Painless delivery management system based on delivery monitoring data

Abstract

The invention relates to the technical field of painless delivery management, in particular to a painless delivery management system based on delivery monitoring data. The system comprises a conventional data weight definition module and a monitoring data weight evaluation module. According to the invention, a conventional data weight definition module is combined with a puerpera delivery industry specification, conventional weights corresponding to various instrument monitoring data and state data are divided, a monitoring data weight evaluation module is combined with influence data, and allowable range values of the instrument monitoring data and the state data corresponding to a puerpera with a specific disease are obtained; influence weights corresponding to instrument monitoring data and state data of puerperae with specific diseases are divided, corresponding monitoring range values are divided and automatically matched for patients with different diseases in advance, monitoring work of the patients with different diseases is adapted in the monitoring process, the response accuracy of the monitoring data in the painless delivery process is improved, and the painless delivery efficiency is improved. And the early warning effect is improved.

Description

Technical Field

[0001] The present invention relates to the technical field of painless delivery management, and in particular to a painless delivery management system based on delivery monitoring data. Background Art

[0002] Painless childbirth is medically known as labor analgesia, which refers to the use of various methods to reduce or eliminate pain during childbirth. The purpose of painless childbirth is to reduce the pain of the mother and improve the childbirth experience through drugs or non-drug means without affecting the labor process and fetal safety.

[0003] Although painless childbirth provides a means of relieving pain for mothers, it also comes with some potential risks and side effects that may affect the health of mother and baby.

[0004] Therefore, during the painless delivery process, it is necessary to monitor the maternal data in real time. Some data can be read directly through instruments, such as vital signs monitoring, and some data need to be directly observed by nursing doctors, such as observing changes in the amniotic fluid of the mother. However, due to the different physical conditions of different mothers, the monitoring data corresponding to different diseases will also be different. For example, a mother with heart disease has insufficient blood supply, and the blood supply to the fetus will also decrease. Compared with normal mothers, the corresponding impact of the same unit change will be greatly different, that is, the same change will have different effects on patients with different diseases. Traditional monitoring instruments are universal, and the warning value is constant during the monitoring process, that is, an alarm will be issued if it exceeds a certain range. For patients with different types of diseases, the corresponding initial range values ​​are different from those of normal mothers. At this time, the monitored data needs to be predicted in real time by medical staff, which makes the monitoring instrument unable to issue an early warning.

[0005] In order to address the above problems, a painless delivery management system based on delivery monitoring data is urgently needed. Summary of the invention

[0006] The purpose of the present invention is to provide a painless delivery management system based on delivery monitoring data to solve the problems raised in the above background technology.

[0007] To achieve the above purpose, a painless delivery management system based on delivery monitoring data is provided, including a delivery data monitoring platform, a past case data summary module, a routine data weight definition module, a monitoring data weight evaluation module, and a weight response warning module;

[0008] The delivery data monitoring platform is used to obtain various data during the delivery process of the parturient, and to display the data changes during the delivery process of the parturient in real time through a medical display instrument. The delivery data monitoring platform includes an instrument monitoring module and a status feedback module. The instrument monitoring module uses a medical monitoring instrument to monitor the delivery process of the parturient in real time and obtain instrument monitoring data. The status feedback module is used to collect status data during the delivery process of the parturient and record the status data to the delivery data monitoring platform;

[0009] The past case data summary module collects past case data information of parturients, and combines the instrument monitoring data and status data to obtain the influencing data that affects the parturient's delivery process;

[0010] The conventional data weight definition module combines the maternal delivery industry standards to obtain the normal range values ​​of various instrument monitoring data and status data without the influence of symptoms, and obtains the degree of influence of the unit change of the instrument monitoring data and status data on the parturient, and divides the conventional weights corresponding to the various instrument monitoring data and status data;

[0011] The monitoring data weight evaluation module combines the impact data to obtain the allowable range values ​​of the instrument monitoring data and status data corresponding to the parturient with the specific disease, and divides the corresponding impact weights of the instrument monitoring data and status data of the parturient with the specific disease in combination with the impact degree of the unit change amount on the parturient with the specific disease specified by the conventional data weight definition module;

[0012] The weight response warning module combines the conventional weight size and the impact weight size, and cooperates with the corresponding unit change amount to affect the parturient, to establish a parturient delivery warning response mode, and to issue warnings for changes in instrument monitoring data and status data generated during the delivery process of different types of parturients.

