CN106919777B - Method and device for processing checklists for medical procedures - Google Patents
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- G16H50/00—ICT specially adapted for medical diagnosis, medical simulation or medical data mining; ICT specially adapted for detecting, monitoring or modelling epidemics or pandemics
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Abstract
Embodiments of the present disclosure relate to methods and apparatus for processing checklists for medical procedures. In one embodiment, a first correlation of items to be inspected in an examination list to a medical procedure may be determined by querying a knowledge base storing prior medical data relating to at least the items to be inspected, the medical procedure, and potential complications associated therewith. Additionally, a second relevance of the item to be inspected to the potential complication can be determined by querying the knowledge base. Based on the first and second correlations, a priority order of the examination items in the examination list may be determined. In this way, the examination items can be automatically sorted according to their importance.
Description
Technical Field
The present disclosure relates generally to the processing of medical checklists, and more particularly, to methods and apparatus for processing checklists for medical procedures.
Background
In clinical diagnosis and treatment, checklists (checklists) are often used to identify, schedule, compare, or verify issues involved in the course of a procedure. Computerized electronic checklist systems have been proposed. By using such an electronic checklist system prior to clinical applications, such as an outpatient information system or an Electronic Medical Record (EMR), medical personnel, such as doctors or nurses, can utilize the electronic checklist to confirm critical checklists. The electronic checklist system may record medical personnel's decisions, present the procedure in an intuitive manner, record the patient's treatment and care processes, allow medical personnel to annotate problems, share information with others, provide step-by-step guidance in emergency situations, and so forth. Clinical studies have shown that: checklists can significantly reduce mortality and complications in a clinical setting.
Checklists typically contain a large number of interrelated items. Generally, it is desirable to ensure that the most important items are inspected and/or confirmed before making a medical decision, particularly before performing life-critical surgery. That is, the items in the checklist need to be sorted by importance. However, due to limiting factors such as human short-term memory limitations, medical personnel cannot ensure that the proper ordering of items is given for each medical checklist.
Disclosure of Invention
Example embodiments of the present disclosure relate to methods and apparatuses for processing checklists for medical procedures.
In a first aspect, a method of processing a checklist for a medical procedure is provided. The method comprises the following steps: determining a first correlation between an item to be inspected and a diagnosis and treatment process in an inspection list by inquiring a knowledge base in which prior diagnosis and treatment data are stored, wherein the prior diagnosis and treatment data at least relate to the associated item to be inspected, the diagnosis and treatment process and potential concurrent diseases; determining a second relevance of the item to be inspected and the potential complication through inquiring a knowledge base; and determining a priority order of the checking items in the checking list at least based on the first relevance and the second relevance.
In some embodiments, determining the first correlation comprises: obtaining a first path between the item to be inspected and the diagnosis and treatment process by querying a knowledge base, and determining the second relevance comprises: by querying the knowledge base, a second path between the item to be examined and the potential complication is obtained.
In some embodiments, obtaining the first path comprises: selecting a path stored in the knowledge base and having a path length between the item to be inspected and the diagnosis and treatment process smaller than a first preset threshold value as a first path, and obtaining a second path comprises: selecting as the second path a path stored in the knowledge base having a path length between the item to be examined and the potential complication smaller than a second predetermined threshold.
In some embodiments, determining the first correlation comprises: determining a weight of a sub-path in the first path, the sub-path being a portion in the first path, the weight of the sub-path representing a correlation between two associated with the portion in the first path; and determining a first correlation based on the weights of the sub-paths in the first path and the number of sub-paths; and determining the second correlation comprises: determining a weight of a sub-path in the second path, the sub-path being a portion in the second path, the weight of the sub-path representing a correlation between two associated with the portion in the second path; and determining the second relevance based on the weights of the sub-paths in the second path and the number of sub-paths.
In some embodiments, determining a statistical weight associated with the second relevance by querying a statistical database storing case statistics, the statistical weight indicating a probability of occurrence of a concurrent disorder related to the item to be inspected, wherein determining the order of priority of the inspection items in the inspection list comprises: based on the first correlation, the second correlation and the statistical weight, the priority order of the checking items in the checking list is determined.
In some embodiments, the statistical weight indicates a ratio of the number of potential complications resulting from non-execution of the item to be inspected to the total number of potential complications that actually occur.
