Monitoring method, system, equipment and medium for hospital operation data

Abstract

The present invention discloses a monitoring method, system, device and medium for hospital operation data, wherein the monitoring method for hospital operation data comprises the following steps: obtaining index sample data corresponding to the hospital operation status within a preset period; calculating the hospital operation health index within the preset period according to the index sample data; determining the fundamental index affecting the hospital operation status within the preset period according to the preset rules based on the operation health index; and monitoring the fundamental index to determine the hospital operation status. The present invention narrows the scope of monitoring and improves the hospital operation efficiency by transforming the overall monitoring of the hospital operation status index data into the monitoring of the fundamental index.

Description

Technical Field

[0001] The present invention relates to the field of hospital information management, and in particular to a method, system, equipment and medium for monitoring hospital operation data. Background Art

[0002] With the continuous improvement of hospital information construction and the continuous improvement of information level, a large number of operational data reports have been generated while realizing the informatization of a large number of software and hardware infrastructure. At present, due to the slow development of artificial intelligence in the medical industry compared with other industries such as the Internet, there is also a lack of managers with strong business capabilities and data analysis capabilities to conduct substantive analysis of the obtained operational reports.

[0003] Therefore, in terms of operational management, hospitals are still at the stage of simply obtaining a large number of operational reports, and lack analysis of indicator data corresponding to the hospital's operational status to determine the fundamental indicators that affect the operational status. In other words, they fail to identify the fundamental indicators in a timely manner and monitor the data values ​​of the fundamental indicators, resulting in low efficiency in the hospital's operational management. Summary of the invention

[0004] The technical problem to be solved by the present invention is to overcome the defect in the prior art that the fundamental indicators are not identified in time and the data values ​​of the fundamental indicators are not monitored, thereby resulting in low efficiency in hospital operation management, and to provide a method, system, equipment and medium for monitoring hospital operation data.

[0005] The present invention solves the above technical problems through the following technical solutions:

[0006] In a first aspect, the present invention provides a method for monitoring hospital operation data, the monitoring method comprising:

[0007] Obtaining indicator sample data corresponding to the hospital's operating status within a preset period; wherein the indicator sample data is divided into multiple levels of indicators, each level of indicator having multiple subordinate indicators;

[0008] Calculate the hospital's operational health index within the preset period based on the indicator sample data;

[0009] Determine the fundamental indicators that affect the hospital's operating status within the preset period based on the operational health index according to preset rules;

[0010] The essential indicators are monitored to determine the operating status of the hospital.

[0011] Preferably, the step of determining the fundamental indicators affecting the hospital operation status within the preset period based on the operation health index according to preset rules includes:

[0012] Determine the target indicator in the indicator sample data within the preset period based on the operational health index;

[0013] Calculate the correlation coefficient between the target indicator and other indicators of the same level as the target indicator to obtain the relevant indicator with a correlation greater than a preset threshold value;

[0014] The fundamental indicator is determined according to a preset linkage relationship between the relevant indicator and the target indicator; wherein the linkage relationship represents a causal relationship between the two indicators.

[0015] Preferably, the indicator sample data includes a plurality of first-level indicators, a second-level indicator corresponding to each first-level indicator, and a data value corresponding to each indicator within the preset period; each first-level indicator and each second-level indicator is assigned a corresponding weight value;

[0016] The step of determining the target indicator in the indicator sample data within the preset period based on the operation health index includes:

[0017] Calculate the first driving force of each of the first-level indicators within the preset period based on the operational health index, and obtain the first-level key indicator according to the first driving force; wherein the first driving force represents the influence of the fluctuation of the first-level indicator on the operational health index;

[0018] The second pulling force of the secondary indicator corresponding to the first-level key indicator within the preset period is calculated according to the data value corresponding to the first-level key indicator, and the target indicator is obtained according to the second pulling force; wherein the second pulling force represents the degree of influence of the fluctuation of the secondary indicator corresponding to the first-level key indicator on the data value corresponding to the first-level key indicator.

[0019] Preferably, the step of calculating the first pulling force of each of the first-level indicators within the preset period based on the operational health index to obtain the first-level key indicators includes:

[0020] Obtaining the structural change value of each of the first-level indicators and the growth rate of the operational health index within the preset period;

[0021] Calculate the first pulling force corresponding to each of the first-level indicators within the preset period according to the structural change value and the growth rate;

[0022] Determine the first-level indicator corresponding to the largest first pulling force as a first-level key indicator;

[0023] The structural change value of each of the first-level indicators within the preset period is obtained by the following formula:

[0024] VSV i=X i1 -X i0

[0025] VSV i represents the structural change value of the i-th level indicator within the preset period, X i1 represents the ratio of the product of the data value and the weight value corresponding to the i-th primary indicator to the operational health index on the last day of the preset period; X i0 It represents the ratio of the product of the data value and the weight value corresponding to the i-th primary indicator on the first day of the preset period to the operation health index on the first day of the preset period.

[0026] Preferably, the calculation of the correlation coefficient between the target indicator and other indicators of the same level as the target indicator is obtained by the following formula:

[0027]

[0028] Wherein, X represents the target indicator, Y represents any indicator of the same level as the target indicator, Cov(X,Y) represents the covariance between the target indicator X and indicator Y, Var(x) represents the variance of the target indicator, and R(X,Y) represents the correlation coefficient between the target indicator X and indicator Y.

[0029] Preferably, the monitoring method further comprises:

[0030] Based on the operational health index, the hospital's operational status within the preset period is graded and rated using the RSR method to generate operational grade information;

[0031] and / or,

[0032] Based on the fundamental indicators, determine whether the factor affecting the hospital's operating status is the ward. If so, determine whether there are special populations and / or special events in the ward. If so, generate early warning information; wherein the factors include at least one of the ward, department and doctor.

[0033] In a second aspect, the present invention provides a monitoring system for hospital operation data, the monitoring system comprising:

[0034] An indicator data acquisition module is used to acquire indicator sample data corresponding to the hospital's operating status within a preset period; wherein the indicator sample data is divided into multiple levels of indicators, and each level of indicator has at least one subordinate indicator;

[0035] An operation health index calculation module, used to calculate the operation health index of the hospital within the preset period according to the indicator sample data;

[0036] A fundamental indicator determination module, used to determine the fundamental indicators that affect the hospital operation status within the preset period based on the operation health index according to preset rules;

[0037] The indicator monitoring module is used to monitor the fundamental indicators to determine the operating status of the hospital.

[0038] Preferably, the fundamental indicator data determination module includes:

[0039] A target indicator determination unit, configured to determine a target indicator in the indicator sample data within the preset period based on the operation health index;

[0040] A correlation coefficient calculation unit, used to calculate the correlation coefficient between the target indicator and other indicators of the same level as the target indicator, so as to obtain a correlation indicator having a correlation with the target indicator greater than a preset threshold;

[0041] The fundamental indicator determination unit is used to determine the fundamental indicator according to the preset linkage relationship between the relevant indicator and the target indicator; wherein the linkage relationship represents the causal relationship between the two indicators.

