阅读说明：本技术 医疗保健提供者数据系统处理和分析 (Healthcare provider data system processing and analysis ) 是由 M·谭 J·奥迪恩 C·凯恩斯 R·希恩 于 2019-08-26 设计创作，主要内容包括：一种用于生成用于维持目标的指令的方法,包括将控制中心系统与多个医疗保健提供者数据系统集成,以及从医疗保健提供者数据系统获得信息。该方法然后可以使用人工智能将获得的信息与识别出的捐献中心的业务目标相关联,并使用启发式模型生成对捐献中心的指令以实现识别出的业务目标。然后,该方法可以向用户和/或用户系统呈现该指令,使得该指令可以被执行。(A method for generating instructions for maintaining a goal includes integrating a control center system with a plurality of healthcare provider data systems and obtaining information from the healthcare provider data systems. The method can then use artificial intelligence to associate the obtained information with the identified business target of the contribution center and generate instructions to the contribution center using a heuristic model to achieve the identified business target. The method may then present the instruction to a user and/or user system so that the instruction may be executed.)

1. A method for generating instructions for maintaining a target, comprising:

integrating a control center system with a plurality of healthcare provider data systems;

obtaining information from at least one of the plurality of healthcare provider data systems;

associating the obtained information with the identified business goals of the at least one donation center using artificial intelligence;

generating instructions to the at least one donation center using a heuristic model to achieve the identified business objective; and

presenting the instructions to at least one user and/or user system such that the instructions are executable by the at least one user and/or user system.

2. The method of claim 1, wherein integrating the control center system with the plurality of healthcare provider data systems comprises autonomously integrating the control center system.

3. The method of claim 1, wherein the data system is selected from the group consisting of: donor systems, screening systems, collection systems, equipment systems, supply systems, inventory systems, test systems, transportation systems, quality systems, payment systems, marketing systems, recruitment systems, engagement systems, warehouse systems, payroll systems, time tracking systems, and security systems.

4. The method of claim 1, wherein the information from the plurality of healthcare provider data systems is selected from the group consisting of: timing data, telemetry data, performance data, quality data, cost data, volume data, quantity data, rate data, personnel data, donor data, donation data, productivity data, performance data, and speed data.

5. The method of claim 1, wherein the business objective is a profile of the at least one donation center inferred based on historical information from the plurality of healthcare provider data systems.

6. The method of claim 1, further comprising:

receiving a company profile comprising a productivity goal, a performance goal, and/or a quality goal, the business goal based at least in part on at least one of the productivity goal, the performance goal, and/or the quality goal.

7. The method of claim 1, wherein the business objective comprises a received corporate profile including a location-specific profile.

8. The method of claim 1, wherein the business objective comprises a received corporate profile including a time-dependent profile.

9. The method of claim 1, wherein the traffic target is measurable.

10. The method of claim 1, wherein the instructions comprise information regarding at least one step taken to achieve the business objective.

11. The method of claim 10, wherein the instructional information is location-specific to achieve the business objective.

12. The method of claim 1, wherein the instructions are presented to the plurality of users via at least one selected from the group consisting of email, SMS, push notifications, phone calls, social media disclosures, visual feedback, auditory feedback, and tactile feedback.

13. The method of claim 1, wherein the instructions are presented to the plurality of user systems via an electronic interface.

14. The method of claim 13, wherein the electronic interface is automated.

15. The method of claim 1, wherein the instructions are presented to the plurality of user systems via a manual file upload performed by a user.

16. The method of claim 1, wherein the instructions are presented to the plurality of users such that the instructions are accessible from the group consisting of a cellular phone, a tablet, a computer, a laptop, a personal digital assistant, a digital display, a smart watch, a telephone, a pager, or a public address system.

17. The method of claim 1, further comprising:

storing information from the plurality of healthcare provider data systems in a data storage device.

18. The method of claim 1, wherein obtaining information from the plurality of healthcare provider data systems comprises extracting information from the plurality of healthcare provider data systems using a data extractor.

19. The method of claim 1, wherein the plurality of healthcare provider data systems comprises a donor management system.

20. The method of claim 1, wherein generating the instructions comprises identifying a gap between at least one production metric and a business objective based on the obtained information.

21. The method of claim 1, further comprising:

a confirmation is received from the user that the user has taken ownership of implementing the instruction.

22. The method of claim 1, further comprising:

artificial intelligence is used to monitor the effectiveness of the instructions against the business goals.

23. A system for generating instructions for maintaining a goal, comprising:

an integrator configured to integrate the control center system with at least one healthcare provider data system;

a data extractor configured to search for production data in the at least one healthcare data system and retrieve the production data from the at least one healthcare provider data system;

a data storage device configured to store the retrieved production data;

an artificial intelligence module configured to associate the retrieved production information with the identified business objective and generate instructions to achieve the identified business objective;

a virtual digital assistant configured to process the instructions and distribute the instructions to at least one recipient such that the recipient is able to execute the instructions.

24. The system of claim 23, wherein the artificial intelligence module generates the instructions using a heuristic model.

25. The system of claim 23, wherein the at least one recipient is at least one user and/or at least one donor management system.

26. The system of claim 23, wherein the integrator is configured to autonomously integrate the control center system with the at least one healthcare provider data system.

