CN114141381A - Clinical data analysis method and device based on diagnosis and treatment events - Google Patents
Clinical data analysis method and device based on diagnosis and treatment events Download PDFInfo
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Abstract
The invention discloses a clinical data analysis method and device based on diagnosis and treatment events. The method comprises the following steps: acquiring data of a user to be analyzed; screening data of a user to be analyzed based on preset event screening conditions to obtain event information corresponding to the preset event screening conditions, wherein the preset event screening conditions comprise behavior event screening conditions and result event screening conditions; and fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result. According to the technical scheme, the data of the user to be analyzed are screened to obtain the event information corresponding to the action event screening condition and the event information corresponding to the result event screening condition, so that the action events are distinguished and selected, and the result events are distinguished and selected; furthermore, by means of fusion of the behavior event information and the result event information, event cause and effect correlation analysis is achieved, and an analysis result has higher research value.
Description
Technical Field
The invention relates to the technical field of data processing, in particular to a clinical data analysis method and device based on diagnosis and treatment events.
Background
With the continuous improvement of the medical informatization degree, the medical information of the user such as medicine taking, inspection, course of illness and the like is recorded in the diagnosis and treatment information system, and a plurality of different clinical data tables are formed.
In the prior art, when research needs to be performed on user data, data in different clinical data tables needs to be summarized and analyzed, the same user data in different clinical data tables needs to be associated, and then analysis needs to be performed on a certain user data, or full-text retrieval analysis needs to be performed on all user data.
The full-text retrieval analysis is carried out on all user data, although the retrieval analysis can be carried out in batches, the analysis logic is simple, the data analysis of complex logic cannot be carried out, and the requirements of clinical data research analysis cannot be met by adopting the existing full-text retrieval analysis mode.
Disclosure of Invention
The invention provides a clinical data analysis method and device based on diagnosis and treatment events, electronic equipment and a storage medium, which realize causal association analysis of the events and enable an analysis result to have higher research value.
In a first aspect, an embodiment of the present invention provides a clinical data analysis method based on a diagnosis and treatment event, including:
acquiring data of a user to be analyzed;
screening the data of the user to be analyzed based on preset event screening conditions to obtain event information corresponding to the preset event screening conditions, wherein the preset event screening conditions comprise behavior event screening conditions and result event screening conditions;
and fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result corresponding to the data of the user to be analyzed.
In a second aspect, an embodiment of the present invention further provides a clinical data analysis device based on a diagnosis and treatment event, including:
the data acquisition module is used for acquiring data of a user to be analyzed;
the event information generating module is used for screening the data of the user to be analyzed based on preset event screening conditions to obtain event information corresponding to the preset event screening conditions, wherein the preset event screening conditions comprise behavior event screening conditions and result event screening conditions;
and the analysis result generation module is used for fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result corresponding to the data of the user to be analyzed.
In a third aspect, an embodiment of the present invention further provides an electronic device, where the electronic device includes:
one or more processors;
a storage device for storing one or more programs,
when the one or more programs are executed by the one or more processors, the one or more processors implement any of the clinical event-based clinical data analysis methods of the embodiments of the present invention.
In a fourth aspect, embodiments of the present invention further provide a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform any one of the clinical event-based clinical data analysis methods described in the embodiments of the present invention.
The method comprises the steps of acquiring data of a user to be analyzed; screening data of a user to be analyzed based on preset event screening conditions to obtain event information corresponding to the preset event screening conditions, wherein the preset event screening conditions comprise behavior event screening conditions and result event screening conditions; and fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result. According to the technical scheme, the data of the user to be analyzed are screened to obtain the event information corresponding to the action event screening condition and the event information corresponding to the result event screening condition, so that the action events are distinguished and selected, and the result events are distinguished and selected; furthermore, by means of fusion of event information corresponding to the action event and event information corresponding to the result event, event cause and effect correlation analysis is achieved, and an analysis result has higher research value.
Drawings
In order to more clearly illustrate the technical solutions of the exemplary embodiments of the present invention, a brief description is given below of the drawings used in describing the embodiments. It should be clear that the described figures are only views of some of the embodiments of the invention to be described, not all, and that for a person skilled in the art, other figures can be derived from these figures without inventive effort.
Fig. 1 is a schematic flowchart of a clinical event-based clinical data analysis method according to an embodiment of the present invention;
fig. 2 is a flowchart illustrating a clinical data analysis method based on a diagnosis and treatment event according to a second embodiment of the present invention;
fig. 3 is a flowchart illustrating a clinical data analysis method based on a diagnosis and treatment event according to a third embodiment of the present invention;
fig. 4 is a flowchart illustrating a clinical data analysis method based on a diagnosis and treatment event according to a fourth embodiment of the present invention;
fig. 5 is a schematic flowchart of a clinical data analysis method based on a diagnosis and treatment event according to a fifth embodiment of the present invention;
fig. 6 is a schematic structural diagram of a clinical data analysis apparatus according to a sixth embodiment of the present invention;
fig. 7 is a schematic structural diagram of an electronic device according to a seventh embodiment of the present invention.
Detailed Description
The present invention will be described in further detail with reference to the accompanying drawings and examples. It is to be understood that the specific embodiments described herein are merely illustrative of the invention and are not limiting of the invention.
