A diagnosis and treatment information management system for osteoporosis patients

Abstract

The present invention discloses a diagnosis and treatment information management system for osteoporosis patients, relates to the field of medical diagnosis and treatment, solves the problem of poor management effect of the diagnosis and treatment information management system, comprises a data acquisition module: used for acquiring the patient's age value, the patient's body index and the patient's sleep monitoring coefficient, and obtaining the patient's physiological data, a treatment monitoring module: used for acquiring the first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient, and obtaining the patient's diagnosis and treatment data, a data analysis module: used for acquiring the first to the mth diagnosis and treatment effect coefficients by analyzing the patient's physiological data and the patient's diagnosis and treatment data, and obtaining diagnosis and treatment information analysis data, an effect evaluation module: used for monitoring the diagnosis and treatment effect according to the diagnosis and treatment information analysis data, and providing diagnosis and treatment feedback according to the monitoring results. The present invention can fully ensure the comprehensiveness and objectivity of the diagnosis and treatment effect evaluation by comprehensively analyzing the diagnosis and treatment effects corresponding to the patient at different diagnosis and treatment stages.

Description

Technical Field

[0001] The present invention belongs to the field of medical diagnosis and treatment, relates to information management technology, and specifically is a diagnosis and treatment information management system applied to osteoporosis patients. Background Art

[0002] The existing diagnosis and treatment information management system has the following defects when conducting diagnosis and treatment management for osteoporosis patients:

[0003] 1. When evaluating the treatment effect, the existing diagnosis and treatment information management system usually ignores the impact of the patient's objective physiological factors on the treatment effect, which leads to the lack of pertinence in the diagnosis and treatment evaluation results;

[0004] 2. Existing diagnosis and treatment information management systems often only focus on the final diagnosis and treatment results, while ignoring the dynamic changes in the treatment process, resulting in a lack of comprehensiveness and objectivity in the evaluation of diagnosis and treatment results;

[0005] To this end, we propose a diagnosis and treatment information management system for osteoporosis patients. Summary of the invention

[0006] In view of the shortcomings of the prior art, the purpose of the present invention is to provide a diagnosis and treatment information management system for osteoporosis patients. The present invention is based on obtaining the patient's age value, the patient's body index and the patient's sleep monitoring coefficient to obtain the patient's physiological data, obtain the patient's diagnosis and treatment records, mark the first diagnosis and treatment to the mth diagnosis and treatment respectively through the patient's diagnosis and treatment records, obtain the patient's bone density coefficient and the patient's index average deviation ratio corresponding to the first diagnosis and treatment to the mth diagnosis and treatment respectively, analyze and obtain the first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient, define the first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient as the patient's diagnosis and treatment data, obtain the first to mth diagnosis and treatment effect coefficients by analyzing the patient's physiological data and the patient's diagnosis and treatment data, obtain diagnosis and treatment information analysis data, monitor the diagnosis and treatment effect according to the diagnosis and treatment information analysis data, and provide diagnosis and treatment feedback according to the monitoring results.

[0007] In order to achieve the above-mentioned purpose, the present invention adopts the following technical scheme: The specific working process of each module of a diagnosis and treatment information management system for osteoporosis patients is as follows:

[0008] Data acquisition module: used to obtain the patient's age value, patient's body index and patient's sleep monitoring coefficient to obtain the patient's physiological data;

[0009] Treatment monitoring module: used to obtain patient diagnosis and treatment records, mark the first diagnosis and treatment to the mth diagnosis and treatment respectively through the patient diagnosis and treatment records, obtain the patient bone density coefficient and the average deviation ratio of the patient index corresponding to the first diagnosis and treatment to the mth diagnosis and treatment respectively, analyze and obtain the first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient, and define the first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient as patient diagnosis and treatment data;

[0010] Data analysis module: used to obtain the first to mth diagnosis and treatment effect coefficients by analyzing the patient's physiological data and the patient's diagnosis and treatment data, and obtain diagnosis and treatment information analysis data;

[0011] Treatment monitoring module: used to analyze data based on diagnosis and treatment information to monitor the diagnosis and treatment effects, and provide diagnosis and treatment feedback based on the monitoring results.

[0012] Furthermore, the data acquisition module acquires the patient's physiological data as follows:

[0013] The patient's age value is obtained to obtain the patient's age value;

[0014] The height of the patient is obtained to obtain the patient's height value, and the weight of the patient is obtained to obtain the patient's weight value;

[0015] The patient's height and weight are calculated to obtain the patient's body index;

[0016] Calculate the patient's body index, the specific formula is as follows:

[0017]

[0018] Among them, Stz is the patient's body index, Tzz is the patient's weight value, and Sgz is the patient's weight value;

[0019] Perform sleep monitoring on the patient to obtain the patient's sleep monitoring coefficient;

[0020] The patient's age value, the patient's body index and the patient's sleep monitoring coefficient are defined as the patient's physiological data.

[0021] Furthermore, the data acquisition module acquires the patient's sleep monitoring coefficient as follows:

[0022] During the process of the patient receiving diagnosis and treatment, n physical monitoring dates are marked and named as the first physiological monitoring date to the nth physiological monitoring date;

[0023] Obtaining the sleep durations corresponding to the first physiological monitoring date to the nth physiological monitoring date respectively, obtaining the first sleep duration to the nth sleep duration, and calculating the average of the first sleep duration to the nth sleep duration to obtain the patient's monitored sleep duration;

[0024] Obtain the patient's sleep onset time and wake-up time on the first physiological monitoring date, and define the time range between the sleep onset time and the wake-up time as the first sleep time range;

[0025] Respectively acquiring the sleep time ranges corresponding to the second physiological monitoring date to the nth physiological monitoring date to obtain the second sleep time range to the nth sleep time range;

[0026] Performing intersection operations on the first sleep time range to the nth sleep time range respectively to obtain the intersection of the sleep time ranges, and obtaining the duration of the intersection of the sleep time ranges to obtain the overlapping duration of the sleep time;

[0027] Obtain the number of awakenings of the patient within the first sleep time range to obtain the number of awakenings at the first night;

[0028] The number of awakenings corresponding to the second to nth sleep time ranges is obtained respectively, to obtain the number of awakenings from the second night to the nth night;

[0029] Calculate the average of the number of awakenings from the first night to the nth night to obtain the monitored average number of awakenings;

[0030] The patient's sleep monitoring coefficient is obtained by calculating the average number of awakenings, the overlapping duration of sleep time, and the patient's monitored sleep duration;

[0031] Calculate the patient's sleep monitoring coefficient, the specific formula configuration is as follows:

[0032]

[0033] Among them, Hsx is the patient's sleep monitoring coefficient, Jsc is the patient's monitored sleep duration, Cfc is the overlap duration of sleep time, and Xlc is the average number of awakenings during monitoring.