[0013] As a further improvement of the technical solution, the instrument monitoring module includes vital sign monitoring, uterine contraction monitoring, fetal heart rate monitoring, anesthesia depth monitoring and hypotension monitoring, and the state feedback module includes analgesic effect evaluation, amniotic fluid observation and drug side effect monitoring;

[0014] Wherein, the vital signs monitoring includes the mother's blood pressure, heart rate, respiration and body temperature;

[0015] The uterine contraction monitoring monitors the frequency, intensity and duration of uterine contractions by an electronic monitor;

[0016] The fetal heart rate monitoring continuously monitors the fetal heart rate changes through a fetal heart monitor;

[0017] The anesthesia depth monitoring is performed by monitoring the effect of anesthetic drugs;

[0018] The hypotension monitoring uses a blood pressure monitor to monitor the blood pressure changes of the parturient in real time;

[0019] The analgesic effect evaluation is performed by the doctor regularly evaluating the pain level and analgesic effect of the parturient;

[0020] The amniotic fluid observation is performed by the doctor monitoring the shape and amount of the amniotic fluid to assess whether the fetus's intrauterine environment is safe;

[0021] The drug side effect monitoring is performed by observing whether the parturient experiences side effects related to anesthetic drugs.

[0022] As a further improvement of the technical solution, the conventional data weight definition module includes a conventional value range definition unit, a deviation unit definition unit and an influence degree calculation unit;

[0023] The conventional value range definition unit combines the maternal delivery industry standards to obtain the normal range values ​​corresponding to the various instrument monitoring data and status data during the maternal delivery process;

[0024] The deviation unit quantity definition unit defines the deviation unit quantity in combination with the normal range value;

[0025] The impact degree calculation unit combines the actual delivery monitoring data to obtain the impact on delivery caused by exceeding the normal range of the instrument monitoring data and the status data by one deviation unit, and classifies the impact degree according to the impact.

[0026] As a further improvement of the technical solution, the impact degree calculation unit classifies the impact degree according to the impact, including five types: observation type I, selective cesarean section type II, as soon as possible delivery type III, non-immediate threat high risk type IV and immediate threat high risk type V;

[0027] Among them, the observation type I is a situation where the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit, which will increase the difficulty of delivery, but there is no need to terminate delivery;

[0028] The selective cesarean section category II is when the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit and the doctor needs to use tools to assist in the delivery;

[0029] The category III of "delivery as soon as possible" refers to the situation where the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit and delivery is required immediately;

[0030] The non-immediate threat high-risk category IV is when the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit, there are high-risk factors that threaten the lives of mothers and children, but it is not an immediate threat;

[0031] The immediate threat high risk category V is a situation where the life of the mother and child will be directly threatened when the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit.

[0032] As a further improvement of the technical solution, the method for defining the deviation unit quantity by the deviation unit quantity definition unit comprises the following steps:

[0033] S1. Collect the changing patterns of monitoring data during delivery and obtain the regular change C variation ;

[0034] S2. Collect the normal change amount C for each change variation The time consumed, calculate the average interval time Ai time ;

[0035] S3. Eliminate the interval time without influence and obtain the regular change C variation The impact time range value Itr value ;

[0036] S4. Bind the normal range values ​​and regular changes corresponding to the monitoring data of each instrument and the status data C variation And the impact time range value Itr value .

[0037] As a further improvement of the technical solution, the method for dividing the conventional weights corresponding to each instrument monitoring data and status data by the conventional data weight definition module includes the following steps:

[0038] S10, combining the classification type divided by the impact degree calculation unit, marking the observation type I as the unit weight Un weight ;

[0039] S20, according to the classification level, the unit weight Un weight Increase and obtain the corresponding weights of each type.

