CN114067982A - Method and device for evaluating hospital operation condition and computer readable storage medium - Google Patents

Abstract

A method, a device and a computer readable storage medium for evaluating hospital operation conditions are provided, which are used for acquiring various hospital operation index data in a current time period, wherein the current time period comprises K time points; starting from the 1 st time point of the K time points and ending to the K-s +1 th time point of the K time points, and respectively taking each time point as an initial time point to determine a time sequence containing s continuous time points from the K time points; for each initial time point, determining a correlation value according to each two time sequences corresponding to each two hospital operation index data; determining a curvature value of a connecting line between two hospital operation index data corresponding to the correlation value larger than or equal to a preset threshold value; determining curvature correlation values corresponding to the initial time points; and obtaining the evaluation content of the hospital operation stability according to the curvature related value of the current time period and the curvature related value of the last time period. The evaluation content has high accuracy.

Description

Method and device for evaluating hospital operation condition and computer readable storage medium

Technical Field

The application relates to the field of hospital management, in particular to a method and a device for evaluating hospital operation conditions and a computer-readable storage medium.

Background

With the improvement of the intelligent level of the hospital, the role of the hospital managers and operators is like that the overall operation condition of the hospital needs to be intuitively known.

Evaluation of the operational condition of a hospital typically requires a medical professional to empirically give an evaluation of the operational condition of the hospital based on a number of factors that may be involved.

However, each evaluation requires a professional to perform the evaluation by experience, and the versatility is not high.

Disclosure of Invention

The technical problem that this application mainly solved is that the evaluation mode commonality of current hospital operation situation is not high.

According to a first aspect, an embodiment provides a method for evaluating hospital operating conditions, comprising:

acquiring various hospital operation index data in a current time period, wherein the current time period comprises K time points, and K is an integer greater than 1;

determining a time sequence comprising s continuous time points from the K time points by taking each time point as an initial time point from the 1 st time point of the K time points to the K-s +1 th time point of the K time points, wherein K and s are positive integers, and s is less than or equal to K;

for each initial time point, determining a correlation value between each two kinds of hospital operation index data according to two time sequences respectively corresponding to each two kinds of hospital operation index data;

determining a curvature value of a connecting line between two hospital operation index data corresponding to a correlation value larger than or equal to a preset threshold value;

determining curvature correlation values corresponding to the initial time points according to the curvature values corresponding to the time sequences;

and obtaining the evaluation content of the hospital operation stability according to the curvature related value corresponding to each initial time point in the current time period and the curvature related value corresponding to each initial time point in the last time period of the current time period.

Optionally, the determining a curvature value of a connection line between two types of hospital operation index data corresponding to a correlation value greater than or equal to a preset threshold includes:

judging whether the correlation value corresponding to each two hospital operation index data is greater than or equal to a preset threshold value or not;

and under the condition that the correlation value corresponding to the two hospital operation index data is greater than or equal to a preset threshold value, obtaining the curvature value of the connecting line between the two hospital operation index data according to the correlation value which is greater than or equal to the preset threshold value and corresponds to the two hospital operation index data respectively.

Optionally, the obtaining, according to the correlation value greater than or equal to the preset threshold value respectively corresponding to the two hospital operation index data, a curvature value of a connection line between the two hospital operation index data includes:

obtaining a curvature value of a connecting line between two hospital operation index data corresponding to a correlation value larger than or equal to a preset threshold value according to the following formula:

wherein FR (E (n, m)) is a curvature value of a connecting line between the nth hospital operation index data and the mth hospital operation index data, R_mnIs a correlation value, R, between the mth kind of hospital operation index data and the nth kind of hospital operation index data corresponding to an initial time point_nkIs the correlation value between the nth hospital operation index data and the kth hospital operation index data corresponding to the initial time point, and R_nkGreater than or equal to a predetermined threshold, R_imIs the correlation value between the m-th hospital operation index data and the i-th hospital operation index data corresponding to the initial time point, andR_imgreater than or equal to a preset threshold.

Optionally, the determining, according to the curvature value corresponding to each time sequence, a curvature related value corresponding to each initial time point includes:

and obtaining the average value of all curvature values corresponding to each time sequence of the initial time point to obtain the curvature related value corresponding to the initial time point.

Optionally, the obtaining, according to the curvature related value corresponding to each initial time point in the current time period and the curvature related value corresponding to each initial time point in the previous time period of the current time period, the evaluation content of the hospital operation stability includes:

determining the sum of curvature related values corresponding to each initial time point in the current time period as an index value of the current time period;

acquiring an index value of a previous time period of the current time period, wherein the index value of the previous time period of the current time period is the sum of curvature related values corresponding to initial time points of the previous time period of the current time period;

determining a change rate between the index value of the current time period and the index value of the last time period of the current time period;

and obtaining the evaluation content of the hospital operation stability according to the change rate and a preset fluctuation threshold value.

Optionally, the preset fluctuation threshold is multiple, and the obtaining of the evaluation content of the hospital operation stability according to the change rate and the preset fluctuation threshold includes:

and comparing the size relationship between the change rate and a plurality of preset fluctuation threshold values to obtain the evaluation content of the operation stability of the hospital.

Optionally, the method further includes:

displaying a graph corresponding to each initial time point, wherein the graph corresponding to each initial time point comprises nodes and partial or all connecting lines among the nodes, the nodes are used for representing the hospital operation index data, and the connecting lines are used for representing that the correlation value among the hospital operation index data represented by the nodes at two ends of the connecting lines is greater than or equal to a preset threshold value;

displaying a curvature related value change graph, wherein the curvature related value change graph comprises curvature related values corresponding to all initial time points of the current time period, or the curvature related value change graph comprises curvature related values corresponding to all initial time points of the current time period and the last time period of the current time period;

and displaying the evaluation content of the hospital operation stability.

Optionally, the acquiring of multiple hospital operation index data in the current time period includes:

acquiring various original hospital operation index data in the current time period;

preprocessing the multiple original hospital operation index data to obtain multiple hospital operation index data in the current time period, wherein the preprocessing comprises the following steps: at least one of a data cleansing process and a data deduplication process.