[0034] Furthermore, the treatment monitoring module acquires the patient's diagnosis and treatment data as follows:

[0035] Obtain the patient's diagnosis and treatment records, obtain the end time values ​​corresponding to m diagnosis and treatments according to the patient's diagnosis and treatment records, obtain m diagnosis and treatment end time values, obtain the time value corresponding to the current moment as the reference time value, obtain the difference between the m diagnosis and treatment end time values ​​and the reference time value, obtain multiple reference time differences, and arrange the multiple reference time differences in descending order according to the values, and mark the m diagnosis and treatments as the first diagnosis and treatment to the mth diagnosis and treatment according to the descending order;

[0036] Monitor the treatment effect of the first diagnosis and treatment to obtain the first diagnosis and treatment result coefficient;

[0037] The diagnosis and treatment result coefficients corresponding to the second diagnosis and treatment to the m-th diagnosis and treatment are obtained respectively, so as to obtain the second diagnosis and treatment result coefficients to the m-th diagnosis and treatment result coefficients.

[0038] Furthermore, the treatment monitoring module obtains the first diagnosis and treatment result coefficient as follows:

[0039] Obtain the patient's bone density coefficient;

[0040] Obtain the average deviation ratio of patient indicators;

[0041] The first diagnosis and treatment result coefficient is obtained by calculating the patient's bone density coefficient and the average deviation ratio of the patient's index;

[0042] The coefficient of the first diagnosis and treatment result is calculated, and the specific formula is configured as follows:

[0043]

[0044] Among them, Z l j1 is the first diagnosis and treatment result coefficient, Gmx is the patient's bone density coefficient, and Zpc is the average deviation ratio of the patient's indicators.

[0045] Furthermore, the treatment monitoring module obtains the patient's bone density coefficient as follows:

[0046] Randomly select i bone monitoring points in the patient's body and name them as the first bone monitoring point to the i-th bone monitoring point respectively;

[0047] The bone density values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point are respectively obtained to obtain the first bone density value to the i-th bone density value, and the first bone density value to the i-th bone density value are averaged to obtain the monitored average bone density value;

[0048] The bone density T values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point are respectively obtained to obtain the first bone density T value to the i-th bone density T value, and the first bone density T value to the i-th bone density T value are averaged to obtain the monitored average bone density T value;

[0049] The bone density Z values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point are obtained respectively to obtain the first bone density Z value to the i-th bone density Z value, and the first bone density Z value to the i-th bone density Z value are averaged to obtain the monitored average bone density Z value;

[0050] The patient's bone density coefficient is obtained by calculating the average bone density value, the average bone density T value and the average bone density Z value;

[0051] The patient's bone density coefficient is calculated, and the specific formula is configured as follows:

[0052]

[0053] Among them, Gmx is the patient's bone density coefficient, Gmz is the monitored average bone density value, Gtz is the monitored average bone density T value, and Gzz is the monitored average bone density Z value.

[0054] Furthermore, the treatment monitoring module obtains the average deviation ratio of the patient index as follows:

[0055] Performing a biochemical index examination on the patient, marking j characteristic biochemical indexes in the biochemical index items of the examination, and naming them as the first characteristic biochemical index to the jth characteristic biochemical index respectively;

[0056] Acquire the indicator values ​​corresponding to the first characteristic biochemical indicator to the jth characteristic biochemical indicator respectively, and obtain the first biochemical indicator value to the jth biochemical indicator value;

[0057] Obtain the reference intervals corresponding to the first characteristic biochemical index to the jth characteristic biochemical index, and obtain the first index reference interval to the jth index reference interval;

[0058] Obtaining the deviations from the first biochemical index value to the jth biochemical index value and the first index reference interval to the jth index reference interval respectively, and obtaining the first index deviation to the jth index deviation value;

[0059] Calculate the ratios of the first indicator deviation to the jth indicator deviation value to the first biochemical indicator value to the jth biochemical indicator value, respectively, to obtain the first indicator deviation ratio to the jth indicator deviation ratio;

[0060] The first indicator deviation ratio to the jth indicator deviation ratio are averaged to obtain the average patient indicator deviation ratio.

[0061] Furthermore, the data analysis module acquires the diagnosis and treatment information analysis data as follows:

[0062] Acquire the patient's physiological data, and acquire the patient's age value, the patient's body index, and the patient's sleep monitoring coefficient according to the patient's physiological data;

[0063] Obtain patient diagnosis and treatment data, and obtain first diagnosis and treatment result coefficients to mth diagnosis and treatment result coefficients according to the patient diagnosis and treatment data;

[0064] Obtain the patient's body baseline index;

[0065] The patient's physiological index coefficient is obtained by calculating the patient's body baseline index, the patient's age value, the patient's body index and the patient's sleep monitoring coefficient;

[0066] Calculate the patient's physiological index coefficients, and the specific formula configuration is as follows:

[0067]

[0068] Among them, S lz is the patient's physiological index coefficient, Stz is the patient's body index, Stzj is the patient's body benchmark index, Hsx is the patient's sleep monitoring coefficient, and N lh is the patient's age value;

[0069] The first diagnosis and treatment result coefficient and the patient's physiological index coefficient are calculated to obtain the first patient diagnosis and treatment effect coefficient;

[0070] The treatment effect coefficient of the first patient is calculated, and the specific formula configuration is as follows:

[0071] Xz1=Slz+Zlj1;

[0072] Among them, Xz1 is the coefficient of the first patient's diagnosis and treatment effect, S lz is the coefficient of the patient's physiological index, and Z l j1 is the coefficient of the first diagnosis and treatment result;

[0073] Obtain the patient diagnosis and treatment effect coefficients corresponding to the second diagnosis and treatment to the mth diagnosis and treatment respectively, and obtain the second patient diagnosis and treatment effect coefficient to the mth diagnosis and treatment effect coefficient;

[0074] The first patient treatment effect coefficient to the mth patient treatment effect coefficient are defined as treatment information analysis data.