In some embodiments, determining a priority order of the inspection items in the inspection list comprises: acquiring a preset priority of an examination item in a diagnosis and treatment process, wherein the preset priority is provided by a user aiming at a given medical factor; and determining a priority order of the inspection items based on the preset priority, the first correlation, the second correlation and the statistical weight.
In some embodiments, a first path and a second path for an inspection item are graphically displayed.
According to a second aspect of the present disclosure, there is provided an apparatus for processing a checklist for a medical procedure, comprising: a knowledge base analysis unit configured to: determining a first correlation between an item to be inspected and a diagnosis and treatment process in an inspection list by inquiring a knowledge base in which prior diagnosis and treatment data are stored, wherein the prior diagnosis and treatment data at least relate to the associated item to be inspected, the diagnosis and treatment process and potential concurrent diseases; determining a second relevance of the item to be inspected and the potential complication through inquiring the knowledge base; and a priority order determination unit configured to determine a priority order of the check items in the check list based on at least the first correlation and the second correlation.
It will be understood that this section is not intended to identify key or critical features of embodiments of the disclosure, nor is it intended to be used to limit the scope of the disclosure. Other features of the present disclosure will become apparent from the following description.
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The above and other advantages, features and objects of the present disclosure will become more apparent from the following more detailed description of some embodiments of the present disclosure in which:
FIG. 1 is a simplified block diagram illustrating an environment according to one embodiment of the present disclosure;
FIG. 2 is a flow diagram illustrating a method according to one embodiment of the present disclosure;
figure 3 is a graph illustrating relationships associated with a medical procedure according to one embodiment of the present disclosure;
FIG. 4 is a relational diagram illustrating a portion of the clinical process shown in FIG. 3;
FIG. 5 is a relationship diagram illustrating another portion of the diagnostic process according to FIG. 3;
FIG. 6 is a relationship diagram illustrating yet another portion of the diagnostic process shown in FIG. 3; and
FIG. 7 is a block diagram illustrating a device suitable for implementing embodiments of the present disclosure.
Throughout the drawings, the same or similar reference numbers refer to the same or similar elements.
Detailed Description
The principles of the present disclosure will now be described with reference to a few exemplary embodiments. It is understood that these examples are described solely for the purpose of illustration and to assist those of ordinary skill in the art in understanding and working the disclosure, and are not intended to suggest any limitation as to the scope of the disclosure. The disclosure described herein may be implemented in various ways other than those described below.
As used herein, the term "include" and its various variants are to be understood as open-ended terms, which mean "including, but not limited to. The term "based on" may be understood as "based at least in part on". The term "one embodiment" may be understood as "at least one embodiment". The term "another embodiment" may be understood as "at least one other embodiment".
In general, some embodiments of the present disclosure relate to methods and apparatus for processing checklists for medical procedures. In some embodiments, the natural language processing may be used to analyze various items on the clinical process and checklist to extract key items (e.g., keywords or other expressions). By using the extracted keywords to query a knowledge base with prior clinical data, various items (e.g., items to be examined, clinical procedures, potential complications, etc.) and relationships between them that are related to the keywords can be determined. The priority of the items to be examined can be determined by analyzing the relationships between the various items, for example by analyzing the weights between the various items. In some embodiments, the determination of project priority may be further aided by a statistics database storing case statistics.
Fig. 1 illustrates a simplified block diagram of an environment 100 for processing a medical checklist according to an embodiment of the present disclosure. The environment 100 includes a natural language processing unit 112, a knowledge base analysis unit 102, a statistical database analysis unit 104, a prioritization unit 110, a display unit 114, a knowledge base 106, a statistical database 108, an unprocessed checklist 116, and a prioritized checklist 118.
In operation, the natural language processing unit 112 may first analyze the unprocessed checklist 116. For example, in one embodiment, the natural language processing unit may load a predefined checklist and understand and analyze semantics on the checklist by means of natural language processing techniques. Any now known or later developed natural language processing techniques may be used in conjunction with embodiments of the present disclosure, the scope of which is not limited in this respect. Keywords in the checklist may be extracted through natural language processing of the checklist. The extracted keywords may be sent to the knowledge base analysis unit 102.