[0042] Preferably, the indicator sample data includes a plurality of first-level indicators, a second-level indicator corresponding to each first-level indicator, and a data value corresponding to each indicator within the preset period; each first-level indicator and each second-level indicator is assigned a corresponding weight value;

[0043] The target indicator determination unit is specifically used for:

[0044] Calculate the first driving force of each of the first-level indicators within the preset period based on the operational health index, and obtain the first-level key indicator according to the first driving force; wherein the first driving force represents the influence of the fluctuation of the first-level indicator on the operational health index;

[0045] The second pulling force of the secondary indicator corresponding to the first-level key indicator within the preset period is calculated according to the data value corresponding to the first-level key indicator, and the target indicator is obtained according to the second pulling force, wherein the second pulling force characterizes the influence of the fluctuation of the secondary indicator corresponding to the first-level key indicator on the data value corresponding to the first-level key indicator.

[0046] Preferably, the step of calculating the first driving force of each of the first-level indicators within the preset period based on the operation health index in the target indicator determination unit to obtain the first-level key indicators includes:

[0047] Obtaining the structural change value of each of the first-level indicators and the growth rate of the operational health index within the preset period;

[0048] Calculate the first pulling force corresponding to each of the first-level indicators within the preset period according to the structural change value and the growth rate;

[0049] Determine the first-level indicator corresponding to the largest first pulling force as a first-level key indicator;

[0050] The structural change value of each of the first-level indicators within the preset period is obtained by the following formula:

[0051] VSV i =X i1 -X i0

[0052] VSV i represents the structural change value of the i-th level indicator within the preset period, X i1 represents the ratio of the product of the data value and the weight value corresponding to the i-th primary indicator to the operational health index on the last day of the preset period; X i0 It represents the ratio of the product of the data value and the weight value corresponding to the i-th primary indicator on the first day of the preset period to the operation health index on the first day of the preset period.

[0053] Preferably, the correlation coefficient calculation unit calculates the correlation coefficient between the target indicator and other indicators of the same level as the target indicator by the following formula:

[0054]

[0055] Wherein, X represents the target indicator, Y represents any indicator of the same level as the target indicator, Cov(X,Y) represents the covariance between the target indicator X and indicator Y, Var(x) represents the variance of the target indicator, and R(X,Y) represents the correlation coefficient between the target indicator X and indicator Y.

[0056] Preferably, the monitoring system further comprises:

[0057] An operation level information generating module, configured to generate operation level information after grading the operation status of the hospital within the preset period by using the RSR method based on the operation health index;

[0058] and / or,

[0059] The early warning information generation module is used to determine whether the factor affecting the hospital's operating status is the ward based on the fundamental indicators. If so, it is used to determine whether there are special populations and / or special events in the ward. If so, early warning information is generated; wherein the factors include at least one of the ward, department and doctor.

[0060] Preferably, the indicator data acquisition module is specifically used for:

[0061] According to the data value corresponding to the normalized lowest level indicator, the operational relationship between the upper level indicator and the lower level indicator in the multi-level indicator system, and the weight value corresponding to each indicator, the data values ​​corresponding to the remaining indicators are calculated step by step.

[0062] In a third aspect, the present invention provides an electronic device comprising a processor, a memory, and a computer program stored in the memory and executable on the processor, wherein the computer program, when executed by the processor, implements the method for monitoring hospital operation data as described in the first aspect.

[0063] In a fourth aspect, the present invention provides a computer-readable storage medium, wherein the computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for monitoring hospital operation data described in the first aspect are implemented.

[0064] The positive and progressive effects of the present invention are: providing a method, system, device and medium for monitoring hospital operation data, calculating the hospital's operation health index through the index sample data corresponding to the hospital's operation status within a preset period; determining the fundamental index affecting the hospital's operation status based on the operation health index, and monitoring the fundamental index. The present invention narrows the scope of monitoring and improves the hospital's operation efficiency by transforming the overall monitoring of the hospital's operation status index data into the monitoring of the fundamental index. BRIEF DESCRIPTION OF THE DRAWINGS

[0065] Figure 1 This is a flow chart of a method for monitoring hospital operation data according to Embodiment 1 of the present invention.

[0066] Figure 2 This is a flow chart of step S3 of the method for monitoring hospital operation data according to embodiment 1 of the present invention.

[0067] Figure 3 This is a flowchart of step S31 of the method for monitoring hospital operation data according to embodiment 1 of the present invention.

[0068] Figure 4 This is a flowchart of step S311 of the method for monitoring hospital operation data according to embodiment 1 of the present invention.

[0069] Figure 5This is a flow chart of a method for monitoring hospital operation data according to Embodiment 2 of the present invention.

[0070] Figure 6 This is a module diagram of a system for monitoring hospital operation data according to Embodiment 3 of the present invention.

[0071] Figure 7 This is a module diagram of a system for monitoring hospital operation data according to Embodiment 4 of the present invention.

[0072] Figure 8 This is a schematic diagram of the hardware structure of an electronic device according to Embodiment 5 of the present invention. DETAILED DESCRIPTION

[0073] The present invention is further described below by way of examples, but the present invention is not limited to the scope of the examples.

[0074] Example 1

[0075] In this embodiment, a method for monitoring hospital operation data is provided. Figure 1 , the method comprises the following steps:

[0076] Step S1, obtaining indicator sample data corresponding to the hospital's operating status within a preset period; wherein the indicator sample data is divided into multiple levels of indicators, and each level of indicator has multiple subordinate indicators.

[0077] In this embodiment, based on the construction principles of the index system of the hospital operation status, i.e., systematicity, typicality, scientificity and operability, the index sample data required for monitoring the hospital operation status is determined. For example, the first-level index composition can be quality analysis, operation analysis, growth analysis and financial analysis, the second-level index composition can be adverse events, treatment level, rationality of resource allocation, operation efficiency, etc., and the third-level index composition can be the incidence of hospital infection, the number of adverse event reports, etc. For each third-level index, a corresponding data caliber can be selected, and the data caliber can be any one of the medical record homepage system, HIS (Hospital Information System) and LIS (Laboratory Information Management System). Of course, the composition of the above-mentioned first-level index, second-level index and third-level index is only used as an example, and this embodiment does not limit the composition of the first-level index, the second-level index and the third-level index. Each first-level indicator, second-level indicator, and third-level indicator can use CRITIC (Criteria Importance Through Intercrieria Correlatio, objective weighting method), entropy weight method, and independence weight method, or use expert scoring to generate the corresponding weight value for each indicator.