It should be further noted that, for the convenience of description, only some but not all of the relevant aspects of the present invention are shown in the drawings. Before discussing exemplary embodiments in more detail, it should be noted that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although a flowchart may describe the operations (or steps) as a sequential process, many of the operations can be performed in parallel, concurrently or simultaneously. In addition, the order of the operations may be re-arranged. The process may be terminated when its operations are completed, but may have additional steps not included in the figure. The processes may correspond to methods, functions, procedures, subroutines, and the like.
Example one
Fig. 1 is a flowchart of a clinical data analysis method based on clinical events according to an embodiment of the present invention, where the embodiment is applicable to a case of performing automatic analysis on clinical data, and the method may be executed by a clinical data analysis apparatus based on clinical events according to an embodiment of the present invention, where the apparatus may be implemented by software and/or hardware, and the apparatus may be configured on an electronic computing device, for example, a terminal and/or a server. The method specifically comprises the following steps:
and S110, acquiring data of a user to be analyzed.
The data of the user to be analyzed may be clinical data of the user, and the clinical data of the user to be analyzed may be recorded in a plurality of different data tables, where the different data tables represent different categories. The data table categories may include, but are not limited to, a base information table, an action event table, and a result event table. For example, the basic information table may include user identifications and user basic information of all users; the behavior event table may include behavior records for all users and all times when positive events occur; the resulting events table may include the resulting records of all users, all times, and observing objective events. Of course, it may be recorded in one or more wide tables, each of which records more than two different categories of data.
Optionally, the data of the user to be analyzed is obtained based on a preset query condition. The preset query conditions may include, but are not limited to, user grouping conditions, a preset time range, and preset filtering conditions.
Illustratively, in a medical scenario, the positive event behavior may be a medication or treatment behavior and the objective event outcome may be an adverse reaction or an examination/check. May be data determining users to be analyzed based on user grouping, such as a group of cardiologists, a group of patients taking certain medications, etc.; or determining to acquire data of the user to be analyzed through a preset time range, for example, acquiring data of the user to be analyzed within a certain time period; it is also possible to determine the data of the user to be analyzed by preset screening conditions, which may include, but are not limited to, blood type, age, occupation, marital, and the like.
S120, screening the data of the user to be analyzed based on preset event screening conditions to obtain event information corresponding to the preset event screening conditions, wherein the preset event screening conditions comprise behavior event screening conditions and result event screening conditions.
The preset event screening condition refers to a preset event screening condition, and optionally, the preset event screening condition is set through a user operation interface. The preset event screening conditions may include, but are not limited to, behavioral event screening conditions and result event screening conditions, the behavioral event screening conditions may be screening for behaviors, and the result event screening conditions may be screening for results.
Specifically, the data of the user to be analyzed is subjected to behavior screening based on the behavior event screening conditions, and the screened behavior is defined as a behavior event, so that event information corresponding to the behavior event screening conditions is obtained; and performing result screening on the data of the user to be analyzed based on the result event screening conditions, and defining the screened result as a result event to obtain event information corresponding to the result event screening conditions.
In the embodiment of the invention, the data of the user to be analyzed is screened by the preset event screening condition, so that the event information corresponding to the action event screening condition and the event information corresponding to the result event screening condition are obtained, the action event is distinguished and selected, the result event is distinguished and selected, and the targeted analysis or research can be realized.
And S130, fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result corresponding to the data of the user to be analyzed.
And the analysis result is obtained by fusing event information corresponding to the action event screening condition and event information corresponding to the result event screening condition. The analysis result can show event information of one or more users and the incidence relation among events. The analysis result can be displayed by using a chart, so that the analysis result of the diagnosis and treatment data can be displayed more intuitively.
Specifically, the fusion of the event information refers to establishing the association between the event information. In some optional embodiments, an association relationship between event information corresponding to the behavior event screening condition and event information corresponding to the result event screening condition may be established; in some optional embodiments, the association between a plurality of event information corresponding to the action event screening condition may also be established, or the association between a plurality of event information corresponding to the result event screening condition may also be established; in some optional embodiments, it may also be to establish an association between event information corresponding to the current behavior and event information corresponding to the historical result. The embodiment of the present invention is not limited thereto.
The embodiment of the invention provides a clinical data analysis method based on diagnosis and treatment events, which is characterized in that event information corresponding to a behavior event screening condition and event information corresponding to a result event screening condition are obtained by screening data of a user to be analyzed, so that behavior events are distinguished and selected, and result events are distinguished and selected; furthermore, causal association analysis is realized through fusion of event information corresponding to the behavior event and event information corresponding to the result event.
Example two
Fig. 2 is a flow chart diagram of a clinical data analysis method based on a diagnosis and treatment event according to a second embodiment of the present invention, and based on the second embodiment, the method further refines "screening data of the user to be analyzed based on a preset event screening condition to obtain event information corresponding to the preset event screening condition". The specific implementation manner of the method can be seen in the detailed description of the technical scheme. The technical terms that are the same as or corresponding to the above embodiments are not repeated herein. As shown in fig. 2, the method of the embodiment of the present invention specifically includes the following steps:
and S210, acquiring data of a user to be analyzed.
