Healthcare provider data systems processing and analysis

Abstract

A method for generating instructions for maintaining goals includes integrating a control center system with multiple healthcare provider data systems and obtaining information from the healthcare provider data systems. The method can then use artificial intelligence to correlate the obtained information with identified business goals of a donation center and use a heuristic model to generate instructions to the donation center to achieve the identified business goals. The method can then present the instructions to a user and / or user system so that the instructions can be executed.

Description

[0001] priority

[0002] This PCT patent application claims priority to U.S. Provisional Patent Application No. 62 / 722,929, filed on August 26, 2018, entitled “Health Care Provider Data Systems Processing and Analytics,” assigned attorney docket number 130670-09101 (formerly 1611 / C91), and naming Melvin Tan, James Odeen, Christopher Cairns, and Ronald Sheehan as inventors, the entire contents of which are incorporated herein by reference. Technical Field

[0003] 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 Art

[0004] Healthcare providers collect and maintain a vast amount of information and data about their business including: donors, patients, staff, productivity, performance, quality, inventory, costs, etc. However, these healthcare providers rely on data reports to understand their operating conditions for performance improvement, corrective actions, risk mitigation, and their other business needs. These reports are generated manually by staff or automatically by computerized systems to provide retrospective insights to the business. The healthcare provider staff members will then analyze the data in the reports and make decisions to adjust conditions / processes to improve productivity. Summary of the invention

[0005] According to some embodiments of the present invention, a method includes integrating with multiple healthcare provider data systems and obtaining information from the data systems. The method can then use artificial intelligence to associate the information with identified business goals and use heuristic methods to arrange instructions to achieve the business goals. The method can then present the instructions to multiple users or user systems at relevant times. In some embodiments, the integration can be autonomous. In other embodiments, the integration is completed in real time (i.e., data is received when business operations are performed in production).

[0006] The data system can 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, an engagement 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 can be 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.

[0007] In some embodiments, the business goal may be a profile of a healthcare provider inferred based on historical information from a healthcare provider data system. In other embodiments, the business goal may be provided by the healthcare provider themselves, rather than inferred by the system. The business goal may include productivity goals, performance goals, and / or quality goals. The inferred profile and the supplied company profile may contain location-specific profiles and / or time-dependent profiles. The business goal may be measurable.

[0008] Instructions can include supplementary information about the steps taken to achieve business goals. Supplementary information can be location-specific, to achieve business goals. In certain embodiments, instructions can be presented to multiple users via email, SMS, push notification, phone call, social media disclosure, visual feedback, auditory feedback or tactile feedback. Additionally or alternatively, instructions can be presented to multiple user systems via manual file uploads performed by electronic interfaces and / or users. In other embodiments, instructions can be presented to multiple users in a method that can be accessed from a cellular phone, tablet computer, computer, laptop, personal digital assistant, digital display, smart watch, phone, pager or public address system.

[0009] According to additional embodiments, a recordable medium having recorded and stored instructions that, when executed on a computing device, perform actions including obtaining information about a plurality of locations and associating the location-specific information with a plurality of time-specific information. The actions may also include: using the plurality of instructions to identify a business goal for a healthcare provider; selecting an instruction associated with the business goal; and providing the instruction to a company. The business goal may be based on (a) a location associated with the business goal, and / or (b) a time associated with the business goal. The instructions may be provided for review by a user or execution by a user system to achieve the business goal.

[0010] According to another embodiment, a system includes: a first interface for collecting information corresponding to multiple healthcare provider data systems, a heuristic module, and an artificial intelligence module. The heuristic module can identify unrealized location-specific, time-related business goals. The artificial intelligence module can (a) select information about the business goal, (b) predict steps to be taken to achieve the business goal, and (c) modify the information using instructions including the steps to be taken. The system can also include second and third interfaces. The second interface can 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 can be arranged to receive 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 goal, (b) select information about the instruction provided for review by the user or the user system, (c) associate the instruction with the business goal, and (d) identify the effectiveness of the instruction for the business goal.

[0011] A method for generating instructions (e.g., business instructions) for maintaining a goal may integrate a control center system with multiple healthcare provider data systems and obtain information from at least one of the healthcare provider data systems. The method may then use artificial intelligence to associate the obtained information with an identified business goal of a donation center and use a heuristic model to generate instructions to (one or more) donation centers to achieve the identified business goal. The method may then present the instructions to a user and / or user system so that the instructions can be executed by the user and / or user system.