According to a second aspect, an embodiment provides an evaluation apparatus for hospital operation status, comprising:

the data acquisition module is used for acquiring various hospital operation index data in a current time period, wherein the current time period comprises a plurality of K time points, and K is an integer greater than 1;

a graph generating module, configured to start from a 1 st time point of the K time points and end to a K-s +1 th time point of the K time points, and determine a time sequence including s consecutive time points from the K time points by taking each time point as an initial time point, where K and s are positive integers, and s is less than or equal to K; for each initial time point, determining a correlation value between each two kinds of hospital operation index data according to two time sequences respectively corresponding to each two kinds of hospital operation index data;

the curvature calculation module is used for determining a curvature value of a connecting line between two hospital operation index data corresponding to the correlation value which is greater than or equal to the preset threshold value; determining curvature correlation values corresponding to the initial time points according to the curvature values corresponding to the time sequences;

and the evaluation module is used for obtaining the evaluation content of the hospital operation stability according to the curvature related value corresponding to each initial time point in the current time period and the curvature related value corresponding to each initial time point in the previous time period of the current time period.

According to a third aspect, an embodiment provides a computer readable storage medium having a program stored thereon, the program being executable by a processor to implement the method according to any of the first aspect above.

According to the method, the device and the computer-readable storage medium for evaluating the hospital operation status in the embodiment, the initial time points are obtained in the current time period by obtaining various hospital operation index data related in the hospital operation process, a graph is constructed for each initial time point, each hospital operation index data in the graph is a node, the correlation between every two hospital operation index data is determined, if the correlation is large, the correlation between the two hospital operation index data is large, a connecting line is constructed between two nodes with relatively large correlation, and the curvature value of each connecting line in the graph is calculated. The curvature related value can be obtained according to each curvature value, indexes obtained by the combined action of various hospital operation data in the current initial time point are represented, and the evaluation content of the hospital operation stability can be obtained according to the curvature related values of the current time period and the last time period. The graph structure is established based on data, the stability of hospital operation is evaluated by using the curvature value, the interaction between directly related hospital operation index factors is considered, the influence of indirectly related hospital operation index factors in the hospital operation system on the system is also considered, the complex nonlinear characteristics of the hospital operation system in the hospital operation index can be better extracted, and therefore the accuracy of evaluation content is high. For hospitals with different types and grades, only the operation index data of various hospitals of the hospitals need to be acquired, so that the electronic equipment can automatically output evaluation contents, and the method is wide in applicability and strong in universality. In addition, the evaluation content is not influenced by artificial subjective factors, the correlation among various hospital operation index data is fully considered, and the accuracy is high. Moreover, the hospital operation index data can be flexibly adjusted, so that the electronic equipment can quickly obtain evaluation content based on the adjusted hospital operation index data, and the expandability is strong.

Drawings

Fig. 1 is a schematic flowchart of an evaluation method for hospital operation status according to an embodiment of the present application;

fig. 2 is a schematic flow chart of another method for evaluating hospital operating conditions according to an embodiment of the present application;

fig. 3 is a schematic flowchart of another method for evaluating hospital operating conditions according to an embodiment of the present application;

fig. 4 is a schematic flowchart of another method for evaluating hospital operating conditions according to an embodiment of the present application;

FIG. 5 is a schematic diagram of a method for constructing a correlation between hospital operation index data according to the present application;

fig. 6 is a schematic diagram of a variation graph of curvature-related values provided in the present application;

fig. 7 is a schematic structural diagram of an evaluation apparatus for hospital operation status according to an embodiment of the present application.

Detailed Description

The present application will be described in further detail below with reference to the accompanying drawings by way of specific embodiments. Wherein like elements in different embodiments are numbered with like associated elements. In the following description, numerous details are set forth in order to provide a better understanding of the present application. However, those skilled in the art will readily recognize that some of the features may be omitted or replaced with other elements, materials, methods in different instances. In some instances, certain operations related to the present application have not been shown or described in detail in order to avoid obscuring the core of the present application from excessive description, and it is not necessary for those skilled in the art to describe these operations in detail, so that they may be fully understood from the description in the specification and the general knowledge in the art.

Furthermore, the features, operations, or characteristics described in the specification may be combined in any suitable manner to form various embodiments. Also, the various steps or actions in the method descriptions may be transposed or transposed in order, as will be apparent to one of ordinary skill in the art. Thus, the various sequences in the specification and drawings are for the purpose of describing certain embodiments only and are not intended to imply a required sequence unless otherwise indicated where such sequence must be followed.

The numbering of the components as such, e.g., "first", "second", etc., is used herein only to distinguish the objects as described, and does not have any sequential or technical meaning. The term "connected" and "coupled" when used in this application, unless otherwise indicated, includes both direct and indirect connections (couplings).

In the embodiment of the application, multiple hospital operation index data related in the hospital operation process are obtained, initial time points are obtained in the current time period, a graph is constructed for each initial time point, each hospital operation index data in the graph is a node, the correlation between every two hospital operation index data is determined, if the correlation is large, the correlation between the two hospital operation index data is large, a connecting line is constructed between the two nodes with the relatively large correlation, and the curvature value of each connecting line in the graph is calculated. The method has the advantages that the curvature related value can be obtained according to each curvature value, indexes obtained by combined action of multiple hospital operation data in the current initial time point are represented, the evaluation content of hospital operation stability can be obtained according to the curvature related values of the current time period and the last time period, for different hospitals, only the multiple hospital operation index data of the hospital need to be obtained, the applicability is wide, in addition, the evaluation content is not affected by artificial subjective factors, the correlation among the multiple hospital operation index data is fully considered, and the accuracy is high.

The technical means of the present application will be described in detail with reference to specific examples.

The first embodiment is as follows:

referring to fig. 1, fig. 1 is a schematic flowchart illustrating a flow of an evaluation method for hospital operation status according to an embodiment of the present application, where the embodiment is executed by an electronic device, and the electronic device may be a server, a computer, a mobile phone, a tablet device, and the like, which is not limited in the present application. The method of the embodiment comprises the following steps:

s101: and acquiring various hospital operation index data in the current time period.