[0040] As a further improvement of the present technical solution, the monitoring data weight evaluation module includes a maternal value range acquisition unit, a fetal value range determination unit, and a safe range value division unit;

[0041] The maternal value range acquisition unit combines the maternal past case data information to acquire the instrument monitoring data corresponding to the maternal under different disease states and the allowable range value of the state data;

[0042] The fetal value range determination unit obtains instrument monitoring data of the parturient maintaining fetal survival under different disease states and an allowable range value of the state data in combination with the fetal value monitoring standard;

[0043] The safety range value division unit integrates the allowable range values ​​of the parturient and the fetus and calculates the final safety range value.

[0044] As a further improvement of the technical solution, the method for the weighted response warning module to establish a maternal delivery warning response mode includes the following steps:

[0045] S100, obtaining the delivery information of expectant mothers, marking asymptomatic expectant mothers as normal expectant mothers, and marking as expectant mothers with symptoms as expectant mothers with symptoms;

[0046] S200, obtaining normal range values ​​and corresponding impact types of various instrument monitoring data and status data of normal parturients, and formulating corresponding response states in combination with weights matching the impact types;

[0047] S300, obtaining the type of symptom of the symptomatic parturient, determining the safety range value and the type of impact degree corresponding to the monitoring data and status data of each instrument, and formulating the corresponding response state according to the weight matching the type of impact degree.

[0048] Compared with the prior art, the present invention has the following beneficial effects:

[0049] In the painless delivery management system based on delivery monitoring data, conventional data weight definition module is used in combination with maternal delivery industry norms to divide the conventional weights corresponding to various instrument monitoring data and status data. The monitoring data weight evaluation module is used in combination with the impact data to obtain the allowable range values ​​of instrument monitoring data and status data corresponding to maternal patients with specific diseases. The corresponding impact weights of various instrument monitoring data and status data of maternal patients with specific diseases are divided, and patients with different diseases are divided in advance, and the corresponding monitoring range values ​​are automatically matched. The monitoring work of patients with different diseases is adapted during the monitoring process, the response accuracy of monitoring data during painless delivery is improved, and the early warning effect is increased. BRIEF DESCRIPTION OF THE DRAWINGS

[0050] Figure 1 It is a flowchart of the overall structure of the present invention.

[0051] The meaning of each number in the figure is:

[0052] 10. Instrument monitoring module;

[0053] 20. Status feedback module;

[0054] 30. Past case data summary module;

[0055] 40. Conventional data weight definition module; 410. Conventional value range definition unit; 420. Deviation unit definition unit; 430. Impact degree calculation unit;

[0056] 50. Monitoring data weight evaluation module; 510. Maternal value range acquisition unit; 520. Fetal value range determination unit; 530. Safety range value division unit;

[0057] 60. Weighted response warning module. DETAILED DESCRIPTION

[0058] The following will be combined with the accompanying drawings in 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.

[0059] See also Figure 1 As shown, a painless delivery management system based on delivery monitoring data is provided, including a delivery data monitoring platform, a past case data aggregation module 30, a conventional data weight definition module 40, a monitoring data weight evaluation module 50, and a weight response warning module 60;

[0060] The delivery data monitoring platform is used to obtain various data during the delivery process of the parturient, and to display the data changes during the delivery process of the parturient in real time through a medical display instrument. The delivery data monitoring platform includes an instrument monitoring module 10 and a status feedback module 20. The instrument monitoring module 10 uses a medical monitoring instrument to monitor the delivery process of the parturient in real time and obtain instrument monitoring data. The status feedback module 20 is used to collect status data during the delivery process of the parturient and record the status data to the delivery data monitoring platform;

[0061] The past case data summary module 30 collects past case data information of parturients, and combines the instrument monitoring data and status data to obtain the influencing data affecting the parturient's delivery process;

[0062] The conventional data weight definition module 40 combines the maternal delivery industry standards to obtain the normal range values ​​corresponding to the various instrument monitoring data and status data without the influence of symptoms, and obtains the degree of influence of the unit change amount corresponding to the instrument monitoring data and status data on the parturient, and divides the conventional weights corresponding to the various instrument monitoring data and status data;

[0063] The monitoring data weight evaluation module 50 combines the impact data to obtain the allowable range values ​​of the instrument monitoring data and status data corresponding to the parturient with the specific disease, and divides the impact weights corresponding to the instrument monitoring data and status data of the parturient with the specific disease in combination with the impact degree of the unit change amount on the parturient with the specific disease specified by the conventional data weight definition module 40;

[0064] The weight response warning module 60 combines the conventional weight size and the impact weight size with the corresponding unit change amount to determine the degree of impact on the parturient, establishes a parturient delivery warning response mode, and issues warnings for instrument monitoring data and status data changes generated during delivery for different types of parturients.

