time interval data between the update of the offline check-in information of the patient in the medical self-service machine and the update of the corresponding patient information in the hospital information system are collected according to the offline check-in patient set to obtain a time interval data set; the update rate data of the patient information in each historical online check-in data collection time period in the hospital information system is obtained to obtain the information system check-in change rate data set; S14, collecting multiple current offline sign-in data of the medical self-service machines and current online sign-in data of the medical self-service machines in multiple time periods.

3. The medical self-service machine process optimization method based on interface-free data interaction according to claim 2 is characterized in that: The S14 comprises the following steps: S141, collecting the check-in time data corresponding to patients who have signed in consecutively at multiple offline medical self-service machines in the current hospital and the time interval data between the update of the offline check-in information of the patient in the medical self-service machine and the update of the corresponding patient information in the hospital information system, to obtain the current check-in time data set and the current time interval data set; S142, collecting the rate of change of the current online medical self-service machine visit sign-in information and the update rate data of the online sign-in data in the current hospital information system, and obtaining the current self-service machine sign-in change rate data set and the current information system sign-in change rate data set.

4. The medical self-service machine process optimization method based on interface-free data interaction according to claim 3 is characterized in that: The S2 comprises the following steps: S21, setting a non-interface data interaction parameter type; collecting data values ​​of various parameters of the hospital during non-interface data interaction according to the non-interface data interaction parameter type set to obtain an initial non-interface data interaction parameter data set; S22, when the number of patients who sign in for online medical consultation is 0, optimizing each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set according to the offline medical consultation sign-in time-consuming data set and the time interval data set, to obtain a first final non-interface data interaction parameter data set; Otherwise, each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set is optimized according to the offline medical visit check-in time-consuming data set, the time interval data set, the historical self-service machine check-in change rate data set, and the information system check-in change rate data set to obtain a second final non-interface data interaction parameter data set.

5. The medical self-service machine process optimization method based on interface-free data interaction according to claim 4 is characterized in that: In S22, each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set is optimized according to the offline medical check-in time-consuming data set and the time interval data set by adopting an ephemeral optimization algorithm.

6. The medical self-service machine process optimization method based on interface-free data interaction according to claim 5 is characterized in that: In S22, each initial non-interface data interaction parameter data in the initial non-interface data interaction parameter data set is optimized to obtain a second final non-interface data interaction parameter data set, including the following steps: S2221: Construct a second mayfly population; set the maximum number of iterations of the second mayfly population to , the current number of iterations is , respectively recorded as the second maximum number of iterations and the second current number of iterations; S2222, setting the initial position of each mayfly in the second mayfly population to obtain a second initial position matrix; S2223, constructing a fitness function of the second mayfly population according to the offline medical check-in time-consuming data set and the time interval data set, the historical self-service machine check-in change rate data set, and the information system check-in change rate data set; S2224, start iteration; in each round of iteration, use the fitness function of the second mayfly population to calculate the fitness value of each mayfly position updated in the previous round of iteration, and update each mayfly position updated in the previous round of iteration; S2225, when When , the iteration is stopped to obtain the second final global optimal position; the second final global optimal position is used as the second final non-interface data interaction parameter data set.

7. The medical self-service machine process optimization method based on interface-free data interaction according to claim 6 is characterized in that: The S3 comprises the following steps: S31, predicting the sign-in time consumption data and time interval data at future moments according to the current sign-in time consumption data set and the current time interval data set, to obtain a future sign-in time consumption data set and a future time interval data set; Predicting the self-service machine sign-in change rate data and the information system sign-in change rate data at future times according to the current self-service machine sign-in change rate data set and the current information system sign-in change rate data set, to obtain a future self-service machine sign-in change rate data set and a future information system sign-in change rate data set; S32, updating and setting the parameters for the current hospital's non-interface data interaction according to the current sign-in time-consuming data set, the current time interval data set, the current self-service machine sign-in change rate data set, and the current information system sign-in change rate data set; The S32 comprises the following steps: S321, performing a difference operation between the current time interval data set and the current sign-in time-consuming data set to obtain a first current difference data set; then performing a difference operation between the current self-service machine sign-in change rate data set and the current information system sign-in change rate data set to obtain a second current difference data set; S322. Perform a one-time update setting for the parameters of the current hospital when performing data interaction without interface based on the first current difference data set and the second current difference data set in conjunction with the first final data interaction parameter data set without interface and the second final data interaction parameter data set without interface; S33. When a one-time update setting is not performed, perform a second-time update setting for the parameters of the current hospital when performing data interaction without interface based on the future check-in time data set, the future time interval data set, the future self-service machine check-in change rate data set and the future information system check-in change rate data set; otherwise, there is no need to perform a second-time update setting for the parameters of the current hospital when performing data interaction without interface.

8. The medical self-service machine process optimization method based on interface-free data interaction according to claim 7 is characterized in that: The S33 comprises the following steps: S331, performing a difference operation between the future sign-in time-consuming data set and the future time interval data set to obtain a first future difference data set; then performing a difference operation between the future self-service machine sign-in change rate data set and the future information system sign-in change rate data set to obtain a second future difference data set; S332. Perform secondary update setting on the parameters for the current hospital's non-interface data interaction according to the first future difference data set and the second future difference data set and in conjunction with the first final non-interface data interaction parameter data set and the second final non-interface data interaction parameter data set.

9. A system for implementing the medical self-service machine process optimization method based on interface-free data interaction as described in any one of claims 1 to 8.

Images