The knowledge base analysis unit 102 uses the received keywords to query the knowledge base 106. The knowledge base 106 stores prior clinical data, which may be obtained through various automated and/or manual approaches. In accordance with an embodiment of the present disclosure, the a priori clinical data stored in the knowledge base 106 relate to at least the items to be examined, the clinical procedures, and the potential complications associated with each other, as will be described in more detail below. Through the query of the knowledge base, various items related to the keywords and the mutual relations among the items can be obtained. One example of a query result will be described below with reference to FIG. 3.
As shown, the respective items and the mutual relationship obtained by the query are provided to the priority determining unit 110. The priority order determination unit 110 determines the priority order of the respective check items in the checklist according to the received pieces of information, and transmits the sorted checklist to the display unit 114. The display unit 114 may display the sorted checklist 118 to a doctor, a nurse, or the like.
Furthermore, the actual statistical case data tends to help further determine which examination item is more important. Thus, in some embodiments, the knowledge base analysis unit 102 optionally sends the queried items and their interrelationships to the statistical database analysis unit 104。The statistical database analysis unit 104 queries the statistical database 108 using the received information. The statistics database 108 stores historical case statistics. These case statistics record information about past real cases, such as clinical manifestations or responses (e.g., complications) that occurred, whether the clinical manifestations or responses were due to an unexecuted examination item, and so on. The results of the query to the statistics database 108 may be utilized as an adjunct in determining the order of priority in the checklist. For example, the query results of the statistical database 108 may be used to weight the relationships queried by the knowledge base 106 for more accurate prioritization. In such embodiments, the statistical database analysis unit 104 may send the weighted individual items and their relationships to the priority determination unit 110. The priority order determination unit 110 then determines the priority order of the respective examination items in the examination list, and transmits the sorted examination list to the display unit 114, so that the display unit 114 can display the sorted examination list 118.
Fig. 2 shows a flow diagram of a method 200 according to an embodiment of the present disclosure. The method 200 may be implemented, for example, by the knowledge base analysis unit 102 and the prioritization unit 110 of fig. 1. Specifically, at step 202, the knowledge base analysis unit 102 determines the correlation between the item to be inspected in the checklist and the diagnosis process by querying the knowledge base 106 storing the prior diagnosis and treatment data according to the received keyword. For purposes of ease of discussion, this correlation will be referred to as a "first correlation" in the context of this disclosure.
It will be appreciated that different procedures typically have different items to be examined, and that each item to be examined may have different relevance in different procedures. Moreover, different diagnostic procedures may lead to different potential complications. In this context, a potential complication represents an adverse outcome associated with the medical procedure, including, for example, disease, infection, bleeding, and various medical errors that are not expected. As described above, the a priori clinical data stored in the knowledge base 106 relates to at least the items to be examined, the clinical process, and the potential complications associated with each other.
At step 204, knowledge base analysis unit 102 determines the relevance of the item to be examined to the potential complication by querying knowledge base 106 based on the received keywords. For ease of discussion, this correlation is referred to herein as a "second correlation". It will be appreciated that for an examination item, there may be one or more potential complications, each of which may have a respective second relevance to the item to be examined. In embodiments of the present disclosure, both the first correlation and the second correlation may be used to represent the importance of the item to be inspected. It should be noted that although step 204 is shown before step 206, this does not mean that the first correlation must be determined before the second correlation. In other embodiments, the determination of the first correlation may be later than or substantially simultaneous with the second correlation.
Next, at step 206, the priority order determination unit 110 determines the priority order of the check items in the checklist based on at least the first and second correlations determined at steps 202 and 204, respectively. Generally, an examination item has a higher priority if the potential association between the examination item and the clinical process or the potential complication is determined to be closer by a priori knowledge in the knowledge base 106. Conversely, if a potential association between an examination item and a clinical procedure or a potential complication is low, the examination item may be given a lower priority. To assist those skilled in the art to better understand the concepts and principles of the present disclosure, a specific example will be described below with reference to fig. 3.
Figure 3 illustrates a relationship diagram associated with a medical procedure according to one embodiment of the present disclosure. The relationship diagram 300 includes a clinical procedure, in this case a catheter intervention, shown as a solid rectangular box. The relationship diagram 300 further includes: items to be examined, in this case salt hydration and detection allergy, are shown in dashed oval; and key factors related to the results shown in dashed rectangle boxes and clinical concepts shown in solid oval boxes. In this example, the natural language processing unit includes the obtained keywords "catheter intervention", "saline" and "exam allergy", for example, by processing the results of the checklist 116. The knowledge base analysis unit 102 retrieves related items in the knowledge base 106 through the three keywords, and obtains the related items and the relationship therebetween as shown in fig. 3, for example.