[0065] During specific use, during the data monitoring of the parturient during painless delivery, firstly, various data of the parturient during delivery are obtained through the delivery data monitoring platform, and the data changes during delivery are displayed in real time through the medical display instrument. The parturient during delivery is monitored in real time by the medical monitoring instrument through the instrument monitoring module 10, and instrument monitoring data, such as the parturient's blood pressure, heart rate, respiration and body temperature, are obtained. However, some secretions and the parturient's analgesic feeling during delivery cannot be monitored by the monitoring instrument. At this time, it is necessary to collect the state data of the parturient during delivery through the state feedback module 20, such as the change state of the parturient's amniotic fluid during delivery, including the shape and amount of the amniotic fluid, and add the state data to the delivery data monitoring platform;

[0066] In order to distinguish whether the parturient has a disease that affects delivery, it is necessary to collect the parturient's past case data information through the past case data summary module 30, and combine the instrument monitoring data and status data to obtain the data that affects the parturient's delivery process, that is, the disease that affects the normal range values ​​of various monitoring data and status data during delivery. For example, if the parturient has heart disease, the corresponding blood supply range value will be different from the range value of the normal parturient, and this blood supply will have an impact on the delivery process;

[0067] For parturients who are not affected by diseases, the normal range values ​​of various instrument monitoring data and status data under the condition of no disease influence are obtained through the conventional data weight definition module 40 in combination with the maternal delivery industry norms, and the degree of influence of the unit change amount of the instrument monitoring data and status data on the parturient is obtained, and the conventional weights corresponding to various instrument monitoring data and status data are divided. The maternal delivery warning response mode established by the weight response warning module 60 is used to issue warnings according to the weight size;

[0068] For pregnant women with conditions that affect delivery, the monitoring data weight assessment module 50 is combined with the impact data to obtain the allowable range values ​​of the instrument monitoring data and status data corresponding to the pregnant women with specific conditions. The unit change amount specified by the conventional data weight definition module 40 on the degree of impact of the pregnant women with specific conditions is combined, and the corresponding impact weights of the various instrument monitoring data and status data of the pregnant women with specific conditions are divided. The pregnant women delivery warning response mode is established in conjunction with the weight response warning module 60, and warnings are issued according to the weight size.

[0069] In addition, the instrument monitoring module 10 includes vital sign monitoring, uterine contraction monitoring, fetal heart rate monitoring, anesthesia depth monitoring, and hypotension monitoring, and the state feedback module 20 includes analgesic effect evaluation, amniotic fluid observation, and drug side effect monitoring;

[0070] Among them, vital signs monitoring includes the mother’s blood pressure, heart rate, respiration, and body temperature;

[0071] Contraction monitoring: The frequency, intensity, and duration of uterine contractions are monitored electronically to assess the regularity of contractions and the progress of labor.

[0072] Fetal heart rate monitoring: Continuously monitor the fetal heart rate changes through the fetal heart monitor to detect possible fetal distress in time;

[0073] Anesthesia depth monitoring monitors the effect of anesthetic drugs to ensure that the anesthesia level is appropriate and will not affect the motor function of the parturient or cause respiratory depression.

[0074] Hypotension monitoring uses a blood pressure monitor to monitor the changes in maternal blood pressure in real time;

[0075] Analgesic effect assessment: Doctors regularly assess the pain level and analgesic effect of the mother to adjust the dose of anesthetic drugs;

[0076] Amniotic fluid observation: Doctors monitor the shape and amount of amniotic fluid to assess whether the fetus's intrauterine environment is safe.

[0077] Drug side effects monitoring is performed by observing whether the mother experiences side effects related to anesthetics, such as headache, nausea, vomiting, etc.

