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WO2019166953A1 - Gestion efficace d'échantillons de patient dans un laboratoire - Google Patents

Gestion efficace d'échantillons de patient dans un laboratoire Download PDF

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Publication number
WO2019166953A1
WO2019166953A1 PCT/IB2019/051553 IB2019051553W WO2019166953A1 WO 2019166953 A1 WO2019166953 A1 WO 2019166953A1 IB 2019051553 W IB2019051553 W IB 2019051553W WO 2019166953 A1 WO2019166953 A1 WO 2019166953A1
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WO
WIPO (PCT)
Prior art keywords
sample
smart
laboratory
tube
hub
Prior art date
Application number
PCT/IB2019/051553
Other languages
English (en)
Inventor
Vishwesh B VISHNUMURTHY
Original Assignee
Beckman Coulter Inc.
Priority date (The priority date is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the date listed.)
Filing date
Publication date
Application filed by Beckman Coulter Inc. filed Critical Beckman Coulter Inc.
Publication of WO2019166953A1 publication Critical patent/WO2019166953A1/fr

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Classifications

    • G—PHYSICS
    • G01—MEASURING; TESTING
    • G01N—INVESTIGATING OR ANALYSING MATERIALS BY DETERMINING THEIR CHEMICAL OR PHYSICAL PROPERTIES
    • G01N33/00—Investigating or analysing materials by specific methods not covered by groups G01N1/00 - G01N31/00
    • G01N33/48—Biological material, e.g. blood, urine; Haemocytometers
    • G01N33/483—Physical analysis of biological material
    • G01N33/487—Physical analysis of biological material of liquid biological material
    • G01N33/4875—Details of handling test elements, e.g. dispensing or storage, not specific to a particular test method
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01L—CHEMICAL OR PHYSICAL LABORATORY APPARATUS FOR GENERAL USE
    • B01L3/00—Containers or dishes for laboratory use, e.g. laboratory glassware; Droppers
    • B01L3/50—Containers for the purpose of retaining a material to be analysed, e.g. test tubes
    • B01L3/508—Containers for the purpose of retaining a material to be analysed, e.g. test tubes rigid containers not provided for above
    • B01L3/5082—Test tubes per se
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01L—CHEMICAL OR PHYSICAL LABORATORY APPARATUS FOR GENERAL USE
    • B01L3/00—Containers or dishes for laboratory use, e.g. laboratory glassware; Droppers
    • B01L3/54—Labware with identification means
    • B01L3/545—Labware with identification means for laboratory containers
    • B01L3/5453—Labware with identification means for laboratory containers for test tubes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01L—CHEMICAL OR PHYSICAL LABORATORY APPARATUS FOR GENERAL USE
    • B01L2200/00—Solutions for specific problems relating to chemical or physical laboratory apparatus
    • B01L2200/14—Process control and prevention of errors
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01L—CHEMICAL OR PHYSICAL LABORATORY APPARATUS FOR GENERAL USE
    • B01L2300/00—Additional constructional details
    • B01L2300/02—Identification, exchange or storage of information
    • B01L2300/021—Identification, e.g. bar codes
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01L—CHEMICAL OR PHYSICAL LABORATORY APPARATUS FOR GENERAL USE
    • B01L2300/00—Additional constructional details
    • B01L2300/02—Identification, exchange or storage of information
    • B01L2300/021—Identification, e.g. bar codes
    • B01L2300/022—Transponder chips
    • B—PERFORMING OPERATIONS; TRANSPORTING
    • B01—PHYSICAL OR CHEMICAL PROCESSES OR APPARATUS IN GENERAL
    • B01L—CHEMICAL OR PHYSICAL LABORATORY APPARATUS FOR GENERAL USE
    • B01L2300/00—Additional constructional details
    • B01L2300/08—Geometry, shape and general structure
    • B01L2300/0832—Geometry, shape and general structure cylindrical, tube shaped

Definitions

  • This disclosure relates to management of patient samples in a laboratory.
  • laboratory instruments are used for performing tests on patient samples.
  • tests performed by laboratory instruments fall under various categories such as biochemistry, microbiology, pathology and so on.
  • biological samples may be collected from patients, which may include living organisms covering humans and animals, and collected samples form the patients may be tested using these laboratory instruments for various know parameters. After testing of the samples, a report may be generated on the various parameters that the patient sample was tested for, and may be provided to the patient or a physician.