Specifically, in the example of fig. 3, catheter intervention is a procedure for diagnosing and treating heart diseases by injecting tiny tubes (called catheters) into arteries and/or veins around the heart, which mainly cope with heart diseases. For diagnostic catheters, it is necessary to inject a radioactive contrast medium into the blood vessel so that the diagnostic catheter can be identified under X-ray. This is commonly referred to as angiography. On the other hand, several types of results can be obtained from the cardiac catheter, including adverse and beneficial results. Adverse consequences include, for example, management errors (e.g., catheter intervention applied to the wrong patient or at the wrong location), allergies, bleeding, complications (e.g., resulting in kidney failure), infection, and so forth. For example, injection of contrast media may cause the concentration of radioactive material in the blood to rise, which may cause problems such as renal insufficiency. In some cases, such as when a patient has both cardiovascular disease and renal insufficiency, this can lead to renal failure if not managed properly. Another potential risk of radiocontrast agents is that they may cause allergies in some patients.
It will be understood that fig. 3 is only a portion of a real knowledge base, which is merely illustrative of a method according to some embodiments of the present disclosure, and is not intended to limit the scope of the present disclosure. Further, to facilitate calculating the correlations, in certain embodiments, edges (sub-paths) between various items in the knowledge base may be given weights, e.g., based on the strength of the clinical evidence, which may be used to calculate the first and second correlations as described above. The specific calculation is shown below.
To compute the first and second correlations described above based on a priori knowledge in the knowledge base represented in FIG. 3, in some embodiments, the relationships between the items to be examined and the clinical process in the relationship graph 300, and the relationships between the items to be examined and the potential complications, may be identified. That is, from a diagram perspective, a path connecting the item to be examined and the clinical process (referred to as a "first path") and a path connecting the item to be examined and the potential complication (referred to as a "second path") can be found in the relationship diagram 300.
As an example, the path shown in fig. 4 may be obtained based on a priori knowledge represented by the relationship diagram 300 in fig. 3. Fig. 4 shows a part of the diagnostic procedure according to fig. 3, i.e. a first path between the salination and the catheter intervention and a second path between the salination and the renal failure. As shown in fig. 4, heart diseases and the like may have concurrent renal failure; on the other hand, catheter interventions use contrast agents. Contrast agents increase contrast agent concentration, which is a risk for patients with renal disease. Salt hydration is an action that reduces contrast agent concentration and is used in renal disease. Therefore, by inquiring the prior knowledge, useful information and description of the item to be checked can be found, and the relation between the item to be checked and the diagnosis and treatment process and potential complications is more obvious.
In one embodiment, the correlation of the first path and the second path may be represented as follows:
C＝ΠWe/N
where c represents the calculated correlation for the path, N represents the number of edges in the path, WeRepresenting the weight of the edge. The formula multiplies the weight of each edge by the total number of edges to obtain the correlation of the path.
In the embodiment shown in fig. 4, the first path from the item to be examined to the clinical process is: salt hydration 412-decrease → blood contrast agent concentration 406 ← increase-injection contrast agent 404 ← catheter intervention 402. The second path from the item to be examined to the potential complication is: salt hydration 412-decrease → blood contrast agent concentration 406 ← risk-renal insufficiency 408 ← risk-renal failure 410. For convenience of description, in this embodiment, the weight of each edge is set to 1. That is, in this example, the importance between the respective paths is considered to be the same. It should be understood that this is by way of example only and is not intended as a limitation on the scope of the present disclosure. It will be appreciated that each edge may be given a different weight value based on the importance between the various terms.
Thus, according to the above formula, a first correlation for the item to be examined (salt hydration) and the procedure (catheter intervention) is calculated as: c1(1 × 1 × 1)/3 ═ 0.33. A second correlation for the item to be examined (salt hydration) and the potential complication (renal failure) was calculated as: c2＝(1×1×1)/3＝0.33。
It will be appreciated that in some more complex relational graphs, there may be different connection paths between the item to be examined and the clinical process, and each path may have a different number of edges. Likewise, there may be different connection paths between the item to be inspected and the potential complication, and each path may have a different number of edges. In one embodiment, an upper limit on the number of edges contained in a path may be set when querying the knowledge base 106. That is, in such embodiments, only paths having less than a predetermined number of edges are selected. The predetermined number may be set according to actual requirements. For example only, in one embodiment, an upper limit on the number of edges may be set to 4, for example.