[0078] Further, the conventional data weight definition module 40 includes a conventional value range definition unit 410, a deviation unit quantity definition unit 420, and an influence degree calculation unit 430;

[0079] The conventional value range definition unit 410 combines the maternal delivery industry standards to obtain the normal range values ​​corresponding to the various instrument monitoring data and status data during the maternal delivery process;

[0080] The deviation unit amount definition unit 420 defines the deviation unit amount in combination with the normal range value;

[0081] The impact degree calculation unit 430 combines the actual delivery monitoring data to obtain the impact on delivery caused by exceeding the normal range of the instrument monitoring data and the status data by one deviation unit, and classifies the impact degree according to the impact.

[0082] The impact degree calculation unit 430 classifies the impact degree according to the impact, including five types: observation type I, selective cesarean section type II, as soon as possible delivery type III, non-immediate threat high risk type IV and immediate threat high risk type V;

[0083] Among them, observation type I refers to situations where the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit, which will increase the difficulty of delivery, but there is no need to terminate delivery;

[0084] Category II selective cesarean section refers to situations where the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit and the doctor needs to use tools to assist in delivery;

[0085] Category III: Delivery as soon as possible refers to situations where delivery is required immediately when the instrument monitoring data and status data exceed the corresponding normal range by one deviation unit;

[0086] Category IV, non-immediate threat high risk, refers to situations where the instrument monitoring data and status data exceed the corresponding normal range by one deviation unit, which may pose a high risk factor to the life of the mother and child but is not an immediate threat;

[0087] Immediate Threat High Risk Category V refers to situations where the instrument monitoring data and status data exceed the corresponding normal range by one deviation unit, which will directly threaten the life of the mother and child.

[0088] The method for defining the deviation unit quantity by the deviation unit quantity definition unit 420 includes the following steps:

[0089] S1. Collect the changing patterns of monitoring data during delivery and obtain the regular change C variation ;

[0090] S2. Collect the normal change amount C for each change variation The time consumed, calculate the average interval time Ai time ;

[0091] S3. Eliminate the interval time without influence and obtain the regular change C variation The impact time range value Itr value ;

[0092] S4. Bind the normal range values ​​and regular changes corresponding to the monitoring data of each instrument and the status data C variation And the impact time range value Itr value .

[0093] The method for defining conventional data weights by the conventional data weight definition module 40 to divide each instrument monitoring data and status data into corresponding conventional weights comprises the following steps:

[0094] S10, combining the classification types divided by the influence degree calculation unit 430, marking the observation type I as the unit weight Un weight ;

[0095] S20, according to the classification level, the unit weight Un weight Increase and obtain the corresponding weights of each type.

[0096] When used specifically, in the process of dividing the conventional weights corresponding to the various instrument monitoring data and status data, firstly, the conventional value range definition unit 410 is combined with the maternal delivery industry specification to obtain the normal range values ​​corresponding to the various instrument monitoring data and status data during the maternal delivery process. The maternal delivery industry specification refers to the general change trends of various indicators of healthy pregnant women during delivery accumulated by doctors and midwives through long-term clinical practice, and a large number of monitoring data of pregnant women are collected. The average value, standard deviation, etc. are obtained by statistical analysis, and the guiding principles and standards formulated by medical professional organizations are combined to define the normal range, and the deviation unit quantity is defined by the deviation unit quantity definition unit 420 in combination with the normal range value. In the definition process, it is necessary to collect the change law of the monitoring data during the maternal delivery process to obtain the conventional change quantity C variation , that is, the common numerical changes detected by the monitoring instrument, and the change with the highest occurrence rate is marked as the regular change C variation At the same time, since each change needs to be separated by a certain time, the same change amount has different corresponding intervals, and the degree of influence will be quite different. Therefore, it is necessary to collect the regular change amount C of each change. variation The time consumed, calculate the average interval time Ai time , remove the interval time without influence and obtain the regular change C variation The impact time range value Itr value , for example, to count the regular change of each change of a certain monitoring value C variation The time consumed is in the range [t1, t n ], where [t1, t 1+m ] is the range without influence, [t p , t n ] is also the range without influence, that is, the final influence time range value Itr value for [t 1+m , t p ], and t1<t 1+m <t p <t n Finally, bind the normal range value and regular change amount C corresponding to the monitoring data of each instrument and the status data variation And the impact time range value Itr value, finally, the influence degree calculation unit 430 combines the actual delivery monitoring data to obtain the influence on delivery when the normal range value of the instrument monitoring data and the status data is exceeded by one deviation unit, and the influence degree is classified and processed according to the influence;