  • Embodiments of the present disclosure relate to a system and method for tracking samples, preferably biological samples, real time in a laboratory.
  • One embodiment may include creating or generating a smart tube, wherein the smart tube may include a simple tube (such as a test tube) comprising a biological sample that may be further embedded with a sample identification label, wherein the sample identification label may be associated with a particular patient.
  • a further embodiment may include embedding the smart tube with a sensor and associating the sensor with the sample identification label for tracking the presence of the smart tube within the laboratory.
  • Other embodiments are also disclosed.
  • FIGURE 1 illustrates an exemplary smart tube 100 in accordance with the embodiments of the present disclosure
  • FIGURE 2 illustrates an exemplary sample collection model 200 in accordance with the embodiments of the presen t disclosure.
  • FIGURE 3 illustrates tin exemplary laboratory workflow model in accordance with the embodiments of the present disclosure.
  • Embodiment of tire present disclosure relate to a system and a method for tracking samples, preferably biological samples, real time in a laboratory.
  • tracking samples real time in a laboratory and/or hospital is a current challenge that is faced by many laboratories.
  • One embodiment may include creating a smart tube, wherein the smart tube essentially comprises a simple test tube containing a biological sample of the patient.
  • a further embodiment may include embedding the simple test tube containing the patient sample with a sample identification label, wherein the sample identification label is associated with a particular patient. In one embodiment, each patient may have a unique sample identification label.
  • a further embodiment may include embedding the smart tube with a sensor.
  • a further embodiment may include associating the sensor with the sample identification label for tracking the smart tube in the laboratory.
  • the senor may include at least one of a MEMS (micro electromechanical system), a NEMS (nano-electromechanical system), or an RFID (radio frequency identifier).
  • the MEMS may be within a range of 0.01 millimeter to 1 millimeter.
  • the NEMS may be within a range of 1 nanometer to 100 nanometers.
  • the RFID may be a bar code.
  • the MEMS and/or the NEMS may include at least one of a carbon allotrope or smart dust.
  • the MEMS and/or NEMS may comprise material that have semiconducting properties.
  • the MEMS and/or NEMS may be configured to store at a large number of parameters that may be associated with the patient sample or tests from the laboratory instruments.
  • the MEMS/NEMS may be configured to store a up to 32 parameters hi a further embodiment, the parameters may include at least one of a patient Identification, a volume of the patient sample, a residual volume of the patient sample after a test is perfonned, a cell layer, a plasma volume of the sample, a temperature of tire sample, a serum clarity of the sample, a clot in the sample, a STAT sample, an ER (emergency room or casualty ward) sample for work flow' assignment, a time spent on track, a time spent in an analyzer, a time spent in a storage, a time from collection of a sample to a first time the sample is analyzed, a temperature changes associated with the samples, a volume changes associated with the sample, a location associated with the sample at any given point in time, an identity associated with
  • data gathered from the smart tubes may be used to reduce a mix up of patients.
  • data collected from the smart tubes may also be used to reduce Pre-Analytical, Analytical and Post-Analytical errors in the laboratory.
  • data may also provide useable and accurate data for any artificial intelligence or machine learning tools.
  • the smart tube may be able to help .41 tools to group tests based on clinical condition of patient to suggest similar group of tests for other patients with comparable clinical parameters, and thereby reduce time taken by the clinician to arrive at a diagnosis.
  • data gathered from these smart tubes may be able to identify a pattern in tire blood results to suggest physician appropriate tests that could probably turn positive for a current patient based on the‘machine learnt’ pattern from past data.
  • the smart tube may be coupled to a hub, in a hub and spoke arrangement, wherein each hub has a number of spokes and each of the smart tube being represented by a spoke.
  • each hub may advantageously include six smart tubes.
  • each hub may be configured to retain information of the smart tubes.
  • each hub may be configured to be coupled to a laboratory computer.
  • the laboratory computer may include a server or a middleware.
  • die laboratory computer may include a at least a memory and a processing device configured to process instruction and perform specified tasks.
  • the hub may be configured to track a smart tube and report a location of the smart tubes within the hub to the laboratory computer.
  • a further embodiment may include a system comprising a plurality of smart tubes, wherein the smart tubes form a hub, the system further comprising a plurality of hubs that may be communicatively coupled to a laboratory computer, which may be a server or a middleware, and configured to perform the method described above.
  • a laboratory computer which may be a server or a middleware, and configured to perform the method described above.