[0078] In this embodiment, the secondary indicator system may include two primary indicators: cost control and medical efficiency; the secondary indicators corresponding to cost control include: outpatient income (yuan), emergency income (yuan), total cost of discharged patients (yuan), average cost of outpatient and emergency visits (yuan), average cost of discharged patients (yuan), outpatient and emergency antibiotic drug costs (yuan), total inpatient medical insurance costs (yuan), total outpatient and emergency medical insurance costs (yuan), proportion of outpatient and emergency drug revenue (%), proportion of inpatient drug revenue (%); the secondary indicators corresponding to medical efficiency include: average length of stay of discharged patients (days (days)), number of outpatient and emergency visits (person-times), number of discharged patients (person-times), outpatient and emergency medical insurance visits (person-times), number of discharged patients per medical and technical staff (person-times), and number of outpatient and emergency visits per medical and technical staff (person-times).

[0079] It should be noted that those skilled in the art can adjust the obtained indicator sample data according to the regulatory requirements of each hospital; there are no specific restrictions on the number of next-level indicators corresponding to the previous-level indicators, and the operational relationship between each level of indicators.

[0080] Step S2: Calculate the hospital's operational health index within a preset period based on the indicator sample data.

[0081] Exemplarily, the data values ​​of all secondary indicators can be calculated by weighted summation according to the data value and weight value corresponding to each tertiary indicator; the data values ​​of all primary indicators can be calculated by weighted summation according to the data value and weight value corresponding to each secondary indicator. It is understandable that the preset period can be 2 days, 3 days, or 5 days, and those skilled in the art can customize the time range corresponding to the preset period according to business scenario requirements.

[0082] Among them, within the preset period, the operation health index can be calculated by the following formula:

[0083]

[0084] X i Indicates the value of the data value corresponding to the i-th level indicator, W i It represents the weight value corresponding to the i-th first-level indicator, and y represents the operation health index.

[0085] Step S3: Determine the fundamental indicators that affect the hospital's operating status within a preset period based on the operational health index according to preset rules.

[0086] In this embodiment, the first level of mining of the operational health index is first performed, and the key first-level key indicators are determined by calculating the first driving force of the fluctuation of each first-level indicator on the fluctuation of the operational health index. The second level of mining is performed with the data values ​​corresponding to the first-level key indicators as the target. The second driving force of the fluctuation of each second-level indicator corresponding to the first-level key indicator on the fluctuation of the first-level key indicator is calculated, and the target indicator is determined according to the size of the second driving force. Finally, based on the target indicator, further mining is performed downward to find the fundamental indicator.

[0087] Step S4: monitor the fundamental indicators to determine the operating status of the hospital.

[0088] For example, if the first preset threshold and the second preset threshold corresponding to the fundamental indicator are 10 and 6 respectively, the neural network model or the time series prediction module is used to monitor the data of the fundamental indicator. If the predicted value output by the model is 12 or 5, it means that the fundamental indicator is abnormal data, which indicates that the operation status of the hospital is unqualified. It is necessary to deploy the operation risk management that may be faced in the future based on the fundamental indicator in advance to prevent it from happening. If the predicted value output by the model is 8, it indicates that the operation status of the hospital is good.

[0089] In one possible implementation, the data values ​​of the fundamental indicator within a preset period are obtained, and a straight line that fits these data to the greatest extent is found as the regression line, and the sum of the squares of the vertical distances from each data point on the regression line to the regression line is the smallest. If the fitted straight line equation is y=ax+b based on the data values ​​corresponding to the fundamental indicator, x represents time, y represents the predicted value of the indicator, and a and b represent the slope coefficient and intercept respectively, the trend of the fundamental indicator is predicted based on the regression equation. If a>0 means that the fundamental indicator will rise, and a<0 means that the fundamental indicator will fall, the predicted result will generate indicator risk information.

[0090] In this embodiment, a method for monitoring hospital operation data is provided. Figure 2 , the step S3 further comprises:

[0091] Step S31: Determine the target indicator in the indicator sample data within a preset period based on the operation health index.

[0092] Step S32: Calculate the correlation coefficient between the target indicator and other indicators of the same level as the target indicator to obtain the relevant indicators whose correlation with the target indicator is greater than a preset threshold.

[0093] Step S33: determining the fundamental indicator according to the preset linkage relationship between the relevant indicator and the target indicator; wherein the linkage relationship represents the causal relationship between the two indicators.

[0094] In this embodiment, the operation monitoring index is determined, and the target indicator in the indicator sample data is determined. The target indicator can be a secondary indicator or a tertiary indicator. If the application is a secondary indicator, it is necessary to determine the similarity coefficient between the secondary indicator and the remaining indicators, and select the relevant indicators whose similarity coefficients meet the preset threshold requirements. This embodiment does not impose specific restrictions on the number of relevant indicators, and does not impose specific restrictions on the preset linkage relationship.

[0095] For example, if it is a secondary indicator system, the target indicator determined is the average length of stay of discharged patients, and the related indicators determined based on the target indicator are the average cost per discharge and the number of discharges. The average length of stay of discharged patients is the factor affecting the average cost per discharge, and the average length of stay of discharged patients is the factor affecting the number of discharges. Based on this linkage relationship, it can be seen that the average length of stay of discharged patients is the fundamental indicator.

[0096] In a possible implementation, if it is a two-level indicator system, the target indicator determined is indicator A, and the related indicators determined based on the target indicator A are indicator B and indicator C. According to the preset first linkage relationship, indicator A is the cause of the impact on indicator B, and indicator C is the cause of the impact on indicator A, then the fundamental indicator is indicator C.

[0097] In another possible implementation, if it is a two-level indicator system, the target indicator determined is indicator A, and the related indicators determined based on the target indicator A are indicator D, indicator E and indicator F. According to the preset second linkage relationship, indicator A is the reason affecting indicator D, indicator E is the reason affecting indicator A, and indicator F is the reason affecting indicator A, but indicator E is the reason affecting indicator F, that is, indicator E is the fundamental indicator.

[0098] In this embodiment, a method for monitoring hospital operation data is provided. Figure 3 The indicator sample data includes multiple first-level indicators, the second-level indicators corresponding to each first-level indicator, and the data value corresponding to each indicator within a preset period; each first-level indicator and second-level indicator is assigned a corresponding weight value, and the step S31 also includes:

[0099] Step S311: Calculate the first driving force of each first-level indicator within a preset period based on the operation health index, and obtain the first-level key indicator according to the first driving force; the first driving force represents the impact of the fluctuation of the first-level indicator on the operation health index;

[0100] Step S312: Calculate the second pulling force of the secondary indicator corresponding to the first-level key indicator within a preset period according to the data value corresponding to the first-level key indicator, and obtain the target indicator according to the second pulling force; wherein the second pulling force represents the influence of the fluctuation of the secondary indicator corresponding to the first-level key indicator on the data value corresponding to the first-level key indicator.