The current time period includes K time points, and K is an integer greater than 1.

The current time period can be a preset time period and can be set according to the condition of a hospital. The time period may be 1 month, 3 months, 6 months, or a year, and the like, and this application is not limited thereto.

The K time points may be set according to hospital operation index data, and for example, assuming that the time period is 1 month (30 days in total), hospital operation index data of each day of the current 30 days may be acquired by taking each day as one time point.

The hospital operation index data is evaluation index data affecting hospital operation conditions. The hospital operational index data may include, but is not limited to, the following index data: outpatient emergency number increase rate, inpatient number increase rate, outpatient emergency number, outpatient number, inpatient key disease proportion, number of surgical cases, minimally invasive surgery proportion, interventional surgery proportion, expert number proportion, emergency critical patient rescue success rate, inpatient rescue success rate, service volume, drug proportion, patient satisfaction, patient complaint number, average examination report length, outpatient number average cost, inpatient number average cost, average inpatient day, daily outpatient number, preoperative average inpatient day, cured patient average inpatient day, bed position usage rate, unit fixed asset service volume, unit human cost service volume, large equipment (project) usage rate, unit dedicated equipment service volume, inpatient and outpatient diagnosis coincidence rate, three-day inpatient confirmation rate, pre-and post-operative coincidence diagnosis rate, inpatient cure success rate, inpatient infection occurrence rate, neonatal mortality rate, patient treatment success rate, unit fixed asset service volume, unit labor cost service volume, unit dedicated equipment service volume, inpatient diagnosis coincidence rate, three-day confirmation rate, post-operative coincidence diagnosis success rate, post-operative coincidence rate, and post-operative survival rate, The hospital mortality, the medical insurance rejection rate, the operation success rate, the proportion of new medical income to total income, the number of new projects to be developed, the scientific research achievements and the number of published papers, the personnel loss rate, the number of people on duty, the bed nurse ratio, the medical personnel ratio and the like.

Optionally, the acquired multiple kinds of hospital operation index data may be multiple kinds of hospital operation index data of one hospital, and the acquired operation index data is processed to obtain evaluation content of hospital operation stability; the acquired multiple hospital operation index data may also be multiple hospital operation index data of one department of the hospital, and the obtained data is processed to obtain evaluation content of operation stability of the department.

Optionally, multiple types of hospital operation index data may be acquired in a predetermined time period, or multiple types of hospital operation index data may be acquired in a current data processing time period. For example, various hospital operational index data may be acquired once a month.

Optionally, the hospital operation index data may be acquired by one or more hospital informatization systems connected with the electronic device. The hospital informatization system may include, but is not limited to, one or more of the following systems: hospital Information Systems (HIS), human resource Management Systems, financial Management Systems, supply chain Management Systems, scientific research Management Systems, equipment Management Systems, medical record Systems, electronic medical record Systems, surgical anesthesia Systems, Laboratory Information Management Systems (LIS), image Archiving and Communication Systems (PACS), and the like.

S102: starting from the 1 st time point of the K time points and ending to the K-s +1 th time point of the K time points, each time point is respectively used as an initial time point to determine a time sequence containing s continuous time points from the K time points.

Wherein K and s are both positive integers, and s is less than or equal to K.

For each initial time point, it is obtained and s time points subsequent thereto are taken as a time series. Since the time point after the K-s +1 th time point of the K time points is taken as the initial time point, the time sequence cannot acquire s consecutive time points, and the length of the time sequence is different during the subsequent processing, so that the acquisition of the initial time point is finished by the K-s +1 th time point.

For example, assuming that the current time period is 1 month (31 days), K is 31 and s is 7, each day is an initial time point for 31 days of data, starting from day 1 and ending until day 25. For example, day 1 corresponds to the time series of day 1 to day 7.

S103: and for each initial time point, determining a correlation value between every two hospital operation index data according to two time sequences respectively corresponding to every two hospital operation index data.

Different hospital operation index data may have a certain correlation, for example, a certain correlation exists between the emergency rescue success rate of the critical patient and the hospital rescue success rate; the average hospital stay day, the average number of people discharged from the hospital day and the usage rate of the bed have a certain correlation, and the above examples do not cover all hospital operation index data with a certain correlation, but illustrate a certain correlation that may exist between the hospital operation index data, and do not limit the present application.

The time series to which the hospital operation index data corresponds includes the hospital operation index data at each time point in the time series. And for each initial time point, determining the time sequence corresponding to the initial time point and respectively corresponding to each two kinds of hospital operation index data, and determining the correlation value between each two kinds of hospital operation index data corresponding to the time sequence. Wherein the correlation value is calculated for each two of the plurality of hospital operation index data.

The correlation value is used for representing the correlation between the time sequences corresponding to the two hospital operation index data.

Alternatively, the correlation value may be an absolute value of the pearson correlation coefficient.

S104: and determining the curvature value of a connecting line between two hospital operation index data corresponding to the correlation value larger than or equal to the preset threshold value.

The correlation value between every two kinds of hospital operation index data is compared with a preset threshold value, whether the correlation value between every two kinds of hospital operation index data is larger than or equal to the preset threshold value or not is judged for every two kinds of hospital operation index data, if yes, the curvature value of a connecting line between every two kinds of hospital operation index data is determined, and whether the correlation value between every two kinds of hospital operation index data in the next pair is larger than or equal to the preset threshold value or not is continuously judged. If not, whether the correlation between the next pair of the two hospital operation index data is larger than or equal to a preset threshold value or not is continuously judged. Until each two of the plurality of hospital operation index data are processed.

For each initial time point, a graph can be established, each hospital operation index is represented by a node in the graph, and when the correlation value between two hospital operation index data is greater than or equal to a preset threshold value, a connecting line is established between two nodes corresponding to the two hospital operation index data. Therefore, the relevance among the existing hospital operation index data is abstracted into a graph, and the direct and indirect relevance among the various hospital operation index data is abstracted into the curvature value of the connecting line.

The preset threshold is preset, and the preset threshold is a value greater than 0 and less than 1, for example, the preset threshold may be 0.5, 0.7, or 0.8. The preset threshold value can be set according to the needs of the service scene.