S220, screening the behavior data based on the behavior event screening conditions to obtain behavior event information, wherein the behavior event information comprises a user identifier.
The behavior data may be behavior data of the user in the diagnosis and treatment process, and the behavior data may include medication behavior data or treatment behavior data of a plurality of users. The behavior event information is event information of behaviors meeting the behavior event screening condition, and in some optional embodiments, the behavior event information may be presented in a table form. The behavior event information may include, but is not limited to, a user identification and a behavior event. The user identification may be a number, a symbol or a combination of a number and a symbol. The action events are in one-to-one correspondence with the user identifications, that is, the action event information may include action events of one or more users. When the behavior event information comprises behavior events of a plurality of users, batch screening of the behaviors of the users can be realized, and the data analysis speed is improved.
On the basis of the above embodiment, the behavior event screening condition includes a behavior event type and/or behavior time ordering information.
The behavior event type refers to a specific type of a researched behavior, and by setting the behavior event type, the behavior event corresponding to the set behavior event type can be observed and analyzed in a targeted manner, so that the pertinence of an analysis result is improved. The time sequencing information refers to sequencing of the occurrence time of the behaviors, and the behaviors can be sequenced according to the occurrence time of the behaviors through the time sequencing information, so that the behaviors are distinguished.
For example, in a medical scenario, the behavioral event type may be a medication type of the user, such as using a drugs, B drugs, C drugs, and so on. In a medical scenario, the time-ordering information may specifically be an ordering of times of medication taken by the user, for example, a time of first medication, a time of second medication.
And S230, screening the result data based on the user identification in the behavior event information and the result event screening condition to obtain result event information.
The result data can be result data generated in the diagnosis and treatment process of the user, and the result data can comprise adverse reaction data or treatment result data of a plurality of users. The result event information is event information of a result satisfying the result event filtering condition, and the result event information may include, but is not limited to, a user identifier and a result event. In some alternative embodiments, the resulting event information may be presented in tabular form.
On the basis of the above-described embodiment, the result event screening condition may include a result event type and/or a result time range. Specifically, the result event type refers to a type corresponding to a result generated by a preset behavior, and by setting the result event type, the result event corresponding to the set result event type can be subjected to targeted observation and analysis, so that the pertinence of the analysis result is improved. The result time range can be a preset time range from the action starting time, and the results outside the preset time range can be removed, so that the obtained result event information is generated by the current action, and the correctness of the association relation between the action and the result is ensured. Optionally, the result time range includes, but is not limited to, a result time range generated by a preset action, or an intersection time range of a time range from the action occurrence time to a next different action occurrence time and a result time range generated by a preset action.
For example, in a medical scenario, the outcome event type may be a user's adverse reaction type, including but not limited to headache, diarrhea, and the like. The result time range may be a preset time range from the start of medication, and adverse reactions within the preset time range after medication are selected as result event information.
And S240, fusing the behavior event information and the result event information to obtain an analysis result corresponding to the data of the user to be analyzed.
The embodiment of the invention provides a clinical data analysis method based on diagnosis and treatment events, which is characterized in that the data of a user to be analyzed is screened to obtain behavior event information corresponding to behavior event screening conditions and result event information corresponding to result event screening conditions, so that behavior events are distinguished and result events are distinguished; furthermore, by means of fusion of the behavior event information and the result event information, causal association analysis is achieved, and an analysis result has higher research value.
EXAMPLE III
Fig. 3 is a flowchart illustrating a clinical data analysis method based on a diagnosis and treatment event according to a third embodiment of the present invention, where the third embodiment of the present invention may be combined with various alternatives in the foregoing embodiments. In the embodiment of the present invention, optionally, the behavior event screening condition further includes a time of occurrence of a history result event corresponding to the user identifier, and a time range of an intervention behavior based on the history result event; the result event screening condition also comprises a result event type and/or an intervention result time range generated by a preset intervention behavior; correspondingly, the fusing the behavior event information and the result event information to obtain an analysis result corresponding to the data of the user to be analyzed includes: and fusing the behavior event information and the result event information corresponding to the behavior time sequencing information to obtain an analysis result corresponding to the data of the user to be analyzed.
As shown in fig. 3, the method of the embodiment of the present invention specifically includes the following steps:
and S310, acquiring data of a user to be analyzed.
S320, screening the behavior data based on the behavior event screening conditions to obtain behavior event information.
In this embodiment, multiple screening of behavior data is included, a behavior event may include, but is not limited to, a first behavior event and an intervention behavior event, a behavior event screening condition corresponding to the first behavior data screening may include a behavior event type and/or behavior time ordering information, the first behavior may be understood as a first behavior occurring by a user, and different subsequent behaviors may be defined as intervention behaviors, which are interventions on a result generated by the first behavior.
Optionally, the action event filtering condition further includes a time range of intervention actions based on the historical result event, and the time range of occurrence time of the historical result event corresponding to the user identifier.
Wherein, the historical result event occurrence time may be the time of the result generated by the last action of the current action. The time range of the intervention action may be a time range from the time of occurrence of the historical result event. And accurately screening the intervention behavior events in a preset time range according to the occurrence time of the historical result events and the time range of the intervention behaviors based on the historical result events to obtain behavior event information.