[0012] 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, an engagement system, a warehouse system, a payroll system, a time tracking system, and / or a security system. 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.

[0013] The business goal may be a profile of a donation center inferred based on historical information from multiple 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 goal may be based at least in part on the productivity goal, the performance goal, and / or the quality goal. The business goal may include a received company profile including a location-specific profile and / or a time-dependent profile, and the business goal may be measurable.

[0014] The instructions may include information about at least one step to be taken to achieve the business goal, and / or the instruction information may be location-specific to achieve the business goal. The method may present the instructions to the user via email, SMS, push notification, phone call, social media disclosure, 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 multiple users so that the instructions may be accessed from a cellular phone, tablet computer, computer, laptop, personal digital assistant, digital display, smart watch, phone, pager, and / or public address system.

[0015] In further embodiments, the method may store information from a 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 instruction may include identifying a gap between a production metric based on the obtained information and a business goal. The method may also receive a confirmation from the user that the user has taken ownership of implementing the instruction and / or using artificial intelligence to monitor the effectiveness of the instruction against the business goal.

[0016] According to another embodiment, a system for generating instructions for maintaining a goal may include: an integrator configured to integrate a control center system with at least one healthcare provider data system; and a data extractor configured to search (one or more) healthcare data systems for production data. The data extractor may also retrieve production data from (one or more) healthcare provider data systems. The system may also include a data storage device and an artificial intelligence module that stores the retrieved production data. The artificial intelligence model may associate the retrieved production information with an identified business goal and generate instructions to achieve the identified business goal. The virtual digital assistant may process the instruction and distribute the instruction to a recipient (e.g., a user and / or a donor management system) so that the recipient can execute the instruction. The artificial intelligence module may use a heuristic model to generate instructions.

[0017] The integrator may autonomously integrate the control center system with the healthcare provider data system(s). The business goals may be measurable and / or inferred healthcare provider profiles based on historical information from the healthcare provider data systems. 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.

[0018] The instructions may include information about at least one step to be taken to achieve the business goal, and / or location-specific information to achieve the business goal. The virtual digital assistant may distribute the instructions via email, SMS, push notification, phone call, social media posting, visual feedback, auditory feedback, and / or tactile feedback.

[0019] The system may also include an electronic interface, and the virtual digital assistant may distribute the instructions to the user system via the electronic interface. Additionally or alternatively, the virtual digital assistant may distribute the instructions to the user system via a manual file upload performed by the user. The instructions may be distributed to the recipient such that the instructions may be accessed from a cellular phone, tablet computer, computer, laptop, personal digital assistant, digital display, smart watch, telephone, pager, and / or public address system.

[0020] In other embodiments, the healthcare provider data system may include a donor management system. The artificial intelligence module may identify a gap between at least one production metric and a business objective. The instruction may be based at least in part on the gap(s). The system may also include an instruction listener that uses artificial intelligence to monitor the effectiveness of the instruction against the business objective. The interface may receive confirmation that the instruction is (a) received by a user or (b) received by a user system.

[0021] According to additional embodiments, a non-transitory computer recordable medium may have computer executable instructions that, when executed on a computing device, perform actions, the actions comprising obtaining location-specific information about a plurality of locations and associating the location-specific information with a plurality of time-specific information. The actions may also include using a plurality of instructions to identify a business objective of a healthcare provider and selecting an instruction associated with 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 the business objective for (a) review by a user and / or (b) execution by a user system. BRIEF DESCRIPTION OF THE DRAWINGS

[0022] The foregoing features of the embodiments will be more readily understood by reference to the following detailed description with reference to the accompanying drawings, in which:

[0023] Figure 1A data system processor and analysis control center system according to some embodiments of the present invention are shown.

[0024] Figure 2 is a flow chart depicting a method of integrating data systems according to various embodiments of the present invention.

[0025] Figures 3A-3E Schematically illustrates flow chart examples for various screening processes according to embodiments of the present invention.

[0026] Figures 4A-4E Schematically illustrates flow chart examples of various phlebotomy processes according to embodiments of the present invention.

[0027] Figures 5A-5C Flowchart examples of various supply inventory processes according to embodiments of the present invention are schematically shown. DETAILED DESCRIPTION

[0028] 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., auto-steering decision support) to the healthcare provider using a virtual digital assistant advisor with artificial intelligence processing and analysis. Details of the illustrative embodiment are discussed below.