[0097] The present invention divides the degree of impact into five categories: observation type I, selective cesarean section type II, early delivery type III, non-immediate threat high risk type IV and immediate threat high risk type V, and assigns weights to the five categories, defining observation type I as the unit weight Un weight , according to the classification level, the unit weight Un weight Increase, get the corresponding weight of each type, for example, the weight of category III for as soon as possible delivery is three times the unit weight Un weight The higher the weight, the greater the corresponding impact, and the final weight response warning module 60 response status will also change

[0098] Further, the monitoring data weight evaluation module 50 includes a maternal value range acquisition unit 510, a fetal value range determination unit 520, and a safety range value division unit 530;

[0099] The parturient value range acquisition unit 510 combines the parturient's past case data information to acquire the instrument monitoring data corresponding to the parturient under different disease states and the allowable range value of the state data;

[0100] The fetal value range determination unit 520 combines the fetal value monitoring standard to obtain the instrument monitoring data of the parturient maintaining the fetus survival under different disease states and the allowable range value of the state data;

[0101] The safety range value division unit 530 integrates the allowable range values ​​of the mother and the fetus and calculates the final safety range value.

[0102] During specific use, since the corresponding instrument monitoring data and status data of parturients with different diseases are different from those of normal parturients, and the survival conditions that the fetus needs to maintain when completing delivery need to be maintained within a certain range, in order to adapt to the monitoring of parturients with different diseases, it is first necessary to obtain the instrument monitoring data and status data corresponding to parturients in different disease states through the parturient numerical range acquisition unit 510 in combination with the parturient's past case data information, that is, within the current allowable range value, the parturient can complete the delivery work, and then obtain the instrument monitoring data and status data of parturients in different disease states to maintain fetal survival through the fetal numerical range determination unit 520 in combination with the fetal numerical monitoring standard, and obtain the corresponding allowable range value of the fetus to maintain the survival condition, and the overlapping part of the two allowable range values ​​is the final safe range value;

[0103] It is worth noting that when dividing the corresponding conventional weights of various instrument monitoring data and status data of pregnant women with different diseases, the division method of the conventional data weight definition module 40 is still used. At this time, the safety range value corresponds to the normal range value obtained in the conventional numerical range definition unit 410, and the method of defining the deviation unit is the same. The corresponding impact degree types are also divided into five types: observation type I, selective cesarean section type II, early delivery type III, non-immediate threat high risk type IV and immediate threat high risk type V.

[0104] Specifically, the method for the weighted response warning module 60 to establish a maternal delivery warning response mode includes the following steps:

[0105] S100, obtaining the delivery information of expectant mothers, marking asymptomatic expectant mothers as normal expectant mothers, and marking as expectant mothers with symptoms as expectant mothers with symptoms;

[0106] S200, obtaining normal range values ​​and corresponding impact types of various instrument monitoring data and status data of normal parturients, and formulating corresponding response states in combination with weights matching the impact types;

[0107] S300, obtaining the type of symptom of the symptomatic parturient, determining the safety range value and the type of impact degree corresponding to the monitoring data and status data of each instrument, and formulating the corresponding response state according to the weight matching the type of impact degree.