[0075] Furthermore, the effect evaluation module monitors the effect of diagnosis and treatment based on the diagnosis and treatment information analysis data, and provides diagnosis and treatment feedback based on the monitoring results, as follows:

[0076] Obtaining diagnosis and treatment information analysis data, and obtaining the first patient diagnosis and treatment effect coefficient to the mth patient diagnosis and treatment effect coefficient respectively according to the diagnosis and treatment information analysis data;

[0077] The first patient's treatment effect coefficient to the mth patient's treatment effect coefficient are calculated to obtain a comprehensive evaluation coefficient of treatment effect;

[0078] The comprehensive evaluation coefficient of diagnosis and treatment effect is calculated, and the specific formula configuration is as follows:

[0079] Zhg=(Xz2-Xz1)+(Xz3-Xz2)+······+(Xzm-Xz(m-1));

[0080] Among them, Zhg is the comprehensive evaluation coefficient of diagnosis and treatment effect, Xz1 to Xzm are the diagnosis and treatment effect coefficients of the first patient to the mth patient, respectively;

[0081] Obtain the threshold value of the comprehensive evaluation coefficient of diagnosis and treatment effect, and compare the comprehensive evaluation coefficient of diagnosis and treatment effect with the threshold value of the comprehensive evaluation coefficient of diagnosis and treatment effect.

[0082] Furthermore, the numerical comparison process is specifically as follows:

[0083] When the comprehensive evaluation coefficient of the diagnosis and treatment effect is greater than or equal to the comprehensive evaluation coefficient threshold of the diagnosis and treatment effect, the feedback content is that the patient's diagnosis and treatment effect is normal;

[0084] When the comprehensive evaluation coefficient of diagnosis and treatment effect is less than the comprehensive evaluation coefficient threshold of diagnosis and treatment effect, the feedback content is that the diagnosis and treatment effect of the patient is not good.

[0085] In summary, due to the adoption of the above technical solution, the beneficial effects of the present invention are:

[0086] 1. When evaluating the diagnosis and treatment effect, the present invention fully considers the impact of the patient's objective physiological factors on the diagnosis and treatment effect, thereby improving the pertinence of the diagnosis and treatment evaluation results;

[0087] 2. The present invention can fully ensure the comprehensiveness and objectivity of the evaluation of the diagnosis and treatment effect by comprehensively analyzing the diagnosis and treatment effects of patients at different diagnosis and treatment stages. BRIEF DESCRIPTION OF THE DRAWINGS

[0088] In order to facilitate understanding by those skilled in the art, the present invention is further described below with reference to the accompanying drawings.

[0089] Figure 1 is the overall system block diagram of the present invention;

[0090] Figure 2 It is a diagram of the implementation steps of the present invention;

[0091] Figure 3 Schematic diagram of osteoporosis in the present invention. DETAILED DESCRIPTION

[0092] The technical solution of the present invention will be clearly and completely described below in conjunction with the embodiments. 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.

[0093] Embodiment 1

[0094] See also Figure 1 The present invention provides a technical solution: a diagnosis and treatment information management system for osteoporosis patients, comprising a data acquisition module, a treatment monitoring module, a data analysis module, an effect evaluation module and a server, wherein the data acquisition module, the treatment monitoring module, the data analysis module and the effect evaluation module are respectively connected to the server, and the server controls the data acquisition module, the treatment monitoring module, the data analysis module and the effect evaluation module respectively;

[0095] The data acquisition module obtains the patient's age value, the patient's body index and the patient's sleep monitoring coefficient respectively to obtain the patient's physiological data;

[0096] The age value of the osteoporosis patient is obtained to obtain the patient's age value;

[0097] The height of the patient is obtained to obtain the patient's height value, and the weight of the patient is obtained to obtain the patient's weight value;

[0098] It should be noted here that:

[0099] See also Figure 3 Osteoporosis is a disease characterized by decreased bone density and destruction of bone tissue microstructure, which leads to bone fragility and susceptibility to fractures. In this application, osteoporosis patients are specifically elderly osteoporosis patients;

[0100] The patient's height and weight are calculated to obtain the patient's body index;

[0101] Calculate the patient's body index, the specific formula is as follows:

[0102]

[0103] Among them, Stz is the patient's body index, Tzz is the patient's weight value, and Sgz is the patient's weight value;

[0104] During the process of the patient receiving diagnosis and treatment, n physical monitoring dates are marked and named as the first physiological monitoring date to the nth physiological monitoring date;

[0105] It should be noted here that:

[0106] In this application, n is the numerical value corresponding to the physiological monitoring date, and n is an integer greater than 0;

[0107] Perform sleep monitoring on the patient to obtain the patient's sleep monitoring coefficient;

[0108] The details are as follows:

[0109] Obtaining the sleep durations corresponding to the first physiological monitoring date to the nth physiological monitoring date respectively, obtaining the first sleep duration to the nth sleep duration, and calculating the average of the first sleep duration to the nth sleep duration to obtain the patient's monitored sleep duration;

[0110] Obtain the patient's sleep onset time and wake-up time on the first physiological monitoring date, and define the time range between the sleep onset time and the wake-up time as the first sleep time range;

[0111] Respectively acquiring the sleep time ranges corresponding to the second physiological monitoring date to the nth physiological monitoring date to obtain the second sleep time range to the nth sleep time range;

[0112] Performing intersection operations on the first sleep time range to the nth sleep time range respectively to obtain the intersection of the sleep time ranges, and obtaining the duration of the intersection of the sleep time ranges to obtain the overlapping duration of the sleep time;

[0113] It should be noted here that:

[0114] The sleep time range intersection involved here specifically refers to the overlapping time period from the first sleep time range to the nth sleep time range;

[0115] For example: the first sleep time range is 22:00-7:00, the second sleep time range is 23:00-8:00, and the third sleep time range is 22:22-6:30, then the sleep time range corresponding to the first sleep time range to the nth sleep time range is 23:00-6:30;

[0116] Obtain the number of awakenings of the patient within the first sleep time range to obtain the number of awakenings at the first night;

[0117] The number of awakening times corresponding to the second to nth sleep time ranges is obtained respectively, to obtain the number of awakening times from the second night to the nth night;