[0029] In general, systems and methods according to various embodiments of the present invention integrate with data systems of multiple healthcare providers to access a large amount of context-sensitive information. The systems and methods process this information using an artificial intelligence subsystem 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 can be generated and presented by a virtual digital assistant advisor. Alternatively, recommendations can be performed automatically without any employee involvement.

[0030] After obtaining information (e.g., telemetry data, timing data, performance data, and related metric data) from multiple healthcare providers' data systems, 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 causing certain outcomes for healthcare providers. Thereafter, these conditions are analyzed and processed by the artificial intelligence subsystem into commands provided to healthcare provider personnel through a variety of methods (such as, email, SMS, push notifications, phone calls, social media, and related methods) to proactively notify healthcare providers of the conditions and provide guidance for modifying the conditions to achieve different outcomes. Using a personal computing device, such as a cellular phone, tablet, computer, laptop, personal digital assistant, smart watch, public broadcast system, or related electronic communication technology, healthcare provider personnel can receive advice in the form of notifications from the virtual digital assistant advisor of the present invention, and the personnel can subsequently access detailed information about the advice notifications from any of the aforementioned computing devices. Additionally or alternatively, the present invention can automatically execute commands without the involvement of healthcare provider personnel.

[0031] For example, with respect to plasma collection systems and donation systems, various embodiments may be integrated with donor management data systems 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 may create personalized recommendations to modify the conditions, and the recommendations may be presented to plasma center staff as proactive guidance via a virtual digital assistant advisor or by automatically executing the recommendations without any staff involvement.

[0032] After obtaining information (e.g., telemetry data, timing data, performance data, and related metric data) from donor management data systems of multiple plasma collectors, the system and method can use the information to train an artificial intelligence data processor to identify conditions that are leading to certain outcomes at 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 plasma center personnel (e.g., via email, SMS, push notifications, phone calls, social media, and related methods) to proactively notify plasma center personnel of the conditions and provide guidance for modifying the conditions to achieve different outcomes.

[0033] 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, plasma center personnel can receive advice in the form of a notification from the virtual digital assistant advisor, and personnel can subsequently access detailed information about the advice notification from any of the aforementioned computing devices. Alternatively, the present invention can automatically execute commands without the involvement of plasma center personnel.

[0034] Figure 1 A control center system according to some embodiments of the present invention is schematically illustrated. The control center system 100 is programmed or includes modules that perform the various functions described above. For example, the system 100 may have an integrator 105 that is linked to a donor management system 210 or any other data system 220 used by a plasma collector and / or plasma center, and enables 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 for production data for a specific record from the plasma data system 210 / 220. For example, depending on the application, the data extractor can search for donors, units, unit volumes, equipment, supplies, transportation, dates, times, users, stages, and anonymous data.

[0035] Once the data extractor 110 finds the desired data / information, the data transmitter 115 takes the data found by the data extractor 110 and transmits the data electronically back to the system server 125. For example, the data transmitter can transmit the data from the source system to the data system processor and analysis system 100 via an Internet connection. The transmission can be over the Internet and using a secure connection. After receiving the data / information from the transmitter 115, the data repository 120 (e.g., a data storage device) receives the data and stores the data on a recordable medium. The data on the recordable media can be secure.

[0036] like Figure 1 As shown in , the system 100 may also have an artificial intelligence 130 (and / or may include or be connected to one or more neural networks) that reads the data stored in the data repository 120. The artificial intelligence analyzes the data using heuristic methods so that it can identify business goals related to the operational performance of the 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 against the business goals. If the real-time performance measurement does not meet (e.g., is above or below) the business goal, then the system 100 creates step-by-step commands aimed at remediating the performance so that it meets or exceeds the business goal. In general, such step-by-step commands are referred to as instructions.

[0037] Once the artificial intelligence program / module 130 (e.g., machine learning module) generates the instruction, it sends the instruction to the virtual digital assistant 145. The virtual digital assistant 145 then processes the instruction for distribution to the intended recipient. For example, the virtual digital assistant 145 can distribute the instruction in a variety of ways, including but not limited to displaying directly on the system screen on an online notification feed, sending the instruction to an external SMS system 230 so that the recipient can receive it as a text message on their mobile device, sending the instruction to an external email system 240 so that the recipient can receive it as an email, and / or sending the instruction to an autopilot system for further processing (discussed in more detail below).