Limiting the path length would be beneficial because as the number of edges increases, the association between the item to be examined and the course and complications decreases. By limiting the number of edges in the path, the validity and availability of the first and second dependencies returned by the query can be effectively ensured. After filtering out undesired excessively long paths, for paths between the item to be examined and the medical procedure, if there are still multiple paths, the path with the highest correlation value is selected. If there are multiple paths with the same highest relevance value, one may be randomly selected as the first path. Alternatively, a first path may be selected based on various factors such as previously saved user preferences, operational history, and the like.
In some embodiments, if there are multiple potential complications and, therefore, multiple paths between the item to be inspected and the potential complications, a sum of second correlations of these paths may be calculated. An example of this is shown in figure 5. In the example shown in fig. 5, another potential complication, namely, contrast agent hypersensitivity 416, is added as compared to fig. 4. Thereby, the associated medical concept, namely radiocontrast allergy 414, is also increased. Thus, in the embodiment of fig. 5, there are two second paths between the item to be examined and the potential complication that form two pairs with the first path from the salination to the catheter intervention. The first pair includes a first path and a second path as described above with respect to fig. 4. The second pairing includes the first understanding as described above for fig. 4 and a second pathway from salt hydration to contrast agent anaphylaxis. In the second pairing, C1＝(1×1×1)/3＝0.33，C2＝(1×1×1)/3＝0.33。
In this example, the item to be inspected priority value may be determined as the sum of weighted values of the respective paths in the respective pairs. For example, the salt hydration priority in FIG. 5 is (C)1+C2)+(C1+C2) (0.33+0.33) + (0.33+0.33) ═ 1.32. It will be appreciated that it would be beneficial to consider both the first and second correlations, since the first correlation directly represents the relationship between the item to be examined and the medical procedure. It will be appreciated that in considering the priority order of the items to be examined, a first correlation between the items to be examined and the medical procedure needs to be considered. On the other hand, if the clinical knowledge is not sufficient, but it is indicated by the knowledge base that the item to be examined was not executed or was not executedIt is sufficiently likely to cause a potential complication and the probability of this potential complication is further shown by the statistical database to be relatively high, the priority of the item to be examined can be boosted by the second correlation. It will be appreciated that this calculation is merely an example and not a limitation on the scope of the present disclosure, and that other suitable calculation means may be used. The priority order calculation unit may prioritize according to a priority value for each item to be inspected.
Furthermore, if there is no connection path between the item to be examined and the medical procedure or between the item to be examined and the potential complication, the number of edges between them can be considered infinite, which results in the first correlation or the second correlation being zero.
As described above, the actual statistical case data can further highlight which examination item is more important. Therefore, in some embodiments, optionally, the knowledge base analysis unit 102 sends the queried items and their related relationships to the statistical database analysis unit 104. The statistical database analysis unit 104 weights the relationships queried by the knowledge base by querying the statistical database 108 storing the case statistical data to obtain a more accurate priority. According to embodiments of the present disclosure, the statistics in statistics database 108 may be from a hospital statistics database or, for example, a statistics database provided by a specialized institution.
As an example, referring to fig. 5, since it has been found that there is a correlation between the salt hydration 412 and the renal failure 410, the statistical database analysis unit 104 looks for the ratio of cases of renal failure due to not performing salt hydration to the total cases of renal failure in the catheter interventional procedure by selecting the following path:
renal failure ═ true 'and complications ═ renal insufficiency' and 'hydration ═ not examined' data in the hypothesis statistics database indicate: 200 of 1000 renal failure cases were due to not performing salinization. Thus, the second correlation from salinization 412 to renal failure 410 may be set to a statistical weight of 200/1000-0.2. Likewise, a statistical weight of the second correlation from the salinization 412 to the contrast agent hypersensitivity 416 may be determined by the statistical database, for example, to be 0.1.
In addition to the statistical weight, a preset priority may be given because, for example, the correlation of some inspection items is not high and priority needs to be set individually. In certain embodiments, the preset priority is provided by the user for a given medical factor, for example.