[0118] Calculate the average of the number of awakenings from the first night to the nth night to obtain the monitored average number of awakenings;

[0119] The patient's sleep monitoring coefficient is obtained by calculating the average number of awakenings, the overlapping duration of sleep time, and the patient's monitored sleep duration;

[0120] Calculate the patient's sleep monitoring coefficient, the specific formula configuration is as follows:

[0121]

[0122] Among them, Hsx is the patient's sleep monitoring coefficient, Jsc is the patient's monitored sleep duration, Cfc is the overlap duration of sleep time, and Xlc is the average number of awakenings during monitoring;

[0123] The patient's age value, the patient's body index and the patient's sleep monitoring coefficient are defined as the patient's physiological data;

[0124] The data acquisition module acquires the patient's physiological data and transmits it to the data analysis module;

[0125] The treatment monitoring module obtains the first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient respectively to obtain the patient diagnosis and treatment data;

[0126] Obtain the patient's diagnosis and treatment records, obtain the end time values ​​corresponding to m diagnosis and treatments according to the patient's diagnosis and treatment records, obtain m diagnosis and treatment end time values, obtain the time value corresponding to the current moment as the reference time value, obtain the difference between the m diagnosis and treatment end time values ​​and the reference time value, obtain multiple reference time differences, and arrange the multiple reference time differences in descending order according to the values, and mark the m diagnosis and treatments as the first diagnosis and treatment to the mth diagnosis and treatment according to the descending order;

[0127] It should be noted here that:

[0128] In this application, m is the number of times the diagnosis and treatment correspond, and m is an integer greater than 0;

[0129] Monitor the treatment effect of the first diagnosis and treatment to obtain the first diagnosis and treatment result coefficient;

[0130] The details are as follows:

[0131] Randomly select i bone quality monitoring points in the patient's body and name them as the first bone quality monitoring point to the i-th bone quality monitoring point respectively;

[0132] It should be noted here that:

[0133] In this application, i is the quantity value corresponding to the bone monitoring point, and i is an integer greater than 0;

[0134] The bone density values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point are respectively obtained to obtain the first bone density value to the i-th bone density value, and the first bone density value to the i-th bone density value are averaged to obtain the monitored average bone density value;

[0135] The bone density T values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point are respectively obtained to obtain the first bone density T value to the i-th bone density T value, and the first bone density T value to the i-th bone density T value are averaged to obtain the monitored average bone density T value;

[0136] The bone density Z values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point are obtained respectively to obtain the first bone density Z value to the i-th bone density Z value, and the first bone density Z value to the i-th bone density Z value are averaged to obtain the monitored average bone density Z value;

[0137] It should be noted here that:

[0138] The bone density T value is the standard deviation value compared with the bone density of young healthy adults, reflecting the deviation of bone density relative to young adults;

[0139] The bone density Z value is the standard deviation value compared with healthy people of the same age and gender, reflecting the deviation of bone density relative to people of the same age;

[0140] The patient's bone density coefficient is obtained by calculating the average bone density value, the average bone density T value and the average bone density Z value;

[0141] The patient's bone density coefficient is calculated, and the specific formula is configured as follows:

[0142]

[0143] Among them, Gmx is the patient's bone density coefficient, Gmz is the monitored average bone density value, Gtz is the monitored average bone density T value, and Gzz is the monitored average bone density Z value;

[0144] Performing a biochemical index examination on the patient, marking j characteristic biochemical indexes in the biochemical index items of the examination, and naming them as the first characteristic biochemical index to the jth characteristic biochemical index respectively;

[0145] Acquire the indicator values ​​corresponding to the first characteristic biochemical indicator to the jth characteristic biochemical indicator respectively, and obtain the first biochemical indicator value to the jth biochemical indicator value;

[0146] It should be noted here that:

[0147] In this application, j is the quantitative value corresponding to the characteristic biochemical index, and j is an integer greater than 0;

[0148] The first characteristic biochemical index involved here may be a blood calcium level, the second biochemical index may be a blood phosphorus level, and the third biochemical index may be a vitamin D level;

[0149] Obtain the reference intervals corresponding to the first characteristic biochemical index to the jth characteristic biochemical index, and obtain the first index reference interval to the jth index reference interval;

[0150] Obtaining the deviations from the first biochemical index value to the jth biochemical index value and the first index reference interval to the jth index reference interval respectively, and obtaining the first index deviation to the jth index deviation value;

[0151] Calculate the ratios of the first indicator deviation to the jth indicator deviation value to the first biochemical indicator value to the jth biochemical indicator value, respectively, to obtain the first indicator deviation ratio to the jth indicator deviation ratio;

[0152] Calculate the average of the first index deviation ratio to the jth index deviation ratio to obtain the average patient index deviation ratio;

[0153] The first diagnosis and treatment result coefficient is obtained by calculating the patient's bone density coefficient and the average deviation ratio of the patient's index;

[0154] The coefficient of the first diagnosis and treatment result is calculated, and the specific formula is configured as follows:

[0155]

[0156] Among them, Z l j1 is the coefficient of the first diagnosis and treatment result, Gmx is the patient's bone density coefficient, and Zpc is the average deviation ratio of the patient's indicators;

[0157] Obtaining the diagnosis and treatment result coefficients corresponding to the second diagnosis and treatment to the mth diagnosis and treatment respectively, and obtaining the second diagnosis and treatment result coefficients to the mth diagnosis and treatment result coefficients;

[0158] The first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient are defined as patient diagnosis and treatment data;

[0159] The treatment monitoring module acquires the patient's diagnosis and treatment data and transmits it to the data analysis module;

[0160] The data analysis module obtains the first to mth diagnosis and treatment effect coefficients by analyzing the patient's physiological data and the patient's diagnosis and treatment data, and obtains diagnosis and treatment information analysis data;

[0161] Acquire the patient's physiological data, and acquire the patient's age value, the patient's body index, and the patient's sleep monitoring coefficient according to the patient's physiological data;

[0162] Obtain patient diagnosis and treatment data, and obtain first diagnosis and treatment result coefficients to mth diagnosis and treatment result coefficients according to the patient diagnosis and treatment data;

[0163] Obtain the patient's body baseline index;