[0038] As described above, in some cases, the virtual digital assistant 145 can send instructions to the autopilot system 140. In such cases, the autopilot system 140 can automatically create new commands for changing the operating parameters of the plasma center (or other medical provider) based on the instructions. The commands can be sent to the donor management system 210 and / or the data system 220 for processing and disposal.

[0039] After receiving and completing instructions and / or commands, the donor management system 210 and / or the data system 220 may provide feedback to the control center 100. To this end, the control center 100 may have an instruction listener 135 that receives feedback from the recipient of the instruction and updates the record within the control center's data repository 120. For example, the instruction listener 135 may receive feedback indicating that the instruction was received by the recipient, read by the recipient, assigned an owner by the recipient, and / or completed by the recipient / owner, etc.

[0040] Figure 2 Schematically illustrated is a flow chart depicting a method 300 of an integrated data system according to various embodiments of the present 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 a plasma center to donate (step 302), a plasma center employee enters all visit data into a donor management system server (step 304), an external data system transmits the data to the donor management system server via an electronic file (step 306), and a screening instrument or single blood collection device transmits the data to the donor management system server via an electronic file (step 308). The method (e.g., data extractor 110) can 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 (step 312) (e.g., via data repository 120).

[0041] Once the data is received and stored, the artificial intelligence 130 can use the data to infer daily business goal metrics through heuristic methods (step 314). Metrics may include total number of donors, total number of units, hourly donation rate, donor door-to-door time, average production, and average equipment turnover, among others. Additionally or alternatively, a system user may also use an application screen to provide daily business goal metrics (step 316). The method (e.g., artificial intelligence 130) may then associate real-time production data with business goals (step 318). For each gap between real-time production and business goals, the method 300 / system 100 creates new instructions that include steps the center can take to bring the production metric to (or better than) the business goal (step 320).

[0042] 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 instructions as a notification on the screen of the logged-in user (step 324), send the instructions to an external system (e.g., SMS system 230 or email system 230) to be processed into a notification and sent to the user (step 326), or send to an external system (or autopilot 140) for automatic execution without human intervention (step 342).

[0043] If the system 100 / method 300 displays the instruction or sends the instruction to the user, the method 300 can then confirm that the user received and read the instruction (step 328), and the system user can confirm that they will take ownership of the instruction and assign the instruction to themselves to complete (step 330). The user can have them execute the necessary instructions (e.g., outside the system 100) (step 332). It should be noted that during this time, the method can track each system user who receives and reads the notification (step 344), and can send a notification to all other recipients that another user is assigned to the instruction (step 346). Once completed, the user can indicate that the instruction is completed (step 334). For example, to confirm that the user has taken ownership of the task and / or the task has been completed, the user can click / press a button on a user interface (e.g., a graphical user interface) located on the system 100 and / or its screen. Alternatively, the user can send a response (e.g., an email, a text message, etc.) back to the system 100 to notify the system 100 that the task has been assigned to the user and / or the task has been completed.

[0044] Once the instruction is completed (e.g., via a user or automatically), the system 100 / method 300 (e.g., artificial intelligence 130) can continuously check the production data to determine whether the issued instruction has been completed (step 336). The donor can then complete the donation (step 338), and the system can continuously measure the effectiveness of the instruction against the business goals (step 340). By continuously monitoring the effectiveness of the production data and instructions, the system 100 can create new instructions and / or modify existing instructions if there are changes to the data, business goals, and / or the instructions are not performing as expected.

[0045] It should be noted that various embodiments of the present invention may be used for any number of applications and for any number of business objectives and process management. Figures 3A to 3E As shown in , various embodiments may be used during the screening process. FIG. 4A to FIG. 4E As shown in , various embodiments can be used to determine the donor processing rate. Finally, as Figures 5A to 5C As shown in , various embodiments are used for supply management.

[0046] Figure 3A A system 100 is schematically shown for meeting and maintaining a business goal of a specific donor door-to-door time (e.g., from the time the donor first arrives to the time the donor leaves). For example, a donation center can establish or the system can infer a 60-minute goal (step 410). The overall flow of a donor through the donation process is that the donor first arrives at the plasma center to donate (step 430), waits for the next screening room to open (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 to donate (step 436). The donor can then wait for a bed / donation facility to become available (step 438), and once one is available, the donor begins donating (e.g., he enters the blood draw phase) (step 440). Once the donation is completed (step 442), the donor is paid (step 444) and the donor can leave the donation center (step 446).