In an embodiment that takes into account factors of statistical weight and pre-set priority, the dynamic priority of the inspection item may be represented as follows:
PD＝PP+Sum(C1+C2×I2)
wherein P isDIndicating dynamic priority, PPDenotes a predetermined priority, C1Denotes a first correlation, C2Denotes a second correlation, I2Representing the statistical weight. For example, if the preset priority for salt hydration in fig. 5 defaults to 1, then the dynamic priority may be calculated as PD＝1+((0.33+0.33×0.2)+(0.33+0.33×0.1))＝1.759。
Referring now to FIG. 6, yet another portion of the relationship diagram of FIG. 3 is shown. Fig. 6 includes catheter intervention 402, contrast agent injection 404, contrast agent staining 426, contrast agent allergy 414, contrast agent anaphylaxis 424, and exam allergy 422. As shown in FIG. 6, a first correlation C, for example, from catheter intervention 402 to detection of allergy 42211 × 1 × 1 × 1/4 ═ 0.25, for example, the second correlation C from examination hypersensitivity 422 to contrast agent hypersensitivity21 × 1/2 equals 0.5. By querying the statistical database, a statistical weight for the second correlation is obtained, for example, of 0.05. The dynamic priority P of the allergy item is checkedD1+0.25+0.5+ 0.05-1.275. Thus, the preference order determination unit 110 may rank the salinization on the checklist 118 before checking for an allergy after receiving the dynamic priority for salinization and the dynamic priority for checking for an allergy.
Then, the display unit 114 may display the sorted checklist. In addition to displaying the examination item names and priority values, in some embodiments, the checklist 118 may also display a local relationship graph including a first path and a second path as shown in FIGS. 4-6. In this way, doctors and nurses can visually and conveniently view and understand the relationship between the items to be checked and the diagnosis and treatment process and potential complications. In addition, the checklist 118 may also display relevant statistics under the item to be checked so that a user, such as a doctor or nurse, may place more emphasis on the item to be checked.
The aforementioned "keywords" and "complications" may be predefined based on medical dictionaries and clinical guidelines.
FIG. 7 illustrates a block diagram of a device 700 that may be used to implement embodiments of the present disclosure. As shown, the device 700 includes a Central Processing Unit (CPU)701, which can perform various appropriate actions and processes according to a program stored in a Read Only Memory (ROM)702 or a program loaded from a storage unit 708 into a Random Access Memory (RAM) 703. In the RAM 703, various programs and data necessary for the operation of the apparatus 700 are also stored. The CPU 701, the ROM 702, and the RAM 703 are connected to each other via a bus 704. An input/output (I/O) interface 705 is also connected to bus 704.
Various components in the device 700 are connected to the I/O interface 705, including: an input unit 706 such as a keyboard, a mouse, or the like; an output unit 707 such as a Cathode Ray Tube (CRT), a Liquid Crystal Display (LCD), a speaker, and the like; a storage unit 708 such as a magnetic disk, optical disk, or the like; and a communication unit 709 such as a network card, a modem, and the like. The communication unit 709 performs communication processing via a network such as the internet.
The processes and procedures described above, for example method 200, may be performed by processing unit 701. Further, the above-described units, such as the natural language processing unit 112, the knowledge base analysis unit 102, the statistical database analysis unit 104, and the prioritization unit 110, may be implemented by the processing unit 701. For example, in an embodiment, a process implementing the method 200 may be implemented as a computer software program, which may be tangibly embodied on a machine-readable medium. In such embodiments, the computer program may be downloaded and installed over a network via the communication unit 709 and/or entered into the device 700 for execution by the processing unit 701 by means of the storage unit 708.
In general, the various embodiments of the disclosure may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. Some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device. While various aspects of the disclosure are illustrated and described as block diagrams, flow charts, or using some other pictorial representation, it is well understood that the blocks, apparatus, systems, techniques or methods described herein may be implemented in, without limitation, hardware, software, firmware, special purpose circuits or logic, general purpose hardware or controller or other computing devices, or some combination thereof.
Further, while operations are described in a particular order, this should not be understood as requiring that such operations be performed in the order shown or in sequential order, or that all illustrated operations be performed, to achieve desirable results. In some cases, multitasking or parallel processing may be advantageous. Similarly, while details of several specific implementations are included in the above discussion, these should not be construed as any limitation on the scope of the disclosure, but rather the description of features is directed to specific embodiments only. Certain features that are described in the context of separate embodiments can also be implemented in combination in a single embodiment. Conversely, various features that are described in the context of a single embodiment can also be implemented in multiple embodiments separately or in any suitable subcombination.
