CN111627538A - Quality monitoring method, device, system, equipment and medium for nursing tasks - Google Patents
Quality monitoring method, device, system, equipment and medium for nursing tasks Download PDFInfo
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Abstract
The disclosure relates to a nursing task quality monitoring method, a nursing task quality monitoring device, a nursing task quality monitoring system, electronic equipment and a computer readable storage medium, relates to the technical field of computers, and can be applied to a scene of monitoring the quality of nursing services. The quality monitoring method of the nursing task comprises the following steps: responding to the starting triggering operation of starting a nursing task of the executive object, and acquiring the identity information and the starting triggering time of the executive object; determining a task to be executed corresponding to the execution object according to the identity information and the starting trigger time; acquiring vital sign data, and generating actual execution data of a task to be executed according to the vital sign data; and responding to the ending triggering operation of the ending nursing task of the executive object, determining the execution score of the task to be executed according to the actual execution data, and determining the quality grade of the nursing task according to the execution score. The system can realize automatic quality monitoring of nursing tasks by combining the label information and the intelligent equipment.
Description
Technical Field
The present disclosure relates to the field of computer technologies, and in particular, to a quality monitoring method for a care task, a quality monitoring device for a care task, a quality monitoring system for a care task, an electronic device, and a computer-readable storage medium.
Background
With the continuous rise and development of the endowment service industry, the item content, quality control and service evaluation and improvement of the endowment service project become the key focus of the endowment service industry. The endowment service items generally include: dietary services, mental and mental support services, educational services, lifestyle care services, geriatric care services, assisted medical care services, and the like.
At present, the quality monitoring of the endowment service project is mainly that a manager initiates a patrol task through a government manager system, and when a nursing institution system receives a task request, the manager can perform institution patrol, quality inspection of nursing tasks, service quality inspection of nursing staff and the like through an offline mode; and then, uploading the inspection result and the score to a nursing institution system to realize quality monitoring of nursing service.
It is to be noted that the information disclosed in the above background section is only for enhancement of understanding of the background of the present disclosure, and thus may include information that does not constitute prior art known to those of ordinary skill in the art.
Disclosure of Invention
The present disclosure is directed to a method for monitoring quality of a care task, a device for monitoring quality of a care task, a system for monitoring quality of a care task, an electronic device, and a computer-readable storage medium, so as to overcome, at least to some extent, a problem that quality control is performed manually, such as a missed recording phenomenon or a problem that care service data is artificially fake.
Additional features and advantages of the disclosure will be set forth in the detailed description which follows, or in part will be obvious from the description, or may be learned by practice of the invention.
According to a first aspect of the present disclosure, there is provided a method of quality monitoring of care tasks, comprising: responding to the starting triggering operation of starting a nursing task of the executive object, and acquiring the identity information and the starting triggering time of the executive object; determining a task to be executed corresponding to the execution object according to the identity information and the starting trigger time; acquiring vital sign data, and generating actual execution data of a task to be executed according to the vital sign data; the vital sign data is obtained by monitoring an executed object corresponding to a task to be executed in real time by intelligent medical equipment; and responding to the ending triggering operation of the ending nursing task of the executive object, determining the execution score of the task to be executed according to the actual execution data, and determining the quality grade of the nursing task according to the execution score.
Optionally, the acquiring the identity information and the start trigger time of the executing subject in response to the starting trigger operation of the executing subject for starting the nursing task includes: controlling the reader to respond to the starting triggering operation, and acquiring the label information of the execution object by the reader; and acquiring identity information and starting triggering time according to the label information acquired by the reader.
Optionally, determining a task to be executed corresponding to the execution object according to the identity information and the start trigger time includes: determining an execution time interval of the nursing task according to the identity information and the starting trigger time; and determining the standard starting time, the standard execution duration and the standard execution times of the target execution item according to the execution time interval.
Optionally, generating actual execution data of the task to be executed according to the vital sign data includes: determining a target execution project corresponding to a task to be executed; determining actual execution data according to the vital sign data; wherein the actual execution data includes a start time, an execution number, and an execution time length of the target execution item.
Optionally, determining an execution score of the task to be executed according to the actual execution data includes: acquiring standard starting time, standard execution duration and standard execution times of a target execution item; the start time, the number of executions, and the execution time period are compared with the standard start time, the standard execution time period, and the standard number of executions, respectively, to determine the execution score.
Optionally, the method further includes: if the reader is detected to respond to multiple trigger operations of the execution object in the execution time interval, acquiring candidate trigger time for determining each trigger operation from the reader; acquiring the suggested end time of the task to be executed in the execution time interval; and determining the actual end time of the task to be executed from the candidate trigger times according to the suggested end time so as to generate actual execution data.
Optionally, the method further includes: acquiring a preset early warning score threshold corresponding to a task to be executed; and if the execution score is smaller than the early warning score threshold value, generating the detailed execution information of the nursing tasks according to the actual execution data, and sending the identity information, the execution score and the detailed execution information to the nursing service monitoring platform.
According to a second aspect of the present disclosure, there is provided a quality monitoring device for a care task, comprising: the starting triggering module is used for responding to the starting triggering operation of starting the nursing task of the executive object and acquiring the identity information and the starting triggering time of the executive object; the task determining module is used for determining a task to be executed corresponding to the execution object according to the identity information and the starting trigger time; the data determining module is used for acquiring the vital sign data and generating actual execution data of a task to be executed according to the vital sign data; the vital sign data is obtained by monitoring an executed object corresponding to a task to be executed in real time by intelligent medical equipment; and the execution score determining module is used for responding to the ending triggering operation of the nursing task ending of the executive object, determining the execution score of the task to be executed according to the actual execution data, and determining the quality grade of the nursing task according to the execution score.
Optionally, the start triggering module includes a start triggering unit, configured to control the reader to respond to the start triggering operation, and the reader acquires tag information of the execution object; and determining identity information and starting triggering time according to the label information acquired by the reader.
Optionally, the task determining module includes a task determining unit, configured to determine an execution time interval of the care task according to the identity information and the start trigger time; and determining the standard starting time, the standard execution duration and the standard execution times of the target execution item according to the execution time interval.