S105: and determining the curvature related value corresponding to each initial time point according to the curvature value corresponding to each time sequence.

For each time series, one or more curvature values may be obtained according to the step S104, and then a curvature related value of an initial time point corresponding to the time series, that is, a curvature related value corresponding to a starting time point of the time series, is determined according to the one or more curvature values obtained corresponding to the time series. Thereby, curvature related values corresponding to the initial time points can be obtained.

S106: and obtaining the evaluation content of the hospital operation stability according to the curvature related value corresponding to each initial time point in the current time period and the curvature related value corresponding to each initial time point in the previous time period of the current time period.

Wherein, the time length of the last time period of the current time period is the same as the time length of the current time period.

The curvature related value corresponding to each initial time point of the previous time period of the current time period may be obtained in a manner similar to the above-described manner for obtaining the curvature related value corresponding to each initial time point of the current time period.

The evaluation content of the operation stability of the hospital is used for indicating the stability of the operation condition of the hospital. The hospital operation stability can reflect whether the current hospital operation has risks.

The form of the evaluation content may be a picture, a character, a score, or the like, and the form of the evaluation content is not limited in the present application.

In this embodiment, multiple types of hospital operation index data related to a hospital operation process are acquired, initial time points are acquired in a current time period, a graph is constructed for each initial time point, each type of hospital operation index data in the graph is a node, correlation between every two types of hospital operation index data is determined, if the correlation is large, the correlation between the two types of hospital operation index data is large, a connecting line is constructed between the two nodes with relatively large correlation, and a curvature value of each connecting line in the graph is calculated. The curvature related value can be obtained according to each curvature value, indexes obtained by the combined action of various hospital operation data in the current initial time point are represented, and the evaluation content of the hospital operation stability can be obtained according to the curvature related values of the current time period and the last time period. The graph structure is established based on data, the stability of hospital operation is evaluated by using the curvature value, the interaction between directly related hospital operation index factors is considered, the influence of indirectly related hospital operation index factors in the hospital operation system on the system is also considered, the complex nonlinear characteristics of the hospital operation system in the hospital operation index can be better extracted, and therefore the accuracy of evaluation content is high. For hospitals with different types and grades, only the operation index data of various hospitals of the hospitals need to be acquired, so that the electronic equipment can automatically output evaluation contents, and the method is wide in applicability and strong in universality. In addition, the evaluation content is not influenced by artificial subjective factors, the correlation among various hospital operation index data is fully considered, and the accuracy is high. Moreover, the hospital operation index data can be flexibly adjusted, so that the electronic equipment can quickly obtain evaluation content based on the adjusted hospital operation index data, and the expandability is strong.

On the basis of the above embodiment, further, in S104, it may be respectively determined whether the correlation value corresponding to each two types of hospital operation index data is greater than or equal to a preset threshold value. And under the condition that the correlation value corresponding to the two hospital operation index data is greater than or equal to the preset threshold, obtaining the curvature value of the connecting line between the two hospital operation index data according to the correlation value which is greater than or equal to the preset threshold and corresponds to the two hospital operation index data respectively. The embodiment shown in FIG. 2 will be described in detail below.

Referring to fig. 2, fig. 2 is a schematic flow chart of another method for evaluating hospital operating conditions according to an embodiment of the present application, where in this embodiment, based on the embodiment shown in fig. 1, S104 may be further implemented by the following steps:

s1041: combining the multiple hospital operation index data pairwise, and traversing to obtain a combination with the corresponding correlation value being greater than or equal to a preset threshold value from the first combination to the last combination.

Combining the multiple kinds of hospital operation index data in pairs, starting from the first combination, judging whether the correlation value corresponding to the two kinds of hospital operation index data in the current combination is larger than or equal to a preset threshold value, updating the current combination to be the next combination, and returning to execute the judgment of whether the correlation value corresponding to the two kinds of hospital operation index data in the current combination is larger than or equal to the preset threshold value or not until all combinations are judged to be finished. Thus, all combinations with corresponding correlation values greater than or equal to the preset threshold are obtained.

S1042: and obtaining a curvature value of a connecting line between the two hospital operation index data according to the correlation value which is respectively corresponding to the two hospital operation index data and is larger than or equal to the preset threshold value.

The correlation value greater than or equal to the preset threshold value corresponding to each of the two types of hospital operation index data means that the correlation value greater than or equal to the preset threshold value is between the multiple types of hospital operation index data and the two types of hospital operation index data, which is equivalent to the correlation value corresponding to all connecting lines of two nodes represented by the two types of hospital operation index data in a graph corresponding to the established initial time point.

Illustratively, assume that the various hospital operational index data are T₁,T₂,T₃,T₄The preset threshold is 0.7. Using hospital operation index data T₁And T₂For the purpose of illustration, assume T₁Respectively with T₂And T₃The correlation value between is greater than 0.7, T₂Respectively with T₁And T₄The correlation value between the two is greater than 0.7, then according to T₁And T₂Correlation value between, T₁And T₃A correlation value between, and T₂And T₄The correlation value between the two, determining T₁And T₂The curvature value of the connecting line between.

Optionally, a curvature value of a connection line between two types of hospital operation index data corresponding to a correlation value greater than a preset threshold may be obtained according to the following formula (1):

wherein FR (E (n, m)) is a curvature value of a connecting line between the nth hospital operation index data and the mth hospital operation index data, R_mnIs the m-th hospital operation index data and the n-th hospital operation index data corresponding to an initial time pointCorrelation value between yard operational index data, R_nkIs the correlation value between the nth hospital operation index data and the kth hospital operation index data corresponding to the initial time point, and R_nkGreater than or equal to a predetermined threshold, R_imIs the correlation value between the m-th hospital operation index data and the i-th hospital operation index data corresponding to the initial time point, and R_imGreater than or equal to a preset threshold.