Although the disclosure has been described in language specific to structural features and/or methodological acts, it is to be understood that the disclosure defined in the appended claims is not necessarily limited to the specific features or acts described above. Rather, the specific features and acts described above are disclosed as example forms of implementing the claims.
Claims (15)
1. A method of processing checklists for medical procedures, comprising:
determining a first correlation between an item to be inspected in the inspection list and the diagnosis and treatment process by inquiring a knowledge base in which prior diagnosis and treatment data are stored, wherein the prior diagnosis and treatment data at least relate to the associated item to be inspected, the diagnosis and treatment process and potential concurrent diseases;
determining a second relevance of the item to be inspected and the potential complication by querying the knowledge base; and
determining a priority order of the items to be inspected in the checklist based on at least the first correlation and the second correlation,
wherein the first correlation indicates a degree of importance of the item to be examined in the medical procedure.
2. The method of claim 1, wherein
Determining the first correlation comprises: obtaining a first path between the item to be examined and the diagnosis and treatment process by querying the knowledge base, an
Determining the second correlation comprises: obtaining a second path between the item to be examined and the potential complication by querying the knowledge base.
3. The method of claim 2, wherein
Obtaining the first path comprises: selecting a path stored in the knowledge base, the path length between the item to be examined and the diagnosis process being smaller than a first predetermined threshold value, as the first path, an
Obtaining the second path comprises: selecting as the second path a path stored in the knowledge base having a path length between the item to be inspected and the potential complication smaller than a second predetermined threshold.
4. The method of claim 3, wherein
Determining the first correlation comprises:
determining weights of sub-paths in the first path, the sub-paths being portions of the first path, the weights of the sub-paths representing correlations between two associated with the portions of the first path; and
determining the first correlation based on weights of the sub-paths in the first path and the number of the sub-paths; and
determining the second correlation comprises:
determining weights of sub-paths in the second path, the sub-paths being portions of the second path, the weights of the sub-paths representing correlations between two associated with the portions of the second path; and
determining the second relevance based on weights of the sub-paths in the second path and the number of sub-paths.
5. The method of claim 1, further comprising:
determining a statistical weight associated with the second correlation by querying a statistical database storing case statistics, the statistical weight indicating a probability of occurrence of the potential complication related to the item to be examined,
wherein said determining a priority of said items to be reviewed in said checklist comprises: determining the priority of the items to be inspected in the checklist based on the first correlation, the second correlation, and the statistical weight.
6. The method of claim 5, wherein the statistical weight indicates a ratio of the number of potential complications resulting from non-execution of the item to be inspected to the total number of potential complications.
7. The method of claim 1, wherein said determining a priority order of said items to be reviewed in said checklist comprises:
acquiring a preset priority of the item to be inspected in the diagnosis and treatment process, wherein the preset priority is provided by a user aiming at given medical factors; and
determining the priority order of the items to be inspected based on the preset priority, the first correlation, the second correlation and a statistical weight, wherein the statistical weight indicates the occurrence probability of the potential complications related to the items to be inspected.
8. The method of claim 3, further comprising:
graphically displaying the first path and the second path for the item to be inspected.
9. An apparatus for processing checklists for medical procedures, comprising:
a processing unit configured to:
determining a first correlation between an item to be inspected in the inspection list and the diagnosis and treatment process by inquiring a knowledge base in which prior diagnosis and treatment data are stored, wherein the prior diagnosis and treatment data at least relate to the associated item to be inspected, the diagnosis and treatment process and potential concurrent diseases;
determining a second relevance of the item to be inspected and the potential complication by querying the knowledge base; and
determining a priority order of the items to be checked in the checklist based on at least the first correlation and the second correlation,
wherein the first correlation indicates a degree of importance of the item to be examined in the medical procedure.
10. The device of claim 9, wherein the processing unit is configured to:
obtaining a first path between the item to be examined and the diagnosis and treatment process by querying the knowledge base, an
Obtaining a second path between the item to be examined and the potential complication by querying the knowledge base.