S330, screening the result data based on the user identification in the behavior event information and the result event screening condition to obtain result event information.
And the result event screening condition also comprises a result event type and/or an intervention result time range generated by the preset intervention behavior. The intervention behavior can be understood as intervention behavior aiming at the result generated by the historical behavior. Intervention result events in a preset time range can be accurately screened out through the type of the result events generated by the preset intervention behaviors and/or the time range of the intervention result, and result event information is obtained. Optionally, the intervention result time range may include, but is not limited to, a result time range generated by the preset intervention action, or an intersection time range of a time range from the intervention action occurrence time to a next different action occurrence time and a result time range generated by the preset intervention action.
S340, the behavior event information and the result event information corresponding to the behavior time sequencing information are fused to obtain an analysis result corresponding to the data of the user to be analyzed.
The embodiment of the invention provides a clinical data analysis method based on diagnosis and treatment events, which is characterized in that a plurality of pieces of behavior event information and result event information are obtained by screening data of a user to be analyzed for a plurality of times of events, and the behavior event information and the result event information corresponding to a plurality of pieces of behavior time sequencing information are fused, so that correlation analysis among a plurality of events is realized, and the analysis by the user is facilitated.
Example four
Fig. 4 is a flowchart illustrating a clinical data analysis method based on a diagnosis and treatment event according to a fourth embodiment of the present invention, where the fourth embodiment of the present invention may be combined with various alternatives in the foregoing embodiments. In the embodiment of the present invention, optionally, the analysis result includes an analysis summary table and/or a mor-base chart.
And S410, acquiring data of a user to be analyzed.
S420, screening the behavior data based on the behavior event screening condition to obtain behavior event information, wherein the behavior event information comprises a user identifier.
S430, screening the result data based on the user identification in the behavior event information and the result event screening condition to obtain result event information.
And S440, fusing the behavior event information and the result event information to obtain an analysis summary table and/or a mor-base chart corresponding to the data of the user to be analyzed.
The analysis summary table may be a summary table of a plurality of user event information, and the analysis summary table may include, but is not limited to, user basic information, behavior event information, and result event information. The sang-based graph can be a sang-based energy flow dividing graph of each behavior event information and result event information, and the width of the extended branch corresponds to the size of each event information flow. In the embodiment of the invention, the incidence relation among the events can be intuitively observed by analyzing the summary table or the mor-base diagram.
On the basis of the above embodiment, the behavior event information includes a behavior event table, and the result event information includes a result event table; the step of fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result corresponding to the data of the user to be analyzed includes: storing data at different positions of the same user identifier in the result event table into the same cell to obtain a fusion result event table; based on the number and the arrangement sequence of each user identifier in the behavior event table, performing left connection on the fusion result event table and the behavior event table to obtain an event analysis table, wherein the number and the arrangement sequence of the rows of the event analysis table are the same as those of the behavior event table; based on the number and the arrangement sequence of each user identifier in the behavior event table, performing left connection on a user information table and the behavior event table to obtain a user basic information table, wherein the number of rows and the arrangement sequence of the user basic information table are the same as those of the behavior event table; and splicing the user basic information table, the behavior event table and the event analysis table to generate an analysis summary table.
The result event table may include a plurality of user identifiers, and any user identifier may correspond to a plurality of result events, and result events at different positions of the same user identifier need to be stored in the same cell, so that the diagnostic data can be observed and counted conveniently. The left connection process is that all data of the left table are displayed, the data of the right table only display the common part, and no corresponding part is displayed in a filling-up mode.
On the basis of the above embodiment, the fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain the analysis result corresponding to the data of the user to be analyzed includes: performing classification statistics on the behavior event information and the result event information to obtain a statistical result, wherein the statistical result comprises the number of users corresponding to each behavior event, user data corresponding to each result event and an incidence relation between the behavior event and any result event; respectively drawing event basic line segments based on the number of users corresponding to each behavior event and the user data corresponding to each result event; and drawing a connecting line segment between the basic line segments of the events based on the incidence relation between the behavior events and any result event, and generating a mulberry-based graph.
In the embodiment of the invention, the logic and the change condition of the behavior event information and the result event information can be truly and intuitively reflected through the mulberry base graph, and the incidence relation among the events is convenient to observe.
The embodiment of the invention provides a clinical data analysis method based on diagnosis and treatment events, which is characterized in that event information corresponding to a behavior event screening condition and event information corresponding to a result event screening condition are obtained by screening data of a user to be analyzed, so that behavior events are distinguished and result events are distinguished; furthermore, an analysis summary table and/or a sang-based chart corresponding to the data of the user to be analyzed are obtained through the fusion of the behavior event information and the result event information, and the incidence relation among the events can be visually observed.
EXAMPLE five
Fig. 5 is a schematic flow chart of a clinical data analysis method based on a diagnosis and treatment event according to a fifth embodiment of the present invention, which is embodied based on the foregoing embodiment. The clinical data may include a patient information table, a medication order table, and an adverse reaction table, as shown in tables 1-3.