[0108] During specific use, during the process of establishing a maternal delivery early warning response mode, due to different types of mothers, the range values ​​of the corresponding instrument monitoring data and status data will be different. In order to adapt to the early warning response of different mothers, it is necessary to distinguish the types of expectant mothers in advance, obtain the expectant mothers' delivery information, mark the mothers without symptoms as normal mothers, and mark the mothers with symptoms as symptomatic mothers. When the mother is asymptomatic, the normal range values ​​corresponding to her various instrument monitoring data and status data are divided according to the normal, and the weights are determined according to the types of influencing states corresponding to the various instrument monitoring data and status data. The response states are divided according to the weights. Different weights have different corresponding response states. For example, the flashing frequency of the alarm light is used as the response state, and the weights are used as the response state. The heavier the instrument monitoring data or status data, the faster the corresponding flashing frequency when it exceeds the normal range value. For pregnant women with illnesses, the corresponding safety range values ​​of various instrument monitoring data and status data are different. It is necessary to match the impact degree type of various instrument monitoring data and status data of the pregnant women with the current illness in advance. For example, pregnant women with heart disease have lower blood supply than normal pregnant women. Therefore, the safety range value corresponding to the blood pressure monitoring data will be lower than that of normal pregnant women. At the same time, the impact degree type corresponding to the blood pressure monitoring data will also be different from that of normal pregnant women. That is, the severity increases, so the weight of the blood pressure monitoring data of the pregnant women with the current illness will also increase, and the matching response status will also be different, that is, the flashing frequency of the alarm light will increase.

[0109] The above shows and describes the basic principles, main features and advantages of the present invention. Those skilled in the art should understand that the present invention is not limited by the above embodiments. The above embodiments and descriptions are only preferred examples of the present invention and are not intended to limit the present invention. Without departing from the spirit and scope of the present invention, the present invention may have various changes and improvements, which fall within the scope of the present invention. The scope of protection of the present invention is defined by the attached claims and their equivalents.

Claims

1. A painless delivery management system based on delivery monitoring data, characterized by: It includes a delivery data monitoring platform, a past case data summary module (30), a routine data weight definition module (40), a monitoring data weight evaluation module (50) and a weight response warning module (60); The delivery data monitoring platform is used to obtain various data during the delivery process of the parturient, and to display the data changes during the delivery process of the parturient in real time through a medical display instrument. The delivery data monitoring platform comprises an instrument monitoring module (10) and a status feedback module (20). The instrument monitoring module (10) uses a medical monitoring instrument to monitor the delivery process of the parturient in real time and obtain instrument monitoring data. The status feedback module (20) is used to collect status data during the delivery process of the parturient and to record the status data into the delivery data monitoring platform. The past case data summary module (30) collects past case data information of parturients, and combines the instrument monitoring data and status data to obtain the influencing data affecting the parturient's delivery process; The conventional data weight definition module (40) combines the maternal delivery industry standards to obtain the normal range values ​​corresponding to the various instrument monitoring data and status data in the absence of symptom influence, and obtains the degree of influence of the unit change amount corresponding to the instrument monitoring data and status data on the parturient, and divides the conventional weights corresponding to the various instrument monitoring data and status data; The monitoring data weight evaluation module (50) combines the impact data to obtain the allowable range values ​​of the instrument monitoring data and status data corresponding to the parturient with the specific disease, and divides the impact weights corresponding to the various instrument monitoring data and status data of the parturient with the specific disease in combination with the impact degree of the unit change amount on the parturient with the specific disease specified by the conventional data weight definition module (40); The weight response warning module (60) combines the conventional weight size and the impact weight size with the corresponding unit change amount to determine the degree of impact on the parturient, establishes a parturient delivery warning response mode, and issues warnings for instrument monitoring data and status data changes generated during delivery for different types of parturients.

2. The painless delivery management system based on delivery monitoring data according to claim 1 is characterized in that: The instrument monitoring module (10) includes vital sign monitoring, uterine contraction monitoring, fetal heart rate monitoring, anesthesia depth monitoring and hypotension monitoring, and the state feedback module (20) includes analgesic effect evaluation, amniotic fluid observation and drug side effect monitoring; Wherein, the vital signs monitoring includes the mother's blood pressure, heart rate, respiration and body temperature; The uterine contraction monitoring monitors the frequency, intensity and duration of uterine contractions by an electronic monitor; The fetal heart rate monitoring continuously monitors the fetal heart rate changes through a fetal heart monitor; The anesthesia depth monitoring is performed by monitoring the effect of anesthetic drugs; The hypotension monitoring uses a blood pressure monitor to monitor the blood pressure changes of the parturient in real time; The analgesic effect evaluation is performed by the doctor regularly evaluating the pain level and analgesic effect of the parturient; The amniotic fluid observation is performed by the doctor monitoring the shape and amount of the amniotic fluid to assess whether the fetus's intrauterine environment is safe; The drug side effect monitoring is performed by observing whether the parturient experiences side effects related to anesthetic drugs.