Optionally, the data determining module includes a first data determining unit, configured to determine a target execution item corresponding to the task to be executed; determining actual execution data according to the vital sign data; wherein the actual execution data includes a start time, an execution number, and an execution time length of the target execution item.
Optionally, the execution score determining module includes an execution score determining unit, configured to obtain a standard start time, a standard execution duration, and a standard execution number of the target execution item; the start time, the number of executions, and the execution time period are compared with the standard start time, the standard execution time period, and the standard number of executions, respectively, to determine the execution score.
Optionally, the data determining module includes a second data determining unit, configured to obtain candidate trigger times of the trigger operations from the reader if it is detected that the reader responds to multiple trigger operations of the execution object within the execution time interval; acquiring the suggested end time of the task to be executed in the execution time interval; and determining the actual end time of the task to be executed from the candidate trigger times according to the suggested end time so as to generate actual execution data.
Optionally, the quality monitoring device for the nursing task further includes a data sending module, configured to obtain a preset early warning score threshold corresponding to the task to be executed; and if the execution score is smaller than the early warning score threshold value, generating the detailed execution information of the nursing tasks according to the actual execution data, and sending the identity information, the execution score and the detailed execution information to the nursing service monitoring platform.
According to a third aspect of the present disclosure, there is provided a quality monitoring system for a care task, comprising: the reader is used for responding to the execution triggering operation of the execution object aiming at the nursing task and determining the task to be executed according to the execution triggering operation; the intelligent medical equipment is used for monitoring vital sign data of an executed object corresponding to a task to be executed in real time; and the score determining subsystem is used for generating actual execution data of the task to be executed according to the vital sign data and determining an execution score of the task to be executed according to the actual execution data.
According to a fourth aspect of the present disclosure, there is provided an electronic device comprising: a processor; and a memory having computer readable instructions stored thereon which, when executed by the processor, implement a method of quality monitoring of care tasks according to any of the above.
According to a fifth aspect of the present disclosure, there is provided a computer readable storage medium having stored thereon a computer program which, when executed by a processor, implements a method of quality monitoring of care tasks according to any one of the above.
The technical scheme provided by the disclosure can comprise the following beneficial effects:
according to the nursing task quality monitoring method in the exemplary embodiment of the disclosure, the starting triggering operation of starting the nursing task by the executing object is responded, and the identity information and the starting triggering time of the executing object are acquired; determining a task to be executed corresponding to the execution object according to the identity information and the starting trigger time; acquiring vital sign data, and generating actual execution data of a task to be executed according to the vital sign data; the vital sign data is obtained by monitoring an executed object corresponding to a task to be executed in real time by intelligent medical equipment; and responding to the ending triggering operation of the ending nursing task of the executive object, determining the execution score of the task to be executed according to the actual execution data, and determining the quality grade of the nursing task according to the execution score. On one hand, the intelligent medical equipment detects the vital sign data of the executed object, the actual execution data of the task to be executed is generated according to the vital sign data, the quality grade of the nursing task can be determined according to the actual execution data, and the processing efficiency of determining the quality grade can be improved. On the other hand, the execution score of the task to be executed is determined according to the actual execution data, so that the patrol personnel do not need to manually acquire the service quality data of the nursing task in an offline mode, and the cost of manpower and material resources can be saved. In another aspect, the actual execution data is obtained through the vital sign data generated by the intelligent medical equipment, and then the execution score of the task to be executed is determined, so that the problems of omission and cheating caused by manual operation can be avoided, and the accuracy of the data such as the execution score and the quality grade can be ensured.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
The accompanying drawings, which are incorporated in and constitute a part of this specification, illustrate embodiments consistent with the present disclosure and together with the description, serve to explain the principles of the disclosure. It is to be understood that the drawings in the following description are merely exemplary of the disclosure, and that other drawings may be derived from those drawings by one of ordinary skill in the art without the exercise of inventive faculty. In the drawings:
fig. 1 schematically shows a flow chart of a method of quality monitoring of care tasks according to an exemplary embodiment of the present disclosure;
FIG. 2 schematically illustrates a data interaction diagram of a quality monitoring method of care tasks according to an exemplary embodiment of the present disclosure;
FIG. 3 schematically illustrates a flow chart for obtaining execution object identity information and execution start time according to an exemplary embodiment of the present disclosure;
FIG. 4 schematically illustrates a flow chart for determining information about a target execution item, according to an exemplary embodiment of the present disclosure;
FIG. 5 schematically illustrates a flow chart for determining actual execution data, according to some exemplary embodiments of the present disclosure;
FIG. 6 schematically illustrates a flow chart for determining an execution score according to an exemplary embodiment of the present disclosure;
FIG. 7 schematically illustrates a flowchart for determining actual execution data according to another exemplary embodiment of the present disclosure;
fig. 8 schematically illustrates a flow chart of sending execution detail information to a monitoring platform, according to some exemplary embodiments of the present disclosure;
FIG. 9 schematically illustrates a block diagram of a quality monitoring device for care tasks according to an exemplary embodiment of the present disclosure;
FIG. 10 schematically illustrates a block diagram of a quality monitoring system for care tasks according to an exemplary embodiment of the present disclosure;
FIG. 11 schematically illustrates a block diagram of an electronic device according to an exemplary embodiment of the present disclosure;
fig. 12 schematically illustrates a schematic diagram of a computer-readable storage medium according to an exemplary embodiment of the present disclosure.
Detailed Description
Example embodiments will now be described more fully with reference to the accompanying drawings. Example embodiments may, however, be embodied in many different forms and should not be construed as limited to the embodiments set forth herein; rather, these embodiments are provided so that this disclosure will be thorough and complete, and will fully convey the concept of example embodiments to those skilled in the art. The same reference numerals denote the same or similar parts in the drawings, and thus, a repetitive description thereof will be omitted.