In this embodiment, by determining whether the correlation value corresponding to each two types of hospital operation index data is greater than or equal to the preset threshold, and under the condition that the correlation value corresponding to the two types of hospital operation index data is greater than or equal to the preset threshold, the curvature value of the connecting line between the two types of hospital operation index data is obtained according to the correlation values respectively corresponding to the two types of hospital operation index data and greater than or equal to the preset threshold, so that the determined curvature value of the connecting line between the two types of hospital operation index data considers the correlation between the two types of hospital operation index data and also fully considers the correlation between the two types of hospital operation index data and other types of hospital operation index data, thereby considering the interaction between directly related hospital operation index factors and considering the influence of indirectly related hospital operation index factors in the hospital operation system on the system, the complex nonlinear characteristics of the hospital operation system in the hospital operation indexes can be better extracted, so that the evaluation content is high in accuracy.

Based on the above embodiment, further, in S105, there may be multiple implementation manners of obtaining the curvature related value corresponding to each initial time point according to the curvature value corresponding to each time series.

In a possible implementation manner, an average value of curvature values corresponding to each time series may be obtained, so as to obtain a curvature related value corresponding to each initial time point.

And for each initial time point, taking the average value of all curvature values calculated by the initial time point to obtain the curvature related value corresponding to the initial time point. Curvature related values corresponding to all initial time points can be obtained.

In the implementation mode, the curvature related values corresponding to the initial time points are obtained by obtaining the average values of the curvature values corresponding to the time sequences, so that the subsequent calculation amount is small, the processing resources are saved, the integral characteristics of the graph constructed by the initial time points are reflected by the curvature related values by taking the average values, and the accuracy of the evaluation content for the whole hospital operation system is higher.

In another possible implementation manner, the maximum value, the minimum value, or the intermediate value of the curvature value corresponding to each time sequence may be obtained to obtain the curvature related value corresponding to each initial time point.

And for each initial time point, taking the maximum value, the minimum value or the middle value of all the curvature values obtained by calculating each time sequence obtained by the initial time point to obtain the curvature related value corresponding to the initial time point. Curvature related values corresponding to all initial time points can be obtained.

In the implementation mode, the curvature related value corresponding to each initial time point is obtained by obtaining the maximum value, the minimum value or the intermediate value of the curvature value corresponding to each time sequence, so that the subsequent calculation amount is small, the processing resource is saved, various possibilities are provided for the calculation mode of the curvature related value, and the user can select the curvature related value according to actual needs.

Based on the above embodiment, further, in S106, an index value may be obtained according to all curvature related values of the current time period, so as to compare the change rates of the index values of the current time period and the last time period of the current time period, thereby determining the evaluation content.

The index value of the current time period and the index value of the last time period of the current time period are obtained in the same mode.

In one possible implementation, the index value may be a maximum value, a minimum value, an average value, or the like of curvature related values corresponding to each initial time point in the time period.

In another possible implementation manner, the index value may be a sum of curvature related values corresponding to each initial time point in the time period. The embodiment shown in FIG. 3 will be described in detail below.

Referring to fig. 3, fig. 3 is a schematic flow chart of another method for evaluating hospital operating conditions according to an embodiment of the present application, where in this embodiment, based on the embodiment shown in fig. 1 or fig. 2, S106 can be further implemented by the following steps:

s1061: and determining the sum of the curvature related values corresponding to the initial time points in the current time period as an index value of the current time period.

One or more initial time points may be included in the current time period, and the sum of the curvature related values corresponding to each obtained initial time point is obtained, so as to obtain an index value of the current time period.

S1062: and acquiring the index value of the last time period of the current time period.

And the index value of the last time period of the current time period is the sum of the curvature related values corresponding to the initial time points of the last time period of the current time period.

The index value of the previous time period of the current time period may be obtained by calculation, or may be directly obtained after the calculation is completed. The calculation method of the index value of the previous time period of the current time period may be similar to that of S1061, and is not described herein again.

It is understood that S1061 and S1062 are performed without a sequential order. S1061 may be performed first, and then S1062 may be performed; or S1062 may be performed first, and then S1061 may be performed; s1061 and S1062 may also be executed simultaneously, which is not limited in this application.

S1063: and determining the change rate between the index value of the current time period and the index value of the last time period of the current time period.

And acquiring the difference between the index value of the last time period of the current time period and the index value of the current time period. And obtaining the absolute value of the ratio of the difference value to the index value of the last time period of the current time period to obtain the change rate.

S1064: and obtaining the evaluation content of the hospital operation stability according to the change rate and a preset fluctuation threshold value.

The preset fluctuation threshold value is preset and can be set according to the actual condition of a hospital, and the preset fluctuation threshold value is larger than 0. The preset fluctuation threshold may be set to one or more.

If the preset fluctuation threshold is one, the preset fluctuation threshold divides the numerical range into two interval ranges. If the change rate is greater than the preset fluctuation threshold value, the fact that the current hospital operation has a large risk can be obtained. If the change rate is less than or equal to the preset fluctuation threshold value, the evaluation content of the current operation state of the hospital can be obtained.

And if the number of the preset fluctuation threshold values is multiple, comparing the size relationship between the change rate and the preset fluctuation threshold values to obtain the evaluation content of the operation stability of the hospital.

The preset fluctuation threshold value divides the numerical range into a plurality of interval ranges, each interval range corresponds to one evaluation content, and if the interval range to which the change rate belongs is determined, the evaluation content is the evaluation content corresponding to the interval range.

Taking two preset fluctuation threshold values of 0.1 and 0.5 as examples for explanation, if the change rate is greater than 0.5, outputting the evaluation content as that the current hospital operation has a greater risk; if the change rate is less than or equal to 0.5 and greater than 0.1, outputting evaluation content to indicate that certain risk exists in current hospital operation; and if the change rate is less than or equal to 0.1, outputting the evaluation content as that the current hospital operation condition is stable.

According to the method and the device, the index value of the time period is obtained by obtaining the sum of the curvature related values corresponding to the initial time points in the time period, the index value is simple in processing mode and high in processing speed, processing resources are saved, and the processing speed is improved, so that the change rate between the index value of the current time period and the index value of the last time period of the current time period is compared, the evaluation content of the operation stability of the hospital is obtained according to the size relation between the change rate and the preset fluctuation threshold, and the method and the device are wide in application range and high in accuracy.

