Patent Issued for Assisting researchers to identify opportunities for new sub-studies in digital health research and decentralized clinical trials (USPTO 11586524): VigNet Incorporated
2023 MAR 15 (NewsRx) -- By a
Patent number 11586524 is assigned to
The following quote was obtained by the news editors from the background information supplied by the inventors: “In many fields, remote devices can be used to monitor changes in conditions over time. Data from the remote devices can be collected over a communication network so that the information from various remote devices can be aggregated and processed. Monitoring programs have varying levels of efficiency and effectiveness, however, as real-world constraints often limit the accuracy and completeness of data gathered. As a result, many monitoring programs do not achieve all of their objectives, in many cases leading to significant inefficiency as devices consume battery power, processing resources, and network bandwidth for actions or entire monitoring programs that fail to achieve the level of monitoring intended. Even monitoring programs that do achieve their objectives may cause inefficiencies by monitoring more devices than are needed or by carrying out broad monitoring that is not well tailored to detect and characterize the events and conditions that are of interest.”
In addition to the background information obtained for this patent, NewsRx journalists also obtained the inventors’ summary information for this patent: “In some implementations, a server system manages monitoring programs that involved distributed monitoring using remote devices. The server system can improve the efficiency and effectiveness of monitoring by selectively changing monitoring parameters for specific groups of devices that the system identifies. For example, a monitoring program can involve a first group of remote devices that each separately make measurements with one or more sensors and report the data to the server system. From the monitoring data received, the server system can detect events and conditions that present opportunities for improvements in efficiency and effectiveness and adapt the monitoring program in response. The server system can then create a new monitoring program, selects a subset of the remote devices to involve in the new monitoring program, and reconfigure the remote devices in the subset to change their monitoring operations.
“As an example, a few of the remote devices involved in a monitoring program may detect a particular condition, and the system may evaluate the monitoring data and determine that the particular condition justifies enhanced monitoring, e.g., to investigate the causes, effects, or rate of occurrence of the particular condition. The system causes the enhanced monitoring to be performed selectively for a subset of remote devices identified as the most efficient and most effective to monitor the particular condition of interest. The system may determine that a subset of the remote devices have a context that results in a high likelihood of experiencing the particular condition, while other remote devices do not. The system can then adapt the monitoring parameters for the original monitoring program to better detect the particular condition and related factors (e.g., by changing sensor operation, measurement frequency, precision or type of reported data, etc.), in many cases generating a new monitoring program tailored the particular condition to be detected. The system can then send updated software, updated firmware, configuration data, instructions, or other elements over a network to remotely alter operation of the remote devices in the subset to begin the new, enhanced monitoring program. By selectively adjusting and expanding monitoring for a targeted subset of devices, the system enables better monitoring results while avoiding increased resource usage (e.g., battery power, CPU usage, network bandwidth, etc.) for devices outside the subset where the expanded monitoring is not likely to provide meaningful monitoring results. In addition, the system limits the need for configuration changes to the devices for which the additional monitoring is most likely to be effective.
“The system can detect conditions, adapt monitoring programs in response, and selectively reconfigure subsets of the devices in the monitoring programs. These techniques improve the efficiency and effectiveness of monitoring using distributed sets of remote devices, including maximizing monitoring coverage with a small number of devices. In addition, the system can leverage the historical data for devices to identify and select devices that have performed well. This allows higher confidence and higher likelihood of successful monitoring as these devices are often likely to continue a pattern of complying with data collection requirements and data quality requirements. With higher likelihoods of high performance, the groups of devices in further monitoring programs can be smaller and still achieve the coverage and reliability needed.
“From an initial monitoring program, the system can adaptively adjust monitoring by creating or initiating one or more additional monitoring programs that operate independently or together with the original monitoring program. The adaptive nature of the system also allows it to automatically investigate unusual conditions that occur, even if those conditions are not anticipated. From a first monitoring program with 1000 devices, the system may detect an unusual result for some number of them, such as 7 of the devices. The unusual result could be a negative event (e.g., a device error) or a positive event (e.g., unusually high performance). Even without a defined or predetermined reference specifying that the unusual result justifies further monitoring, the system can detect that the result is significant based on comparison with the prior monitored history, patterns (e.g., trends, progressions, rates of change, etc.), distribution of results among devices, clustering of results, and other techniques.