Furthermore, the described features, structures, or characteristics may be combined in any suitable manner in one or more embodiments. In the following description, numerous specific details are provided to give a thorough understanding of embodiments of the disclosure. One skilled in the relevant art will recognize, however, that the subject matter of the present disclosure can be practiced without one or more of the specific details, or with other methods, components, devices, steps, and so forth. In other instances, well-known structures, methods, devices, implementations, materials, or operations are not shown or described in detail to avoid obscuring aspects of the disclosure.
The block diagrams shown in the figures are functional entities only and do not necessarily correspond to physically separate entities. That is, these functional entities may be implemented in the form of software, or in one or more software-hardened modules, or in different networks and/or processor devices and/or microcontroller devices.
The item content, quality control and service evaluation and improvement of the endowment service project are becoming important concerns of the endowment service industry. At present, the quality monitoring of the endowment service project is mainly that a manager initiates a patrol task through a government manager system, and when a nursing institution system receives a task request, the manager can perform institution patrol, quality inspection of nursing tasks, service quality inspection of nursing staff and the like through an offline mode; and then, uploading the inspection result and the score to a nursing institution system to realize quality monitoring of nursing service. The patrol quality monitoring mode of the nursing task lacks the automatic patrol support of the system and needs manual participation; in addition, since the quality inspection for the nursing tasks and the inspection for the quality of service of the nursing staff are both completed manually, the acquired quality inspection data may have data omission or artificial counterfeiting.
Based on this, in the present exemplary embodiment, first, a quality monitoring method for a care task is provided, where the quality monitoring method for a care task of the present disclosure may be implemented by using a server, for example, the server may be a background server for implementing patrol quality monitoring for a care task, and the method of the present disclosure may also be implemented by using a terminal device, where the terminal described in the present disclosure may include a mobile terminal such as a mobile phone, a tablet computer, a notebook computer, a palm computer, a Personal Digital Assistant (PDA), and a fixed terminal such as a desktop computer. Fig. 1 schematically illustrates a schematic diagram of a quality monitoring method flow of a care task, according to some embodiments of the present disclosure. Referring to fig. 1, the quality monitoring method of a care task may include the steps of:
step S110, responding to the starting triggering operation of starting the nursing task of the executive object, and acquiring the identity information and the starting triggering time of the executive object.
And step S120, determining the task to be executed corresponding to the execution object according to the identity information and the starting trigger time.
Step S130, vital sign data are obtained, and actual execution data of a task to be executed are generated according to the vital sign data; the vital sign data is obtained by monitoring an executed object corresponding to a task to be executed in real time by the intelligent medical equipment.
Step S140, responding to the ending triggering operation of the ending nursing task of the executive object, determining the execution score of the task to be executed according to the actual execution data, and determining the quality grade of the nursing task according to the execution score.
According to the quality monitoring method for nursing tasks in the exemplary embodiment, on one hand, the intelligent medical device detects the vital sign data of the executed subject, the actual execution data of the task to be executed is generated according to the vital sign data, the quality level of the nursing task can be determined according to the actual execution data, and the processing efficiency of determining the quality level can be improved. On the other hand, the execution score of the task to be executed is determined according to the actual execution data, so that the patrol personnel do not need to manually acquire the service quality data of the nursing task in an offline mode, and the cost of manpower and material resources can be saved. In another aspect, the actual execution data is obtained through the vital sign data generated by the intelligent medical equipment, and then the execution score of the task to be executed is determined, so that the problems of omission and cheating caused by manual operation can be avoided, and the accuracy of the data such as the execution score and the quality grade can be ensured.
Next, a quality monitoring method of a care task in the present exemplary embodiment will be further described.
In step S110, in response to the start trigger operation for starting the care task by the executing subject, the identity information and the start trigger time of the executing subject are acquired.
In some exemplary embodiments of the present disclosure, the execution target may be a caregiver of a medical institution such as a nursing home, a hospital, or the like, or may be an intelligent medical robot capable of executing a nursing service. The executed object can be a patient or other nursing staff in a medical institution, and the like, and can also be a simulated machine patient. The nursing task may be a nursing service performed by the performing subject for the performed subject, for example, the nursing task may be turning care, oral care, health care, etc. performed by a nursing staff for a bedridden patient; the nursing task can also be postpartum nursing of the nursing staff for the lying-in woman; the nursing task may also be related nursing of the elderly by nursing staff, and the like, and the specific form of the nursing task is not limited in any particular way by the present disclosure. The start trigger operation may be a trigger operation performed on the relevant device before the subject intends to start performing the care task. The identity information may be relevant identity information of the subject of execution, for example, the identity information may include the name, position, sex, etc. of the caregiver; the identity information may also be a number, careable scope, etc. of the intelligent medical robot. The starting trigger time may be a time of a corresponding starting trigger operation when the execution object starts the task to be executed.
Referring to fig. 2, fig. 2 schematically shows a data interaction diagram of a quality monitoring method of a care task. In step S201, when the executing subject prepares for a care service for the executed subject, the executing subject may make contact with the reader 220 through the electronic tag 210 to perform a start trigger operation for a care task; in step S202, when the start triggering operation of the execution subject is responded, the identity information and the start triggering time of the execution subject may be acquired, and in step S203, the start timing of the nursing task in the nursing system 250 is started in synchronization.
According to some exemplary embodiments of the present disclosure, a reader is controlled to respond to a start trigger operation, and tag information of an execution object is acquired by the reader; and determining identity information and starting triggering time according to the label information acquired by the reader. The principle of Radio Frequency Identification (RFID) technology may be that non-contact data communication is performed between a Reader and an electronic Tag (Tag) to achieve the purpose of identifying a target. The reader can be a device for reading information in the tag or writing information required to be stored by the tag into the tag; the electronic tag may be composed of a transmitting/receiving antenna, an alternating current/direct current (AC/DC) circuit, a demodulation circuit, a logic control circuit, a memory, and a modulation circuit.