TABLE 1 patient information Table
| User identification | Name (I) | Sex | Age (age) |
| 111 | X11 | For male | 21 |
| 112 | X85 | Woman | 25 |
| 113 | X32 | Woman | 43 |
| 114 | X54 | For |
32 |
It should be noted that the patient information table in this embodiment is the user information table in the above embodiment, the medication order table is the behavior data in the above embodiment, and the adverse reaction table is the result data in the above embodiment; the base table is the behavior event information of the first behavior in the embodiment, and the intermediate table is the result event information or the behavior event information corresponding to the intervention behavior in the embodiment; the first event is the first occurring behavior event in the above embodiment, the second event is the result event generated by the first behavior in the above embodiment, the third event is the intervention behavior event in the above embodiment, and the fourth event is the intervention result event in the above embodiment.
TABLE 2 medication order
| User identification | Time of administration | Name of medicine |
| 111 | 2021.10.20.13:31:59 | A |
| 116 | 2021.10.20.13:32:30 | C |
| 128 | 2021.10.20.13:35:01 | E |
| 142 | 2021.10.21.12:31:23 | B |
| 153 | 2021.10.21.13:11:09 | D |
TABLE 3 adverse reactions table
| User identification | Time to adverse reaction | Type of adverse reaction |
| 112 | 2021.10.20.18:31:53 | d |
| 117 | 2021.10.20.18:32:30 | v |
| 153 | 2021.10.20.19:35:01 | r |
| 131 | 2021.10.21.10:31:23 | g |
| 142 | 2021.10.21.14:11:09 | s |
| 111 | 2021.10.21.17:22:23 | a |
| 116 | 2021.10.22.19:32:14 | b |
The specific analysis flow is as follows:
and S510, setting a query analysis range of the patient.
In a medical scenario, a user may be a patient for diagnosis and treatment, and specifically may be determined according to patient groups, such as a cardiac patient group, a patient group taking a certain medication, and the like, or may determine a patient analysis range by date, or may determine a patient analysis range by screening patients meeting preset conditions through full-text retrieval.
S520, setting a data analysis event.
In this embodiment, the preset event screening condition is set as "take medicine a for the first time", the event for the first time is screened in table 2 according to the behavior time sorting information, and then the user data for taking medicine a is screened, which may be other medicines or multiple medicines simultaneously screened in batch to generate the base table. The traditional full text retrieval mode can not distinguish the data table to be analyzed, can not distinguish the first medicine, and can only retrieve the data of the patient who takes the medicine A, so that the data analysis method of the embodiment of the invention is more intelligent and faster.
If the user sets two event analyses, the analysis logic of the second event depends on the analysis result and the occurrence time of the first event, for example, if the user sets the second event analysis logic as "first adverse reaction" in this application, the analyzed table 3 and the associated data table 2 and the base table generated according to table 2 in the last associated event analysis are determined first.
Secondly, according to the data record occurrence time of the patients screened from the base table, the adverse reaction time period of each patient taking the medicine A for the first time is calculated.
For example, the preset time range of adverse reactions after the first administration is defined as the time range from the first administration time to 7 days after the first administration, the preset time range is adjustable, and the preset time is different according to different administered drugs, the action time and the metabolism time of the drugs. For example, intravenous injection can work immediately, while oral administration takes half an hour before it works; some medicines can be completely metabolized in one day, and some medicines can be metabolized in 3 days; the drug metabolism time of people with normal liver and kidney functions is shorter, and the metabolism time of people with abnormal liver and kidney functions is longer; and so on. The adverse reaction within this time period is an adverse reaction to the first administration of the drug, and the reaction outside the time period is not considered by default to be a reaction caused by the first administration of the drug.
And finally, screening adverse reaction data records of patients after the first medication in the table 3 according to the user identification determined by the base table and the preset adverse reaction time range, and generating an intermediate table.
Preferably, all medication records of each user in the table 2 are obtained according to the user identification in the base table, the time range between the first medication time and the medication change time is recorded as the first medication time range, the intersection of the first medication time range and the preset time range is taken, and the adverse reaction time range is determined. And finally, screening adverse reaction data records of patients after the first medication in the table 3 according to the user identification and the adverse reaction time range determined by the base table to generate an intermediate table.
Further, adverse reaction screening conditions can be set in the setting, and adverse reaction types of key researches of users can be further screened out from the screening results quickly. The traditional full-text retrieval mode cannot distinguish the first medication, even cannot distinguish the adverse reaction after the first medication, and can only retrieve the data of the patient who has completely taken the medicine A and all the adverse reaction data of the patient, so that the data analysis method of the embodiment of the invention is more intelligent and rapid.
If the user sets three event analyses, the analysis logic for the third event depends on the second event analysis result and the occurrence time. First, table 2 and the intermediate table generated in the last correlation event analysis are obtained.
Secondly, acquiring the time of each adverse reaction after the first medication according to the analysis result of the second event, and calculating the time period for intervention after each user has an adverse reaction.
For example, the predetermined time range for intervention therapy to define adverse effects is the time range from the occurrence of adverse effects to within 3 days of the occurrence. The preset time range is adjustable, and the preset time range is different according to different types of adverse reactions, different intensities of the adverse reactions, different physical conditions of researchers and different time ranges. For example, diarrhea is an adverse reaction and intervention treatment is needed as soon as possible, and nausea is an adverse reaction and intervention treatment is not needed very urgently. The intervention measures within this time period are intervention measures for the adverse reaction, and the measures outside the time period default to measures not for the adverse reaction.
