Remotely-executed medical diagnosis and therapy including emergency automation

• US 10,468,131 B2
• Filed: 12/11/2018
• Issued: 11/05/2019
• Est. Priority Date: 11/23/2011
• Status: Active Grant

• Current Assignee: Whenmed VC LLC
• Original Assignee: Remedev, Inc.
• Inventors: Macoviak, John A., Poulis, Stefanos, Vlachos, Andreas, Macoviak, James J., Macoviak, Richard L.
• Primary Examiner(s): Paulson, Sheetal R
• Application Number:
  US16/216,688
• Publication Number:
  US 20190115097A1
• Time in Patent Office: 329 Days
• CPC Class Codes: A61B 8/4427 Device being portable or laptop-like
• CPC Class Codes: G06Q 10/10 Office automation; Time management
• CPC Class Codes: G06Q 30/018 Certifying business or products
• CPC Class Codes: G06Q 40/08 Insurance
• CPC Class Codes: G16H 10/60 for patient-specific data, e.g. for electronic patient records
• CPC Class Codes: G16H 20/10 relating to drugs or medications, e.g. for ensuring correct administration to patients
• CPC Class Codes: G16H 20/13 delivered from dispensers
• CPC Class Codes: G16H 40/20 for the management or administration of healthcare resources or facilities, e.g. managing hospital staff or surgery rooms
• CPC Class Codes: G16H 40/63 for local operation
• CPC Class Codes: G16H 40/67 for remote operation
• CPC Class Codes: G16H 50/20 for computer-aided diagnosis, e.g. based on medical expert systems
• CPC Class Codes: G16H 50/30 for calculating health indices; for individual health risk assessment

Abstract

Devices, systems, methods, and software for providing remote medical diagnosis and therapy to a subject comprising: a module for conducting telecommunications with a telemedicalist; a module for applying a diagnostic or a therapeutic analysis; an apparatus for dispensing one or more medical items from an inventory of medical items, the inventory of medical items risk profiled to a subject, a population, a venue, or a situation; and optionally, a biosensor apparatus.

Claims

1. A computer-implemented method for distributing medicine to a plurality of subjects, comprising:

storing a medical inventory of one or more medical items in a non-refillable container, the non-refillable container being configured for wireless communication to automatically dispense at least a portion of the one or more medical items to one of the subjects upon receipt of a signal, the one or more medical items being selected for inclusion in the medical inventory, and the selection of the one or more medical items being based on a result of risk profiling the subject associated with the non-refillable container;

determining, at a remote device, whether or not to transmit a signal causing the non-refillable container to be enabled to dispense the at least portion of the one or more medical items; and

in response to determining to transmit the signal, receiving the signal, wherein the signal is transmitted by the remote device, and wherein receiving the signal enables the non-refillable container to automatically dispense the at least a portion of the one or more medical items to the subject,

wherein the determination step includes using at least an observed, a measured, or a reported biometric data of the subject generated during a healthcare encounter between the subject and a diagnostic device, and

wherein the risk profiling includes a processor-executed digital media-containing software using at least the biometric data to calculate a statistical probability that an immediate or future adverse change in a health or an economic condition of the subject will require a current or a future medical treatment for the subject involving the at least a portion of the one or more medical items immediately or during a future time period, or using at least the biometric data as input to at least a machine learning technique to classify a current or a future health or economic risk for the subject or a population that includes the subject that requires a current or a future medical treatment for the subject involving the at least a portion of the one or more medical items.

2. The computer-implemented method of claim 1, further comprising:

generating the biometric data using one or more biometric sensors.

3. The computer-implemented method of claim 1, wherein the signal that causes the at least a portion of the one or more medical items to be automatically dispensed is generated by the remote device, and wherein the signal represents a remote telemedical care provider authorizing dispensing the at least a portion of the one or more medical items of the medical inventory to the subject.

4. The computer-implemented method of claim 1, wherein the risk profiling of the subject includes a processor-executed digital media-containing software using one or more machine-learning techniques to predict a health or economic risk for the subject or a population that includes the subject, the one or more machine learning techniques selected from the group of techniques consisting of nearest neighbor, k-nearest neighbor, decision trees, additive logistics, multivariant adaptive regression splines, support vector machines, neural networks, graphical models, random forests, spectral clustering, principal component analysis, and hidden Markov models.

5. The computer-implemented method of claim 1, wherein the risk profiling of the subject involves one or more statistical likelihood calculations that indicate that treatment for the subject will include the one or more medical items to be provided to cover a predicted defined time period in the future, and wherein the predicted defined time period is a time period happening within two years, one year, six months, one month, two weeks, one week, or one day.

6. The computer-implemented method of claim 1, wherein the biometric data associated with the subject comprises one or more of a systolic blood pressure, a diastolic blood pressure, a heart rate, a respiratory rate, a body temperature, an oxygen saturation, a troponin level, a beta natriuretic peptide level, and a blood glucose level.

7. The computer-implemented method of claim 1, wherein the non-refillable container is further configured to be remotely electronically identifiable.

8. A medicine distribution system comprising:

a non-refillable container adapted to contain therein one or more medical items and further adapted for wireless communication to remotely enable automatic dispensing at least a portion of the one or more medical items to a subject in response to receipt of a signal;

a remote device adapted to provide diagnosis of or therapy to the subject based on an observed or a reported biometric data of the subject following a healthcare encounter between the subject and a diagnosis device, the remote device comprising a processor for executing a digital media-containing software, the software adapted to,

using at least the biometric data to calculate a statistical probability that an immediate or future adverse change in a health condition of the subject will require a current or a future medical treatment for the subject involving the at least a portion of the one or more medical items immediately or during a future time period,

using at least the biometric data as input to at least a machine learning technique to classify a current or a future health or economic risk for the subject or a population that includes the subject that requires a current medical treatment for the subject involving the at least a portion of the one or more medical items, and

transmitting the signal to the non-refillable container to enable it to dispense.

9. The system of claim 8, further comprising:

a biosensor for generating the biometric data, the biometric data being generated in response to one or more measurements taken from the subject.

10. The system of claim 8, wherein the signal includes information that represents a remote telemedical care provider electronically authorizing the dispensing of the at least a portion of the one or more medical items to the subject.

11. The system of claim 8, wherein the result of the classification by the machine learning technique is provided to a healthcare provider.

12. The system of claim 8, wherein the time period is a time period happening within two years, one year, six months, one month, two weeks, one week, and one day.

13. The system of claim 8, wherein the biometric data comprises one or more of a systolic blood pressure, a diastolic blood pressure, a heart rate, a respiratory rate, a body temperature, an oxygen saturation, a troponin level, a beta natriuretic peptide level, and a blood glucose level.