In the disclosure, the electronic tag technology can be fused to realize quality monitoring of nursing tasks. In an exemplary embodiment of the present disclosure, the caregiver uniform may be equipped with an RFID passive electronic tag, for example, the electronic tag may be placed in the caregiver's sleeve, chest, etc.; in addition, a reader may be installed on a care bed of the subject to be performed (i.e., the subject to be cared). Referring to fig. 3, fig. 3 schematically shows a flowchart for obtaining execution object identity information and an execution start time. In step S310, when the caregiver aligns the electronic tag with the reader installed on the nursing bed, a start triggering operation for starting a nursing task may be performed, and the reader will acquire the electronic tag of the execution target. When the reader responds to the starting triggering operation, the card punching operation of the executed object is completed. In step S320, the nursing patrol quality control server, referred to as a quality control server for short, may acquire the identity information and the card punching time (i.e., the start trigger time) of the execution object according to the tag information of the execution object.
In step S120, a task to be executed corresponding to the execution object is determined according to the identity information and the start trigger time.
In some exemplary embodiments of the present disclosure, the task to be performed may be a specific care task corresponding to a care service that needs to be performed by the subject at this time. The start execution state may indicate a state in which the execution object is executing the task to be executed, in which the execution of the task to be executed has already started. Referring to fig. 2, in step S204, a task to be performed corresponding to the execution object is stored in the care system. In step S205, the quality control server 230 may determine and acquire the task to be executed by the execution target in the time period according to the acquired identity information of the execution target and the start trigger time, and switch the state of the task to be executed to the start execution state, which indicates that the execution target has started to perform the care service.
According to some exemplary embodiments of the present disclosure, the task to be performed includes at least one target execution item, and an execution time interval of the care task is determined according to the identity information and the start trigger time; and determining the standard starting time, the standard execution duration and the standard execution times of the target execution item according to the execution time interval. The target execution item may be a task included in the task to be executed, and one or more target execution items may be included in the task to be executed. For example, a nursing task for a bedridden patient may include a target execution item of 10 turns, and the present disclosure will be described by taking as an example a nursing task in which a subject turns for a subject to be executed. The execution time interval may be a time interval in which a care task performed by the subject is executed. The standard start time may be a task start time corresponding to each target execution item according to a preset task plan. The standard execution time length may be a duration corresponding to each target execution item according to a preset mission plan. The standard execution times may be times that each target execution item should be executed according to a preset mission plan.
Referring to fig. 4, fig. 4 schematically shows a flowchart for determining relevant information of a target execution item. In step S410, the quality control server may obtain the care task corresponding to the execution object according to the identity information of the execution object and the start trigger time, and determine an execution time interval of the care task according to the care task plan. In step S420, a target execution item included in the task to be executed in the execution time interval may be determined, and a standard start time, a standard execution duration, and a standard execution number of the target execution item may be determined.
In step S130, vital sign data is acquired, and actual execution data of a task to be executed is generated according to the vital sign data; the vital sign data is obtained by monitoring an executed object corresponding to a task to be executed in real time by the intelligent medical equipment.
In some exemplary embodiments of the present disclosure, the smart medical device may be a device capable of acquiring vital sign data of a human body through sensors or other sensing technologies. For example, the intelligent medical device may be an intelligent mattress, which may employ fiber optic sensing technology to monitor vital sign data of a human body. The vital sign may be basic vital data, such as blood pressure, heart rate, pulse, respiration, blood oxygen, etc., which is basically embodied by a living person. The vital sign data may be vital sign data of a certain subject being performed, e.g., the vital sign data may include, but is not limited to, a blood pressure value, a heart rate value, a pulse value, a respiration value, a blood oxygen value, and the like. The actual execution data may be execution data generated when the caregiver performs a care service with respect to the carereceiver.
Referring to fig. 2, in step S206, the smart medical device 240 may monitor vital sign data of the executed subject in real time through sensors or other sensing technologies on the device. Since the vital sign data of the executed subject reflects the execution situation of the task to be executed to a certain extent, the actual execution data of the executed subject in the nursing task can be generated according to the change situation of the vital sign data. Therefore, in step S207, the quality control server monitors the vital sign data of the executed object according to the smart medical device, and may correspondingly generate the actual execution data of the task to be executed according to the real-time change of the vital sign data.
According to some exemplary embodiments of the present disclosure, a target execution item corresponding to a task to be executed is determined; determining actual execution data according to the vital sign data; wherein the actual execution data includes a start time, an execution number, and an execution time length of the target execution item. The target execution item may be an execution item included in a care service actually performed by the execution subject with respect to the executed subject. The start time may be the actual start time of the target execution item. The number of executions may be the number of executions corresponding to the target execution item. The execution duration may be the actual duration of the target execution item.
Referring to fig. 5, fig. 5 schematically shows a flowchart for determining actual execution data. In step S510, the monitoring server may determine a target execution item corresponding to the executed object according to the task to be executed, for example, the monitoring server may determine a target execution item that the executed object should perform in a certain time interval according to the task to be executed in the time interval. In step S520, the monitoring server may determine actual execution data of the task to be processed through the vital sign data of the executed subject acquired by the smart medical device. For example, when a nursing staff performs a turning nursing service for a bedridden patient, and the nursing staff turns over the patient, the vital sign data of the patient will change correspondingly, for example, if the lying position mode of the patient changes, the vital sign data will change correspondingly. According to the changed vital sign data, the patient can be judged to be performed with the turnover nursing service. It is easily understood by those skilled in the art that other nursing operations performed by the nursing staff for the patient can be derived according to other vital sign data change rules of the patient, and the disclosure is not limited in any way. According to the vital sign data, the execution starting time, the execution times and the execution duration of each target execution item can be determined. For example, it can be determined when a caregiver starts to perform a turn-over nursing service on a patient according to vital sign data of the patient during each turn-over, the specific duration of the turn-over nursing service during each turn-over, the number of times that the caregiver performs the turn-over nursing service for the patient, and the like. The care services performed by the performing subjects can be scored according to these actual performance data.
In step S140, in response to an end triggering operation in which the executing subject ends the care task, an execution score of the task to be executed is determined according to the actual execution data, so as to determine a quality level of the care task according to the execution score.