And finally, acquiring a medication intervention treatment record which is different from the first medication and is taken by each user in the table 2 according to the user identification, the adverse reaction occurrence time and the preset intervention treatment time range in the analysis result of the second event.
Furthermore, the setting of the third event can also set the screening conditions of adverse reaction intervention treatment measures, so that adverse reaction intervention treatment measures which are intensively researched by the user can be further screened out from the screening results quickly. However, the traditional full-text retrieval mode cannot distinguish the first medication, cannot distinguish the adverse reaction after the first medication, cannot acquire the intervention treatment measures of the adverse reaction, and can only retrieve all the data of the medication taken by the user and all the data of the adverse reaction of the user, so that the data analysis method provided by the embodiment of the invention is more intelligent and faster.
By analogy, if the user sets four event analyses, the analysis logic of the fourth event depends on the analysis result and the occurrence time of the third event, and first, the analyzed data table 3 and the associated data table 2 and the intermediate table generated in the last associated event analysis are obtained.
Secondly, according to the occurrence time of the user data records screened from the previous intermediate table, the adverse reaction time period of each user taking the intervention treatment medicine is calculated.
And finally, screening adverse reaction data records after the user intervention treatment medication in the table 3 according to the user identification determined by the previous intermediate table and the preset adverse reaction time range to generate an intermediate table.
Preferably, all medication records of each patient in table 2 are obtained according to the user identifier in the previous intermediate table, the time range between the intervention treatment medication time and the second time medication change time is recorded as the intervention treatment medication time range, the intersection of the intervention treatment medication time range and the preset time range is taken, and the adverse reaction time range is determined. And finally, screening adverse reaction data records after the user intervention treatment medication in the table 3 according to the user identification and the adverse reaction time range determined by the previous intermediate table to generate an intermediate table.
Further, adverse reaction screening conditions can be set in the setting of the fourth event, so that adverse reaction types which are mainly researched by the user can be further screened out from the screening results quickly. And the traditional full-text retrieval mode cannot distinguish the data, so that the data analysis method provided by the embodiment of the invention is more intelligent and faster.
It should be noted that the above-mentioned a and B medicines may represent one medicine, that is, the user only takes the research medicine without taking other medicines, or may represent a combination of medicines or a prescription.
And S530, rapidly fusing the analysis results of the data tables to generate an analysis summary table.
The method comprises the following steps: and (3) intermediate table data fusion, namely fusing the data of different rows of the same user in the intermediate table generated in each step of the previous stage into user data of one row, and putting the data of the same field of different rows of the same user into one cell in the user data of one row after de-duplication. For example, adverse reactions such as nausea, headache, diarrhea and the like occur in sequence after a user takes a medicine for the first time, corresponding 3 rows of adverse reaction data with different time correspond to the user identification in the corresponding table 3 and the intermediate table generated by the table 3, when rows of the intermediate table are listed, 3 rows of data corresponding to the user in the intermediate table are converted into one row of data, and three adverse reactions such as nausea, headache, diarrhea and the like are put into the same cell;
step two: and connecting the fused intermediate tables with the base table to the left, and generating an event analysis table with the same number and the same sequence as those of the patients in the base table. For example, if 20 users in the base table take a certain medicine for the first time, 20 rows of data in the base table are arranged in the sequence X, wherein 15 users have different types or degrees of adverse reactions, 20 rows of data in the event analysis table generated by the left connection of the second event analysis are also arranged in the sequence X, but 5 rows of data are null, and so on.
Step three: connecting the patient information table with the base table to obtain basic information of the analyzed patient, and generating a basic information table of the analyzed patient;
step four: and deleting the patient identification field and the time-related field from the basic information table, the base table and the related event analysis table of the analyzed patient, and sequentially splicing the fields to generate an analysis summary table. Because the user does not need to manually analyze and study, the patient identification field and the time-related field are deleted in order to prevent redundancy and facilitate the viewing of the analysis result. In some embodiments, the patient identification field and the time-related field may not be deleted, facilitating manual review and data tracing.
And S540, generating a moresky graph in real time according to the analysis result of each data table, and displaying the analysis data.
The method comprises the following steps: carrying out classification statistics according to the base table, and drawing corresponding width line segments at the initial positions of the morse base graph according to statistical data;
step two: carrying out classification statistics on the data in each intermediate table, and drawing line segments with corresponding widths at corresponding positions of the mulberry-based graph according to the statistical data;
step three: and drawing a curve with a certain width according to the data of each patient in each intermediate table, and connecting line segments with corresponding widths of the two adjacent event analyses. The setting can truly and visually reflect the logic and result change condition of event analysis, and is convenient and practical.
EXAMPLE six
Fig. 6 is a schematic structural diagram of a clinical data analysis device based on clinical events according to a sixth embodiment of the present invention, where the clinical data analysis device based on clinical events provided in this embodiment may be implemented by software and/or hardware, and may be configured in a terminal and/or a server to implement the clinical data analysis method based on clinical events according to the sixth embodiment of the present invention. The device may specifically include: a data acquisition module 610, an event information generation module 620, and an analysis result generation module 630.