[0047] After the donation / plasma center has established a business goal (step 410) or the system 100 has inferred a business goal, the system 100 (or method) can then identify the donor throughput required to meet the business goal (e.g., in this case, 50 donors per hour) (step 420). The system 100 can then track the donor arrival rate (step 450) to determine how many donors there are and how quickly the donors arrive and track the screening room rate (step 460) to determine how quickly the donors are processed and / or screened at the screening room. If the screening rate is below a threshold determined at least in part based on the donor arrival rate (e.g., less than 50 donors per hour), the system 100 can then track the number of open screening rooms (step 470) to determine if there is a shortage of screening rooms (step 475). If the system 100 determines that there is a lack of open screening rooms, the system 100 can generate instructions to the plasma center, commanding the plasma center to open additional screening rooms to meet donor demand (step 480). In response, the center can then open additional screening rooms (step 485), and the system 100 can continue to monitor the effectiveness of the instructions (e.g., it can track donor arrival rate, screening room rate, number of screening rooms opened, etc.) to ensure that the instructions are helping the center achieve its business goals (step 490). If the instructions no longer help achieve the business goals or the collected data (e.g., the rate and number of screening rooms described above) changes, the system 100 can modify the instructions.

[0048] As described above, in some embodiments, the system 100 can automatically execute instructions to achieve business goals. Figure 3B As shown in , the system 100 can automatically execute instructions instead of creating and sending instructions to users and / or plasma centers for execution by the users / plasma centers. For example, after determining that the plasma center lacks screening rooms (step 475), the system 100 can use the digital assistant 145 to send a message to the donor management system 210, which in turn automatically opens additional screening rooms to meet donor needs and door-to-door business goals / objectives.

[0049] Figure 3C and 3D Another example is shown where the donor processing rate during screening is higher than the donor arrival pattern at the plasma center. Figure 3A and 3B In the example of FIG. 4 , the plasma center may set a donor door-to-door goal of 60 minutes (step 410), and then the system 100 may determine a target number of donations (e.g., each Figure 3C300 in the example above) and / or a target number of donations / donors per hour (e.g., 50 donors per hour) to meet the business goals / objectives set by the plasma center (step 420). The system 100 can then monitor / track the donor arrival rate (e.g., Figure 3C 40 donors per hour) (step 510) and the screening room rate (step 460) so that the system can compare the screening rate to the established metric. If the screening rate is greater than the metric (e.g., 50 donors per hour) (step 465), then the system 100 can track the number of open screening rooms (step 470) to determine if the number of screening rooms is excessive (step 520). If the number of screening rooms is excessive, then the system 100 can generate instructions to the user / plasma center to close some screening rooms (step 530). The center can then close the screening rooms as instructed by the system 100 (step 540), and the system 100 can continue to measure the effectiveness of the instructions. Alternatively, if Figure 3D As shown in , the system 100 can automatically close the screening room instead of instructing the user / plasma center to close the screening room (step 550).

[0050] Figure 3E Another example related to a donor screening process is shown in which the system 100 identifies long wait times within a plasma center. In this example, the plasma center may set a business goal / objective of a maximum wait time (e.g., 10 minutes) for donors 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 objective. For example, the system 100 may track two screenings with 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 commanding 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 staff in accordance with the instructions (step 640). The system 100 may then monitor / measure the effectiveness of the instructions (step 490) and make adjustments as needed. It should be noted that while Figure 3E The system 100 is shown only viewing screening wait times, but the system 100 can similarly view bed / donation machine wait times, payment wait times, etc.

[0051] Figure 4A An exemplary use of the system 100 is shown, where the donor processing rate during the blood draw phase (e.g., at the point where donors are waiting for a bed / single blood draw device; step 438) is lower than the arrival rate. In this example, the business goal set by the plasma center (or inferred by the system 100) may be similar to Figure 3A and 3Bbusiness goal of 60 minutes of donor door-to-door time (step 410). Thus, in a manner similar to that described above, the system 100 can identify the required donor throughput (step 420) and can track the donor arrival rate (step 450). At various points during donor processing and donation, the system 100 can monitor and track various criteria and / or data. For example, when donors are waiting for a bed / single blood collection device to become available (step 438), the system 100 can track the donor floor rate (e.g., how long donors wait for a bed / single blood collection device and how long it takes for them to go through donation processing) (step 710), and if that rate is less than the required throughput (e.g., 60 donors per hour) (step 720), then the system 100 will track the number of open beds / single blood collection devices (step 730).