In some exemplary embodiments of the present disclosure, the end triggering operation may be a triggering operation performed by the subject with respect to the relevant device at the time of ending the care service. For example, the tag information of the execution object may be read by the reader, so that the execution object completes the start triggering operation. Therefore, when the executing object finishes the nursing task, the electronic tag held by the executing object can be contacted with the reader again, so that the reader reads the tag information of the executing object and finishes the finishing triggering operation. The execution score may be a score determined for an actual execution situation of the execution object after the execution object finishes the task to be executed. The quality level may be a level corresponding to the quality of the nursing service performed by the subject, and the quality level may include very good (5), good (4), general (3), poor (2), (1), and the like, and the quality level may be expressed in percentage, which is not limited in any way by the present disclosure.
Referring to fig. 2, in step 208, when the subject completes the care task, the electronic tag may be used to trigger the reader to complete the end trigger operation (i.e., leave the punch operation); in step S209, after the end trigger operation is performed, the nursing task ends the time count. In step S210, the reader responds to the trigger operation for ending the nursing task of the executive object, and the quality control server may determine the execution score of the task to be executed according to the comparison result between the actual execution data and the preset nursing plan, and determine the quality level of the nursing service according to the execution score, so as to determine the quality control operation of the next step according to the quality level.
According to some exemplary embodiments of the present disclosure, a standard start time, a standard execution duration, and a standard execution number of a target execution item are acquired; the start time, the number of executions, and the execution time period are compared with the standard start time, the standard execution time period, and the standard number of executions, respectively, to determine the execution score. Referring to fig. 6, fig. 6 schematically shows a flow chart for determining an execution score. In step S610, the task to be executed corresponding to the user in the time interval is obtained from the care plan, and the standard start time, the standard execution number, and the like of the target execution item in the task to be executed are determined. In step S620, the start time, the execution times and the execution time of the target execution items performed by the caregiver for the cared person may be compared, and the execution score of the task to be executed may be determined according to the comparison result.
For example, the calculation flow of the task to be executed is as follows: the score calculation is performed in units of one day, for example, the care plan defines that the turnover care is executed 4 times per day, the total score is 100 points per day, and each score is 25 points. Namely, the total score S is 100, the execution times are marked as N, and each execution score full score P is S/N. In calculating the performance score of the task to be performed, a score influencing factor may be determined, for example, the error of the starting time of the caregiver for performing the care task from the standard starting time may be taken as the influencing factor. Subtracting 5 minutes from 30 minutes before and after the predicted execution starting time, namely the error range of the starting time is [ -30, 30 ]; 30 to 60 minutes before and after the expected execution start time, i.e., the error range of the start time is [ -60, -30 ]. sup.30, 60], minus 10 minutes; more than 60 minutes before and after the predicted execution start time, i.e. the error range of the start time is [ -90, -60 ]. sup.60, 90], minus 20 minutes, until the total subtraction; if not, the score is 0. In addition, the comparison result of the execution time length of the nursing task of the nursing staff and the standard execution time length can be used as the influence factor. For example, the standard execution time length of the turn-over care task defined in the care plan is 5 minutes, and when the nursing staff executes the turn-over care task for less than 5 minutes, corresponding deduction is carried out according to the difference time length.
According to the execution score calculation rule, the nursing staff 1 needs to execute the turnover nursing task for the nursing staff A on a certain day, and the nursing plan defines that the nursing staff 1 needs to execute 4 turnover tasks on the day, and the duration of each turnover nursing is 5 minutes. If the nursing staff 1 executes the turnover nursing task on time every time on the day and the duration of executing the turnover nursing task is 5 minutes, the executive score of the nursing staff is 100 points. If the nursing staff 1 carries out the turnover task for the first time, the starting time is 15 minutes earlier, but the execution time is 5 minutes; when the turning-over nursing is carried out for the second time and the third time, the starting time is 15 minutes later, but the execution time is 5 minutes; and fourthly, turning over nursing is carried out according to the standard starting time, the duration is 5 minutes, and the execution score of the nursing staff 1 is 85 according to the score influence factors.
It should be noted that, in other exemplary embodiments of the present disclosure, other factors may also be used as the influence factors of the execution score, and the present disclosure does not make any special limitation on this.
According to some exemplary embodiments of the present disclosure, if it is detected that the reader responds to multiple trigger operations of the execution object within the execution time interval, candidate trigger times of the trigger operations are acquired from the reader; acquiring the suggested end time of the task to be executed in the execution time interval; and determining the actual end time of the task to be executed from the candidate trigger times according to the suggested end time so as to generate actual execution data. The trigger operation may be a corresponding trigger operation when the execution object aligns the electronic tag with the reader. The candidate trigger time may be a corresponding time for each trigger operation. The suggested end time may be an end time corresponding to the task to be executed determined according to the standard start time and the standard execution duration. The actual end time may be an end time actually corresponding to the execution object when the to-be-executed task is performed. The actual execution data may be execution data generated by the execution object in the process of executing the task to be executed.
Since in some scenarios the reader may be mounted on the nursing bed of the nursing staff. When nursing service is performed on a patient by a nursing staff, a false trigger operation can be generated, for example, in the process of performing nursing service for a certain time, an electronic tag of the nursing staff contacts a reader for multiple times to generate the false trigger operation. When the nursing staff starts to perform the nursing task, the reader can be contacted once through the electronic tag, and the fact that the nursing task is started to be performed is identified. Referring to fig. 7, fig. 7 schematically shows another flowchart for determining actual execution data. In step S710, when the reader is touched carelessly multiple times during the execution, the reader may record the trigger time of each trigger operation as a candidate trigger time. In step S720, the quality control server may calculate the recommended end time of the task according to the standard start time and the standard execution time of the task to be executed recorded in the care task plan, and a time value obtained by adding the earliest start time to the standard execution time is the recommended end time. In step S730, the candidate trigger times corresponding to the multiple trigger operations are compared, the candidate trigger time closest to the time value is used as the actual end time of the current task, and the actual execution data is generated according to the determined actual end time.