27. The system of claim 23, wherein the at least one healthcare provider data system comprises at least one selected from the group consisting of: donor systems, screening systems, collection systems, equipment systems, supply systems, inventory systems, test systems, transportation systems, quality systems, payment systems, marketing systems, recruitment systems, engagement systems, warehouse systems, payroll systems, time tracking systems, and security systems.

28. The system of claim 23, wherein production information from the plurality of healthcare provider data systems is selected from the group consisting of: timing data, telemetry data, performance data, quality data, cost data, volume data, quantity data, rate data, personnel data, donor data, donation data, productivity data, performance data, and speed data.

29. The system of claim 23, wherein the business objective is a profile of the healthcare provider inferred based on historical information from the at least one healthcare provider data system.

30. The system of claim 23, wherein the business objective is based at least in part on at least one of a productivity objective, a performance objective, and/or a quality objective contained within a company profile.

31. The system of claim 23, wherein the traffic objective is measurable.

32. The system of claim 23, wherein the instructions include information regarding at least one step to be taken to achieve the business objective.

33. The system of claim 23, wherein the instructions include location-specific information for achieving the business goals.

34. The system of claim 23, wherein the virtual digital assistant distributes the instructions via at least one selected from the group consisting of email, SMS, push notifications, phone calls, social media disclosures, visual feedback, auditory feedback, and tactile feedback.

35. The system of claim 23, further comprising an electronic interface, the virtual digital assistant configured to distribute the instructions to a plurality of user systems via the electronic interface.

36. The system of claim 23, wherein the instructions are distributed to a plurality of user systems via manual file uploads performed by users.

37. The system of claim 23, wherein the instructions are distributed to the at least one recipient such that the instructions are accessible from the group consisting of a cellular telephone, a tablet, a computer, a laptop, a personal digital assistant, a digital display, a smart watch, a telephone, a pager, or a public address system.

38. The system of claim 23, wherein the plurality of healthcare provider data systems comprises a donor management system.

39. The system of claim 23, wherein the artificial intelligence module is configured to identify at least one gap between at least one production metric and the business objective, the instructions based at least in part on the at least one gap.

40. The system of claim 23, further comprising:

an instruction listener configured to monitor the effectiveness of the instructions against a business target using artificial intelligence.

41. The system of claim 23, further comprising:

an interface configured to receive confirmation that the instruction was (a) received by a user or (b) received by a user system.

42. A non-transitory computer recordable medium having computer-executable commands that, when executed on a computing device, perform acts comprising:

obtaining location-specific information about a plurality of locations;

associating the location-specific information with a plurality of time-specific information;

identifying a business objective of a healthcare provider using a plurality of instructions;

instructions related to the business objective are selected based on (a) a location related to the business objective and/or (b) a time related to the business objective; and

instructions for achieving the business goals are provided for (a) user review and/or (b) user system execution.

Technical Field

The present invention relates to healthcare provider data systems, and more particularly to a command center for integrating multiple healthcare provider data systems for processing and analysis.

Background

Healthcare providers collect and maintain a vast amount of information and data about their businesses, including: donor, patient, employee, productivity, performance, quality, inventory, cost, etc. However, these healthcare providers rely on data reports to learn their operating conditions for performance improvement, corrective action, risk mitigation, and other business needs. These reports are generated manually by employees or automatically by computerized systems to provide a retrospective view for the business. Staff members of the healthcare provider will then analyze the data in the report and make decisions to adjust the conditions/processes to improve productivity.

Disclosure of Invention

According to some embodiments of the invention, a method includes integrating with and obtaining information from a plurality of healthcare provider data systems. The method may then use artificial intelligence to associate the information with the identified business goals and use heuristics to arrange the instructions to achieve the business goals. The method may then present the instructions to multiple users or user systems at the relevant time. In some embodiments, the integration may be autonomous. In other embodiments, the integration is done in real-time (i.e., data is received while business operations are in production).

The data system may be a donor system, a screening system, a collection system, an equipment system, a supply system, an inventory system, a testing system, a transportation system, a quality system, a payment system, a marketing system, a recruitment system, a participation system, a warehouse system, a payroll system, a time tracking system, a security system, and/or another data system. The information from the plurality of data systems may be timing data, telemetry data, performance data, quality data, cost data, volume data, quantity data, rate data, personnel data, donor data, donation data, production rate data, performance data, and/or speed data.

In some embodiments, the business objective may be a profile of the healthcare provider inferred based on historical information from the healthcare provider data system. In other embodiments, the business goals may be provided by the healthcare provider itself, rather than inferred by the system. The business goals may include a productivity goal, a performance goal, and/or a quality goal. The inferred profile and the provisioned corporate profile may contain location-specific profiles and/or time-dependent profiles. The business objective may be measurable.

The instructions may include information that supplements the steps taken to achieve the business goals. The supplemental information may be location specific to achieve business goals. In some embodiments, the instructions may be presented to the plurality of users via email, SMS, push notifications, phone calls, social media disclosures, visual feedback, auditory feedback, or tactile feedback. Additionally or alternatively, the instructions may be presented to multiple user systems via an electronic interface and/or manual file upload performed by the user. In other embodiments, the instructions may be presented to multiple users in a manner accessible from a cellular phone, tablet, computer, laptop, personal digital assistant, digital display, smart watch, telephone, pager, or public address system.