Referring to fig. 4, fig. 4 is a schematic flow chart of another method for evaluating hospital operating conditions according to an embodiment of the present application, and in this embodiment, based on the embodiments shown in fig. 1 to fig. 3, further, the method provided in this embodiment further includes S107, S108, and/or S109:

s107: and displaying a graph corresponding to the initial time point.

The graph (graph) corresponding to the initial time point comprises nodes and partial or all connecting lines among the nodes, the nodes are used for representing hospital operation index data, and the connecting lines are used for representing that correlation values among the hospital operation index data represented by the nodes at two ends of the connecting lines are larger than or equal to a preset threshold value.

Fig. 5 is a schematic diagram illustrating a form of a diagram corresponding to an initial time point, and fig. 5 is a schematic diagram constructed according to a relationship between hospital operation index data provided by the present application. Each node in fig. 5 is used to represent a kind of hospital operation index data, and the connecting line is used to represent that the correlation value between the hospital operation index data represented by the nodes at two ends of the connecting line is greater than or equal to the preset threshold value.

Namely, the graph established for each initial time point can be displayed, so that the relation among different hospital operation indexes can be more intuitively understood.

Optionally, in a case that the evaluation content indicates that the current hospital operation risk is large, outputting early warning information, where the early warning information may include but is not limited to: initial time point corresponds to the graph.

S108: a graph of change in curvature-related value is displayed.

The curvature-related value change map includes curvature-related values corresponding to initial time points of a current time period, or the curvature-related value change map includes curvature-related values corresponding to initial time points of the current time period and a previous time period of the current time period.

Optionally, the curvature related value corresponding to each initial time point in the multiple time periods may be acquired, so that the variation graph of the curvature related value may display the curvature related value corresponding to each initial time point in the multiple time periods. Namely, the change map of the curvature-related value includes a set time-series curvature-related value.

Fig. 6 is a schematic diagram of a variation graph of curvature-related values provided in the present application, where an abscissa in fig. 6 represents time, and an ordinate represents a numerical value of the curvature-related value. As can be seen from fig. 6, in around 10/18 th of 2007, if the curvature-related value fluctuates greatly, the corresponding evaluation content may output a large risk to the current operation.

S109: and displaying the evaluation content of the operation stability of the hospital.

The evaluation content may be in the form of characters or diagrams.

This embodiment, through showing various data, can more directly perceived effectual understanding hospital operation condition and the incidence relation between the different hospital operation index data to the stability of the current operation of hospital is known to more directly perceivedly.

On the basis of the above embodiment, further, S101 may be implemented by:

step 1011: and acquiring various original hospital operation index data in the current time period.

Optionally, the original hospital operation index data may be acquired by one or more hospital informatization systems connected to the electronic device. The hospital information system may include, but is not limited to, the following systems: hospital Information Systems (HIS), human resource Management Systems, financial Management Systems, supply chain Management Systems, scientific research Management Systems, equipment Management Systems, medical record Systems, electronic medical record Systems, surgical anesthesia Systems, Laboratory Information Management Systems (LIS), image Archiving and Communication Systems (PACS), and the like.

Step 1012: preprocessing various original hospital operation index data to obtain various hospital operation index data in the current time period.

Among them, the pretreatment may include, but is not limited to: at least one of a data cleansing process and a data deduplication process.

Alternatively, each data item in the preprocessed hospital operation index data may be stored in the database as a time series in the form of a database table.

Optionally, in S106, the hospital operation index data that needs to be used for the curvature related value corresponding to each initial time point in the last time period of the current time period may be obtained by preprocessing multiple kinds of original hospital operation index data in the last time period of the current time period.

According to the embodiment, the original hospital operation index data can be preprocessed, and the preprocessed various hospital operation index data are used for subsequent processing to obtain the evaluation content, so that the hospital operation index data are more accurate, and the evaluation content obtained according to the hospital operation index data is more accurate.

The method of the above embodiment is described below by specific examples.

For example, assume that there are N hospital operation indexes for evaluating hospital operation status, which are respectively marked as X₁,X₂,…,X_NWherein X is₁Indicates the first hospital operating index, X₂Represents a second hospital operating index, … …, X_NAnd (4) representing the Nth hospital operation index.

Each hospital operation index data corresponds to a single time sequence in the current time period and is recorded as T₁,T₂,…,T_NWherein, T₁Indicating a first hospital operational index data, T, in the current time period₂Indicating a second hospital operational index data, … …, T, during the current time period_NAnd representing the operation index data of the No. S hospital in the current time period.

Assuming that the time unit of the time series is day and the length of each time period is K, the operation index data T of the nth kind of hospital_nCan be expressed by the following formula (2):

T_n＝(t_n(1),t_n(2),…,t_n(K) equation (2)

Wherein the kth value t of the time series_n(k) Means for indicating the operation of the nth hospital at the kth time pointAnd marking the data.

Starting from the 1 st time point of the K time points and ending to the K-s +1 th time point of the K time points, taking each time point l as an initial time point, and establishing a graph for each initial time point l, wherein each hospital operation index X is_nOr operation index data T of each hospital_nIs a node in the graph, it can be understood that the node in the graph is understood as an index or the data corresponding to the index has no essential difference.

In each time period, a preset time sequence length s (hereinafter, s is assumed to be 7, that is, the time sequence length is one week) is used, and from an initial time point l, the data corresponding to the time sequence of the nth hospital operation index is (t)_n(l),t_n(l+1),…t_n(l + s-1)), the data corresponding to the time series of the operation index of the mth kind of hospital is (t)_m(l),t_m(l+1),…t_m(l + s-1)), determining a correlation value R between the two time-series data of length s at the initial time point l_nm(l) Wherein l is 1,2, …, K-s + 1.

The preset threshold value of the correlation value is denoted by D, where D is assumed to be 0.7. When R_nm(l) When | ≧ D, two nodes X in the graph at the initial time point l_nAnd X_mBetween them, a connecting line is established with R_nm(l) As two nodes X in the graph at that point in time_nAnd X_mA connection weight between; when R_nm(l)|<D, corresponding to two nodes X_nAnd X_mThere is no connection between them.

Thus, K-s +1 graphs, denoted G (l), are created in relation to the initial point in time l, and stored in the database.