According to some exemplary embodiments of the present disclosure, a pre-set early warning score threshold corresponding to a task to be executed is obtained; and if the execution score is smaller than the early warning score threshold value, generating the detailed execution information of the nursing tasks according to the actual execution data, and sending the identity information, the execution score and the detailed execution information to the nursing service monitoring platform. The early warning score threshold may be a preset value for comparison with the performance score. The detailed execution information may be detailed information of an execution process correspondingly generated in the process of executing the nursing task by the subject. The monitoring platform can be a management platform used for monitoring the execution condition of the nursing tasks of the executed subjects, and the monitoring platform can record the execution scores of the executed subjects, so that an administrator using the monitoring platform can perform corresponding operations according to the execution scores recorded by the monitoring platform.
Referring to fig. 8, fig. 8 schematically shows a flow chart for sending execution detail information to a monitoring platform. In step S810, after obtaining the execution score of the execution object, an early warning score threshold value preset by the system and corresponding to the task to be executed may be obtained. In step S820, the execution score is compared with the early warning score threshold, if the execution score is smaller than the early warning score threshold, actual execution data corresponding to the execution score is acquired, and detailed execution information of the care task is generated according to the actual execution data. And sending the identity information, the execution score and the execution detailed information of the execution object to a monitoring platform corresponding to the execution object. Referring to fig. 2, in step S211, the monitoring platform may issue warning information according to the execution score and the execution detailed information of the execution subject, i.e. provide corresponding advice and direction modification to the execution subject, so as to implement monitoring and controlling of the care quality of the care task. The care system may respond to the processing score result transmitted from the quality control server in step S212, and transmit the score result to the execution subject in step S213, so that the execution subject responds to the relevant information.
For example, within a period of time, the full score corresponding to each day of nursing tasks of the executed subject is 100, the early warning score threshold value may be set to 90, and after the execution score is determined, the execution score and the early warning score threshold value may be compared, for example, if the execution score is 100, the execution score and the execution detailed information are sent to the monitoring platform, and then the monitoring platform does not need to perform any subsequent operation; if the execution score is 85 scores, after the execution score and the execution detailed information are sent to the monitoring platform, the monitoring platform can send a corresponding correction suggestion to the execution object according to the execution condition of the execution object so that the execution object can correspondingly adjust the execution process of the nursing service; or the corresponding task quantity of each executive object is adjusted according to the actual requirement so that the executive objects can better complete the nursing service.
In summary, the nursing task quality monitoring method disclosed by the present disclosure responds to the starting trigger operation of the executed object for the nursing task, and acquires the identity information and the starting trigger time of the executed object; determining a task to be executed corresponding to the execution object according to the identity information and the starting trigger time; acquiring vital sign data, and generating actual execution data of a task to be executed according to the vital sign data; the vital sign data is obtained by monitoring an executed object corresponding to a task to be executed in real time by intelligent medical equipment; and responding to the ending triggering operation of the ending nursing task of the executive object, determining the execution score of the task to be executed according to the actual execution data, and determining the quality grade of the nursing task according to the execution score. On one hand, the intelligent medical equipment detects the vital sign data of the executed object, the actual execution data of the task to be executed is generated according to the vital sign data, the quality grade of the nursing service can be determined according to the actual execution data, and the processing efficiency of determining the quality grade can be improved. On the other hand, the execution fraction of the task to be executed is determined according to the actual execution data, so that the quality monitoring of the nursing task executed by the execution object by the night patrol staff can be realized, the night patrol staff does not need to manually acquire the service quality data of the nursing task through an offline mode, and the cost of manpower and material resources can be saved. On the other hand, the vital sign data generated by the intelligent medical equipment is used for obtaining actual execution data and generating an execution score of a task to be executed, so that the problems of omission and cheating caused by manual operation can be avoided, the accuracy of the data such as the execution score and the quality grade can be ensured, on the other hand, the execution score and the execution detailed information of an execution object are sent to a monitoring platform, and the monitoring platform can send nursing service rectification feedback information to the execution object according to the execution detailed information to realize the quality monitoring of the nursing service.
It is noted that although the steps of the methods of the present invention are depicted in the drawings in a particular order, this does not require or imply that the steps must be performed in this particular order, or that all of the depicted steps must be performed, to achieve desirable results. Additionally or alternatively, certain steps may be omitted, multiple steps combined into one step execution, and/or one step broken down into multiple step executions, etc.
Furthermore, in the present exemplary embodiment, a quality monitoring device for care tasks is also provided. Referring to fig. 9, the quality monitoring apparatus 900 for the care task may include: a start triggering module 910, a task determining module 920, a data determining module 930, and an execution score determining module 940.
Specifically, the start triggering module 910 may be configured to respond to a start triggering operation for starting a care task by an executing subject, and acquire identity information and start triggering time of the executing subject; the task determining module 920 may be configured to determine a task to be executed corresponding to the execution object according to the identity information and the start trigger time; the data determining module 930 may be configured to obtain the vital sign data, and generate actual execution data of a task to be executed according to the vital sign data; the vital sign data is obtained by monitoring an executed object corresponding to a task to be executed in real time by intelligent medical equipment; the execution score determining module 940 may be configured to determine an execution score of the task to be executed according to the actual execution data in response to an end triggering operation of the executing subject for ending the care task, so as to determine a quality level of the care task according to the execution score.
The quality monitoring device 900 for nursing tasks monitors vital sign data of an executed subject in real time through the intelligent medical equipment, can generate actual execution data of tasks to be executed according to the vital sign data, and determines execution scores of the tasks to be executed according to the actual execution data, so that accuracy of the execution scores can be ensured, and processing efficiency is improved. The automatic patrol quality monitoring of the nursing tasks is realized by combining the electronic tag technology and the intelligent medical equipment, the patrol personnel are not required to manually acquire the service quality data of the nursing tasks in an offline mode, and the labor and material cost can be saved. Is an effective quality monitoring device for nursing tasks.
In an exemplary embodiment of the present disclosure, the start triggering module includes a start triggering unit for controlling the reader to respond to a start triggering operation and acquiring, by the reader, tag information of the execution object; and determining identity information and starting triggering time according to the label information acquired by the reader.