“The system can evaluate the factors in common among the devices that reported the unusual result (e.g., aspects of location, attributes, history, environment, etc.) and determine which are shared or are most correlated with the result. This allows the system to generate a set of criteria for selecting devices for which the result is likely to occur, even if the result has not occurred yet for those devices. For example, the system may determine that certain locations (e.g., western
The claims supplied by the inventors are:
“1. A method of managing health research studies involving remote devices, the method comprising: communicating, by one or more computers, with a set of remote devices involved in a first health research study that involves collection of data from the remote devices over a communication network, wherein the set of remote devices involved in the first health research study are remote devices respectively used by different participants in a cohort of the first health research study, wherein communicating with the remote devices comprises receiving, from each of the remote devices over the communication network, a series of messages including monitoring data collected by the remote device at different times for first types of data specified by the first health research study; comparing, by the one or more computers, the monitoring data for individual participants in the cohort with one or more aggregate measures for the cohort that are generated based on the monitoring data for multiple participants in the cohort; based on the comparisons, determining, by the one or more computers, that a difference between individual participant monitoring data and the one or more aggregate measures for the cohort is shared by multiple of the participants in the cohort of the first health research study; determining, by the one or more computers, that the prevalence with which the difference from the one or more aggregate measures occurs among the cohort satisfies one or more criteria for initiating a sub-study from the first health research study; in response to determining that the prevalence satisfies the one or more criteria, determining, by the one or more computers, second types of data to collect in a second health research study that is a sub-study of the first health research study, the second health research study having a cohort of participants that includes one or more of the participants in the cohort of the first health research study; generating, by the one or more computers, a software module for the second health research study or configuration data for the second health research study, wherein the software module or configuration data is configured to cause collection of data of the second types of data; and configuring, by the one or more computers, one or more devices of participants in the second health research study to perform monitoring for the second health research study that includes acquiring data for the second types of data and providing the acquired data to a server over the communication network, wherein configuring the one or more devices comprises distributing, to the one or more devices, the software module or configuration data that is configured to cause the one or more devices to collect data of the second types of data.
“2. The method of claim 1, wherein the second types of data comprise measurements made using one or more sensors of the one or more devices or of devices communicatively coupled to the one or more devices.
“3. The method of claim 2, wherein the measurements comprise one or more physiological or behavioral measurements.
“4. The method of claim 1, wherein the second types of data comprise user inputs as responses to surveys provided as part of the second health research study.
“5. The method of claim 1, wherein the second types of data comprise the first types of data and one or more additional types of data.
“6. The method of claim 1, comprising: storing data indicating predetermined conditions for generating new health research studies; and determining that the predetermined conditions are satisfied; wherein the configuring is performed in response to determining that the predetermined conditions are satisfied.
“7. The method of claim 6, wherein the predetermined conditions comprise detecting a health outcome among at least a minimum number of participants in the cohort of the first health research study.
“8. The method of claim 1, further comprising determining, by the one or more computers, one or more parameters for the second health research study including at least one of: selection criteria for selecting devices or participants to involve in the second health research study; timing parameters that specify timing of data collection in the second health research study; or data collection techniques that specify techniques for collecting the second types of data; wherein the software module or configuration data for the second health research study is generated based in part on the determined one or more parameters.
“9. A system comprising: one or more computers; and one or more computer-readable media storing instructions that are operable, when executed by the one or more computers, to cause the system to perform operations comprising: communicating, by one or more computers, with a set of remote devices involved in a first health research study that involves collection of data from the remote devices over a communication network, wherein the set of remote devices involved in the first health research study are remote devices respectively used by different participants in a cohort of the first health research study, wherein communicating with the remote devices comprises receiving, from each of the remote devices over the communication network, a series of messages including monitoring data collected by the remote device at different times for first types of data specified by the first health research study; comparing, by the one or more computers, the monitoring data for individual participants in the cohort with one or more aggregate measures for the cohort that are generated based on the monitoring data for multiple participants in the cohort; based on the comparisons, determining, by the one or more computers, that a difference between individual participant monitoring data and the one or more aggregate measures for the cohort is shared by multiple of the participants in the cohort of the first health research study; determining, by the one or more computers, that the prevalence with which the difference from the one or more aggregate measures occurs among the cohort satisfies one or more criteria for initiating a sub-study from the first health research study; in response to determining that the prevalence satisfies the one or more criteria, determining, by the one or more computers, second types of data to collect in a second health research study that is a sub-study of the first health research study, the second health research study having a cohort of participants that includes one or more of the participants in the cohort of the first health research study; generating, by the one or more computers, a software module for the second health research study or configuration data for the second health research study, wherein the software module or configuration data is configured to cause collection of data of the second types of data; and configuring, by the one or more computers, one or more devices of participants in the second health research study to perform monitoring for the second health research study that includes acquiring data for the second types of data and providing the acquired data to a server over the communication network, wherein configuring the one or more devices comprises distributing, to the one or more devices, the software module or configuration data that is configured to cause the one or more devices to collect data of the second types of data.
“10. The system of claim 9, wherein the second types of data comprise measurements made using one or more sensors of the one or more devices or of devices communicatively coupled to the one or more devices.
“11. The system of claim 10, wherein the measurements comprise one or more physiological or behavioral measurements.
“12. The system of claim 9, wherein the second types of data comprise user inputs as responses to surveys provided as part of the second health research study.”
There are additional claims. Please visit full patent to read further.
URL and more information on this patent, see: Jain, Praduman. Assisting researchers to identify opportunities for new sub-studies in digital health research and decentralized clinical trials.
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