According to additional embodiments, a recordable medium having recorded and stored commands, which when executed on a computing device, performs actions comprising obtaining information about a plurality of locations and associating the location-specific information with a plurality of time-specific information. The actions may further include: identifying a business objective of a healthcare provider using a plurality of instructions; selecting an instruction associated with a business objective; and providing the instructions to the company. The business objectives may be based on (a) a location associated with the business objective, and/or (b) a time associated with the business objective. Instructions may be provided for user review or user system execution to achieve business goals.

According to further embodiments, a system comprises: a first interface for collecting information corresponding to a plurality of healthcare provider data systems, a heuristic module, and an artificial intelligence module. The heuristics module may identify unrealized location-specific, time-related business objectives. The artificial intelligence module can (a) select information about the business objective, (b) predict steps to be taken to achieve the business objective, and (c) modify the information with instructions that include the steps to be taken. The system may also include second and third interfaces. The second interface may be arranged to provide instructions to be executed (a) for review by a user or (b) for review by a user system. The third interface may be arranged to receive a confirmation that the instruction is (a) received by the user or (b) received by the user system. The artificial intelligence module can also (a) select information about the business objective, (b) select information about instructions provided for review by the user or user system, (c) associate the instructions with the business objective, and (d) identify the validity of the instructions for the business objective.

A method for generating instructions (e.g., business instructions) for maintaining a goal may integrate a control center system with a plurality of healthcare provider data systems and obtain information from at least one of the healthcare provider data systems. The method can then use artificial intelligence to associate the obtained information with the identified business targets of the donation center, and generate instructions to the donation center(s) using a heuristic model to achieve the identified business targets. The method may then present the instruction to the user and/or user system such that the instruction may be executed by the user and/or user system.

In some embodiments, integrating the control center system with the healthcare provider data system may include autonomously integrating the control center system. The data system may include a donor system, a screening system, a collection system, an equipment system, a supply system, an inventory system, a testing system, a transportation system, a quality system, a payment system, a marketing system, a recruitment system, a participation system, a warehouse system, a payroll system, a time tracking system, and/or a security system. The information from the healthcare provider data system may include timing data, telemetry data, performance data, quality data, cost data, volume data, quantity data, rate data, personnel data, donor data, donation data, productivity data, performance data, and/or speed data.

The business objective may be a profile of the donation center inferred based on historical information from a plurality of healthcare provider data systems. The method may also include receiving a company profile including a productivity goal, a performance goal, and/or a quality goal. The business objective may be based at least in part on a productivity objective, a performance objective, and/or a quality objective. The business objectives may include received corporate profiles containing location-specific profiles and/or time-dependent profiles, and the business objectives may be measurable.

The instructions may include information regarding at least one step to be taken to achieve the business objective, and/or the instruction information may be location specific to achieve the business objective. The method may present the instructions to the user via email, SMS, push notification, phone call, social media publication, visual feedback, auditory feedback, and/or tactile feedback. Additionally or alternatively, the instructions may be presented to the user system via an electronic interface (e.g., an automated electronic interface) and/or via a manual file upload performed by the user. The instructions may be presented to a plurality of users such that the instructions may be accessed from a cellular telephone, a tablet, a computer, a laptop, a personal digital assistant, a digital display, a smart watch, a telephone, a pager, and/or a public address system.

In further embodiments, the method may store information from the healthcare provider data system in a data storage device. Additionally or alternatively, the method may obtain the information by extracting the information from the healthcare provider data system using a data extractor. The healthcare provider data system may include a donor management system. Generating the instructions may include identifying a gap between a production metric based on the obtained information and a business objective. The method may also receive confirmation from the user that the user has taken ownership of the fulfillment instruction and/or monitored the validity of the business objective using artificial intelligence.

According to further embodiments, a system for generating instructions for maintaining a goal may comprise: an integrator configured to integrate the control center system with at least one healthcare provider data system; and a data extractor configured to search the healthcare data system(s) for production data. The data extractor may also retrieve production data from the healthcare provider data system(s). The system may also include a data storage device to store the retrieved production data and an artificial intelligence module. The artificial intelligence model can associate the retrieved production information with the identified business objective and generate instructions to achieve the identified business objective. The virtual digital assistant can process the instruction and distribute the instruction to the recipient (e.g., a user and/or donor management system) so that the recipient can execute the instruction. The artificial intelligence module can generate the instructions using a heuristic model.

The integrator may autonomously integrate the control center system with the healthcare provider data system(s). Based on historical information from the healthcare provider data system, the business objective may be a measurable and/or inferred profile of the healthcare provider. Additionally or alternatively, the business goals may be based at least in part on productivity goals, performance goals, and/or quality goals contained within the company profile.

The instructions may include information regarding at least one step to be taken to achieve the business objective, and/or location-specific information to achieve the business objective. The virtual digital assistant can distribute the instructions via email, SMS, push notifications, phone calls, social media disclosures, visual feedback, auditory feedback, and/or tactile feedback.

The system may also include an electronic interface, and the virtual digital assistant may distribute instructions to the user system via the electronic interface. Additionally or alternatively, the virtual digital assistant may distribute instructions to the user system via manual file uploads performed by the user. The instructions may be distributed to a recipient such that the instructions may be accessed from a cellular telephone, a tablet, a computer, a laptop, a personal digital assistant, a digital display, a smart watch, a telephone, a pager, and/or a public address system.

In other embodiments, the healthcare provider data system may include a donor management system. The artificial intelligence module can identify a gap between at least one production metric and a business objective. The instructions may be based at least in part on the gap(s). The system may also include an instruction listener that monitors the effectiveness of the needle instructions against the business objectives using artificial intelligence. The interface may receive a confirmation that the instruction was (a) received by the user or (b) received by the user system.