In an exemplary embodiment of the disclosure, the task determination module comprises a task determination unit for determining an execution time interval of the care task based on the identity information and the start trigger time; and determining the standard starting time, the standard execution duration and the standard execution times of the target execution item according to the execution time interval.
In an exemplary embodiment of the present disclosure, the data determining module includes a first data determining unit for determining a target execution item corresponding to a task to be executed; determining actual execution data according to the vital sign data; wherein the actual execution data includes a start time, an execution number, and an execution time length of the target execution item.
In an exemplary embodiment of the present disclosure, the execution score determining module includes an execution score determining unit for acquiring a standard start time, a standard execution duration, and a standard number of execution times of the target execution item; the start time, the number of executions, and the execution time period are compared with the standard start time, the standard execution time period, and the standard number of executions, respectively, to determine the execution score.
In an exemplary embodiment of the present disclosure, the data determining module includes a second data determining unit, configured to acquire a candidate trigger time of each trigger operation from the reader if it is detected that the reader responds to a plurality of trigger operations of the execution object within the execution time interval; acquiring the suggested end time of the task to be executed in the execution time interval; and determining the actual end time of the task to be executed from the candidate trigger times according to the suggested end time so as to generate actual execution data.
In an exemplary embodiment of the present disclosure, the quality monitoring device for nursing tasks further includes a data sending module, configured to obtain a preset early warning score threshold corresponding to a task to be executed; and if the execution score is smaller than the early warning score threshold value, generating the detailed execution information of the nursing tasks according to the actual execution data, and sending the identity information, the execution score and the detailed execution information to the nursing service monitoring platform.
Further, in another example embodiment, a quality monitoring system 1000 for care tasks is also provided. In particular, the quality monitoring system 1000 for a care task may include a reader 1010, an intelligent medical device 1020, and a score determination subsystem 1030.
Specifically, the reader 1010 may be configured to respond to an execution trigger operation of the execution object for the care task, and determine the task to be executed according to the execution trigger operation; the smart medical device 1020 may be used to monitor vital sign data of the executed subject corresponding to the task to be performed in real time; the score determining subsystem 1030 may be configured to generate actual execution data of the task to be executed according to the vital sign data, and determine an execution score of the task to be executed according to the actual execution data.
The quality monitoring system 1000 for nursing tasks can realize automatic patrol quality monitoring of nursing tasks by combining an electronic tag technology and intelligent medical equipment so as to monitor the nursing quality of nursing staff.
The specific details of the virtual module of the quality monitoring device for each nursing task are already described in detail in the quality monitoring method for the corresponding nursing task, and therefore are not described herein again.
It should be noted that although in the above detailed description several modules or units of the quality monitoring device of the care task are mentioned, this division is not mandatory. Indeed, the features and functionality of two or more modules or units described above may be embodied in one module or unit, according to embodiments of the present disclosure. Conversely, the features and functions of one module or unit described above may be further divided into embodiments by a plurality of modules or units.
In addition, in an exemplary embodiment of the present disclosure, an electronic device capable of implementing the above method is also provided.
As will be appreciated by one skilled in the art, aspects of the present invention may be embodied as a system, method or program product. Thus, various aspects of the invention may be embodied in the form of: an entirely hardware embodiment, an entirely software embodiment (including firmware, microcode, etc.) or an embodiment combining hardware and software aspects that may all generally be referred to herein as a "circuit," module "or" system.
An electronic device 1100 according to such an embodiment of the invention is described below with reference to fig. 11. The electronic device 1100 shown in fig. 11 is only an example and should not bring any limitations to the function and the scope of use of the embodiments of the present invention.
As shown in fig. 11, electronic device 1100 is embodied in the form of a general purpose computing device. The components of the electronic device 1100 may include, but are not limited to: the at least one processing unit 1110, the at least one memory unit 1120, a bus 1130 connecting different system components (including the memory unit 1120 and the processing unit 1110), and a display unit 1140.
Wherein the storage unit stores program code that is executable by the processing unit 1110 to cause the processing unit 1110 to perform steps according to various exemplary embodiments of the present invention as described in the above section "exemplary methods" of the present specification.
The storage unit 1120 may include readable media in the form of volatile storage units, such as a random access memory unit (RAM)1121 and/or a cache memory unit 1122, and may further include a read-only memory unit (ROM) 1123.
The storage unit 1120 may also include a program/utility 1124 having a set (at least one) of program modules 1125, such program modules 1125 including, but not limited to: an operating system, one or more application programs, other program modules, and program data, each of which, or some combination thereof, may comprise an implementation of a network environment.
The electronic device 1100 may also communicate with one or more external devices 1170 (e.g., keyboard, pointing device, bluetooth device, etc.), one or more devices that enable a user to interact with the electronic device 1100, and/or any devices (e.g., router, modem, etc.) that enable the electronic device 1100 to communicate with one or more other computing devices. Such communication may occur via an input/output (I/O) interface 1150. Also, the electronic device 1100 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN), and/or a public network such as the internet) via the network adapter 1160. As shown, the network adapter 1160 communicates with the other modules of the electronic device 1100 over the bus 1130. It should be appreciated that although not shown, other hardware and/or software modules may be used in conjunction with the electronic device 1100, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
Through the above description of the embodiments, those skilled in the art will readily understand that the exemplary embodiments described herein may be implemented by software, or by software in combination with necessary hardware. Therefore, the technical solution according to the embodiments of the present disclosure may be embodied in the form of a software product, which may be stored in a non-volatile storage medium (which may be a CD-ROM, a usb disk, a removable hard disk, etc.) or on a network, and includes several instructions to enable a computing device (which may be a personal computer, a server, a terminal device, or a network device, etc.) to execute the method according to the embodiments of the present disclosure.
In an exemplary embodiment of the present disclosure, there is also provided a computer-readable storage medium having stored thereon a program product capable of implementing the above-described method of the present specification. In some possible embodiments, aspects of the invention may also be implemented in the form of a program product comprising program code means for causing a terminal device to carry out the steps according to various exemplary embodiments of the invention described in the above-mentioned "exemplary methods" section of the present description, when said program product is run on the terminal device.