[0052] Based on this information and whether the beds / single blood collection devices are insufficient to handle the flow of donors (step 740), the system 100 will generate instructions to instruct the user / plasma center to add additional beds (step 750). The plasma center can then add more beds according to the instructions (step 760), and the system 100 will continue to monitor / measure the effectiveness of the instructions (step 490). Alternatively, if Figure 4B As shown in , the system 100 can automatically close the screening room (step 770), for example, by causing the virtual digital assistant 145 to send a command to the downstream donor management 210.

[0053] Figure 4C and 4D An example of a system 100 is shown that determines that the wait time for a blood draw is long (e.g., at step 438), which conflicts with the wait time limit / goal of the plasma center (e.g., less than 10 minutes) (step 810). In this case, the system 100 can track the blood draw wait time (step 820) and determine whether the time is greater than the center's goal (e.g., whether the time is greater than 10 minutes). If the wait time exceeds the goal / goal, then the system 100 will generate an instruction that commands the user / plasma center to add a phlebotomist to the floor, such as via a digital assistant 145 (step 840). Alternatively, if Figure 4D As shown in , the system 100 can automatically address the extended wait time by automatically opening additional beds (e.g., by sending a command to the donor management system 210 via the digital assistant 145) (step 860). In either case, once the center adds additional phlebotomists and / or additional beds are opened, the system 100 can continue to measure the effectiveness of the instructions (step 490).

[0054] Although Figure 4C and 4DThe case where the waiting time is too long is addressed, but in some cases the waiting time may be too short and may indicate some inefficiency and / or overcapacity at the plasma center. Figure 4E As shown in , the system 100 can track the blood draw wait time (step 820), and if there is no wait time (e.g., the wait time is 0) (step 870), then the system 100 can generate instructions to command the user / plasma center to remove staff (or close beds) (step 880) to reduce any inefficiencies in the center (e.g., idle staff, open beds, etc.). The center can then execute the instructions by removing staff (step 890), and the system 100 can then continue to monitor / measure the effectiveness of the instructions (step 490).

[0055] In addition to monitoring the efficiency and business objectives of the screening process and / or blood draw process, other embodiments may be used to monitor, track, and maintain proper inventory of supplies on the plasma center floor. Figure 5A As shown in , if the plasma center has established a goal / target with sufficient available supply (step 910), the system 100 can establish a donation goal and / or an hourly donor goal (step 920), for example, based on the center's known business goals, and can 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 can replenish the donation supply available on the floor (step 930) and determine whether the availability of the supply is insufficient to meet the current demand (e.g., whether there is insufficient to process 60 donors per hour) (step 940). If the amount of supply is insufficient, the system 100 will generate an instruction to command the user / plasma center to replenish the supply (step 950), and send the message / instruction to the user / plasma center, for example, via the digital assistant 145. The user / center can then replenish the supply in response to the received instruction (step 960), and the system 100 can monitor / measure the effectiveness of the instruction (step 490).

[0056] In other cases, such as Figure 5BAs shown in , the plasma center may additionally or alternatively desire to have a balanced supply (e.g., supply line and bin balance) within the plasma center (step 1010). Based on the business goal / objective, the system 100 identifies the required donor throughput (e.g., to meet the plasma center collection objectives) (step 1020), and the system 100 tracks the donor arrival rate (step 1030). During the blood draw phase, for example, when donors are waiting for an open bed (step 438), the system 100 can track the donation floor supply ratio (step 1040) and determine whether the supply is balanced (e.g., the ratio is 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 can balance the supply (step 1070). To ensure that the instructions are working effectively, the system 100 can continue to monitor / measure effectiveness (step 490).

[0057] Figure 5C Another example is shown in which the system 100 tracks the activities of phlebotomists and commands them to perform alternative tasks, such as replenishing supplies. In this example, the plasma center can again set a business goal / objective to maximize supply inventory (step 1110). Then, during the blood draw phase (e.g., when the donor is in the bed; step 440), the system 100 can track the activities of the phlebotomists (step 1120) to determine if any phlebotomists are idle (step 1130). If there are idle phlebotomists, the system 100 can then determine if there is enough room on the floor for additional supplies (step 1140), and if so, the system 100 can instruct the idle phlebotomists to replenish the supplies (step 1150).