[0164] The patient's physiological index coefficient is obtained by calculating the patient's body baseline index, the patient's age value, the patient's body index and the patient's sleep monitoring coefficient;

[0165] Calculate the patient's physiological index coefficients, and the specific formula configuration is as follows:

[0166]

[0167] Among them, S lz is the patient's physiological index coefficient, Stz is the patient's body index, Stzj is the patient's body benchmark index, Hsx is the patient's sleep monitoring coefficient, and N lh is the patient's age value;

[0168] The first diagnosis and treatment result coefficient and the patient's physiological index coefficient are calculated to obtain the first patient diagnosis and treatment effect coefficient;

[0169] The treatment effect coefficient of the first patient is calculated, and the specific formula configuration is as follows:

[0170] Xz1=Slz+Zlj1;

[0171] Among them, Xz1 is the coefficient of the first patient's diagnosis and treatment effect, S lz is the coefficient of the patient's physiological index, and Z l j1 is the coefficient of the first diagnosis and treatment result;

[0172] Obtain the patient diagnosis and treatment effect coefficients corresponding to the second diagnosis and treatment to the mth diagnosis and treatment respectively, and obtain the second patient diagnosis and treatment effect coefficient to the mth diagnosis and treatment effect coefficient;

[0173] The first patient treatment effect coefficient to the mth patient treatment effect coefficient are defined as treatment information analysis data;

[0174] The data analysis module acquires the diagnosis and treatment information analysis data and transmits it to the effect evaluation module;

[0175] The effect evaluation module monitors the effect of diagnosis and treatment based on the diagnosis and treatment information analysis data, and provides diagnosis and treatment feedback based on the monitoring results;

[0176] Obtaining diagnosis and treatment information analysis data, and obtaining the first patient diagnosis and treatment effect coefficient to the mth patient diagnosis and treatment effect coefficient respectively according to the diagnosis and treatment information analysis data;

[0177] The first patient's treatment effect coefficient to the mth patient's treatment effect coefficient are calculated to obtain a comprehensive evaluation coefficient of treatment effect;

[0178] The comprehensive evaluation coefficient of diagnosis and treatment effect is calculated, and the specific formula configuration is as follows:

[0179] Zhg=(Xz2-Xz1)+(Xz3-Xz2)+······+(Xzm-Xz(m-1));

[0180] Among them, Zhg is the comprehensive evaluation coefficient of diagnosis and treatment effect, Xz1 to Xzm are the diagnosis and treatment effect coefficients of the first patient to the mth patient, respectively;

[0181] Obtaining a threshold value of a comprehensive evaluation coefficient of diagnosis and treatment effects, and comparing the comprehensive evaluation coefficient of diagnosis and treatment effects with the threshold value of the comprehensive evaluation coefficient of diagnosis and treatment effects;

[0182] It should be noted here that:

[0183] The threshold value of the comprehensive evaluation coefficient of diagnosis and treatment effect involved here is the minimum comprehensive evaluation coefficient of diagnosis and treatment effect corresponding to patients with normal diagnosis and treatment effect;

[0184] When the comprehensive evaluation coefficient of the diagnosis and treatment effect is greater than or equal to the comprehensive evaluation coefficient threshold of the diagnosis and treatment effect, the feedback content is that the patient's diagnosis and treatment effect is normal;

[0185] When the comprehensive evaluation coefficient of diagnosis and treatment effect is less than the comprehensive evaluation coefficient threshold of diagnosis and treatment effect, the feedback content is that the diagnosis and treatment effect of the patient is not good.

[0186] In this application, if corresponding calculation formulas appear, the above calculation formulas are all dimensionless and take their numerical calculations. The weight coefficients, proportional coefficients and other coefficients in the formulas are set to a result value obtained by quantifying each parameter. The size of the weight coefficient and the proportional coefficient can be determined as long as it does not affect the proportional relationship between the parameter and the result value.

[0187] Embodiment 2

[0188] See also Figure 2 Based on another concept of the same invention, a diagnosis and treatment information management method for osteoporosis patients is proposed, which is applied to the diagnosis and treatment information management system. The information management method includes the following steps:

[0189] Step S1: respectively obtaining the patient's age value, the patient's body index and the patient's sleep monitoring coefficient to obtain the patient's physiological data;

[0190] Step S11: Acquire the patient's age value to obtain the patient's age value;

[0191] Step S12: obtaining the height of the patient to obtain the height value of the patient, and obtaining the weight of the patient to obtain the weight value of the patient;

[0192] Step S13: Calculate the patient's height and weight to obtain the patient's body index;

[0193] Calculate the patient's body index, the specific formula is as follows:

[0194]

[0195] Among them, Stz is the patient's body index, Tzz is the patient's weight value, and Sgz is the patient's weight value;

[0196] Step S14: During the process of the patient receiving diagnosis and treatment, n physical monitoring dates are marked respectively and named as the first physiological monitoring date to the nth physiological monitoring date;

[0197] Step S15: performing sleep monitoring on the patient to obtain a sleep monitoring coefficient of the patient;

[0198] The details are as follows:

[0199] Step S151: respectively obtaining the sleep durations corresponding to the first physiological monitoring date to the nth physiological monitoring date, obtaining the first sleep duration to the nth sleep duration, and calculating the average of the first sleep duration to the nth sleep duration to obtain the patient's monitored sleep duration;

[0200] Step S152: obtaining the patient's sleep time and wake-up time on the first physiological monitoring date, and defining the time range between the sleep time and the wake-up time as a first sleep time range;

[0201] Step S153: respectively acquiring the sleep time ranges corresponding to the second physiological monitoring date to the nth physiological monitoring date to obtain the second sleep time range to the nth sleep time range;

[0202] Step S154: performing intersection operations on the first sleep time range to the nth sleep time range respectively to obtain the intersection of the sleep time ranges, and obtaining the duration of the intersection of the sleep time ranges to obtain the overlapping duration of the sleep time;

[0203] Step S155: Obtain the number of awakenings of the patient within the first sleep time range to obtain the number of awakenings at the first night;

[0204] Step S156: acquiring the number of awakenings corresponding to the second to nth sleep time ranges respectively, to obtain the number of awakenings from the second night to the nth night;

[0205] Step S157: Calculate the average of the number of awakenings from the first night to the nth night to obtain the monitored average number of awakenings;

