Abstract: Techniques for administering a care plan for a patient. A monitoring device is selected, at a care plan management system based on a care plan, to use in administering the care plan. The care plan specifies biometric data to monitor for a patient. The monitoring device is configured to collect the biometric data, based on the care plan. The biometric data collected using the monitoring device is received at the care plan management system. The biometric data includes a first event initially classified as a first type of event using the monitoring device. The first event is selected for reclassification, based on the initial classification, and in response the first event is reclassified as a second type of event using the care plan management system. The patient is treated based on the care plan and the reclassified first event.

Abstract: A system is provided for operation with a facility providing peritoneal dialysis exchanges for multiple peritoneal dialysis patients. The system can include a peritoneal dialysis solution supply, peritoneal dialysis sets to deliver peritoneal dialysis solution to the peritoneal dialysis patients at the facility, a computer, and a treatment station. The computer can electronically read a prescription for a patient, electronically identify a quantity of the peritoneal dialysis solution from the prescription, and electronically identify a peritoneal dialysis set from the peritoneal dialysis sets for use with the identified quantity of the peritoneal dialysis solution.

Abstract: One variation of a method for accessing medication parameters for prescription medications includes: reading a unique identifier from a medication cartridge installed in a medication dispenser; based on the unique identifier and a dispenser identifier assigned to the medication dispenser, confirming assignment of the medication cartridge to the medication dispenser; based on the dispenser identifier, retrieving medication parameters for a medication contained in the medication cartridge; and at the medication dispenser, outputting a dynamic visual queue to consume a dose of the medication from the medication cartridge during a medication window, the medication window of a duration based on the medication parameters.

Abstract: The method of obtaining DICOM files may comprise receiving, by a processor, scanning data of a scannable graphic associated with an item, wherein the scannable graphic is associated with DICOM tag data; extracting, by the processor, the DICOM tag data from the scanning data; determining, by the processor, that the DICOM tag data is associated with a first DICOM file; identifying, by the processor, a user of the first DICOM file; retrieving, by the processor, the first DICOM file; searching, by the processor, for other DICOM files that are associated with at least one of the user or the first DICOM file; retrieving, by the processor, the other DICOM files; and sending, by the processor and to the user, the first DICOM file and the other DICOM files.

Abstract: Devices, systems, and methods are provided for adherence monitoring and patient interaction. In general, the devices, systems, and methods can facilitate a patient's adherence to a medication schedule and can facilitate monitoring and tracking of the patient's adherence to the medication schedule. In one embodiment, a medical accessory such as a cap is provided that can be configured to attach to existing medication dispensers, such as asthma inhalers, or to be integrated into a custom-made medication dispenser. The accessory can be configured to provide a notification to the patient when medication is due. The accessory can be configured to detect usage of the dispenser. The accessory can be configured to provide data regarding dispensing of the medication to an external device. The data can be analyzed and provided for visualization on a user interface.

Abstract: A method includes obtaining prescribing drug information and published guidelines for each of a plurality of ADMs available for managing glucose levels, and receiving patient information associated with a patient. The method also includes ordering total demerit values from lowest to highest, selecting a predetermined number of recommended ADMs associated with the lowest total demerit values, and determining a recommended dosage for each recommended ADM. The method also includes transmitting a therapy regimen to a patient device associated with the patient. The therapy regimen includes the recommended ADMs and the recommended dosage for each recommended ADM.

Abstract: Provided herein are methods and systems for making patient-specific therapy recommendations of an anti-inflammatory therapy for patients with known or suspected cardiovascular disease, such as atherosclerosis.

Abstract: Provided herein are methods and systems for making patient-specific therapy recommendations of an anti-diabetic therapy for patients with known or suspected cardiovascular disease, such as atherosclerosis.

Abstract: Methods, systems, and computer-readable media are provided for facilitating record matching and entity resolution and for enabling improvements in record linkage. A power-spectrum-based temporal pattern-specific weight may be incorporated into record linkage methods to enhance the record linkage accuracy and statistical performance. For example, in embodiments, a value-specific weight may be calculated from a population-based frequency of field-specific values or dichotomized values of selected phenotypic variables, and provides an opportunity to capture and measure the relative importance of specific values found in a field. A phenotypic bit-vector “fingerprint” pattern-specific weight or Bayesian power spectrum weight may be determined and incorporated into record linkage methods.

Abstract: Systems, methods and computer-readable media are provided for facilitating patient health care through automatic discovery, establishment, and statistical validation of safety signals in repositories of EMR information, identifying safety signals regarding therapeutics or therapeutics combinations administered to patients. In an embodiment, a method includes identifying, from a dataset of health care records, a first group of patients that received a drug; extracting one or more medical events that the first group experienced; identifying a second group of patients similar to the first group who have received one or more concomitant comparator drugs that address the same set of conditions that prevail in both the first group and second group; extracting one or more medical events that the second group of patients have experienced; and comparing the medical events of the first group to the medical events of the second group to determine statistically significant differences in occurrences between the groups.