[0058] It is important to note that Figures 3A-3E , 4A-4E and 5A-5C illustrate only examples of how the system 100 can be used to meet various business objectives of a plasma center. The system 100 can be used for any number of additional examples and business instructions. In addition, the system 100 can be used to implement multiple business instructions at any given time.

[0059] 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 present invention, and should not be construed as limiting the present invention to any particular device type or system unless the context otherwise requires. Thus, a system may include, but is not limited to, a client, a server, a computer, an appliance, or other types of devices. 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) configured to perform device and / or system functions accordingly. Communication networks may typically include public and / or private networks; may include local area networks, wide area networks, metropolitan area networks, storage networks, and / or other types of networks; and may employ communication technologies, including but by no means limited to analog technology, digital technology, optical technology, wireless technology, networking technology, and interconnection technology.

[0060] The various components of the control program can be implemented individually or in combination. For example, each component can be implemented or a dedicated server or a group of servers can be configured in a distributed manner.

[0061] It should also be noted that the devices may use communication protocols and messages (e.g., messages created, transmitted, received, stored and / or processed by the system), and such messages may be communicated by a communication network or medium. Unless the context otherwise requires, the present invention should not be construed as being limited to any particular communication message type, communication message format, or communication protocol. Therefore, communication messages may generally include, but are not limited to, frames, packets, datagrams, user datagrams, cellular or other types of communication messages. Unless the context otherwise requires, references to specific communication protocols are exemplary, and it should be understood that alternative embodiments may appropriately employ variations of such communication protocols (e.g., modifications or extensions to the protocol that may sometimes be made) or other protocols known or developed in the future.

[0062] It should also be noted that 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 specific logic flow or logic implementation. The described logic can be divided into different logic blocks (e.g., programs, modules, interfaces, functions, or subroutines) without changing the overall result or otherwise departing from the true scope of the present invention. In general, logic elements can be added, modified, omitted, performed in different orders, or implemented using different logic constructions (e.g., logic gates, loop primitives, conditional logic, and other logic constructions) without changing the overall result or otherwise departing from the true scope of the present invention.

[0063] The present invention may be implemented in many different forms, including but not limited to computer program logic used with a processor (e.g., a microprocessor, a microcontroller, a digital signal processor, or a general purpose computer), programmable logic used with a programmable logic device (e.g., a field programmable gate array (FPGA) or other programmable logic device (PLD)), discrete components, integrated circuit systems (e.g., an application specific integrated circuit (ASIC)), or any other components, including any combination thereof. In some embodiments of the present invention, the logic described in principle is implemented as a set of computer program commands that are converted into a computer executable form, stored in a computer readable medium, and executed by a microprocessor under the control of an operating system.

[0064] The computer program logic that implements all or part of the functions previously described herein can be implemented in various forms, including but not limited to source code form, computer executable form, 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, 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 a computer executable form (e.g., via an interpreter), or the source code may be converted into a computer executable form (e.g., via a translator, assembler, or compiler).

[0065] A computer program may be fixed in any form (e.g., source code form, computer executable form, or intermediate form) 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 a fixed disk), an optical memory device (e.g., a CD-ROM), a PC card (e.g., a PCMCIA card), or other memory device. A 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 technologies (including, but not limited to, analog, digital, optical, wireless, networking, and interconnect technologies). A computer program may be distributed in any form as a removable storage medium with an accompanying printed or electronic document (e.g., compressed packaged software), pre-installed with a computer system (e.g., on a system ROM or fixed disk), or distributed from a server or electronic bulletin board via a communication system (e.g., the Internet or the World Wide Web).

[0066] Hardware logic that implements all or part of the functionality previously described herein (including programmable logic used with programmable logic devices) can be designed using traditional manual methods, or can be electronically designed, captured, simulated, or documented 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).

[0067] Programmable logic may be permanently or temporarily fixed 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 a fixed disk), an optical memory device (e.g., a CD-ROM), or other memory devices. Programmable logic may be fixed in a signal that can be transmitted to a computer using any of a variety of communication technologies, including but not limited to analog technology, digital technology, optical technology, wireless technology (e.g., Bluetooth), networking technology, and interconnect technology. Programmable logic may be distributed as a removable storage medium pre-installed with a computer system (e.g., on a system ROM or fixed disk) with an accompanying printed or electronic document (e.g., compressed packaged software), or distributed from a server or electronic device bulletin board via a communication system (e.g., the Internet or the World Wide Web). In fact, some embodiments may be implemented in a software as a service model ("SAAS") or a cloud computing model. Of course, some embodiments of the present invention may be implemented as a combination of both software (e.g., a computer program product) and hardware. Still other embodiments of the present invention are implemented entirely in hardware or entirely in software.