[0101] In this embodiment, the structural change analysis method is used to calculate the first driving force of each primary indicator in turn, and the primary indicator corresponding to the largest first driving force is selected as the primary key indicator. For example, if there are two primary indicators, namely cost control and medical efficiency, the first driving force corresponding to medical efficiency is 1.2, and cost control is 1.1, then medical efficiency is the first key indicator. For the primary indicator of medical efficiency, the secondary indicators below it are analyzed, and the second driving force of the secondary indicators corresponding to the primary key indicators within the preset period is calculated. According to the size of the second driving force, the secondary indicator with the greatest impact on the fluctuation of the primary indicator is determined as the target indicator. For example, in the secondary indicator of medical efficiency, the second driving force corresponding to the average length of stay of discharged patients is 1.4, the second driving force corresponding to the number of outpatient and emergency visits is 1.3, and the second driving force corresponding to the number of outpatient and emergency medical insurance visits is 1.1, then the secondary indicator of the average length of stay of hospital patients is used as the target indicator.

[0102] In this embodiment, a method for monitoring hospital operation data is described as follows: Figure 4 , step S311 includes:

[0103] Step S3111, obtaining the structural change value of each primary indicator and the growth rate of the operation health index within a preset period;

[0104] Step S3112: Calculate the first pulling force corresponding to each primary indicator within a preset period according to the structural change value and the growth rate.

[0105] Step S3113: determine the first-level indicator corresponding to the largest first pulling force as the first-level key indicator.

[0106] Specifically, the structural change value of each first-level indicator within the preset period can be calculated according to the following formula:

[0107] VSV i =X i1 -X i0

[0108] Among them, VSV i represents the structural change value of the i-th first-level indicator within the preset period, X i1 It represents the ratio of the product of the data value and weight value corresponding to the i-th first-level indicator to the operational health index of that day on the last day of the preset cycle; X i0 It represents the ratio of the product of the data value and weight value corresponding to the i-th first-level indicator on the first day of the preset cycle to the operational health index of that day.

[0109] The growth rate of the operational health index within a preset period can be calculated according to the following formula:

[0110]

[0111] Wherein, P represents the growth rate of the operational health index within the preset period, M1 represents the operational health index of the hospital on the last day of the preset period, and M0 represents the operational health index of the hospital on the first day of the preset period.

[0112] Add the absolute values ​​of the structural change degree corresponding to each first-level indicator to generate the structural change degree DSV of the first-level indicator within the preset period. Calculate the first contribution rate corresponding to each first-level indicator, which is equal to the percentage of the structural change value to the structural change degree. Multiply the first contribution rate corresponding to each first-level indicator by the growth rate of the operation health index to obtain the first driving force. Select the first-level indicator corresponding to the maximum value of all first driving forces as the first-level key indicator.

[0113] In step 32, the correlation coefficient between the target indicator and the other indicators of the same level as the target indicator is calculated by the following formula:

[0114]

[0115] Where X represents the target indicator, Y represents any indicator of the same level as the target indicator, Cov(X,Y) represents the covariance between the target indicator X and the indicator Y, Var(x) represents the variance of the target indicator, and R(X,Y) represents the correlation coefficient between the target indicator X and the indicator Y.

[0116] In this embodiment, step S1 includes the following:

[0117] According to the data values ​​corresponding to the normalized indicators of the lowest level, the operational relationship between the upper-level indicators and the lower-level indicators in the multi-level indicator system, and the weight values ​​corresponding to each indicator, the data values ​​corresponding to the remaining indicators are calculated step by step.

[0118] Specifically, if the lowest level indicator is a third-level indicator, the table storing all indicators is called an indicator information table, and the data value corresponding to each third-level indicator is obtained by the following formula:

[0119]

[0120] X represents the initial value of the three-level index to be normalized. min Indicates the minimum initial value of the three-level indicator corresponding to the initial value of the three-level indicator to be normalized in the indicator information table. max It indicates that the initial value corresponding to the third-level indicator to be normalized is the maximum initial value corresponding to the third-level indicator in the series in the indicator information table, and Xnormalization indicates the data value corresponding to the third-level indicator to be normalized.

[0121] Because each third-level indicator in the indicator sample data includes positive indicators and reverse indicators, and the dimensions of different third-level indicators are inconsistent, in order to unify the data of all third-level indicators into the range of 0 to 1, the data needs to be normalized. After calculating the positive indicator using the above formula, the dimension is eliminated, and the units of all third-level indicators can be unified.

[0122] In one possible implementation, for the reverse indicator, you need to first take the reciprocal to convert it into a forward indicator or directly use the formula: The meaning of the formula will not be elaborated here.

[0123] A method for monitoring hospital operation data is provided, which calculates the hospital's operation health index through the indicator sample data corresponding to the hospital's operation status within a preset period; determines the fundamental indicator that affects the hospital's operation status based on the operation health index; and monitors the fundamental indicator. The present invention narrows the scope of monitoring and improves the hospital's operation efficiency by transforming the overall monitoring of the hospital's operation status indicator data into the monitoring of the fundamental indicator.

[0124] Example 2

[0125] like Figure 5 As shown, the method for monitoring hospital operation data in this embodiment is a further improvement of Embodiment 1, and specifically includes:

[0126] After step S4, the method further includes:

[0127] Step S5: Based on the operational health index, the hospital's operational status within a preset period is graded and rated using the RSR method to generate operational grade information.

[0128] Specifically, the data values ​​and operational health index corresponding to the first-level indicators are obtained. If the preset period is 5 days, the rank sum ratio RSR method is used to calculate the comprehensive score of the daily operational status within 5 days. The RSR method obtains the dimensionless statistic RSR (rank sum ratio) through rank conversion, and the comprehensive scores of the hospital's operational status within 5 days are ranked by the RSR value. The core of the RSR method for grade rating is to convert the comprehensive score of the daily operational status into a rank, then map the rank distribution to the normal distribution curve, and finally use the 3σ principle of the normal distribution for grading and output the operational grade information.

[0129] Step S6: Based on the fundamental indicators, determine whether the factor affecting the hospital's operating status is the ward. If so, determine whether there are special populations and / or special events in the ward. If so, generate early warning information; wherein the factors include at least one of the ward, department, and doctor.

[0130] In this embodiment, the calculated operation health index is graded using the RSR method, and the operation status is divided into different levels, so as to achieve a qualitative analysis of the hospital's operation status. By finding the root cause corresponding to the fundamental indicator, a reasonable response plan is provided for the hospital's operation status.