And calculating the curvature value of each connecting line for the graph G (l) corresponding to each initial time point l. And calculating the average value of the curvature values of all the connecting lines in the current graph as the curvature related value of the initial time point. Thereby obtaining a time series consisting of curvature related values at each initial time point. The time series is stored in a database.

Assuming that the time period K is 28, the preset fluctuation threshold θ is 15%. The rate of change of the sum of curvature related values over the current time period K (i.e. 28 days) compared to the sum of curvature related values over the previous time period is more than 15%, the current hospital experience is considered to be at a greater risk, otherwise the current hospital operating conditions are considered to be more stable.

Example two:

referring to fig. 7, fig. 7 is a schematic structural diagram of an evaluation apparatus for hospital operating conditions according to an embodiment of the present application, where the apparatus according to the embodiment includes:

the data acquisition module 701 is used for acquiring various hospital operation index data in a current time period, wherein the current time period comprises K time points, and K is an integer greater than 1;

a graph generating module 702, configured to determine, from a 1 st time point of the K time points to a K-s +1 th time point of the K time points, a time sequence including s consecutive time points from the K time points by taking each time point as an initial time point, where K and s are positive integers, and s is less than or equal to K; for each time sequence, determining a correlation value between each two hospital operation index data according to each two hospital operation index data corresponding to the time sequence;

a curvature calculating module 703, configured to determine a curvature value of a connection line between two hospital operation index data corresponding to a correlation value greater than or equal to a preset threshold; determining curvature correlation values corresponding to the initial time points according to the curvature values corresponding to the time sequences;

the evaluation module 704 is configured to obtain an evaluation content of the hospital operation stability according to the curvature related value corresponding to each initial time point in the current time period and the curvature related value corresponding to each initial time point in the previous time period of the current time period.

Optionally, the curvature calculating module 703 is specifically configured to:

judging whether the correlation value corresponding to each two hospital operation index data is greater than or equal to a preset threshold value or not;

and under the condition that the correlation value corresponding to the two hospital operation index data is greater than or equal to the preset threshold, obtaining the curvature value of the connecting line between the two hospital operation index data according to the correlation value which is greater than or equal to the preset threshold and corresponds to the two hospital operation index data respectively.

Optionally, the curvature calculating module 703 is specifically configured to:

obtaining a curvature value of a connecting line between two hospital operation index data corresponding to a correlation value larger than or equal to a preset threshold value according to the following formula:

wherein FR (E (n, m)) is a curvature value of a connecting line between the nth hospital operation index data and the mth hospital operation index data, R_mnIs a correlation value, R, between the mth kind of hospital operation index data and the nth kind of hospital operation index data corresponding to an initial time point_nkIs the correlation value between the nth hospital operation index data and the kth hospital operation index data corresponding to the initial time point, and R_nkGreater than or equal to a predetermined threshold, R_imIs the correlation value between the m-th hospital operation index data and the i-th hospital operation index data corresponding to the initial time point, and R_imGreater than or equal to a preset threshold.

Optionally, the curvature calculating module 703 is specifically configured to:

and obtaining the average value of the curvature values corresponding to each time sequence to obtain the curvature related value corresponding to each initial time point.

Optionally, the evaluation module 704 is specifically configured to:

determining the sum of curvature related values corresponding to each initial time point in the current time period as an index value of the current time period;

acquiring an index value of a previous time period of the current time period, wherein the index value of the previous time period of the current time period is the sum of curvature related values corresponding to each initial time point of the previous time period of the current time period;

determining a change rate between the index value of the current time period and the index value of the last time period of the current time period;

and obtaining the evaluation content of the hospital operation stability according to the change rate and a preset fluctuation threshold value.

Optionally, there are a plurality of preset fluctuation thresholds, and the evaluation module 704 is specifically configured to:

and comparing the size relationship between the change rate and a plurality of preset fluctuation threshold values to obtain the evaluation content of the operation stability of the hospital.

Optionally, the apparatus further comprises:

the display module is used for displaying a graph corresponding to the initial time point, the graph corresponding to the initial time point comprises nodes and partial or all connecting lines among the nodes, the nodes are used for representing hospital operation index data, and the connecting lines are used for representing that the correlation value among the hospital operation index data represented by the nodes at two ends of the connecting lines is larger than or equal to a preset threshold value;

optionally, the display module is further configured to display a variation graph of the curvature-related value, where the variation graph of the curvature-related value includes curvature-related values corresponding to initial time points of a current time period, or the variation graph of the curvature-related value includes curvature-related values corresponding to initial time points of the current time period and a previous time period of the current time period;

optionally, the display module is further configured to display evaluation content of hospital operation stability.

Optionally, the data acquisition module 701 is specifically configured to:

acquiring various original hospital operation index data in the current time period;

preprocessing various original hospital operation index data to obtain various hospital operation index data in the current time period, wherein the preprocessing comprises the following steps: at least one of a data cleansing process and a data deduplication process.

The principle and the beneficial effects of the apparatus provided by the embodiment are similar to those of the method provided by the first embodiment, and are not described again here.

Example three:

the present embodiment provides a computer-readable storage medium having a program stored thereon, the program being executable by a processor to implement the method according to any one of the first embodiment.

Those skilled in the art will appreciate that all or part of the functions of the various methods in the above embodiments may be implemented by hardware, or may be implemented by computer programs. When all or part of the functions of the above embodiments are implemented by a computer program, the program may be stored in a computer-readable storage medium, and the storage medium may include: a read only memory, a random access memory, a magnetic disk, an optical disk, a hard disk, etc., and the program is executed by a computer to realize the above functions. For example, the program may be stored in a memory of the device, and when the program in the memory is executed by the processor, all or part of the functions described above may be implemented. In addition, when all or part of the functions in the above embodiments are implemented by a computer program, the program may be stored in a storage medium such as a server, another computer, a magnetic disk, an optical disk, a flash disk, or a removable hard disk, and may be downloaded or copied to a memory of a local device, or may be version-updated in a system of the local device, and when the program in the memory is executed by a processor, all or part of the functions in the above embodiments may be implemented.