  • Figure 1 illustrates an exemplary smart tube 100 in accordance with the embodiments of the present disclosure.
  • Figure 1 illustrates a simple tube, for example a test tube.
  • Tire tube contains biological sample 110 collected and stored in the tube by the laboratory.
  • the tube has a barcode 130, for example in the fomi of a sticker printed and pasted on the tube, to identify the tube.
  • the tube contains one or more sensors 120 embedded with the tube thereby making the present tube a smart tube.
  • Sensor 120 may preferably be at least one of a MEMS, NEMS, RFID or smart dust.
  • smart tube has a sensor 120 embedded into sample identifying label or marker 130, wherein sample identifying label 130 has a pre-existing bar code, which is printed on a label and attached to the tube.
  • Sensor 120 may be printed on any material, which for example may be a patient label that identifies a patient hr
  • the smart tube may be configured to communicate via RFID technology with a node (not shown in the figure), which in turn is configured to communicated to a processing device, for example a laboratory' ⁇ computer or a tablet or the likes. In one embodiment, this is a waterproof, battery less and wireless mode of communication.
  • the smart tube system may be configured to manage patient sample quality, to identify volume of a sample, sub-volume of gel separator, sub-volume of cells and sub-volume of plasma temperature of sample, micro-clots and serum index.
  • the smart tube system may be enabled such that an exact location of the tube may be obtained at any point in time within the laboratory, in real time.
  • the patient sample in a Power Express track, the patient sample may be in Analyzer‘A’, or‘B’ etc.
  • the smart tube may further quantify the residual volume of sample in a tube.
  • the smart tube may bond a soft relation between aliquots so that there is no missing or mixing of samples and patients.
  • the smart tube may be configured to identify clots in any of the patient sample .
  • the smart tube may be configured to separate between regular and STAT/A & E samples.
  • the smart tube may be configured to reduce any pre-anaiytieal errors.
  • tire pre-analytical space may include a number of parameters or activities such as sample collection, Sample handling may include the time from collection of the sample to loading the sample into the analyzers or automation track, sample workflow that may include aliquoting, any re-runs, reflex and reflective testing and sample storage.
  • the analytical space may include a number of parameters or activities such as samples for the entire duration they are in the lab, samples while they are in the automation track, and samples while they are being stored until they are discarded from the system.
  • the present disclosure may include a disruptive technology that is not used presently in order to achieve significant benefits in sample management and workflow area to address most of the latent needs of our customers from large to small volume laboratories.
  • sensors for example MEMS and/or NEMS, which are tiny energy efficient systems that work wirelessly through RFID and do not need power to work themselves may be used in the present disclosure for creating a smart tube.
  • the sensors may be waterproof and may be embedded on to materials like bandages, paper stickers (labels or markers) or skin patches and the likes. In a further embodiment, this may be considered as a disruptive technology product that is yet to be used for tracking samples efficiently in a laboratory, which may also include a hospital .
  • artificial intelligence, machine learning or rule based systems may be used to perform the operation mentioned above .
  • Artificial intelligence may be representative of a simulation of human intelligence processes by machines, especially computer systems and/or hub used in the present disclosure.
  • tills processes include learning (the acquisition of information and rules for using the information), reasoning (using rules to reach approximate or definite conclusions) and self- correction
  • the AI techniques used may be weak AI or strong AT
  • machine learning may be used, wherein ML is a method of data analysis that automates analytical model building.
  • the systems can learn from data, identify patterns and make decisions with minimal human intervention.
  • rule based systems may be used, such as a Bayesian belief network or the likes using the data that may be captured and stored in a repository.
  • FIG. 2 illustrates an exemplary sample collection model 200 in accordance with the embodiments of the present disclosure.
  • multiple patient samples in the smart tubes i.e., the tubes with patient samples with sensors embedded to the tubes, can be easily tracked by a single hub device.
  • Each hub in the laboratory includes central hub computer 210 that has at least six (6) samples 220-1, ... , 220-6 coupled to central hub computer 210.
  • the smart tubes 220-1, . . , 220-6, which are multiple sample tubes are coupled through central hub computer 210 to main laboratory computer 230.
  • laboratory computer 230 may include a laboratory information services system, a middleware, a server, a laptop computer or a portable electronic device that configured to process information.
  • the present arrangement allows a seamless flow' of information (data) across the smart tube containing the patient sample and the laboratory computer (server or LIS or middleware).