The data acquiring module 610 is configured to acquire data of a user to be analyzed; an event information generating module 620, configured to screen the data of the user to be analyzed based on preset event screening conditions to obtain event information corresponding to the preset event screening conditions, where the preset event screening conditions include behavior event screening conditions and result event screening conditions; an analysis result generating module 630, configured to fuse the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result corresponding to the data of the user to be analyzed.
The embodiment of the invention provides a clinical data analysis device based on diagnosis and treatment events, which is used for acquiring data of a user to be analyzed; screening data of a user to be analyzed based on preset event screening conditions to obtain event information corresponding to the preset event screening conditions, wherein the preset event screening conditions comprise behavior event screening conditions and result event screening conditions; and fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result. According to the technical scheme, the data of the user to be analyzed are screened to obtain the event information corresponding to the action event screening condition and the event information corresponding to the result event screening condition, so that the action events are distinguished and the result events are distinguished; furthermore, by fusing the event information corresponding to the behavior event and the event information corresponding to the result event, causal association analysis is realized, and the analysis result has higher research value.
On the basis of any optional technical solution in the embodiment of the present invention, optionally, the data of the user to be analyzed includes behavior data and result data, and the event information generating module 620 includes:
the behavior event information generating unit is used for screening the behavior data based on the behavior event screening conditions to obtain behavior event information, wherein the behavior event information comprises a user identifier;
a result event information generating unit, configured to filter the result data based on the user identifier in the behavior event information and the result event filtering condition to obtain result event information;
accordingly, the analysis result generation module 630 may be configured to:
and fusing the behavior event information and the result event information to obtain an analysis result corresponding to the data of the user to be analyzed.
On the basis of any optional technical solution in the embodiment of the present invention, optionally, the behavior event screening condition includes a behavior event type and/or behavior time sorting information, and the result event screening condition includes a result event type and/or a result time range.
On the basis of any optional technical scheme in the embodiment of the present invention, optionally, the behavior event screening condition further includes a time of occurrence of a history result event corresponding to the user identifier, and a time range of an intervention behavior based on the history result event;
the result event screening condition also comprises a result event type and/or an intervention result time range generated by a preset intervention behavior;
accordingly, the analysis result generation module 630 may be configured to:
and fusing the behavior event information and the result event information corresponding to the behavior time sequencing information to obtain an analysis result corresponding to the data of the user to be analyzed.
On the basis of any optional technical scheme in the embodiment of the present invention, optionally, the analysis result includes an analysis summary table and/or a mor-base chart.
On the basis of any optional technical solution in the embodiment of the present invention, optionally, the analysis result generating module 630 may be further configured to:
storing data at different positions of the same user identifier in the result event table into the same cell to obtain a fusion result event table;
based on the number and the arrangement sequence of each user identifier in the behavior event table, performing left connection on the fusion result event table and the behavior event table to obtain an event analysis table, wherein the number and the arrangement sequence of the rows of the event analysis table are the same as those of the behavior event table;
based on the number and the arrangement sequence of each user identifier in the behavior event table, performing left connection on a user information table and the behavior event table to obtain a user basic information table, wherein the number of rows and the arrangement sequence of the user basic information table are the same as those of the behavior event table;
and splicing the user basic information table, the behavior event table and the event analysis table to generate an analysis summary table.
On the basis of any optional technical solution in the embodiment of the present invention, optionally, the analysis result generating module 630 may be further configured to:
performing classification statistics on the behavior event information and the result event information to obtain a statistical result, wherein the statistical result comprises the number of users corresponding to each behavior event, user data corresponding to each result event and an incidence relation between the behavior event and any result event;
respectively drawing event basic line segments based on the number of users corresponding to each behavior event and the user data corresponding to each result event;
and drawing a connecting line segment between the basic line segments of the events based on the incidence relation between the behavior events and any result event, and generating a mulberry-based graph.
The clinical data analysis device based on the diagnosis and treatment events provided by the embodiment of the invention can execute the clinical data analysis method based on the diagnosis and treatment events provided by any embodiment of the invention, and has the corresponding functional modules and beneficial effects of the execution method.
EXAMPLE seven
Fig. 7 is a schematic structural diagram of an electronic device according to a seventh embodiment of the present invention. FIG. 7 illustrates a block diagram of an exemplary electronic device 12 suitable for use in implementing embodiments of the present invention. The electronic device 12 shown in fig. 7 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiment of the present invention.
As shown in FIG. 7, electronic device 12 is embodied in the form of a general purpose computing device. The components of electronic device 12 may include, but are not limited to: one or more processors or processing units 16, a system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM)30 and/or cache memory 32. The electronic device 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 7, and commonly referred to as a "hard drive"). Although not shown in FIG. 7, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the invention.
A program/utility 36 having a set (at least one) of program modules 26 may be stored, for example, in system memory 28, such program modules 26 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 26 generally perform the functions and/or methodologies of the described embodiments of the invention.
The processing unit 16 executes programs stored in the system memory 28 to execute various functional applications and data processing, for example, to implement a clinical event-based clinical data analysis method provided by the embodiment of the present invention.