According to additional embodiments, a non-transitory computer recordable medium may have computer-executable commands that, when executed on a computing device, perform actions including obtaining location-specific information about a plurality of locations and associating the location-specific information with a plurality of time-specific information. The actions can also include identifying a business objective of the healthcare provider using the plurality of instructions and selecting an instruction related to the business objective. The instructions may be based on (a) a location associated with the business objective, and/or (b) a time associated with the business objective. The actions may also include providing instructions for achieving business goals for (a) user review and/or (b) user system execution.

Drawings

The foregoing features of the embodiments will be more readily understood by reference to the following detailed description, taken with reference to the accompanying drawings, in which:

FIG. 1 illustrates a data system processor and an analysis control center system according to some embodiments of the invention.

FIG. 2 is a flow diagram depicting a method of integrating data systems in accordance with various embodiments of the invention.

3A-3E schematically show example flow diagrams for various screening processes according to embodiments of the present invention.

Fig. 4A-4E schematically illustrate examples of flow diagrams of various blood drawing (phlebotomy) processes according to embodiments of the invention.

5A-5C schematically illustrate examples of flow diagrams of various supply inventory processes according to embodiments of the invention.

Detailed Description

In an illustrative embodiment, a data system processor and analysis system for a healthcare provider integrates various data systems within the healthcare provider and provides decision support (e.g., automated steering decision support) for the healthcare provider using a virtual digital assistant advisor with artificial intelligence processing and analysis. Details of illustrative embodiments are discussed below.

Generally, systems and methods according to various embodiments of the present invention are integrated with data systems of multiple healthcare providers to access large amounts of context-sensitive information. The system and method uses an artificial intelligence subsystem to process this information to identify valid or predicted emerging conditions, create personalized recommendations to modify the conditions, and provide these recommendations as proactive guidance to healthcare provider employees. Such recommendations may be generated and presented by the virtual digital assistant advisor. Alternatively, the recommendation may be performed automatically without any employee involvement.

After obtaining information (e.g., telemetry data, timing data, performance data, and related metric data) from data systems of multiple healthcare providers, systems and methods according to various embodiments of the present invention use this information to train an artificial intelligence data processor to identify conditions that are leading to certain outcomes of the healthcare providers. Thereafter, these conditions are analyzed and processed by the artificial intelligence subsystem into commands that are provided to healthcare provider personnel through a variety of methods, such as email, SMS, push notifications, telephone, social media, and related methods, to proactively notify the healthcare provider of the conditions and provide guidance for modifying the conditions to achieve different results. Using a personal computing device, such as a cellular phone, tablet, computer, laptop, personal digital assistant, smart watch, public address system, or related electronic communication technology, healthcare provider personnel can receive recommendations in the form of notifications from the virtual digital assistant advisor of the present invention, and personnel can then access detailed information about the suggested notifications from any of the aforementioned computing devices. Additionally or alternatively, the present invention may automatically execute the command without the involvement of healthcare provider personnel.

For example, with respect to plasma collection systems and donation systems, various embodiments may be integrated with a donor management data system for multiple plasma collectors for large amounts of context sensitive information. The system/method may then process this information using an artificial intelligence subsystem to identify valid or predicted emerging conditions. Based on these conditions, the system/method can create personalized recommendations to modify the conditions, and the recommendations can be presented to plasma center personnel as proactive guidance via a virtual digital assistant advisor or by automatically performing the recommendations without any personnel involvement.

After obtaining information (e.g., telemetry data, timing data, performance data, and associated metric data) from a donor management data system of multiple plasma collectors, the systems and methods may use this information to train an artificial intelligence data processor to identify conditions that are leading to certain outcomes for the plasma center. Thereafter, the system/method analyzes the conditions and the artificial intelligence subsystem processes the conditions and information into commands that are provided to the plasma centric personnel by (e.g., via email, SMS, push notification, phone, social media, and related methods) to proactively notify the plasma centric personnel of the conditions and provide guidance for modifying the conditions to achieve different results.

Using a personal computing device, such as a cellular phone, tablet, computer, laptop, personal digital assistant, smart watch, public address system, or related electronic communication technology, the plasma center personnel can receive recommendations in the form of notifications from the virtual digital assistant advisor, and the personnel can then access detailed information about the recommended notifications from any of the aforementioned computing devices. Alternatively, the present invention may automatically execute the commands without the involvement of plasma center personnel.

FIG. 1 schematically illustrates a control center system according to some embodiments of the invention. The control center system 100 is programmed or contains modules that perform the various functions described above. For example, the system 100 may have an integrator 105 that links to the donor management system 210 or any other data system 220 used by the plasma collector and/or plasma center and allows the system 100 to access data recorded and stored in these external data systems. The system 100 also has a data extractor program/module 110 that uses the integrator 105 to search the plasma data system 210/220 for a particular recorded production data. For example, depending on the application, the data extractor may search for donor, unit volume, device, supply, shipping, date, time, user, stage, and anonymous data.

Once the data extractor 110 finds the desired data/information, the data transmitter 115 takes the data found by the data extractor 110 and electronically transmits the data back to the system server 125. For example, the data transmitter may transmit data from the source system to the data system processor and analysis system 100 via an internet connection. The transmission may be over the internet and using a secure connection. Upon receiving the data/information from the transmitter 115, the data store 120 (e.g., a data storage device) receives the data and stores the data onto a recordable medium. Data on recordable media may be secure.