[0131] Example 3

[0132] This embodiment provides a monitoring system for hospital operation data, such as Figure 6 As shown, the monitoring system of hospital operation data includes: an indicator data acquisition module 110, an operation health index calculation module 120, a fundamental indicator determination module 130, and an indicator monitoring module 140. The fundamental indicator determination module 130 also includes: a target indicator determination unit 131, a correlation coefficient calculation unit 132, and a fundamental indicator determination unit 133.

[0133] The indicator data acquisition module 110 is used to obtain indicator sample data corresponding to the hospital's operating status within a preset period; wherein the indicator sample data is divided into multiple levels of indicators, and each level of the indicator system has multiple subordinate indicators.

[0134] In this embodiment, based on the construction principles of the index system of the hospital operation status, namely, systematicity, typicality, scientificity and operability, the index sample data required for monitoring the hospital operation status is determined. For example, the first-level index composition can be quality analysis, operation analysis, growth analysis and financial analysis, the second-level index composition can be adverse events, treatment level, rationality of resource allocation, operation efficiency, etc., and the third-level index composition can be the incidence of hospital infection, the number of adverse event reports, etc. For each third-level index, a corresponding data caliber can be selected, and the data caliber can be any one of the medical record homepage system, HIS system and LIS system. Of course, the composition of the above-mentioned first-level index, second-level index and third-level index is only used as an example, and this embodiment does not make any limitation on the composition of the first-level index, second-level index and third-level index. Each first-level index, second-level index and third-level index can adopt the CRITIC weight method, entropy weight method and independence weight method, or, the weight value corresponding to each index can be generated by expert scoring.

[0135] In this embodiment, the secondary indicator system may include two primary indicators: cost control and medical efficiency; the secondary indicators corresponding to cost control include: outpatient income (yuan), emergency income (yuan), total cost of discharged patients (yuan), average cost of outpatient and emergency visits (yuan), average cost of discharged patients (yuan), outpatient and emergency antibiotic drug costs (yuan), total inpatient medical insurance costs (yuan), total outpatient and emergency medical insurance costs (yuan), proportion of outpatient and emergency drug revenue (%), proportion of inpatient drug revenue (%); the secondary indicators corresponding to medical efficiency include: average length of stay of discharged patients (days (days)), number of outpatient and emergency visits (person-times), number of discharged patients (person-times), outpatient and emergency medical insurance visits (person-times), number of discharged patients per medical and technical staff (person-times), and number of outpatient and emergency visits per medical and technical staff (person-times).

[0136] It should be noted that those skilled in the art can adjust the obtained indicator sample data according to the regulatory requirements of each hospital; there are no specific restrictions on the number of next-level indicators corresponding to the previous-level indicators, and the operational relationship between each level of indicators.

[0137] The operation health index calculation module 120 is used to calculate the operation health index of the hospital within a preset period based on the indicator sample data.

[0138] Exemplarily, the data values ​​of all secondary indicators can be calculated by weighted summation according to the data value and weight value corresponding to each tertiary indicator; the data values ​​of all primary indicators can be calculated by weighted summation according to the data value and weight value corresponding to each secondary indicator. It is understandable that the preset period can be 1 day, 2 days, or 3 days, and those skilled in the art can customize the time range corresponding to the preset period according to business scenario requirements.

[0139] Among them, within the preset period, the operation health index can be calculated by the following formula:

[0140]

[0141] X i Indicates the value of the data value corresponding to the i-th level indicator, W i It represents the weight value corresponding to the i-th first-level indicator, and y represents the operation health index.

[0142] The fundamental indicator determination module 130 is used to determine the fundamental indicators that affect the hospital operation status within a preset period based on the operation health index according to preset rules.

[0143] In this embodiment, the first level mining of the operation health index is first carried out, and the key first-level key indicators are determined by calculating the first driving force of the fluctuation of each first-level indicator on the fluctuation of the operation health index. The second level mining is carried out with the data value corresponding to the first-level key indicator as the target, and the target indicator is determined by calculating the second driving force of the fluctuation of each second-level indicator corresponding to the first-level key indicator on the fluctuation of the first-level key indicator. Then, based on the target indicator, further mining is carried out downward to find the fundamental indicator.

[0144] The indicator monitoring module 140 monitors fundamental indicators to determine the operating status of the hospital.

[0145] For example, if the first preset threshold and the second preset threshold corresponding to the fundamental indicator are 10 and 6 respectively, and a neural network model or a time series prediction module is used to monitor the data of the fundamental indicator, if the predicted value output by the model is 12 or 5, it means that the fundamental indicator is abnormal data, and it is necessary to deploy in advance the operational risk management that may be faced in the future based on the fundamental indicator to prevent problems before they occur.

[0146] In one possible implementation, the data values ​​of the fundamental indicator within a preset period are obtained, and a straight line that fits these data to the greatest extent is found as the regression line, and the sum of the squares of the vertical distances from each data point on the regression line to the regression line is the smallest. If the fitted straight line equation is y=ax+b based on the data values ​​corresponding to the fundamental indicator, x represents time, y represents the predicted value of the indicator, and a and b represent the slope coefficient and intercept respectively, the trend of the fundamental indicator is predicted based on the regression equation. If a>0 means that the fundamental indicator will rise, and a<0 means that the fundamental indicator will fall, the predicted result will generate indicator risk information.

[0147] In this embodiment, a method for monitoring hospital operation data is provided. Figure 6 The fundamental indicator determination module 130 also includes: a target indicator determination unit 131, a correlation coefficient calculation unit 132, and a fundamental indicator determination unit 133.

[0148] The target indicator determination unit 131 is used to determine the target indicator in the indicator sample data within a preset period based on the operation health index.

[0149] The correlation coefficient calculation unit 132 calculates the correlation coefficient between the target indicator and other indicators of the same level as the target indicator to obtain the relevant indicator whose correlation with the target indicator is greater than a preset threshold.

[0150] The fundamental indicator determination unit 133 determines the fundamental indicator according to a preset linkage relationship between the relevant indicator and the target indicator; wherein the linkage relationship represents a causal relationship between two indicators.

[0151] In this embodiment, the operation monitoring index is determined, and the target indicator in the indicator sample data is determined. The target indicator can be a secondary indicator or a tertiary indicator. If the application is a secondary indicator, it is necessary to determine the similarity coefficient between the secondary indicator and the remaining indicators, and select the relevant indicators whose similarity coefficients meet the preset threshold requirements. This embodiment does not impose specific restrictions on the number of relevant indicators, and does not impose specific restrictions on the preset linkage relationship.

[0152] For example, if it is a secondary indicator system, the target indicator determined is the average length of stay of discharged patients, and the related indicators determined based on the target indicator are the average cost per discharge and the number of discharges. The average length of stay of discharged patients is the factor affecting the average cost per discharge, and the average length of stay of discharged patients is the factor affecting the number of discharges. Based on this linkage relationship, it can be seen that the average length of stay of discharged patients is the fundamental indicator.