  • the arrangement as disclosed in the embodiments herein works as a hub and spoke model, wherein multiple such smart tubes containing the sensors may be connected to a node, and multiple nodes may be in turn connected to a computer.
  • bidirectional flow of information may be enabled in this architecture presented herein.
  • sensors may be embedded for creating the smart tubes and typically these sensors may be typically having a dimension of about 1 / 10 th the size of a pinhead.
  • these sensors may be attached to patient labels that may be stuck on the tubes that are used to collect blood or other patient samples.
  • these smart tubes may be configured to gather information about light, temperature, vibration, magnetism, or chemical properties etc., based on any requirement.
  • these smart tubes may be configured to gather information and transmit the information/data to the laboratory computer or a processing device coupled to the smart tubes for further processing the information.
  • vendors may choose to replace existing tubes that may be used to collect patient samples.
  • vendors may paste waterproof stickers or labels containing at least one sensor on each of the tube to create a smart tube.
  • the cost for one such sensor may be about 5 cents or lesser, but advantageously attaching such sensors to the tubes brings in tremendous value in terms of tracking samples and/or efficiently managing samples, and customer are not impacted by this change in the system .
  • quality of smart tube including parameters like its temperature, moisture content, and air quality can be gathered even before collecting a patient sample in the tube .
  • a sample may be linked to a patient using a unique patient ID and from there on be linked to that specific patient.
  • it can be programmed to create a‘child’ number that may be linked to the original or‘parent’ number
  • these tubes may be configured to capture the quality of blood in terms of its volume, temperature and many other parameters.
  • the blood if the blood is centrifuged, it may further go onto measuring the volume of ceils and plasma and may he able to sense any micro clots within the sample.
  • the sample may be configured to provide information on serum indices.
  • accidental spillage in the de-capped stage or while manually handling may be recorded.
  • the sample may be usually stored for a defined period, for any further tests to be conducted under specific conditions to preserve the samples.
  • the sensors on the tube may help provide the information required until the samples are finally discarded hi a further embodiment, if some equipment is reused the sensor may be reprogrammed to bear a new' patient ID or number thereby make it re-usable.
  • smart tubes may significantly impact on the way samples are handled within a lab.
  • the present disclosure addresses most of the latent needs of customers.
  • the present disclosure brings about a huge change to customer experience and thereby improve the overall process of handling and managing samples.
  • being reusable makes this system more desirable and cost efficient to manufacturers and vendors.
  • FIG. 3 is an exemplar)' ⁇ laboratory' workflow model in accordance with the embodiments of the present disclosure.
  • a number of parameters may be measured that may include for example volume of the sample, wherein the sample may be blood or urine, residual volume of the sample after a test is performed. cell layer, plasma volume which may be useful for pipetting depth computations, mapping the right patient to the right sample, temperature of the sample, serum clarity, clots in the sample, identify STAT and ER samples for separate workflow, time spent on tract, time spent on analyzer, time spent in storage, time since collection of the sample to first analyzer, temperature changes, volume changes, identifying a sample at any point in time in the laboratory', locating a sample in the laboratory' etc.
  • a computing system may be integrated wi thin the lab instrument for (not represented in Figures), as being an in tegral part of the lab instrument.
  • the computing system may reside outside the lab instrument and may be configured to operate the lab instrument. It should be understood that such a computing system is only intended to depict the representative major components of the computing system and that individual components may have greater complexity. Moreover, m addition other components such as the number, type, and configuration of such components may vary for such computer systems. Several particular examples of such additional complexity or additional variations are disclosed herein; it being understood that these are by way of example only and are not necessarily the only such variations.
  • the computing system may be interfaced with a laboratory' information system (LIS) or a hospital information system (HIS) and/or a repository which may be part of the LIS/HIS or may be separate.
  • LIS laboratory' information system
  • HIS hospital information system
  • artificial intelligence, machine learning or rule based systems may be used to perform the operation mentioned above.
  • This computing system embodiment comprises a plurality of central processing units (herein generically referred to as a processor or a CPU) connected to a main memory unit, a mass storage interface, a terminal/display interface, a network interface, and an input/output ("I/O") interface by a system bus.
  • the mass storage interfaces connect the system bus to one or more mass storage devices, such as a direct access storage device or a readable/writable optical disk drive.
  • the network interfaces allow the computing system to communicate with other computing systems over the communications medium.