As shown in fig. 1, the system 100 may also have artificial intelligence 130 (and/or may include or be connected to one or more neural networks) that reads data stored in the data store 120. Artificial intelligence uses heuristics to analyze data so that it can identify business goals related to the operational performance of a plasma collector (or other blood processing center, healthcare provider, etc.), and analyzes real-time data so that it can measure and compare the real-time performance of the plasma collector for the business goals. If the real-time performance measurement does not meet (e.g., is above or below) the business goal, the system 100 creates a step-by-step command directed to remediate performance such that it meets or exceeds the business goal. In general, such step-by-step commands are referred to as instructions.

Once the artificial intelligence program/module 130 (e.g., machine learning module) generates instructions, it sends the instructions to the virtual digital assistant 145. The virtual digital assistant 145 in turn processes the instructions for distribution to the intended recipients. For example, the virtual digital assistant 145 can distribute instructions in a variety of ways, including but not limited to display directly on the system screen on an online notification feed, sending instructions to the external SMS system 230 so that the recipient can receive them as text messages on their mobile device, sending instructions to the external email system 240 so that the recipient can receive them as emails, and/or sending instructions to an automatic steering system for further processing (discussed in more detail below).

As described above, in some cases, virtual digital assistant 145 may send instructions to autopilot system 140. In such cases, the automatic steering system 140 may automatically create a new command for changing the operating parameters of the plasma center (or other medical provider) based on the instructions. Commands may be sent to donor management system 210 and/or data system 220 for processing and disposal.

Upon receiving and completing the instructions and/or commands, the donor management system 210 and/or the data system 220 can provide feedback to the control center 100. To this end, the control center 100 may have an instruction listener 135, the instruction listener 135 receiving feedback from the recipient of the instruction and updating the records within the data store 120 of the control center. For example, instruction listener 135 may receive feedback indicating that the instruction was received by the recipient, read by the recipient, assigned to the owner by the recipient, and/or completed by the recipient/owner, among others.

FIG. 2 schematically shows a flow diagram depicting a method 300 of integrating data systems according to various embodiments of the invention. It should be noted that the method relates to a plasma donation center, but other embodiments may be used for other healthcare and non-healthcare applications. Initially, when a plasma donor enters the plasma hub for donation (step 302), the plasma hub employee enters all of the access data into the donor management system server (step 304), the external data system transmits the data to the donor management system server via an electronic file (step 306), and the screening instrument or apheresis device transmits the data to the donor management system server via an electronic file (step 308). The method (e.g., data extractor 110) may then run an application to extract and receive data from the donor management system 210 (step 310), and record/store the data on a recordable medium on the system server 125 (e.g., via the data store 120) (step 312).

Once the data is received and stored, the artificial intelligence 130 can use the data to infer daily business target metrics through heuristics (step 314). The indicators may include total number of donors, total number of units, donation rate per hour, donor door time, average production and average equipment turnover, etc. Additionally or alternatively, the system user may also use the application screen to provide daily business objective metrics (step 316). The method (e.g., artificial intelligence 130) may then associate the real-time production data with the business objective (step 318). For each gap between real-time production and business goals, the method 300/system 100 creates new instructions that include steps that the center can take to bring the production metrics to (or better than) the business goals (step 320).

The digital assistant 145 may then receive these instructions and process them for distribution to the appropriate system users (step 322). For example, the method 300/system may display the instruction as a notification on the screen of the logged-in user (step 324), send the instruction to an external system (e.g., the SMS system 230 or the email system 230) to process it into a notification and send it to the user (step 326), or send it to an external system (or the automated steering 140) to be automatically executed without human intervention (step 342).

If the system 100/method 300 displays or sends instructions to the user, the method 300 may then confirm that the user received and read the instructions (step 328) and the system user may confirm that they will take ownership of the instructions and assign the instructions to themselves for completion (step 330). The user may cause them to execute the necessary instructions (e.g., external to system 100) (step 332). It should be noted that during this time, the method may track each system user that receives and reads the notification (step 344) and may send a notification to all other recipients that another user is assigned to the instruction (step 346). Once completed, the user may indicate that the instruction is complete (step 334). For example, to confirm that the user has taken ownership of the task and/or that the task is complete, the user may click/press a button located on a user interface (e.g., a graphical user interface) on system 100 and/or its screen. Alternatively, the user may send a response (e.g., an email, text message, etc.) back to the system 100 to notify the system 100 that a task has been assigned to the user and/or that the task has been completed.

Once the instruction is complete (e.g., via a user or automatically), the system 100/method 300 (e.g., artificial intelligence 130) may continuously check the production data to determine if the issued instruction has been completed (step 336). The donor may then complete the donation (step 338), and the system may continuously measure the effectiveness of the instructions against the business goals (step 340). By continuously monitoring the effectiveness of production data and instructions, the system 100 can create new instructions and/or modify existing instructions if there is a change in data, business goals, and/or instructions do not execute as expected.

It should be noted that the various embodiments of the present invention may be used for any number of applications and for any number of business goals and process management. For example, as shown in fig. 3A through 3E, various embodiments may be used during a screening process. Furthermore, as shown in fig. 4A-4E, various embodiments may be used to determine donor processing rates. Finally, as shown in fig. 5A through 5C, various embodiments are for provisioning management.