[0153] In a possible implementation, if it is a two-level indicator system, the target indicator determined is indicator A, and the related indicators determined based on the target indicator A are indicator B and indicator C. According to the preset first linkage relationship, indicator A is the cause of the impact on indicator B, and indicator C is the cause of the impact on indicator A, then the fundamental indicator is indicator C.

[0154] In another possible implementation, if it is a two-level indicator system, the target indicator determined is indicator A, and the related indicators determined based on the target indicator A are indicator D, indicator E and indicator F. According to the preset second linkage relationship, indicator A is the reason affecting indicator D, indicator E is the reason affecting indicator A, and indicator F is the reason affecting indicator A, but indicator E is the reason affecting indicator F, that is, indicator E is the fundamental indicator.

[0155] In this embodiment, a monitoring system for hospital operation data is provided. Figure 6 The indicator sample data includes multiple first-level indicators, the second-level indicators corresponding to each first-level indicator, and the data value corresponding to each indicator within a preset period; each first-level indicator and second-level indicator is assigned a corresponding weight value, and the target indicator determination unit 131 is specifically used to:

[0156] Based on the operational health index, the first driving force of each first-level indicator within a preset period is calculated, and the first-level key indicator is obtained according to the first driving force; wherein the first driving force represents the degree of influence of the fluctuation of the first-level indicator on the operational health index;

[0157] The second pulling force of the secondary indicator corresponding to the first-level key indicator within a preset period is calculated according to the data value corresponding to the first-level key indicator, and the target indicator is obtained according to the second pulling force, wherein the second pulling force represents the influence of the fluctuation of the secondary indicator corresponding to the first-level key indicator on the data value corresponding to the first-level key indicator.

[0158] In this embodiment, the structural change analysis method is used to calculate the first driving force of each primary indicator in turn, and the primary indicator corresponding to the largest first driving force is selected as the primary key indicator. For example, if there are two primary indicators, namely cost control and medical efficiency, the first driving force corresponding to medical efficiency is 1.2, and cost control is 1.1, then medical efficiency is the first key indicator. For the primary indicator of medical efficiency, the secondary indicators below it are analyzed, and the second driving force of the secondary indicators corresponding to the primary key indicators within the preset period is calculated. According to the size of the second driving force, the secondary indicator with the greatest impact on the fluctuation of the primary indicator is determined as the target indicator. For example, in the secondary indicator of medical efficiency, the second driving force corresponding to the average length of stay of discharged patients is 1.4, the second driving force corresponding to the number of outpatient and emergency visits is 1.3, and the second driving force corresponding to the number of outpatient and emergency medical insurance visits is 1.1, then the secondary indicator of the average length of stay of hospital patients is used as the target indicator.

[0159] In this embodiment, a monitoring system for hospital operation data, the target indicator determination unit 131 calculates the first driving force of each of the first-level indicators within the preset period based on the operation health index to obtain the first-level key indicators, including:

[0160] Obtaining the structural change value of each primary indicator and the growth rate of the operational health index within a preset period;

[0161] Calculate the first driving force corresponding to each first-level indicator within a preset period according to the structural change value and growth rate;

[0162] Determine the first-level indicator corresponding to the largest first pulling force as the first-level key indicator;

[0163] Among them, the structural change value of each primary indicator within the preset period is obtained by the following formula:

[0164] VSV i =X i1 -X i0

[0165] VSV i represents the structural change value of the i-th first-level indicator within the preset period, X i1 It represents the ratio of the product of the data value and weight value corresponding to the i-th first-level indicator to the operational health index of that day on the last day of the preset cycle; X i0 It represents the ratio of the product of the data value and the weight value corresponding to the i-th primary indicator on the first day of the preset period to the operational health index of that day.

[0166] The growth rate of the operational health index within a preset period can be calculated according to the following formula:

[0167]

[0168] Wherein, P represents the growth rate of the operational health index within the preset period, M1 represents the operational health index of the hospital on the last day of the preset period, and M0 represents the operational health index of the hospital on the first day of the preset period.

[0169] Add the absolute values ​​of the structural change degree corresponding to each first-level indicator to generate the structural change degree DSV of the first-level indicator within the preset period. Calculate the first contribution rate corresponding to each first-level indicator, which is equal to the percentage of the structural change value VSV and the structural change degree DSV. Multiply the first contribution rate corresponding to each first-level indicator and the growth rate of the operation health index to obtain the first driving force, and take the first-level indicator corresponding to the maximum value of all first driving forces as the first-level key indicator.

[0170] In this embodiment, a monitoring system for hospital operation data, the correlation coefficient calculation unit 132 calculates the correlation coefficient between the target indicator and the other indicators of the same level as the target indicator by the following formula:

[0171]

[0172] Where X represents the target indicator, Y represents any indicator of the same level as the target indicator, Cov(X,Y) represents the covariance between the target indicator X and the indicator Y, Var(x) represents the variance of the target indicator, and R(X,Y) represents the correlation coefficient between the target indicator X and the indicator Y.

[0173] In this embodiment, the indicator data acquisition module 110 is specifically used for:

[0174] According to the data values ​​corresponding to the normalized indicators of the lowest level, the operational relationship between the upper-level indicators and the lower-level indicators in the multi-level indicator system, and the weight values ​​corresponding to each indicator, the data values ​​corresponding to the remaining indicators are calculated step by step.

[0175] Specifically, if the lowest level indicator is a third-level indicator, the table storing all indicators is called an indicator information table, and the data value corresponding to each third-level indicator is obtained by the following formula:

[0176]

[0177] X represents the initial value of the three-level index to be normalized. min Indicates the minimum initial value of the three-level indicator corresponding to the initial value of the three-level indicator to be normalized in the indicator information table. maxIt indicates that the initial value corresponding to the third-level indicator to be normalized is the maximum initial value corresponding to the third-level indicator in the series in the indicator information table, and Xnormalization indicates the data value corresponding to the third-level indicator to be normalized.

[0178] Because each third-level indicator in the indicator sample data includes positive indicators and reverse indicators, and the dimensions of different third-level indicators are inconsistent, in order to unify the data of all third-level indicators into the range of 0 to 1, the data needs to be normalized. After calculating the positive indicator using the above formula, the dimension is eliminated, and the units of all third-level indicators can be unified.

[0179] In one possible implementation, for the reverse indicator, you need to first take the reciprocal to convert it into a forward indicator or directly use the formula: The meaning of the formula will not be elaborated here.

[0180] A monitoring system for hospital operation data is provided, wherein an indicator data acquisition module acquires indicator sample data corresponding to the hospital's operation status within a preset period; an operation health index calculation module calculates the hospital's operation health index within a preset period based on the indicator sample data; a fundamental indicator determination module determines the fundamental indicators that affect the hospital's operation status within a preset period based on the operation health index according to preset rules; and an indicator monitoring module monitors the fundamental indicators to determine the hospital's operation status. The present invention improves the hospital's operation efficiency by monitoring and analyzing the fundamental indicators.

