Data assessment and visualization platform for use in a network environment including computing devices

A computer-implemented method for providing analytics relating to patients and medical interventions, the method comprising:

• receiving a first request to analyze historical sensor data collected from a plurality of computing devices, wherein the first request includes (i) first characteristics data associated with the plurality of computing devices, and (ii) second characteristics data associated with a plurality of target actions, wherein at least a first subset of the historical sensor data is associated with a first type of target actions and a second subset of the historical sensor data is associated with a second type of target actions different from the first type of target actions;
• and
• identifying a set of temporal windows based at least in part on the historical sensor data associated with a first computing device of the plurality of computing devices and a first target action associated with a reference point, wherein identifying the set of temporal windows comprises one or both of (i) identifying two or more pre-reference temporal windows preceding the reference point based at least in part on the historical sensor data collected prior to the reference point exhibiting a first threshold level of change, or (ii) two or more post-reference temporal windows following the reference point based at least in part on the historical sensor data collected subsequent to the reference point exhibiting a second threshold level of change different from the first threshold level of change;
• generating outcome data based at least in part on a comparison of the historical sensor data in two or more temporal windows of the set of temporal windows, wherein the outcome data indicates a level of effectiveness of the first target action for the historical sensor data collected from the first computing device;
• and
• storing, in a data repository, the outcome data in association with (a) at least a portion of the first characteristics data associated with the first computing device and (b) at least a portion of the second characteristics data associated with the first target action, such that the outcome data is retrievable in a characteristics-specific manner;
• receiving, from a second computing device, a second request to analyze additional sensor data collected from a third computing device and not included in the historical sensor data, wherein the second request includes third characteristics data associated with the third computing device not included in the plurality of computing devices;
• retrieving, from the data repository, first analytics data based at least in part on the third characteristics data and a second target action of the plurality of target actions, wherein the first analytics data is a subset of the outcome data stored in the data repository that corresponds to at least a portion of the third characteristics data and the second target action;
• determining, based at least in part on the first analytics data and the additional sensor data collected from the third computing device, (a) a predicted effectiveness value associated with the second target action for the additional sensor data and (b) an indication of predicted sensor data values to be collected from the third computing device subsequent to the second target action;
• retrieving, from the data repository, second analytics data based at least in part on the third characteristics data and a third target action of the plurality of target actions different from the second target action, wherein the second analytics data is a subset of the outcome data stored in the data repository that corresponds to at least a portion of the third characteristics data and the third target action;
• determining, based at least in part on the second analytics data and the additional sensor data collected from the third computing device, (c) a predicted effectiveness value associated with the third target action for the additional sensor data and (d) an indication of predicted sensor data values to be collected from the third computing device subsequent to the third target action;
• generating one or both of (i) a first comparison of (a) the predicted effectiveness value associated with the second target action for the additional sensor data and (c) the predicted effectiveness value associated with the third target action for the additional sensor data, or (ii) a second comparison of (b) the indication of predicted sensor data values to be collected from the third computing device subsequent to the second target action and (d) the indication of predicted sensor data values to be collected from the third computing device subsequent to the third target action;
• and
• outputting, via a user interface associated with the second computing device, a visualization of one or both of the first comparison or the second comparison.

A non-transitory computer-readable medium storing instructions that, when executed by a computing system, cause the computing system to perform operations comprising:

• receiving a first request to analyze historical sensor data collected from a plurality of computing devices, wherein the first request includes (i) first characteristics data associated with the plurality of computing devices, and (ii) second characteristics data associated with a plurality of target actions, wherein at least a first subset of the historical sensor data is associated with a first type of target actions and a second subset of the historical sensor data is associated with a second type of target actions different from the first type of target actions;
• and
• identifying a set of temporal windows based at least in part on the historical sensor data associated with a first computing device of the plurality of computing devices and a first target action associated with a reference point, wherein identifying the set of temporal windows comprises one or both of (i) identifying two or more pre-reference temporal windows preceding the reference point based at least in part on the historical sensor data collected prior to the reference point exhibiting a first threshold level of change, or (ii) two or more post-reference temporal windows following the reference point based at least in part on the historical sensor data collected subsequent to the reference point exhibiting a second threshold level of change different from the first threshold level of change;
• generating outcome data based at least in part on a comparison of the historical sensor data in two or more temporal windows of the set of temporal windows, wherein the outcome data indicates a level of effectiveness of the first target action for the historical sensor data collected from the first computing device;
• and
• storing, in a data repository, the outcome data in association with (a) at least a portion of the first characteristics data associated with the first computing device and (b) at least a portion of the second characteristics data associated with the first target action, such that the outcome data is retrievable in a characteristics-specific manner;
• receiving, from a second computing device, a second request to analyze additional sensor data collected from a third computing device and not included in the historical sensor data, wherein the second request includes third characteristics data associated with the third computing device not included in the plurality of computing devices;
• retrieving, from the data repository, first analytics data based at least in part on the third characteristics data and a second target action of the plurality of target actions, wherein the first analytics data is a subset of the outcome data stored in the data repository that corresponds to at least a portion of the third characteristics data and the second target action;
• determining, based at least in part on the first analytics data and the additional sensor data collected from the third computing device, (a) a predicted effectiveness value associated with the second target action for the additional sensor data and (b) an indication of predicted sensor data values to be collected from the third computing device subsequent to the second target action;
• retrieving, from the data repository, second analytics data based at least in part on the third characteristics data and a third target action of the plurality of target actions different from the second target action, wherein the second analytics data is a subset of the outcome data stored in the data repository that corresponds to at least a portion of the third characteristics data and the third target action;
• determining, based at least in part on the second analytics data and the additional sensor data collected from the third computing device, (c) a predicted effectiveness value associated with the third target action for the additional sensor data and (d) an indication of predicted sensor data values to be collected from the third computing device subsequent to the third target action;
• generating one or both of (i) a first comparison of (a) the predicted effectiveness value associated with the second target action for the additional sensor data and (c) the predicted effectiveness value associated with the third target action for the additional sensor data, or (ii) a second comparison of (b) the indication of predicted sensor data values to be collected from the third computing device subsequent to the second target action and (d) the indication of predicted sensor data values to be collected from the third computing device subsequent to the third target action;
• and
• outputting, via a user interface associated with the second computing device, a visualization of one or both of the first comparison or the second comparison.