Figure 3A schematically illustrates a system 100 for meeting and maintaining a business goal for a particular donor door-to-door time (e.g., from the time the donor first arrives to the time the donor departs). For example, a donation center may establish or the system may infer the goal of 60 minutes (step 410). The overall flow of the donor through the donation process is that the donor first arrives at the plasma hub for donation (step 430), waits for the next screening room to be opened (step 432), and then enters the screening process once the screening room is developed (step 434). The screening process will determine whether the donor is approved for donation (step 436). The donor may then wait for the bed/donor equipment to become available (step 438), and once one is available, the donor begins donation (e.g., he enters a blood draw session) (step 440). Once the donation is complete (step 442), the donor is paid (step 444) and may leave the donation center (step 446).

After the donation/plasma hub has established a business goal (step 410) or the system 100 has inferred a business goal, the system 100 (or method) may then identify the donor throughput (e.g., 50 donors per hour in this case) needed to meet the business goal (step 420). The system 100 may then track donor arrival rates (step 450) to determine how many donors and how fast donors arrive and track screening room rates (step 460) to determine how fast donors are processed and/or screened at the screening room. If the screening rate is below a threshold determined based at least in part on the donor arrival rate (e.g., less than 50 donors per hour), then the system 100 may track the number of screening chambers that are open (step 470) to determine if the screening chambers are inadequate (step 475). If the system 100 determines that an open screening room is missing, the system 100 may generate instructions to the plasma hub instructing the plasma hub to open additional screening rooms to meet the donor requirements (step 480). In response, the center may then open additional screening rooms (step 485), and the system 100 may continue to monitor the validity of the instructions (e.g., it may track donor arrival rates, screening room rates, the number of screening rooms opened, etc.) to ensure that the instructions are helping the center achieve business goals (step 490). The system 100 may modify the instructions if the instructions no longer contribute to achieving the business goals or the collected data (e.g., the rate and number of screening rooms described above) changes.

As described above, in some embodiments, the system 100 may automatically execute instructions to achieve business goals. To this end, as shown in fig. 3B, the system 100 may automatically execute the instructions, rather than creating and sending the instructions to the user and/or the plasma center for execution by the user/plasma center. For example, after determining that the plasma center lacks a screening room (step 475), the system 100 can use the digital assistant 145 to send a message to the donor management system 210, which the donor management system 210 in turn automatically opens additional screening rooms to meet donor needs and goal business objectives/objectives.

Fig. 3C and 3D show another example in which the donor processing rate during screening is higher than the donor arrival pattern at the plasma center. In a manner similar to the example in fig. 3A and 3B, the plasma hub may set the donor door-to-door purpose to 60 minutes (step 410), and then the system 100 may determine an index number of donations (e.g., 300 per example in fig. 3C) and/or an index number of donations/donors per hour (e.g., 50 donors per hour) to meet the business goals/purposes set by the plasma hub (step 420). The system 100 may then monitor/track the donor arrival rate (e.g., 40 donors per hour in fig. 3C) (step 510) and the screening room rate (step 460), so that the system may compare the screening rate to established metrics. If the screening rate is greater than the index (e.g., 50 donors per hour) (step 465), then the system 100 may track the number of screening chambers that are open (step 470) to determine if the number of screening chambers is excessive (step 520). If there are too many screening rooms, then system 100 may generate instructions to the user/plasma center to close some of the screening rooms (step 530). The center may then close the screening room as instructed by the system 100 (step 540), and the system 100 may continue to measure the validity of the instructions. Alternatively, as shown in fig. 3D, rather than instructing the user/plasma center to close the screening chamber, the system 100 may automatically close the screening chamber (step 550).

Fig. 3E illustrates another example associated with a donor screening process, wherein the system 100 determines a longer wait time in the plasma center. In this example, the plasma hub may set a business goal/objective for the donor for a maximum wait time (e.g., 10 minutes) throughout the donation process (step 605). The system 100 may then look at various points in the process to determine if the wait time exceeds the goal. For example, the system 100 may track the screening of both wait times (step 610) and determine if the wait time is greater than the objective (e.g., if it is greater than 10 minutes) (step 620). The system 100 may then generate instructions to the user/plasma center instructing the plasma center to add additional staff to the screening process (step 630). The center may then open more screening rooms and/or add additional personnel as instructed (step 640). The system 100 may then monitor/measure the validity of the instructions (step 490) and make adjustments as needed. It should be noted that although fig. 3E only shows the system 100 viewing the screening wait time, the system 100 may similarly view the wait time for beds/donation machines, the wait time for payments, etc.

Figure 4A illustrates an exemplary use of the system 100 in which the donor processing rate is lower than the arrival rate during the blood draw phase (e.g., at the point where the donor is waiting for the bed/apheresis device; step 438). In this example, the business goals set by the plasma center (or inferred by the system 100) may be similar to those of fig. 3A and 3B, i.e., 60 minutes donor door-to-door time (step 410). Thus, in a manner similar to that described above, system 100 may identify the required donor throughput (step 420) and may track the donor arrival rate (step 450). At various points during donor processing and donation, the system 100 may monitor and track various criteria and/or data. For example, while the donor is waiting for a bed/apheresis device to be available (step 438), the system 100 may track the donor floor (floor) rate (e.g., how long the donor waits for a bed/apheresis device and how long they have been subject to donation processing) (step 710), and if the rate is below the required throughput (e.g., 60 donors per hour) (step 720), the system 100 will track the number of open beds/apheresis devices (step 730).