[0181] Example 4

[0182] like Figure 7 As shown, the hospital operation data monitoring system of this embodiment is a further improvement of the embodiment 3, and the system further includes: an operation level information generating module 150 and an early warning prompt information generating module 160.

[0183] The operation level information generating module 150 generates operation level information by grading and rating the operation status of the hospital within a preset period using the RSR method based on the operation health index.

[0184] Specifically, the data values ​​and operational health index corresponding to the first-level indicators are obtained. If the preset period is 5 days, the rank sum ratio RSR method is used to calculate the comprehensive score of the daily operational status within 5 days. The RSR method obtains the dimensionless statistic RSR (rank sum ratio) through rank conversion, and the comprehensive scores of the hospital's operational status within 5 days are ranked by the RSR value. The core of the RSR method for grade rating is to convert the comprehensive score of the daily operational status into a rank, then map the rank distribution to the normal distribution curve, and finally use the 3σ principle of the normal distribution for grading and output the operational grade information.

[0185] The early warning information generation module 160 determines whether the factor affecting the hospital's operating status is the ward based on the fundamental indicators. If so, it determines whether there are special populations and / or special events in the ward. If so, it generates early warning information; wherein the factors include at least one of the ward, department and doctor.

[0186] In this embodiment, the calculated operation health index is graded using the RSR method, and the operation status is divided into different levels, so as to achieve a qualitative analysis of the hospital's operation status. By finding the root cause corresponding to the fundamental indicator, a reasonable response plan is provided for the hospital's operation status.

[0187] Example 5

[0188] Figure 8 This is a schematic diagram of the structure of an electronic device provided in this embodiment. The electronic device includes a memory, a processor, and a computer program stored in the memory and executable on the processor. When the processor executes the program, the method for monitoring hospital operation data of embodiment 1 or 2 is implemented. Figure 8 The electronic device 30 shown is only an example and should not bring any limitation to the functions and scope of use of the embodiments of the present invention.

[0189] The electronic device 30 may be in the form of a general-purpose computing device, for example, it may be a server device. The components of the electronic device 30 may include, but are not limited to: at least one processor 31, at least one memory 32, and a bus 33 connecting different system components (including the memory 32 and the processor 31).

[0190] The bus 33 includes a data bus, an address bus, and a control bus.

[0191] The memory 32 may include a volatile memory, such as a random access memory (RAM) 321 and / or a cache memory 322 , and may further include a read-only memory (ROM) 323 .

[0192] The memory 32 may also include a program / utility 325 having a set (at least one) of program modules 324, such program modules 324 including but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which or some combination may include an implementation of a network environment.

[0193] The processor 31 executes various functional applications and data processing by running the computer programs stored in the memory 32, such as the method for monitoring hospital operation data of embodiment 1 or 2 of the present invention.

[0194] The electronic device 30 may also communicate with one or more external devices 34 (e.g., keyboards, pointing devices, etc.). Such communication may be performed via an input / output (I / O) interface 35. Furthermore, the model-generated device 30 may also communicate with one or more networks (e.g., a local area network (LAN), a wide area network (WAN), and / or a public network, such as the Internet) via a network adapter 36. As shown, the network adapter 36 communicates with other modules of the model-generated device 30 via a bus 33. It should be understood that, although not shown in the figure, other hardware and / or software modules may be used in conjunction with the model-generated device 30, including but not limited to: microcode, device drivers, redundant processors, external disk drive arrays, RAID (RAID) systems, tape drives, and data backup storage systems.

[0195] It should be noted that although several units / modules or sub-units / modules of the electronic device are mentioned in the above detailed description, this division is merely exemplary and not mandatory. In fact, according to an embodiment of the present invention, the features and functions of two or more units / modules described above can be embodied in one unit / module. Conversely, the features and functions of one unit / module described above can be further divided into multiple units / modules to be embodied.

[0196] Example 6

[0197] This embodiment provides a computer-readable storage medium on which a computer program is stored. When the program is executed by a processor, the steps of the method for monitoring hospital operation data of embodiment 1 or 2 are implemented.

[0198] The readable storage medium may include but is not limited to: a portable disk, a hard disk, a random access memory, a read-only memory, an erasable programmable read-only memory, an optical storage device, a magnetic storage device or any suitable combination of the above.

[0199] In a possible implementation, the present invention can also be implemented in the form of a program product, which includes a program code. When the program product is run on a terminal device, the program code is used to enable the terminal device to execute the steps of the hospital operation data monitoring method of Example 1 or 2.

[0200] The program code for executing the present invention may be written in any combination of one or more programming languages, and may be executed entirely on a user device, partially on a user device, as an independent software package, partially on a user device and partially on a remote device, or entirely on a remote device.

[0201] Although the specific embodiments of the present invention are described above, it should be understood by those skilled in the art that this is only for illustration and the protection scope of the present invention is defined by the appended claims. Those skilled in the art may make various changes or modifications to these embodiments without departing from the principles and essence of the present invention, but these changes and modifications all fall within the protection scope of the present invention.

Claims

1. A method for monitoring hospital operation data, characterized in that: The monitoring method comprises: Obtaining indicator sample data corresponding to the hospital's operating status within a preset period; wherein the indicator sample data is divided into multiple levels of indicators, each level of indicator having multiple subordinate indicators; Calculate the hospital's operational health index within the preset period based on the indicator sample data; Determine the fundamental indicators that affect the hospital's operating status within the preset period based on the operational health index according to preset rules; Monitoring the said essential indicators to determine the operational status of the hospital; The step of determining the fundamental indicators that affect the hospital operation status within the preset period based on the operation health index according to preset rules includes: Determine the target indicator in the indicator sample data within the preset period based on the operational health index; Calculate the correlation coefficient between the target indicator and other indicators of the same level as the target indicator to obtain the relevant indicator with a correlation greater than a preset threshold value; Determine the fundamental indicator according to the preset linkage relationship between the relevant indicator and the target indicator; wherein the linkage relationship represents the causal relationship between the two indicators; The indicator sample data includes a plurality of first-level indicators, a second-level indicator corresponding to each first-level indicator, and a data value corresponding to each indicator within the preset period; each first-level indicator and each second-level indicator is assigned a corresponding weight value; The step of determining the target indicator in the indicator sample data within the preset period based on the operation health index includes: Calculate the first driving force of each of the first-level indicators within the preset period based on the operational health index, and obtain the first-level key indicator according to the first driving force; wherein the first driving force represents the influence of the fluctuation of the first-level indicator on the operational health index; Calculate the second pulling force of the secondary indicator corresponding to the primary key indicator within the preset period according to the data value corresponding to the primary key indicator, and obtain the target indicator according to the second pulling force; wherein the second pulling force represents the influence of the fluctuation of the secondary indicator corresponding to the primary key indicator on the data value corresponding to the primary key indicator; The step of calculating the first driving force of each of the first-level indicators within the preset period based on the operation health index to obtain the first-level key indicators includes: Obtaining the structural change value of each of the first-level indicators and the growth rate of the operational health index within the preset period; Calculate the first pulling force corresponding to each of the first-level indicators within the preset period according to the structural change value and the growth rate; Determine the first-level indicator corresponding to the largest first pulling force as a first-level key indicator; The structural change value of each of the first-level indicators within the preset period is obtained by the following formula: VSV i =X i1 -X i0 VSV i represents the structural change value of the i-th level indicator within the preset period, X i1 represents the ratio of the product of the data value and the weight value corresponding to the i-th primary indicator to the operational health index on the last day of the preset period; X i0 It represents the ratio of the product of the data value and the weight value corresponding to the i-th primary indicator on the first day of the preset period to the operation health index on the first day of the preset period; The step of obtaining the indicator sample data corresponding to the hospital's operating status within a preset period includes: According to the data value corresponding to the normalized lowest level indicator, the operational relationship between the upper level indicator and the lower level indicator in the multi-level indicator system, and the weight value corresponding to each indicator, the data values ​​corresponding to the remaining indicators are calculated step by step.