The present application has been described with reference to specific examples, which are provided only to aid understanding of the present application and are not intended to limit the present application. For a person skilled in the art to which the application pertains, several simple deductions, modifications or substitutions may be made according to the idea of the application.

Claims (10)

1. A method for evaluating hospital operation conditions is characterized by comprising the following steps:

acquiring various hospital operation index data in a current time period, wherein the current time period comprises K time points, and K is an integer greater than 1;

determining a time sequence comprising s continuous time points from the K time points by taking each time point as an initial time point from the 1 st time point of the K time points to the K-s +1 th time point of the K time points, wherein K and s are positive integers, and s is less than or equal to K;

for each initial time point, determining a correlation value between each two kinds of hospital operation index data according to two time sequences respectively corresponding to each two kinds of hospital operation index data;

determining a curvature value of a connecting line between two hospital operation index data corresponding to a correlation value larger than or equal to a preset threshold value;

determining curvature correlation values corresponding to the initial time points according to the curvature values corresponding to the time sequences;

and obtaining the evaluation content of the hospital operation stability according to the curvature related value corresponding to each initial time point in the current time period and the curvature related value corresponding to each initial time point in the last time period of the current time period.

2. The method of claim 1, wherein determining a curvature value of a connecting line between two hospital operation index data corresponding to a correlation value greater than or equal to a preset threshold comprises:

judging whether the correlation value corresponding to each two hospital operation index data is greater than or equal to a preset threshold value or not;

and under the condition that the correlation value corresponding to the two hospital operation index data is greater than or equal to a preset threshold value, obtaining the curvature value of the connecting line between the two hospital operation index data according to the correlation value which is greater than or equal to the preset threshold value and corresponds to the two hospital operation index data respectively.

3. The method of claim 2, wherein obtaining the curvature value of the connection line between the two hospital operation index data according to the correlation value greater than or equal to the preset threshold value respectively corresponding to the two hospital operation index data comprises:

obtaining a curvature value of a connecting line between two hospital operation index data corresponding to a correlation value larger than or equal to a preset threshold value according to the following formula:

wherein FR (E (n, m)) is a curvature value of a connecting line between the nth hospital operation index data and the mth hospital operation index data, R_mnIs a correlation value, R, between the mth kind of hospital operation index data and the nth kind of hospital operation index data corresponding to an initial time point_nkIs the correlation value between the nth hospital operation index data and the kth hospital operation index data corresponding to the initial time point, and R_nkGreater than or equal to a predetermined threshold, R_imIs the correlation value between the m-th hospital operation index data and the i-th hospital operation index data corresponding to the initial time point, and R_imGreater than or equal to a preset threshold.

4. The method of claim 1, wherein determining the curvature-related value corresponding to each initial time point according to the curvature value corresponding to each time series comprises:

and obtaining the average value of all curvature values corresponding to all time sequences at the initial time points to obtain curvature related values corresponding to all the initial time points.

5. The method according to any one of claims 1 to 4, wherein the obtaining of the evaluation content of the hospital operation stability according to the curvature related value corresponding to each initial time point in the current time period and the curvature related value corresponding to each initial time point in the last time period of the current time period comprises:

determining the sum of curvature related values corresponding to each initial time point in the current time period as an index value of the current time period;

acquiring an index value of a previous time period of the current time period, wherein the index value of the previous time period of the current time period is the sum of curvature related values corresponding to initial time points of the previous time period of the current time period;

determining a change rate between the index value of the current time period and the index value of the last time period of the current time period;

and obtaining the evaluation content of the hospital operation stability according to the change rate and a preset fluctuation threshold value.

6. The method according to claim 5, wherein there are a plurality of preset fluctuation threshold values, and the obtaining of the evaluation content of the hospital operation stability according to the change rate and the preset fluctuation threshold values comprises:

and comparing the size relationship between the change rate and a plurality of preset fluctuation threshold values to obtain the evaluation content of the operation stability of the hospital.

7. The method of any one of claims 1-4, further comprising:

displaying a graph corresponding to each initial time point, wherein the graph corresponding to each initial time point comprises nodes and partial or all connecting lines among the nodes, the nodes are used for representing the hospital operation index data, and the connecting lines are used for representing that the correlation value among the hospital operation index data represented by the nodes at two ends of the connecting lines is greater than or equal to a preset threshold value;

displaying a curvature related value change graph, wherein the curvature related value change graph comprises curvature related values corresponding to all initial time points of the current time period, or the curvature related value change graph comprises curvature related values corresponding to all initial time points of the current time period and the last time period of the current time period;

and displaying the evaluation content of the hospital operation stability.

8. The method of any one of claims 1-4, wherein said obtaining a plurality of hospital operational index data for a current time period comprises:

acquiring various original hospital operation index data in the current time period;

preprocessing the multiple original hospital operation index data to obtain multiple hospital operation index data in the current time period, wherein the preprocessing comprises the following steps: at least one of a data cleansing process and a data deduplication process.

9. An evaluation device for hospital operation conditions, comprising:

the system comprises a data acquisition module, a data processing module and a data processing module, wherein the data acquisition module is used for acquiring various hospital operation index data in a current time period, the current time period comprises K time points, and K is an integer greater than 1;

a graph generating module, configured to start from a 1 st time point of the K time points and end to a K-s +1 th time point of the K time points, and determine a time sequence including s consecutive time points from the K time points by taking each time point as an initial time point, where K and s are positive integers, and s is less than or equal to K; for each initial time point, determining a correlation value between each two kinds of hospital operation index data according to two time sequences respectively corresponding to each two kinds of hospital operation index data;

the curvature calculation module is used for determining a curvature value of a connecting line between two hospital operation index data corresponding to the correlation value which is greater than or equal to the preset threshold value; determining curvature correlation values corresponding to the initial time points according to the curvature values corresponding to the time sequences;

and the evaluation module is used for obtaining the evaluation content of the hospital operation stability according to the curvature related value corresponding to each initial time point in the current time period and the curvature related value corresponding to each initial time point in the previous time period of the current time period.

10. A computer-readable storage medium, characterized in that the medium has stored thereon a program which is executable by a processor to implement the method according to any one of claims 1-8.

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