[0206] Step S158: Calculate the average number of awakenings, the overlapping duration of sleep time, and the monitored sleep duration of the patient to obtain a patient sleep monitoring coefficient;

[0207] Calculate the patient's sleep monitoring coefficient, the specific formula configuration is as follows:

[0208]

[0209] Among them, Hsx is the patient's sleep monitoring coefficient, Jsc is the patient's monitored sleep duration, Cfc is the overlap duration of sleep time, and Xlc is the average number of awakenings during monitoring;

[0210] Step S16: defining the patient's age value, the patient's body index and the patient's sleep monitoring coefficient as the patient's physiological data;

[0211] Step S2: respectively obtaining the first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient to obtain the patient diagnosis and treatment data;

[0212] Step S21: Obtain the patient's diagnosis and treatment records, obtain the end time values ​​corresponding to m diagnosis and treatments according to the patient's diagnosis and treatment records, obtain m diagnosis and treatment end time values, obtain the time value corresponding to the current moment as the reference time value, obtain the difference between the m diagnosis and treatment end time values ​​and the reference time value, obtain multiple reference time differences, and arrange the multiple reference time differences in descending order according to the values, and mark the m diagnosis and treatments as the first diagnosis and treatment to the mth diagnosis and treatment according to the descending order;

[0213] Step S22: monitoring the treatment effect of the first diagnosis and treatment to obtain a first diagnosis and treatment result coefficient;

[0214] Step S221: Obtaining the patient's bone density coefficient;

[0215] The details are as follows:

[0216] Step S2211: randomly selecting i bone quality monitoring points in the patient's body, and naming them as the first bone quality monitoring point to the i-th bone quality monitoring point respectively;

[0217] Step S2212: respectively obtaining the bone density values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point to obtain the first bone density value to the i-th bone density value, and averaging the first bone density value to the i-th bone density value to obtain the monitored average bone density value;

[0218] Step S2213: respectively obtaining the bone density T values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point to obtain the first bone density T value to the i-th bone density T value, and averaging the first bone density T value to the i-th bone density T value to obtain the monitored average bone density T value;

[0219] Step S2214: respectively obtaining the bone density Z values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point to obtain the first bone density Z value to the i-th bone density Z value, and averaging the first bone density Z value to the i-th bone density Z value to obtain the monitored average bone density Z value;

[0220] Step S2215: Calculate the patient's bone density coefficient by using the monitored average bone density value, the monitored average bone density T value, and the monitored average bone density Z value;

[0221] The patient's bone density coefficient is calculated, and the specific formula is configured as follows:

[0222]

[0223] Among them, Gmx is the patient's bone density coefficient, Gmz is the monitored average bone density value, Gtz is the monitored average bone density T value, and Gzz is the monitored average bone density Z value;

[0224] Step S222: obtaining the average deviation ratio of patient indicators;

[0225] The details are as follows:

[0226] Step S2221: Perform a biochemical index examination on the patient, mark j characteristic biochemical indexes in the biochemical index items examined, and name them as the first characteristic biochemical index to the jth characteristic biochemical index respectively;

[0227] Step S2222: respectively acquiring the index values ​​corresponding to the first characteristic biochemical index to the j-th characteristic biochemical index, to obtain the first biochemical index value to the j-th biochemical index value;

[0228] Step S2223: Obtain the reference interval corresponding to the first characteristic biochemical index to the jth characteristic biochemical index, and obtain the first index reference interval to the jth index reference interval;

[0229] Step S2224: respectively obtaining the deviations from the first biochemical index value to the jth biochemical index value and the first index reference interval to the jth index reference interval, and obtaining the first index deviation to the jth index deviation value;

[0230] Step S2225: Calculate the ratios of the first indicator deviation to the jth indicator deviation value to the first biochemical indicator value to the jth biochemical indicator value, and obtain the first indicator deviation ratio to the jth indicator deviation ratio;

[0231] Step S2226: Calculate the average of the first indicator deviation ratio to the jth indicator deviation ratio to obtain the average patient indicator deviation ratio;

[0232] Step S223: Calculating the patient's bone density coefficient and the average deviation ratio of the patient's index to obtain a first diagnosis and treatment result coefficient;

[0233] The coefficient of the first diagnosis and treatment result is calculated, and the specific formula is configured as follows:

[0234]

[0235] Among them, Z l j1 is the coefficient of the first diagnosis and treatment result, Gmx is the patient's bone density coefficient, and Zpc is the average deviation ratio of the patient's indicators;

[0236] Step S23: respectively obtaining the diagnosis and treatment result coefficients corresponding to the second diagnosis and treatment to the mth diagnosis and treatment, and obtaining the second diagnosis and treatment result coefficients to the mth diagnosis and treatment result coefficients;

[0237] Step S24: defining the first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient as patient diagnosis and treatment data;

[0238] Step S3: Obtaining the first to mth diagnosis and treatment effect coefficients by analyzing the patient's physiological data and the patient's diagnosis and treatment data, and obtaining diagnosis and treatment information analysis data;

[0239] Step S31: Acquire the patient's physiological data, and acquire the patient's age value, the patient's body index, and the patient's sleep monitoring coefficient according to the patient's physiological data;

[0240] Step S32: Acquire patient diagnosis and treatment data, and acquire the first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient according to the patient diagnosis and treatment data;

[0241] Step S33: Obtaining the patient's body baseline index;

[0242] Step S34: Calculate the patient's physiological index coefficient by using the patient's body baseline index, the patient's age value, the patient's body index and the patient's sleep monitoring coefficient;

[0243] Calculate the patient's physiological index coefficients, and the specific formula configuration is as follows:

[0244]

[0245] Among them, S lz is the patient's physiological index coefficient, Stz is the patient's body index, Stzj is the patient's body benchmark index, Hsx is the patient's sleep monitoring coefficient, and N lh is the patient's age value;

[0246] Step S35: Calculating the first diagnosis and treatment result coefficient and the patient's physiological index coefficient to obtain the first patient diagnosis and treatment effect coefficient;

[0247] The treatment effect coefficient of the first patient is calculated, and the specific formula configuration is as follows:

[0248] Xz1=Slz+Zlj1;

[0249] Among them, Xz1 is the coefficient of the first patient's diagnosis and treatment effect, S lz is the coefficient of the patient's physiological index, and Z l j1 is the coefficient of the first diagnosis and treatment result;