[0068] The embodiments of the present invention described above are exemplary only; many variations and modifications will be apparent to those skilled 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.

Claims

1. A method for generating instructions for maintaining a goal, comprising: integrating control center systems with multiple healthcare provider data systems; obtaining information from at least one of the plurality of health care provider data systems associated with one or more plasma or blood donation centers, the obtained information 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; using artificial intelligence to correlate the obtained information with an identified business goal of at least one plasma or blood donation center, the business goal comprising one or more of a productivity goal, a performance goal, an efficiency goal, and / or a quality goal; generating instructions including at least one direction to the at least one plasma or blood donation center using the heuristic model to achieve the identified business goal; as well as The instructions are presented to at least one user and / or user system so that the instructions can be executed 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: 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 recruiting system, a contact system, a warehouse system, a payroll system, a time tracking system, and a security system.

4. The method of claim 1, wherein the instructions are based on gaps between the obtained information and the identified business objectives.

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

6. The method according to claim 1, further comprising: A company profile is received that includes productivity goals, performance goals, and / or quality goals, the business goal being based at least in part on at least one of the productivity goals, performance goals, and / or quality goals. The method of claim 1 , wherein the business goal comprises a received corporate profile including a location-specific profile. The method of claim 1 , wherein the business goal comprises a received company profile including a time-related profile.

9. The method of claim 1, wherein the business goal is measurable.

10. The method of claim 1, wherein the instructions include information regarding at least one step to be taken to achieve the business goal. The method of claim 10 , wherein the instruction information is location-specific to achieve the business goal.

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 notification, phone call, social media posting, 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 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.

17. The method according to claim 1, further comprising: Information from the plurality of healthcare provider data systems is stored 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 based on the obtained information and a business objective.

21. The method according to 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 objectives.

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 associated with one or more plasma or blood donation centers; a data extractor configured to search the at least one healthcare data system for production data and to retrieve the production data from the at least one healthcare provider data system, the information obtained being 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 velocity data; a data storage device configured to store the retrieved production data; an artificial intelligence module configured to associate the retrieved production information with an identified business goal and generate instructions including at least one indication to achieve the identified business goal, the business goal including one or more of a productivity goal, a performance goal, an efficiency goal, and / or a quality goal; A virtual digital assistant is configured to process the instructions and distribute the instructions to at least one recipient so that the recipient can execute the instructions.

24. The system of claim 23, wherein the artificial intelligence module uses a heuristic model to generate the instructions.

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: 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 recruiting system, an engagement system, a warehouse system, a payroll system, a time tracking system, and a security system.

28. The system of claim 23, wherein the instructions are based on gaps between the obtained information and the identified business objectives.

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

31. The system of claim 23, wherein the business goal 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 goal.

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

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 notification, phone call, social media posting, visual feedback, auditory feedback, and tactile feedback.

35. The system of claim 23, further comprising an electronic interface, the virtual digital assistant being 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 upload performed by a user.

37. The system of claim 23, wherein the instructions are distributed to the at least one recipient such that the instructions can be accessed 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.

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 being based at least in part on the at least one gap.

40. The system of claim 23, further comprising: An instruction listener is configured to monitor the effectiveness of the instructions against the business objectives using artificial intelligence.

41. The system of claim 23, further comprising: The interface is configured to receive a confirmation that the instruction is (a) received by the user or (b) received by the user system.

42. A non-transitory computer recordable medium having computer executable instructions that, when executed on a computing device, perform actions comprising: obtaining location-specific information regarding a plurality of locations associated with one or more plasma or blood donation centers, the location-specific information 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; associating the location-specific information with a plurality of time-specific information; identifying, using the plurality of instructions, a business goal for at least one plasma or blood donation center, the business goal comprising one or more of a productivity goal, a performance goal, an efficiency goal, and / or a quality goal; selecting instructions associated with the business objective based on (a) a location associated with the business objective and / or (b) a time associated with the business objective; as well as Instructions for achieving the business objectives are provided for (a) review by a user and / or (b) execution by a user's system.

43. The non-transitory computer recordable medium of claim 42, wherein the instructions are based on a gap between the obtained information and the identified business objectives.

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