Example eight
An eighth embodiment of the present invention further provides a storage medium containing computer-executable instructions, which when executed by a computer processor, are configured to perform a method for clinical data analysis based on a diagnosis and treatment event, the method including:
acquiring data of a user to be analyzed;
screening the data of the user to be analyzed based on preset event screening conditions to obtain event information corresponding to the preset event screening conditions, wherein the preset event screening conditions comprise behavior event screening conditions and result event screening conditions;
and fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result corresponding to the data of the user to be analyzed.
Computer storage media for embodiments of the invention may employ any combination of one or more computer-readable media. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples (a non-exhaustive list) of the computer readable storage medium would include the following: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take many forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for embodiments of the present invention may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, Smalltalk, C + + or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is to be noted that the foregoing is only illustrative of the preferred embodiments of the present invention and the technical principles employed. It will be understood by those skilled in the art that the present invention is not limited to the particular embodiments described herein, but is capable of various obvious changes, rearrangements and substitutions as will now become apparent to those skilled in the art without departing from the scope of the invention. Therefore, although the present invention has been described in greater detail by the above embodiments, the present invention is not limited to the above embodiments, and may include other equivalent embodiments without departing from the spirit of the present invention, and the scope of the present invention is determined by the scope of the appended claims.
Claims (10)
1. A clinical data analysis method based on diagnosis and treatment events is characterized by comprising the following steps:
acquiring data of a user to be analyzed;
screening the data of the user to be analyzed based on preset event screening conditions to obtain event information corresponding to the preset event screening conditions, wherein the preset event screening conditions comprise behavior event screening conditions and result event screening conditions;
and fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result corresponding to the data of the user to be analyzed.
2. The method of claim 1, wherein the data of the user to be analyzed comprises behavior data and result data; the screening the data of the user to be analyzed based on the preset event screening condition to obtain event information corresponding to the preset event screening condition includes:
screening the behavior data based on the behavior event screening condition to obtain behavior event information, wherein the behavior event information comprises a user identifier;
screening the result data based on the user identification in the behavior event information and the result event screening condition to obtain result event information;
correspondingly, the fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result corresponding to the data of the user to be analyzed includes:
and fusing the behavior event information and the result event information to obtain an analysis result corresponding to the data of the user to be analyzed.
3. The method of claim 2, wherein the behavioral event screening criteria includes behavioral event type and/or behavioral time ordering information, and wherein the outcome event screening criteria includes outcome event type and/or outcome time range.
4. The method of claim 2, wherein the behavioral event screening criteria further includes a time of occurrence of a corresponding historical result event identified by a user, a time range of intervention behavior based on the historical result event;
the result event screening condition also comprises a result event type and/or an intervention result time range generated by a preset intervention behavior;
correspondingly, the fusing the behavior event information and the result event information to obtain an analysis result corresponding to the data of the user to be analyzed includes:
and fusing the behavior event information and the result event information corresponding to the behavior time sequencing information to obtain an analysis result corresponding to the data of the user to be analyzed.
5. The method of claim 2, wherein the analysis results comprise an analysis summary table and/or a mor-base chart.
6. The method of claim 5, wherein the behavioral event information comprises a behavioral event table and the resultant event information comprises a resultant event table; the step of fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result corresponding to the data of the user to be analyzed includes:
storing data at different positions of the same user identifier in the result event table into the same cell to obtain a fusion result event table;
based on the number and the arrangement sequence of each user identifier in the behavior event table, performing left connection on the fusion result event table and the behavior event table to obtain an event analysis table, wherein the number and the arrangement sequence of the rows of the event analysis table are the same as those of the behavior event table;
based on the number and the arrangement sequence of each user identifier in the behavior event table, performing left connection on a user information table and the behavior event table to obtain a user basic information table, wherein the number of rows and the arrangement sequence of the user basic information table are the same as those of the behavior event table;
and splicing the user basic information table, the behavior event table and the event analysis table to generate an analysis summary table.
7. The method according to claim 5, wherein the fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain the analysis result corresponding to the data of the user to be analyzed comprises:
performing classification statistics on the behavior event information and the result event information to obtain a statistical result, wherein the statistical result comprises the number of users corresponding to each behavior event, user data corresponding to each result event and an incidence relation between the behavior event and any result event;
respectively drawing event basic line segments based on the number of users corresponding to each behavior event and the user data corresponding to each result event;
and drawing a connecting line segment between the basic line segments of the events based on the incidence relation between the behavior events and any result event, and generating a mulberry-based graph.
8. A clinical data analysis device based on a diagnosis and treatment event, comprising:
the data acquisition module is used for acquiring data of a user to be analyzed;
the event information generating module is used for screening the data of the user to be analyzed based on preset event screening conditions to obtain event information corresponding to the preset event screening conditions, wherein the preset event screening conditions comprise behavior event screening conditions and result event screening conditions;
and the analysis result generation module is used for fusing the event information corresponding to the behavior event screening condition and the event information corresponding to the result event screening condition to obtain an analysis result corresponding to the data of the user to be analyzed.
9. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method for clinical event-based clinical data analysis of any of claims 1-7.
10. A storage medium containing computer-executable instructions for performing the method for clinical event-based clinical data analysis of any one of claims 1-7 when executed by a computer processor.
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