[0250] Step S36: respectively obtaining the patient diagnosis and treatment effect coefficients corresponding to the second diagnosis and treatment to the mth diagnosis and treatment, and obtaining the second patient diagnosis and treatment effect coefficient to the mth diagnosis and treatment effect coefficient;

[0251] Step S37: defining the first patient diagnosis and treatment effect coefficient to the mth diagnosis and treatment effect coefficient as diagnosis and treatment information analysis data;

[0252] Step S4: monitor the treatment effect according to the diagnosis and treatment information analysis data, and provide diagnosis and treatment feedback according to the monitoring results;

[0253] Step S41: Acquire diagnosis and treatment information analysis data, and acquire the first patient diagnosis and treatment effect coefficient to the mth patient diagnosis and treatment effect coefficient respectively according to the diagnosis and treatment information analysis data;

[0254] Step S42: Calculating the first patient's treatment effect coefficient to the mth patient's treatment effect coefficient to obtain a comprehensive evaluation coefficient of the treatment effect;

[0255] The comprehensive evaluation coefficient of diagnosis and treatment effect is calculated, and the specific formula configuration is as follows:

[0256] Zhg=(Xz2-Xz1)+(Xz3-Xz2)+······+(Xzm-Xz(m-1));

[0257] Among them, Zhg is the comprehensive evaluation coefficient of diagnosis and treatment effect, Xz1 to Xzm are the diagnosis and treatment effect coefficients of the first patient to the mth patient, respectively;

[0258] Step S43: obtaining a threshold value of a comprehensive evaluation coefficient of diagnosis and treatment effect, and comparing the comprehensive evaluation coefficient of diagnosis and treatment effect with the threshold value of the comprehensive evaluation coefficient of diagnosis and treatment effect;

[0259] Step S431: When the comprehensive evaluation coefficient of the diagnosis and treatment effect is greater than or equal to the comprehensive evaluation coefficient threshold of the diagnosis and treatment effect, the feedback content is that the diagnosis and treatment effect of the patient is normal;

[0260] Step S432: When the comprehensive evaluation coefficient of the diagnosis and treatment effect is less than the comprehensive evaluation coefficient threshold of the diagnosis and treatment effect, the feedback content is that the diagnosis and treatment effect of the patient is not good.

[0261] The preferred embodiments of the present invention disclosed above are only used to help explain the present invention. The preferred embodiments do not describe all the details in detail, nor do they limit the invention to only specific implementation methods. 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 present invention, so that those skilled in the art can understand and use the present invention well. The present invention is limited only by the claims and their full scope and equivalents.

Claims

1. A diagnosis and treatment information management system for osteoporosis patients, characterized in that: include: Data acquisition module: used to obtain the patient's age value, patient's body index and patient's sleep monitoring coefficient to obtain the patient's physiological data; Treatment monitoring module: used to obtain patient diagnosis and treatment records, mark the first diagnosis and treatment to the mth diagnosis and treatment respectively through the patient diagnosis and treatment records, obtain the patient bone density coefficient and the average deviation ratio of the patient index corresponding to the first diagnosis and treatment to the mth diagnosis and treatment respectively, analyze and obtain the first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient, and define the first diagnosis and treatment result coefficient to the mth diagnosis and treatment result coefficient as patient diagnosis and treatment data; Data analysis module: used to obtain the first to mth diagnosis and treatment effect coefficients by analyzing the patient's physiological data and the patient's diagnosis and treatment data, and obtain diagnosis and treatment information analysis data; Effect evaluation module: used to analyze data based on diagnosis and treatment information to monitor the diagnosis and treatment effects, and provide diagnosis and treatment feedback based on the monitoring results; Monitor the treatment effect of the first diagnosis and treatment to obtain the first diagnosis and treatment result coefficient; Obtaining the diagnosis and treatment result coefficients corresponding to the second diagnosis and treatment to the mth diagnosis and treatment respectively, and obtaining the second diagnosis and treatment result coefficients to the mth diagnosis and treatment result coefficients; The first diagnosis and treatment result coefficient is obtained, including: Obtain the patient's bone density coefficient; Obtain the average deviation ratio of patient indicators; The first diagnosis and treatment result coefficient is obtained by calculating the patient's bone density coefficient and the average deviation ratio of the patient's index; Obtain the patient's bone density coefficient, including: Randomly select i bone monitoring points in the patient's body and name them as the first bone monitoring point to the i-th bone monitoring point respectively; The bone density values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point are respectively obtained to obtain the first bone density value to the i-th bone density value, and the first bone density value to the i-th bone density value are averaged to obtain the monitored average bone density value; The bone density T values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point are respectively obtained to obtain the first bone density T value to the i-th bone density T value, and the first bone density T value to the i-th bone density T value are averaged to obtain the monitored average bone density T value; The bone density Z values ​​corresponding to the first bone monitoring point to the i-th bone monitoring point are obtained respectively to obtain the first bone density Z value to the i-th bone density Z value, and the first bone density Z value to the i-th bone density Z value are averaged to obtain the monitored average bone density Z value; The patient's bone density coefficient is obtained by calculating the average bone density value, the average bone density T value and the average bone density Z value.

2. A diagnosis and treatment information management system for osteoporosis patients according to claim 1, characterized in that: The data acquisition module acquires the patient's physiological data as follows: The patient's age value is obtained to obtain the patient's age value; The height of the patient is obtained to obtain the patient's height value, and the weight of the patient is obtained to obtain the patient's weight value; The patient's height and weight are calculated to obtain the patient's body index; Calculate the patient's body index, the specific formula is as follows: Among them, Stz is the patient's body index, Tzz is the patient's weight value, and Sgz is the patient's weight value; Perform sleep monitoring on the patient to obtain the patient's sleep monitoring coefficient; The patient's age value, the patient's body index and the patient's sleep monitoring coefficient are defined as the patient's physiological data.