  • the main memory ' unit in this embodiment also compri ses an operating system, a plurality of application program s (such as the application component manager that may control the lab instrument), and some program data.
  • tire computing system is a general-purpose computing device.
  • the CPU’s may be any device capable of executing program instructions stored in the main memory and may themselves be constructed from one or more microprocessors and/or integrated circuits.
  • the computing system may contain multiple processors and/or processing cores, as is typical of larger, more capable computer systems; however, the computing systems may include a single processor system and/or a single processor designed to emulate a multiprocessor system.
  • the associated processor(s) when the computing system starts up, the associated processor(s) initially execute the program instructions that make up the operating system, which manages the physical and logical resources of the computing system.
  • these resources include the main memory, the mass storage interface, the terminal/display interface, the network interface, and the system bus.
  • some computing system may utilize multiple system interfaces and buses, which in turn, may each include their own separate, fully programmed microprocessors.
  • system bus may be any device that facilitates communication between and among the processors; the ma memory; and the interfaces.
  • system bus is relatively simple, single bus structure that provides a direct communication path among the system bus, other bus structures are within the scope of the present disclosure, including without limitation, point-to-point links in hierarchical, star or web configurations, multiple hierarchical buses, parallel and redundant paths, etc.
  • the main memory ' and the mass storage devices w'ork cooperatively in this to store the operating system, the application programs, and the program data.
  • the mam memory is a random-access semiconductor device capable of storing data and programs.
  • this device as a single monolithic entity the main memory may be a more complex arrangement, such as a hierarchy of caches and other memory devices.
  • the main memor may exist in multiple levels of caches, and these caches may be further divided by function, so that one cache holds instructions while another holds non-instruction data, which is used by the processor or processors.
  • the memory may be further distributed and associated with different CPUs or sets of CPUs, as is known in any of various so-called non- uniform memory' access (NUMA) computer architectures.
  • NUMA non- uniform memory' access
  • some embodiments may utilize virtual addressing mechanisms that allow the computing systems to behave as if it has access to a large, single storage entity instead of access to multiple, smaller storage entities such as the mam memory and the mass storage device.
  • the operating system, the application programs, and the program data are typically contained within the main memory , some or ail of them may be physically located on different computing systems and may be accessed remotely, e.g., via the network. In a further embodiment, while the operating system, the application programs, and the program data are typically contained within the main memory, these elements are not necessarily all completely contained in the same physical device at the same time, and may even reside in the virtual memory of other computing systems.
  • the system interface units support communication with a variety of storage and I/O devices
  • the mass storage interface unit supports the attachment of one or more mass storage devices, which are typically rotating magnetic disk drive storage devices, although they could alternatively be other devices, including arrays of disk drives configured to appear as a single large storage device to a host and/or archival storage media, such as hard disk dri ves, tape (e.g., mini-DV), writable compact disks (e.g., CD-R and CD-RW), digital versatile disks (e.g , DVD, DVD-R, DVD+R, DVD+RW, DVD-RAM), holography storage systems, blue laser disks, IBM Millipede devices and the like.
  • mass storage devices which are typically rotating magnetic disk drive storage devices, although they could alternatively be other devices, including arrays of disk drives configured to appear as a single large storage device to a host and/or archival storage media, such as hard disk dri ves, tape (e.g., mini-DV
  • the tenninal/display interface is used to directly connect one or more display units to the computing system.
  • the display units may be non-mteliigent (i.e., dumb) terminals, such as a cathode ray tube, or may themselves be fully programmable workstations used to allow IT administrators and users to communicate with the computing system or the lab instrument itself.
  • dumb non-mteliigent terminals
  • the interface is provided to support communication with one or more displays, the computing systems does not necessarily require a display because all needed interaction with users and other processes may occur via network interface.
  • the computing system with multiple attached terminals such as might be typical of a multi-user“mainframe” computer system. In such a case, the actual number of attached devices is typically a larger number.
  • the computing systems may alternatively be a single-user system, typically containing only a single user display and keyboard input, or might be a server or similar device which has little or no direct user interface, but receives requests from other computer systems (clients).
  • the computing systems may be implemented as a personal computer, portable computer, laptop or notebook computer, PDA (Personal Digital Assistant), tablet computer, pocket computer, telephone, pager, automobile, teleconferencing system, appliance, or any other appropriate type of electronic device.
  • the network may be any suitable network or combination of networks and may support any appropriate protocol suitable for communication of data and/or code to/from multiple computing systems.