Abstract: A system for generating a gestational disorder nourishment program comprising a computing device, the computing device configured to obtain a maternal marker, calculate a gestational phase as a function of the maternal marker, wherein calculating the gestational phase further comprises, identifying a gestational goal, and calculating the gestational phase as a function of the maternal marker and the gestational goal as a function of a gestational machine-learning model, determine an edible as a function of the gestational phase, and generate a nourishment program as a function of the edible.

Abstract: A mechanism is provided in a data processing system comprising least one processor and at least one memory, the at least one memory comprising instructions executed by the at least one processor to cause the at least one processor to implement a clinical decision support system. The mechanism receives a plurality of patient electronic medical records (EMRs) for a patient from a plurality of different sources. For a portion of a patient EMR record of the plurality of patient EMRs, the mechanism detects entities and analyzes a document structure of the portion of the patient EMR to identify a hierarchical structure of the portion of the patient EMR. The mechanism generates a container representation of the portion of the patient EMR based on the hierarchical structure. The mechanism placing each of the one or more sentences within the container representation based on relative position within the hierarchical structure.

Abstract: Systems, methods and computer-readable media are provided for facilitating patient health care through automatic discovery, establishment, and statistical validation of diagnostic-signals in repositories of EMR information, identifying phenotypic diagnostic signals regarding markers or combinations or sequences of patient attributes. Some methods include identifying a first group of patients that have one or more markers and extracting one or more diagnostic statuses that pertain to the whole genome sequencing (WGS) or whole exome sequencing (WES). Statistically significant differences involving frequent itemsets are identified and may be used to evaluate membership of an individual in a class indicative of potential diagnosis via WGS or WES.

Abstract: Systems and methods for reducing acute incident risks for dementia patients are provided. Benefits of the systems and methods include reducing healthcare costs, improving patient and caregiver outcomes and reducing caregiver burden. A server system analyzes data related to a dementia patient and the corresponding caregivers (e.g., family member, paid caregiver, physician) and calculates an acute incident risk. Based on the acute incident risk, the server system determines patient therapies to reduce the acute incident risk and also identifies caregiver education to improve the caregiver belief state, which reduces the acute incident risk. The system periodically re-calculates the acute incident risk and identifies patient therapies and caregiver education and motivation to further reduce or maintain the acute incident risk.

Abstract: Provided herein are methods and systems for making patient-specific therapy recommendations of an anti-inflammatory therapy for patients with known or suspected cardiovascular disease, such as atherosclerosis.

Abstract: A method includes obtaining prescribing drug information and published guidelines for each of a plurality of ADMs available for managing glucose levels, and receiving patient information associated with a patient. The method also includes ordering total demerit values from lowest to highest, selecting a predetermined number of recommended ADMs associated with the lowest total demerit values, and determining a recommended dosage for each recommended ADM. The method also includes transmitting a therapy regimen to a patient device associated with the patient. The therapy regimen includes the recommended ADMs and the recommended dosage for each recommended ADM.

Abstract: A system for calculating an edible score in a display interface, including a computing device configured to initiate, a display interface; retrieve, a performance profile relating to a user; determine, an edible of interest; receive, nourishment information relating to the edible of interest; generate, a score machine-learning process to output an edible score; and display, the edible score within the display interface.

Abstract: A computer-implemented therapy management system is operated to collect patient data associated with medical device users. Treatment of the users is managed by healthcare professionals (HCPs), which include a customer HCP and a plurality of non-customer HCPs. The system receives a first set of attributes for a first individual patient or a first group of patients under care of the customer HCP, and a second set of attributes for a second individual patient or a second group of patients. The system identifies a first set of patient records associated with the customer HCP that satisfy the received first attributes, and a second set of patient records that satisfy the received second attributes, and compares patient outcomes from the first set of records against patient outcomes from the second set of records. A comparative therapy report is generated and communicated to a client device associated with the customer HCP.

Abstract: In some examples, a processor of a system evaluates a therapy program based on a score determined based on a volume of tissue expected to be activated (“VTA”) by therapy delivery according to the therapy program. The score may be determined using an efficacy map comprising a plurality of voxels that are each assigned a value. In some examples, the efficacy map is selected from a plurality of stored efficacy maps based on a patient condition, one or more patient symptoms, or both the patient condition and one or more patient symptoms. In addition, in some examples, voxels of the efficacy map are assigned respective values that are associated with a clinical rating scale.

Abstract: A neural network is trained with patient historical data including features of patient pathways and labels characterizing a type of the patient pathways. During a runtime phase, the trained neural network matches a current patient profile with the patient historical data to extract selected portions of clinical practice guidelines (CPGs) identified according to one or more generated CPG models, the patient pathway models, and the current patient profile.