Based on this information and whether the bed/apheresis device is insufficient to handle donor flow (step 740), the system 100 will generate instructions to command the user/plasma hub to add additional beds (step 750). The plasma center may then add more beds per the order (step 760) and the system 100 will continue to monitor/measure the validity of the order (step 490). Alternatively, as shown in fig. 4B, system 100 may automatically close the screening room (step 770), for example, by having virtual digital assistant 145 send a command to downstream donor management 210.

Fig. 4C and 4D illustrate an example of a system 100 that determines that the wait time for blood draw is long (e.g., at step 438), contradictory to the wait time limit/objective of the plasma center (e.g., less than 10 minutes) (step 810). In this case, the system 100 may track the blood draw waiting time (step 820) and determine if the time is greater than a central indicator (e.g., if the time is greater than 10 minutes). If the wait time exceeds the index/purpose, the system 100 will generate instructions that instruct the user/plasma center to add a phlebotomist to the floor, e.g., via the digital assistant 145 (step 840). Alternatively, as shown in fig. 4D, the system 100 may automatically account for the extended wait time by automatically opening additional beds (e.g., by sending commands to the donor management system 210 via the digital assistant 145) (step 860). In either case, once the hub has added an additional phlebotomist and/or additional beds are opened, the system 100 may continue to measure the validity of the order (step 490).

While fig. 4C and 4D process situations where the latency is too long, in some cases the latency may be too short and may indicate some inefficiency and/or over-capacity at the plasma center. In this case, as shown in fig. 4E, the system 100 may track the blood draw latency (step 820), and if there is no latency (e.g., latency is 0) (step 870), the system 100 may generate instructions to instruct the user/plasma center to remove employees (or close beds) (step 880) to reduce any inefficiencies of the center (e.g., idle employees, open beds, etc.). The center may then execute the instructions by removing the employee (step 890), and the system 100 may then continue to monitor/measure the effectiveness of the instructions (step 490).

In addition to monitoring the efficiency and business goals of the screening process and/or the blood drawing process, other embodiments may be used to monitor, track, and maintain an appropriate inventory of supplies on the plasma center floor. For example, as shown in fig. 5A, if a plasma hub establishes a destination/goal with sufficient available supply (step 910), system 100 may establish a donation destination and/or an hourly donor destination (step 920), e.g., based on known business goals of the hub, and may track the donor arrival rate (step 450) in a manner similar to that described above. Then, during the blood draw phase (e.g., during step 438), the system 100 may replenish the donation supplies available on the floor (step 930) and determine whether the availability of supplies is insufficient to meet the current demand (e.g., whether there are insufficient 60 donors to process per hour) (step 940). If the number of supplies is insufficient, the system 100 will generate instructions to instruct the user/plasma center to replenish supplies (step 950) and send a message/instruction to the user/plasma center, for example, via the digital assistant 145. The user/center may then supplement the supply in response to the received instructions (step 960), and the system 100 may monitor/measure the effectiveness of the instructions (step 490).

In other cases, as shown in fig. 5B, the plasma center may additionally or alternatively desire to have a balanced supply (e.g., supply line and chamber balance) within the plasma center (step 1010). Based on the business objective/objective, the system 100 identifies the required donor throughput (e.g., to meet plasma hub collection objectives) (step 1020), and the system 100 tracks the donor arrival rate (step 1030). During the blood draw phase, for example, when the donor is waiting for an open bed (step 438), the system 100 may track the donation floor supply ratio (step 1040) and determine whether the supply is balanced (e.g., a ratio of 1:1) (step 1050). If not, the system 100 generates instructions and instructs the center to rebalance the supply lines and bins (step 1060), and in response, the center may balance the supply (step 1070). To ensure that the instructions are working effectively, the system 100 may continue to monitor/measure effectiveness (step 490).

Fig. 5C shows another example, where the system 100 tracks the activity of the phlebotomist and commands them to perform an alternative task, such as replenishment. In this example, the plasma center may again set a business goal/objective of maximizing supply inventory (step 1110). Then, during the blood drawing session (e.g., while the donor is at bed; step 440), the system 100 may track the phlebotomist's activities (step 1120) to determine if any phlebotomists are free (step 1130). If there is an idle phlebotomist, the system 100 may then determine if there is sufficient space on the floor for additional supplies (step 1140), and if so, the system 100 may instruct the idle phlebotomist to replenish supplies (step 1150).

It is important to note that fig. 3A-3E, 4A-4E, and 5A-5C illustrate only examples of how the system 100 may be used to meet various business goals for plasma centers. System 100 may be used for any number of additional examples and business instructions. Additionally, the system 100 may be used to implement multiple business instructions at any given time simultaneously.

It should be noted that terms such as "controller," "processor," and "server" may be used herein to describe devices that may be used in certain embodiments of the invention, and should not be construed to limit the invention to any particular device type or system unless the context requires otherwise. Thus, a system may include, but is not limited to, a client, a server, a computer, an appliance, or other type of device. Such devices typically include one or more network interfaces for communicating over a communication network and a processor (e.g., a microprocessor with memory and other peripherals and/or dedicated hardware) that is accordingly configured to perform device and/or system functions. The communication network may generally comprise a public and/or private network; may include a local area network, a wide area network, a metropolitan area network, a storage network, and/or other types of networks; and may employ communication technologies including, but in no way limited to, analog technologies, digital technologies, optical technologies, wireless technologies, networking technologies, and internetworking technologies.