3. The painless delivery management system based on delivery monitoring data according to claim 1, characterized in that: The conventional data weight definition module (40) comprises a conventional value range definition unit (410), a deviation unit quantity definition unit (420) and an influence degree calculation unit (430); The conventional value range definition unit (410) combines the industry norms for maternal delivery to obtain normal range values ​​corresponding to various instrument monitoring data and status data during the maternal delivery process; The deviation unit quantity definition unit (420) defines the deviation unit quantity in combination with the normal range value; The impact degree calculation unit (430) combines actual delivery monitoring data to obtain the impact on delivery caused by exceeding the normal range of instrument monitoring data and status data by one deviation unit, and classifies the impact degree according to the impact.

4. The painless delivery management system based on delivery monitoring data according to claim 3 is characterized in that: The impact degree calculation unit (430) classifies the impact degree according to the impact into five types: observation type I, selective cesarean section type II, rapid delivery type III, non-immediate threat high risk type IV and immediate threat high risk type V; Among them, the observation type I is a situation where the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit, which will increase the difficulty of delivery, but there is no need to terminate delivery; The selective cesarean section category II is when the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit and the doctor needs to use tools to assist in the delivery; The category III of "delivery as soon as possible" refers to the situation where the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit and delivery is required immediately; The non-immediate threat high-risk category IV is when the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit, there are high-risk factors that threaten the lives of mothers and children, but it is not an immediate threat; The immediate threat high risk category V is a situation where the life of the mother and child will be directly threatened when the instrument monitoring data and status data exceed the corresponding normal range value by one deviation unit.

5. The painless delivery management system based on delivery monitoring data according to claim 3 is characterized in that: The method for defining the deviation unit quantity by the deviation unit quantity definition unit (420) comprises the following steps: S1. Collect the changing patterns of monitoring data during delivery and obtain the regular change C variation ; S2. Collect the normal change amount C for each change variation The time consumed, calculate the average interval time Ai time ; S3. Eliminate the interval time without influence and obtain the regular change C variation The impact time range value Itr value ; S4. Bind the normal range values ​​and regular changes corresponding to the monitoring data of each instrument and the status data C variation And the impact time range value Itr value .

6. The painless delivery management system based on delivery monitoring data according to claim 3 is characterized in that: The method for the conventional data weight definition module (40) to divide each instrument monitoring data and status data into corresponding conventional weights comprises the following steps: S10, combining the classification types divided by the influence degree calculation unit (430), marking the observation type I as the unit weight Un weight ; S20, according to the classification level, the unit weight Un weight Increase and obtain the corresponding weights of each type.

7. The painless delivery management system based on delivery monitoring data according to claim 1, characterized in that: The monitoring data weight evaluation module (50) comprises a maternal value range acquisition unit (510), a fetal value range determination unit (520) and a safety range value division unit (530); The maternal value range acquisition unit (510) combines the maternal past case data information to acquire the instrument monitoring data corresponding to the maternal under different disease states and the allowable range value of the state data; The fetal value range determination unit (520) obtains instrument monitoring data for maintaining fetal survival of parturients under different disease states and an allowable range value of the state data in combination with the fetal value monitoring standard; The safety range value division unit (530) integrates the allowable range values ​​of the parturient and the fetus and calculates the final safety range value.

8. The painless delivery management system based on delivery monitoring data according to claim 1, characterized in that: The method for the weighted response warning module (60) to establish a maternal delivery warning response mode comprises the following steps: S100, obtaining the delivery information of expectant mothers, marking asymptomatic expectant mothers as normal expectant mothers, and marking as expectant mothers with symptoms as expectant mothers with symptoms; S200, obtaining normal range values ​​and corresponding impact types of various instrument monitoring data and status data of normal parturients, and formulating corresponding response states in combination with weights matching the impact types; S300, obtaining the type of symptom of the symptomatic parturient, determining the safety range value and the type of impact degree corresponding to the monitoring data and status data of each instrument, and formulating the corresponding response state according to the weight matching the type of impact degree.

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