Abstract: The example systems, methods, and devices disclosed herein generally relate to handling operating data from non-communicative assets. In some instances, a data-analytics platform receives operating data points from a given asset of a plurality of assets. Based on that data, the data-analytics platform detects a communication abnormality at the given asset, in accordance with one or more techniques disclosed herein. In response to detecting the communication abnormality, the data-analytics platform designates the given asset as being non-communicative. The data-analytics platform handles operating data points received from the given asset in accordance with the non-communicative designation.

Abstract: Disclosed herein are systems, devices, and methods related to a determination of whether an asset has a fluid issue. In particular, examples involve a platform defining a predictive model for outputting an indicator of whether an asset is likely to have a fluid issue based at least on historical fluid data for one or more assets. The historical fluid data may comprise at least one of a plurality of fluid reports for the one or more assets and an indication of a fluid issue for each fluid report. The platform may receive at least one fluid report associated with a given asset and based at least on the predictive model and the received at least one fluid report, make a determination that the given asset is likely to have a fluid issue. The platform may cause a computing device to output an indication of the determination.

Abstract: Disclosed herein are systems, devices, and methods related to patient response to outreach options of healthcare facilities. Examples involve determining patient response metrics for patients based on patient data and/or other data. A patient response metric indicates a probability that a patient will perform a medically-related patient action in response to an outreach option. Example output data can indicate various outreach options, patient response metrics for outreach options, expected value of implementing outreach options, and/or recommendations of outreach options.

Abstract: Implementations generally relate to forecasting a support requirement for a health care unit to use in preparing patient support at a target time. In some implementations, a method includes accessing external conditions data for a plurality of different external conditions projected for the location at the target time. The target time and the external conditions data may be provided into a prediction model, which identifies one or more reference times prior to the target time that are predictive of the target time, accesses historical data for the reference times, and outputs the data indicating a support requirement based on the historical data and external conditions data.