The individual components of the control program may be implemented individually or in combination. For example, each component may be implemented, or a dedicated server or a group of servers may be configured in a distributed manner.

It should also be noted that devices may use communication protocols and messages (e.g., messages created, transmitted, received, stored, and/or processed by a system), and such messages may be conveyed by a communication network or medium. The present invention should not be construed as limited to any particular communication message type, communication message format, or communication protocol unless the context requires otherwise. Thus, a communication message may generally include, but is not limited to, a frame, a packet, a datagram, a user datagram, a cellular, or other type of communication message. Unless the context requires otherwise, references to particular communication protocols are exemplary, and it should be understood that alternative embodiments may employ variations of such communication protocols as appropriate (e.g., modifications or extensions to the protocols that may be made from time to time) or other protocols known or developed in the future.

It should also be noted that a logic flow may be described herein to demonstrate various aspects of the present invention and should not be construed as limiting the present invention to any particular logic flow or logic implementation. The described logic may be partitioned into different logic blocks (e.g., programs, modules, interfaces, functions, or subroutines) without changing the overall results or otherwise departing from the true scope of the invention. In general, logic elements may be added, modified, omitted, performed in a different order, or implemented using different logic constructs (e.g., logic gates, looping primitives, conditional logic, and other logic constructs) without changing the overall results or otherwise departing from the true scope of the invention.

The invention can be implemented in many different forms, including, but not limited to, computer program logic for use with a processor (e.g., a microprocessor, microcontroller, digital signal processor, or general purpose computer), programmable logic for use with a programmable logic device (e.g., a Field Programmable Gate Array (FPGA) or other Programmable Logic Device (PLD)), discrete components, integrated circuitry (e.g., an Application Specific Integrated Circuit (ASIC)), or any other component, including any combination thereof. In some embodiments of the invention, substantially all of the described logic is implemented as a set of computer program commands that are converted into a computer executable form, stored as such in a computer readable medium, and executed by a microprocessor under the control of an operating system.

Computer program logic implementing all or part of the functionality previously described herein may be embodied in various forms, including, but in no way limited to, source code forms, computer executable forms, and various intermediate forms (e.g., forms generated by an assembler, compiler, linker, or locator). The source code may include a series of computer program commands implemented in any of a variety of programming languages (e.g., object code, assembly language, or a high-level language such as FORTRAN, C + +, JAVA, or HTML) for use with various operating systems or operating environments. The source code may define and use various data structures and communication messages. The source code may be in computer-executable form (e.g., via an interpreter), or the source code may be converted into computer-executable form (e.g., via a translator, assembler, or compiler).

The computer program may be fixed in any form (e.g., source code form, computer executable form, or intermediate form) either permanently or temporarily in a tangible storage medium, such as a semiconductor memory device (e.g., RAM, ROM, PROM, EEPROM or flash programmable RAM), a magnetic memory device (e.g., floppy or fixed disk), an optical memory device (e.g., CD-ROM), a PC card (e.g., PCMCIA card), or other memory device. The computer program may be fixed in any form as a signal that can be transmitted to a computer using any of a variety of communication techniques, including, but not limited to, analog techniques, digital techniques, optical techniques, wireless techniques, networking techniques, and internetworking techniques. The computer program may be distributed in any form as a removable storage medium with accompanying printed or electronic documentation (e.g., shrink wrapped software), preloaded with a computer system, e.g., on system ROM or fixed disk, or distributed from a server or electronic bulletin board over the communication system (e.g., the internet or world wide web).

Hardware logic implementing all or part of the functionality previously described herein, including programmable logic used with programmable logic devices, may be designed using conventional manual methods, or may be designed, captured, simulated or documented electronically using various tools, such as Computer Aided Design (CAD), hardware description languages (e.g., VHDL or AHDL), or PLD programming languages (e.g., PALASM, ABEL, or CUPL).

Programmable logic may be fixed permanently or temporarily in a tangible storage medium such as a semiconductor memory device (e.g., RAM, ROM, PROM, EEPROM, or flash programmable RAM), a magnetic memory device (e.g., a floppy disk or fixed disk), an optical memory device (e.g., a CD-ROM), or other memory device. Programmable logic may be fixed in a signal that may be transmitted to a computer using any of a variety of communication technologies, including, but in no way limited to, analog technologies, digital technologies, optical technologies, wireless technologies (e.g., bluetooth), networking technologies, and internetworking technologies. Programmable logic may be distributed as a removable storage medium with an accompanying printed or electronic document (e.g., shrink-wrapped software), pre-loaded with a computer system (e.g., on system ROM or fixed disk), or distributed from a server or electronic device bulletin board over the communication system (e.g., the internet or world wide web). Indeed, some embodiments may be implemented in a software as a service model ("SAAS") or cloud computing model. Of course, some embodiments of the invention may be implemented as a combination of both software (e.g., a computer program product) and hardware. Still other embodiments of the invention are implemented as entirely hardware, or entirely software.

The embodiments of the invention described above are intended to be exemplary only; many variations and modifications will be apparent to those of ordinary skill in the art. All such variations and modifications are intended to fall within the scope of the present invention as defined by any appended claims.