2. The method for monitoring hospital operation data according to claim 1, characterized in that: The calculation of the correlation coefficient between the target indicator and the other indicators of the same level as the target indicator is obtained by the following formula: Wherein, X represents the target indicator, Y represents any indicator of the same level as the target indicator, Cov(X,Y) represents the covariance between the target indicator X and indicator Y, Var(x) represents the variance of the target indicator, and R(X,Y) represents the correlation coefficient between the target indicator X and indicator Y.

3. The method for monitoring hospital operation data according to claim 1, characterized in that: The monitoring method further comprises: Based on the operational health index, the hospital's operational status within the preset period is graded and rated using the RSR method to generate operational grade information; and / or, Based on the fundamental indicators, determine whether the factor affecting the hospital's operating status is the ward. If so, determine whether there are special populations and / or special events in the ward. If so, generate early warning information; wherein the factors include at least one of the ward, department and doctor.

4. A monitoring system for hospital operation data, characterized in that: The monitoring system comprises: An indicator data acquisition module is used to acquire indicator sample data corresponding to the hospital's operating status within a preset period; wherein the indicator sample data is divided into multiple levels of indicators, and each level of indicator has multiple subordinate indicators; An operation health index calculation module, used to calculate the operation health index of the hospital within the preset period according to the indicator sample data; A fundamental indicator determination module, used to determine the fundamental indicators that affect the hospital operation status within the preset period based on the operation health index according to preset rules; An indicator monitoring module, used to monitor the fundamental indicators to determine the operating status of the hospital; The fundamental indicator data determination module includes: A target indicator determination unit, configured to determine a target indicator in the indicator sample data within the preset period based on the operation health index; A correlation coefficient calculation unit, used to calculate the correlation coefficient between the target indicator and other indicators of the same level as the target indicator, so as to obtain a correlation indicator having a correlation with the target indicator greater than a preset threshold; A fundamental indicator determination unit, configured to determine a fundamental indicator according to a preset linkage relationship between the relevant indicator and the target indicator; wherein the linkage relationship represents a causal relationship between the two indicators; The indicator sample data includes a plurality of first-level indicators, a second-level indicator corresponding to each first-level indicator, and a data value corresponding to each indicator within the preset period; each first-level indicator and each second-level indicator is assigned a corresponding weight value; The target indicator determination unit is specifically used for: Calculate the first driving force of each of the first-level indicators within the preset period based on the operational health index, and obtain the first-level key indicator according to the first driving force; wherein the first driving force represents the influence of the fluctuation of the first-level indicator on the operational health index; Calculating a second pulling force of a secondary indicator corresponding to the primary key indicator within the preset period according to the data value corresponding to the primary key indicator, and obtaining a target indicator according to the second pulling force, wherein the second pulling force represents the degree of influence of the fluctuation of the secondary indicator corresponding to the primary key indicator on the data value corresponding to the primary key indicator; The step of calculating the first driving force of each of the first-level indicators within the preset period based on the operation health index to obtain the first-level key indicators includes: Obtaining the structural change value of each of the first-level indicators and the growth rate of the operational health index within the preset period; Calculate the first pulling force corresponding to each of the first-level indicators within the preset period according to the structural change value and the growth rate; Determine the first-level indicator corresponding to the largest first pulling force as a first-level key indicator; The structural change value of each of the first-level indicators within the preset period is obtained by the following formula: VSV i =X i1 -X i0 VSV i represents the structural change value of the i-th level indicator within the preset period, X i1 represents the ratio of the product of the data value and the weight value corresponding to the i-th primary indicator to the operational health index on the last day of the preset period; X i0 It represents the ratio of the product of the data value and the weight value corresponding to the i-th primary indicator on the first day of the preset period to the operation health index on the first day of the preset period; The indicator data acquisition module is specifically used for: According to the data value corresponding to the normalized lowest level indicator, the operational relationship between the upper level indicator and the lower level indicator in the multi-level indicator system, and the weight value corresponding to each indicator, the data values ​​corresponding to the remaining indicators are calculated step by step.

5. The hospital operation data monitoring system according to claim 4, characterized in that: The correlation coefficient calculation unit calculates the correlation coefficient between the target indicator and other indicators of the same level as the target indicator by the following formula: Wherein, X represents the target indicator, Y represents any indicator of the same level as the target indicator, Cov(X,Y) represents the covariance between the target indicator X and indicator Y, Var(x) represents the variance of the target indicator, and R(X,Y) represents the correlation coefficient between the target indicator X and indicator Y.

6. The hospital operation data monitoring system according to claim 4, characterized in that: The monitoring system further comprises: An operation level information generating module, configured to generate operation level information after grading the operation status of the hospital within the preset period by using the RSR method based on the operation health index; and / or, The early warning information generation module is used to determine whether the factor affecting the hospital's operating status is the ward based on the fundamental indicators. If so, it is used to determine whether there are special populations and / or special events in the ward. If so, early warning information is generated; wherein the factors include at least one of the ward, department and doctor.

7. An electronic device comprising a memory, a processor, and a computer program stored in the memory and executable on the processor, characterized in that: When the processor executes the computer program, a method for monitoring hospital operation data according to any one of claims 1 to 3 is implemented.

8. A computer-readable storage medium, characterized in that: The computer-readable storage medium stores a computer program, and when the computer program is executed by a processor, the steps of the method for monitoring hospital operation data according to any one of claims 1 to 3 are implemented.

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