Abstract: Apparatus for assessing medical risks of a patient includes an analytics engine and equipment that provides data to the analytics engine. The analytics engine analyzes the data from the equipment to determine a sepsis risk score, a falls risk score, and a pressure injury score. The apparatus further include displays that are communicatively coupled to the analytics engine and that display the sepsis, falls, and pressure injury risk scores. The displays include a status board display located at a master nurse station, an in-room display provided by a room station of a nurse call system, an electronic medical records (EMR) display of an EMR computer, and a mobile device display of a mobile device of a caregiver assigned to the patient.

Abstract: Systems include a plurality of sensors coupled to a person support apparatus, at least one moisture sensor configured to sense a moisture level between the person and the support surface, and at least one computing device coupled to the plurality of sensors coupled to the person support apparatus and the at least one moisture sensor. The at least one computing device receives data from the plurality of sensors coupled to the person support apparatus and the at least one moisture sensor, obtains data from an electronic medical record associated with the person supported by the person support apparatus, calculates a pressure injury score indicative of a likelihood that the person will develop a pressure injury based on the data from the plurality of sensors, the at least one moisture sensor, and the electronic medical record, and alters a treatment plan for the person based on the calculated pressure injury score.

Abstract: An example method includes identifying images of an individual and determining, based on the images, a facial feature of the individual. The example method further includes determining a contextual feature of the individual. Based on the facial feature and the contextual feature, an identity of the individual is determined.

Abstract: An example method includes capturing images using a camera and detecting a medical device in a first image among the images. A request is transmitted to the medical device. Based on transmitting the request, the example method includes determining that the medical device has output a chirp signal in a second image among the images. Based on the chirp signal, the method includes causing the medical device to perform an action by transmitting a control message to the medical device.

Abstract: An example method includes receiving a 2D image of a 3D space from an optical camera, identifying, in the 2D image. A virtual image generated by an optical instrument refracting and/or reflecting the light is identified. The example method further includes identifying, in the 2D image, a first object depicting a subject disposed in the 3D space from a first direction extending from the optical camera to the subject and identifying, in the virtual image, a second object depicting the subject disposed in the 3D space from a second direction extending from the optical camera to the subject via the optical instrument, the second direction being different than the first direction. A 3D image depicting the subject based on the first object and the second object is generated. Alternatively, a location of the subject in the 3D space is determined based on the first object and the second object.

Abstract: Various techniques for determining risks to patients and care providers based on images are described herein. According to some examples, images of an individual in a clinical setting are identified. A risk that the individual will experience an adverse event, such as an injury, is calculated. An alert or report is output based on the risk.

Abstract: An example patient scheduling system can include: at least one processor; and system memory encoding instructions which, when executed by the at least one processor, cause the system to: provide a schedule for a patient, the schedule defining care items associated with the patient; allow for acceptance of a patient care activity; and notify a caregiver and the patient of changes to the patient care activity.

Abstract: Apparatus for assessing medical risks of a patient includes an analytics engine and equipment that provides data to the analytics engine. The equipment includes a patient support apparatus such as a patient bed, a nurse call computer, a physiological monitor, a patient lift, a locating computer of a locating system, and an incontinence detection pad. The analytics engine analyzes the data from the equipment to determine a sepsis risk score, a falls risk score, and a pressure injury score. The apparatus further include displays that are communicatively coupled to the analytics engine and that display the sepsis, falls, and pressure injury risk scores. The displays include a status board display located at a master nurse station, an in-room display provided by a room station of a nurse call system, an electronic medical records (EMR) display of an EMR computer, and a mobile device display of a mobile device of a caregiver assigned to the patient.

Abstract: An example method includes outputting, by an output device, a first Graphical User Interface (GUI) associated with a patient. A font size of the first GUI is adjusted based on a position of the patient. Based on determining that a position of a care provider is within the threshold distance of the output device or within the room associated with the patient, outputting, by the output device, the second GUI being different than the first GUI.

Abstract: A microclimate management system including a person support surface including one or more sensors, a fluid supply device coupled to an inlet of the person support surface and configured to supply fluid to an outlet the person support surface, and a controller configured to detect an inlet condition value at the inlet of the person support surface, detect an outlet condition value at the outlet of the person support surface, determine a difference between the inlet condition value and the outlet condition value, and transmit a first alert in response to determining that a rate of change of the difference between the inlet condition value and the outlet condition value is below a lower condition threshold.