11. The device of claim 10, wherein the processing unit is configured to:
selecting a path stored in the knowledge base, the path length between the item to be examined and the diagnosis process being smaller than a first predetermined threshold value, as the first path, an
Selecting as the second path a path stored in the knowledge base having a path length between the item to be inspected and the potential complication smaller than a second predetermined threshold.
12. The device of claim 11, wherein the processing unit is configured to:
determining weights of sub-paths in the first path, the sub-paths being portions of the first path, the weights of the sub-paths representing correlations between two associated with the portions of the first path;
determining the first correlation based on weights of the sub-paths in the first path and the number of the sub-paths;
determining weights of sub-paths in the second path, the sub-paths being portions of the second path, the weights of the sub-paths representing correlations between two associated with the portions of the second path; and
determining the second relevance based on weights of the sub-paths in the second path and the number of sub-paths.
13. The device of claim 9, wherein the processing unit is further configured to:
determining a statistical weight associated with the second correlation by querying a statistical database storing case statistics, the statistical weight indicating a probability of occurrence of the potential complication related to the item to be inspected; and
determining the priority of the items to be inspected in the checklist based on the first correlation, the second correlation, and the statistical weight.
14. The apparatus of claim 13, wherein the statistical weight indicates a ratio of a number of the potential complications to a total number of the potential complications resulting from a failure to execute the item to be inspected.
15. The device of claim 9, wherein the processing unit is configured to:
acquiring a preset priority of the item to be inspected in the diagnosis and treatment process, wherein the preset priority is provided by a user aiming at given medical factors; and
determining the priority order of the items to be inspected based on the preset priority, the first correlation, the second correlation and a statistical weight, wherein the statistical weight indicates the occurrence probability of the potential complications related to the items to be inspected.
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Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101937489A (en) * | 2010-08-26 | 2011-01-05 | 无锡北邮感知技术产业研究院有限公司 | Medical guide information service system based on event driving and work method thereof |
| CN101976389A (en) * | 2010-10-26 | 2011-02-16 | 镇江科大船苑计算机网络工程有限公司 | Medical examination electronic-queuing management system and method |
| WO2013104799A1 (en) * | 2012-01-13 | 2013-07-18 | Sovinty | Interactive system for tracking a series of ordered steps |
| CN103617343A (en) * | 2013-11-06 | 2014-03-05 | 中国人民解放军第四军医大学 | Emergency treatment electronic medical record system and information processing method thereof |
| CN103714236A (en) * | 2012-10-02 | 2014-04-09 | 佳能株式会社 | Medical image display apparatus and medical image display method |
| CN104200079A (en) * | 2014-08-22 | 2014-12-10 | 首都医科大学附属北京佑安医院 | Clinical diagnosis and treatment route generating method and system |
| CN104463748A (en) * | 2014-10-29 | 2015-03-25 | 广州河谷互动医疗科技有限公司 | Imaging medical information sharing system based on embedded type operation system and cloud platform |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20120290322A1 (en) * | 2011-05-10 | 2012-11-15 | David Bergman | Systems and methods for coordinating the delivery of high-quality health care over an information network |
-
2015
- 2015-12-25 CN CN201510997303.XA patent/CN106919777B/en active Active
Patent Citations (7)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN101937489A (en) * | 2010-08-26 | 2011-01-05 | 无锡北邮感知技术产业研究院有限公司 | Medical guide information service system based on event driving and work method thereof |
| CN101976389A (en) * | 2010-10-26 | 2011-02-16 | 镇江科大船苑计算机网络工程有限公司 | Medical examination electronic-queuing management system and method |
| WO2013104799A1 (en) * | 2012-01-13 | 2013-07-18 | Sovinty | Interactive system for tracking a series of ordered steps |
| CN103714236A (en) * | 2012-10-02 | 2014-04-09 | 佳能株式会社 | Medical image display apparatus and medical image display method |
| CN103617343A (en) * | 2013-11-06 | 2014-03-05 | 中国人民解放军第四军医大学 | Emergency treatment electronic medical record system and information processing method thereof |
| CN104200079A (en) * | 2014-08-22 | 2014-12-10 | 首都医科大学附属北京佑安医院 | Clinical diagnosis and treatment route generating method and system |
| CN104463748A (en) * | 2014-10-29 | 2015-03-25 | 广州河谷互动医疗科技有限公司 | Imaging medical information sharing system based on embedded type operation system and cloud platform |
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