  • tire network interfaces can be any device that facilitates such communication, regardless of whether the network connection is made using present day analog and/or digital techniques or via some networking mechanism of the future.
  • suitable communication media include, but are not limited to, networks implemented using one or more of the IEEE (Institute of Electrical and Electronics Engineers) 802.3x“Ethernet” specification: cellular transmission networks; and wireless networks implemented one of the IEEE 802.1 lx, IEEE 802.16, General Packet Radio Service (“GPRS”), FRS (Family Radio Service), or Bluetooth specifications.
  • GPRS General Packet Radio Service
  • FRS Freamily Radio Service
  • Bluetooth Bluetooth
  • inventions described with reference to Figures 1-3 generally may also use a client-server network architecture. These embodiments are desirable because the clients can utilize the services without either computer system requiring knowledge of the working details about the other.
  • client-server network architectures are within the scope of the present invention. Examples of other suitable network architectures include peer-to-peer architectures, grid architectures, and multi-tier architectures. Accordingly, the terms web server and client computer should not be construed to limit the invention to client-server network architectures.
  • the computing system may be operating on different operating systems such Linux, Windows, iOS etc.
  • Linux a single w'orkstations, lap-top computers, mobile telephones, personal digital assistants ("PDAs"), video game systems, or the like.
  • PDAs personal digital assistants
  • suitable tangible, computer-readable signal bearing media include, but are not limited to: (i) non -writable storage media (e.g., read only memory devices ("ROM”), CD-ROM disks readable by a CD drive, and Digital Versatile Disks ("DVDs") readable by a DVD drive); (ii) waitable storage media (e.g., floppy disks readable by a diskette drive, CD-R and CD-RW disks readable by a CD drive, random access memory (“RAM ), and hard disk drives); and (iii) communications media (e.g., computer networks, such as those implemented using“Infmiband” or IEEE 802.3x“Ethernet’ specifications; telephone networks, including cellular transmission networks; and wireless networks, such as those implemented using the IEEE 802.1 lx, IEEE 802.16, General Packet Radio Service (“GPRS”), Family Radio Service (“FRS”), and Bluetooth specifications).
  • GPRS General Packet Radio Service
  • FSS Family Radio Service
  • Bluetooth Bluetooth
  • Embodiments of the present disclosure may also be delivered as part of a service engagement with a client corporation, laboratory information system, hospital system, nonprofit organization, government entity, internal organizational structure, or the like. Aspects of these embodiments may include configuring a computing system to perform, and deploy software, hardware, and services that implement, some or all of tire methods described herein. Aspects of these embodiments may also include analyzing the client’s operations, creating recommendations responsive to the analysis, building systems that implement portions of the recommendations, integrating the systems into existing processes and infrastructure, metering use of the systems, allocating expenses to users of the systems, and billing for use of the systems.
  • Any sen-ice engagement may be directed at providing both the client sendees and the application management sendees may be limited to only application management services, or some combination thereof. Accordingly, these embodiments may further comprise receiving charges from other entities and associating that charge with users of the application m anager.
  • the various software components illustrated in Figures 1-3 and implementing various embodiments of the disclosure may be implemented in a number of manners, including using various computer software applications, routines, components, programs, objects, modules, data structures, etc., referred to hereinafter as "computer programs," or simply “programs.”
  • the computer programs typically comprise one or more instructions that are resident at various times in various memory and storage devices in the computer system, and that, when read and executed by one or more processors in the computing system, cause the computing system to perform steps necessary to execute steps or elements comprising various aspects of an embodiment of the disclosure.
  • the various software components may also be located on different systems. Some embodiments may reside on a computing system and request services from itself or from another computer system. Some embodiments may reside on one or more separate physical devices that are communicatively coupled into a larger, logical computer system .

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Abstract

Des modes de réalisation de la présente invention concernent un procédé et un système de suivi des échantillons en temps réel dans un laboratoire en créant un tube intelligent. Le tube intelligent comprend un échantillon biologique incorporé avec une étiquette d'identification d'échantillon et l'étiquette d'identification d'échantillon est associée à un patient. Le procédé comprend également l'incorporation du tube intelligent avec un capteur et l'association du capteur à l'étiquette d'identification d'échantillon pour suivre le tube intelligent dans le laboratoire.
PCT/IB2019/051553 2018-02-27 2019-02-27 Gestion efficace d'échantillons de patient dans un laboratoire WO2019166953A1 (fr)

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