Abstract: An example system for assessing catheterization risk can include: a processor; and memory with instructions which, when executed by the processor, cause the processor to: receive information relating to a current state of a patient; perform an assessment of risk associated with catheterization of the patient; and provide a recommendation for the catheterization based upon the assessment of risk

Abstract: This disclosure is directed towards a patient management system for anticipating patient needs associated with toileting. In some examples, a computing device of the patient management system determines a toilet need schedule for a patient based on conditions of the patient (e.g., from an electronic medical record of the patient) and/or events that occur associated with the patient, such as meals or beverages consumed, toileting events, medications taken, and so forth. Additionally, the patient management system may sense when a patient is moving towards a patient relief device, when the patient is using the patient relief device, and/or when the patient has concluded using the patient relief device. Such information may be provided to a healthcare provider so that the healthcare provider may assist with toileting needs to increase safety of the patient and/or to reduce accidents associated with toileting needs of the patient.

Abstract: A mobility management system receives movement data from sensors that detect movements of a patient resting in a patient support apparatus and movement data from one or more mobility detection devices that detect movement of the patient when the patient exits the patient support apparatus. The system determines a mobility status based on at least the movement data received from the patient support apparatus and the one or more mobility detection devices, and adjusts a care protocol for the patient based on the mobility status.

Abstract: A monitoring system for tracking pressure related injury risk includes a support apparatus with a controller and communication circuitry configured to communicate via a communication network. A control unit is configured to communicate with at least one of a remote server and the support apparatus via the communication network. The control unit is configured to determine at least one of a risk status and a risk score for developing a pressure injury in response to communication from the at least one of the remote server and the support apparatus, determine at least one contributing risk factor for developing the pressure injury, and generate a notification configured to be communicated to a user interface assembly.

Abstract: This disclosure is directed towards a patient management system for analyzing images of wounds and tracking the progression of wounds over time. In some examples, a computing device of the patient management system receives an image, and determines that the image depicts a wound. The computing device inputs the image into a machine-learned model trained to classify wounds, and receives, from the machine-learned model, a classification of the wound. The computing device may then display the classification of the wound in a user interface. Additionally, the patient management system may train a machine-learned model to classify wounds.

Abstract: Various systems, devices, and methods for predicting and identifying root causes of pressure injuries in a clinical environment are described. An example method includes identifying, based on an electronic medical record (EMR) of a patient, that the patient has an injury; receiving, from one or more sensors, sensor data indicating one or more parameters of the patient; determining, based on the sensor data, at least one root cause of the injury; and transmitting, to an external computing device, a report indicating the at least one root cause of the injury.

Abstract: This disclosure is directed towards a patient management system for selectively generating, storing, and/or sharing patient activity data. A patient management system may receive, at an activity device, patient activity data indicative of activities of a patient. The patient management system may determine a raw score for the patient based on the activity data. The patient management system may combine component scores associated with activities performed by the patient to determine the raw score. Further, the patient management system may determine that the raw score is greater than a score threshold, and generate an activity score based on determining that the raw score is greater than the score threshold. The patient management system may output the activity score to an electronic device, such as a clinician device and/or a device associated with the patient, determine trends associated with the activity score, and/or compare the activity score to a mobility protocol.

Abstract: Systems, methods, and devices relate to monitoring biological conditions (e.g., vital signs) using patient-specific ranges. An example method includes receiving, from a sensor, first measurements of a vital sign of an individual determined automatically during a first time period and determining a baseline of the vital sign based on the first measurements by averaging the first measurements. A threshold of the vital sign can be a predetermined percentage of the baseline. Second measurements of the vital sign can be received from the sensor. In response to determining that at least one of the second measurements is outside of the range, an alarm may be triggered.

Abstract: A sepsis monitoring system determines an initial sepsis risk assessment score, and automatically and continuously updates the sepsis risk assessment score using a sepsis risk assessment model that receives vital signs data, electronic medical records data, and admissions data to continuously update the sepsis risk assessment score. The system determines whether the patient is likely to develop sepsis based on the updated sepsis risk assessment score, and in response to determining that the patient is likely to develop sepsis, generates a notification to drive an early intervention by one or more caregivers.

Abstract: A sepsis automated reporting system generate a sepsis report that is accessible on one or more workstations. The sepsis report includes a display area that is customizable based on a selection of one or more parameters in a parameter configuration box. The customizable display area and the parameter configuration box are both displayed in the sepsis report, and the display area is automatically updated based on the selection of the one or more parameters.