3. A diagnosis and treatment information management system for osteoporosis patients according to claim 2, characterized in that: The data acquisition module acquires the patient's sleep monitoring coefficient, as follows: During the process of the patient receiving diagnosis and treatment, n physical monitoring dates are marked and named as the first physiological monitoring date to the nth physiological monitoring date; Obtaining the sleep durations corresponding to the first physiological monitoring date to the nth physiological monitoring date, respectively, to obtain the first sleep duration to the nth sleep duration, and calculating the average of the first sleep duration to the nth sleep duration to obtain the patient's monitored sleep duration; Obtain the patient's sleep onset time and wake-up time on the first physiological monitoring date, and define the time range between the sleep onset time and the wake-up time as the first sleep time range; Respectively acquiring the sleep time ranges corresponding to the second physiological monitoring date to the nth physiological monitoring date to obtain the second sleep time range to the nth sleep time range; Performing intersection operations on the first sleep time range to the nth sleep time range respectively to obtain the intersection of the sleep time ranges, and obtaining the duration of the intersection of the sleep time ranges to obtain the overlapping duration of the sleep time; Obtain the number of awakenings of the patient within the first sleep time range to obtain the number of awakenings at the first night; The number of awakenings corresponding to the second to nth sleep time ranges is obtained respectively, to obtain the number of awakenings from the second night to the nth night; Calculate the average of the number of awakenings from the first night to the nth night to obtain the monitored average number of awakenings; The patient's sleep monitoring coefficient is obtained by calculating the average number of awakenings, the overlapping duration of sleep time, and the patient's monitored sleep duration; Calculate the patient's sleep monitoring coefficient, the specific formula configuration is as follows: Among them, Hsx is the patient's sleep monitoring coefficient, Jsc is the patient's monitored sleep duration, Cfc is the overlap duration of sleep time, and Xlc is the average number of awakenings during monitoring.

4. The diagnosis and treatment information management system for osteoporosis patients according to claim 1, characterized in that: The treatment monitoring module obtains the average deviation ratio of the patient index as follows: Performing a biochemical index examination on the patient, marking j characteristic biochemical indexes in the biochemical index items of the examination, and naming them as the first characteristic biochemical index to the jth characteristic biochemical index respectively; Acquire the indicator values ​​corresponding to the first characteristic biochemical indicator to the jth characteristic biochemical indicator respectively, and obtain the first biochemical indicator value to the jth biochemical indicator value; Obtain the reference intervals corresponding to the first characteristic biochemical index to the jth characteristic biochemical index, and obtain the first index reference interval to the jth index reference interval; Obtaining the deviations from the first biochemical index value to the jth biochemical index value and the first index reference interval to the jth index reference interval respectively, and obtaining the first index deviation to the jth index deviation value; Calculate the ratios of the first indicator deviation to the jth indicator deviation value to the first biochemical indicator value to the jth biochemical indicator value, respectively, to obtain the first indicator deviation ratio to the jth indicator deviation ratio; The first indicator deviation ratio to the jth indicator deviation ratio are averaged to obtain the average patient indicator deviation ratio.

5. The diagnosis and treatment information management system for osteoporosis patients according to claim 1, characterized in that: The data analysis module acquires the diagnosis and treatment information analysis data, as follows: Acquire the patient's physiological data, and acquire the patient's age value, the patient's body index, and the patient's sleep monitoring coefficient according to the patient's physiological data; Obtain patient diagnosis and treatment data, and obtain first diagnosis and treatment result coefficients to mth diagnosis and treatment result coefficients according to the patient diagnosis and treatment data; Obtain the patient's body baseline index; The patient's physiological index coefficient is obtained by calculating the patient's body baseline index, the patient's age value, the patient's body index and the patient's sleep monitoring coefficient; Calculate the patient's physiological index coefficients, and the specific formula configuration is as follows: Among them, Slz is the patient's physiological index coefficient, Stz is the patient's body index, Stzj is the patient's body benchmark index, Hsx is the patient's sleep monitoring coefficient, and Nlh is the patient's age value; The first diagnosis and treatment result coefficient and the patient's physiological index coefficient are calculated to obtain the first patient diagnosis and treatment effect coefficient; The treatment effect coefficient of the first patient is calculated, and the specific formula configuration is as follows: Xz1=Slz+Zlj1; Among them, Xz1 is the coefficient of the first patient's diagnosis and treatment effect, Slz is the coefficient of the patient's physiological index, and Zlj1 is the coefficient of the first diagnosis and treatment result; Obtain the patient diagnosis and treatment effect coefficients corresponding to the second diagnosis and treatment to the mth diagnosis and treatment respectively, and obtain the second patient diagnosis and treatment effect coefficient to the mth diagnosis and treatment effect coefficient; The first patient treatment effect coefficient to the mth patient treatment effect coefficient are defined as treatment information analysis data.

6. A diagnosis and treatment information management system for osteoporosis patients according to claim 1, characterized in that: The effect evaluation module monitors the effect of diagnosis and treatment based on the diagnosis and treatment information analysis data, and provides diagnosis and treatment feedback based on the monitoring results, as follows: Obtaining diagnosis and treatment information analysis data, and obtaining the first patient diagnosis and treatment effect coefficient to the mth patient diagnosis and treatment effect coefficient respectively according to the diagnosis and treatment information analysis data; The first patient's treatment effect coefficient to the mth patient's treatment effect coefficient are calculated to obtain a comprehensive evaluation coefficient of treatment effect; The comprehensive evaluation coefficient of diagnosis and treatment effect is calculated, and the specific formula configuration is as follows: Zhg=(Xz2-Xz1)+(Xz3-Xz2)+······+(Xzm-Xz(m-1)); Among them, Zhg is the comprehensive evaluation coefficient of diagnosis and treatment effect, Xz1 to Xzm are the diagnosis and treatment effect coefficients of the first patient to the mth patient, respectively; Obtain the threshold value of the comprehensive evaluation coefficient of diagnosis and treatment effect, and compare the comprehensive evaluation coefficient of diagnosis and treatment effect with the threshold value of the comprehensive evaluation coefficient of diagnosis and treatment effect.

7. A diagnosis and treatment information management system for osteoporosis patients according to claim 6, characterized in that: The numerical comparison process is specifically as follows: When the comprehensive evaluation coefficient of the diagnosis and treatment effect is greater than or equal to the comprehensive evaluation coefficient threshold of the diagnosis and treatment effect, the feedback content is that the patient's diagnosis and treatment effect is normal; When the comprehensive evaluation coefficient of diagnosis and treatment effect is less than the comprehensive evaluation coefficient threshold of diagnosis and treatment effect, the feedback content is that the diagnosis and treatment effect of the patient is not good.

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