Referring to fig. 12, a program product 1200 for implementing the above method according to an embodiment of the present invention is described, which may employ a portable compact disc read only memory (CD-ROM) and include program code, and may be run on a terminal device, such as a personal computer. However, the program product of the present invention is not limited in this regard and, in the present document, a 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.
The program product may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. A 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 readable storage medium include: an electrical connection having one or more wires, a portable disk, 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.
A computer readable signal medium may include a propagated data signal with 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 readable signal medium may also be any readable medium that is not a 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 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.
Program code for carrying out operations for aspects 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, 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 computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device and partly on a remote computing device, or entirely on the remote computing device or server. In the case of a remote computing device, the remote computing device may be connected to the user computing device through any kind of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or may be connected to an external computing device (e.g., through the internet using an internet service provider).
Furthermore, the above-described figures are merely schematic illustrations of processes involved in methods according to exemplary embodiments of the invention, and are not intended to be limiting. It will be readily understood that the processes shown in the above figures are not intended to indicate or limit the chronological order of the processes. In addition, it is also readily understood that these processes may be performed synchronously or asynchronously, e.g., in multiple modules.
Other embodiments of the disclosure will be apparent to those skilled in the art from consideration of the specification and practice of the disclosure disclosed herein. This application is intended to cover any variations, uses, or adaptations of the disclosure following, in general, the principles of the disclosure and including such departures from the present disclosure as come within known or customary practice within the art to which the disclosure pertains. It is intended that the specification and examples be considered as exemplary only, with a true scope and spirit of the disclosure being indicated by the following claims.
It will be understood that the present disclosure is not limited to the precise arrangements described above and shown in the drawings and that various modifications and changes may be made without departing from the scope thereof. The scope of the present disclosure is to be limited only by the terms of the appended claims.
Claims (10)
1. A method of monitoring the quality of a care task, comprising:
responding to starting triggering operation of starting a nursing task by an executing object, and acquiring identity information and starting triggering time of the executing object;
determining a task to be executed corresponding to the execution object according to the identity information and the starting trigger time;
acquiring vital sign data, and generating actual execution data of the task to be executed according to the vital sign data; the vital sign data is obtained by monitoring an executed object corresponding to the task to be executed in real time by intelligent medical equipment;
and responding to the ending triggering operation of the executing object for ending the nursing task, determining the execution score of the task to be executed according to the actual execution data, and determining the quality grade of the nursing task according to the execution score.
2. The method for monitoring the quality of care tasks according to claim 1, wherein the acquiring the identity information and the start trigger time of the executing object in response to the executing object starting the start trigger operation of the care task comprises:
controlling a reader to respond to the starting triggering operation, and acquiring the label information of the execution object by the reader;
and determining the identity information and the start triggering time according to the tag information acquired by the reader.
3. The method for monitoring the quality of care tasks according to claim 1, wherein the task to be executed comprises at least one target execution item, and the determining the task to be executed corresponding to the execution object according to the identity information and the start trigger time comprises:
determining an execution time interval of the nursing task according to the identity information and the starting trigger time;
and determining the standard starting time, the standard execution duration and the standard execution times of the target execution item according to the execution time interval.
4. The method of claim 1, wherein the generating actual performance data for the task to be performed from the vital sign data comprises:
determining a target execution project corresponding to the task to be executed;
determining the actual execution data according to the vital sign data; wherein the actual execution data includes a start time, an execution number, and an execution time length of the target execution item.
5. The method of claim 4, wherein the determining the performance score of the task to be performed based on the actual performance data comprises:
acquiring standard starting time, standard execution duration and standard execution times of the target execution item;
comparing the start time, the execution times, and the execution duration with the standard start time, the standard execution duration, and the standard execution times, respectively, to determine the execution score.
6. The method of quality of care task monitoring according to claim 4, further comprising:
if the situation that the reader responds to the multiple trigger operations of the execution object within the execution time interval is detected, acquiring the candidate trigger time of each trigger operation from the reader;
acquiring the suggested end time of the task to be executed in the execution time interval;
and determining the actual end time of the task to be executed from each candidate trigger time according to the suggested end time so as to generate the actual execution data.
7. The method of quality of care task monitoring according to claim 1, further comprising:
acquiring a preset early warning score threshold corresponding to the task to be executed;
and if the execution score is smaller than the early warning score threshold value, generating execution detailed information of the nursing task according to the actual execution data, and sending the identity information, the execution score and the execution detailed information to a nursing service monitoring platform.
8. A quality monitoring device for a care task, comprising:
the starting triggering module is used for responding to the starting triggering operation of starting the nursing task of the executive object and acquiring the identity information and the starting triggering time of the executive object;
the task determining module is used for determining a task to be executed corresponding to the execution object according to the identity information and the starting trigger time;
the data determining module is used for acquiring vital sign data and generating actual execution data of the task to be executed according to the vital sign data; the vital sign data is obtained by monitoring an executed object corresponding to the task to be executed in real time by intelligent medical equipment;
and the execution score determining module is used for responding to the ending triggering operation of the nursing task ending of the execution object, determining the execution score of the task to be executed according to the actual execution data, and determining the quality grade of the nursing task according to the execution score.
9. An electronic device, comprising:
a processor; and
a memory having stored thereon computer readable instructions which, when executed by the processor, implement a method of quality monitoring of care tasks according to any of claims 1 to 7.
10. A computer-readable storage medium, on which a computer program is stored which, when being executed by a processor, carries out a method of quality monitoring of care tasks according to any one of claims 1 to 7.
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| CN114152953A (en) * | 2021-11-24 | 2022-03-08 | 山东蓝创网络技术股份有限公司 | Long-term care insurance service supervision system based on stereoscopic dot matrix technology |
| CN117542498A (en) * | 2024-01-08 | 2024-02-09 | 安徽医科大学第一附属医院 | Gynecological nursing management system and method based on big data analysis |
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