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公开(公告)号：US20210383923A1
公开(公告)日：2021-12-09
申请号：US17283684
申请日：2019-10-09
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Reza SHARIFI SEDEH , Eran SIMHON
Abstract: A care plan tool for defining care plans for patients with constrained care plan resources, including: a patient clustering and risk stratification module configured to cluster a group of patients into patient cohorts and configured to produce a machine learning model to predict the risk of a medical condition for each patient cohort based upon medical data for the patients in the cohort; an optimization module configured to determine an optimized care plan for each patient cohort based upon the machine learning models for each patient cohort and the constrained care plan resources; a matching care plan module configured to receive patient data for new patients and configured to match the new patients to a patient cohort and associated care plan; and a new care plan optimization module configured to receive patient specific constraints for new patients from a care manager and configured to determine a new optimized care plan for each new patient based upon the machine learning models for each patient cohort, the constrained care plan resources, patient data for new patients, and patient specific constraints.
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公开(公告)号：US20230162864A1
公开(公告)日：2023-05-25
申请号：US17422790
申请日：2020-01-14
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Eran SIMHON , Reza SHARIFI SEDEH
Abstract: A method for identifying risk factors that have an impact on health outcomes, including: receiving, by a graphical user interface (GUI), from a user features of similarity, a risk factor, and a key performance indicator (KPI); receiving, by the GUI, from the user values for the features of similarity and risk factor; selecting, by a processor, patient data including features of similarity data, risk factor data, and KPI data; and determining, by the processor, the optimal features of similarity by optimizing the minimum value of an average standard deviation (STD) of the KPI based upon the received user features of similarity, received risk factor, and the received values for the features of similarity and risk factor.
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公开(公告)号：US20220101986A1
公开(公告)日：2022-03-31
申请号：US17298043
申请日：2019-12-11
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Jin LIU , Eran SIMHON , Reza SHARIFI SEDEH
Abstract: A method for scheduling patients for medical appointments, including: predicting the no-show risk and no-show cost for the patients; forecasting the cost of a transportation assistance service for the patients; optimizing the scheduling of patients based upon cost of the transportation assistance service, the no-show risk, and the no-show cost; selecting a population of patients to receive the transportation assistance service; and scheduling the population of patients for their medical appointment and transportation assistance service.
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公开(公告)号：US20230049068A1
公开(公告)日：2023-02-16
申请号：US17879938
申请日：2022-08-03
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Eran SIMHON , Lasith ADHIKARI , Gregory BOVERMAN , David Paul NOREN , Chaitanya KULKARNI , Larry James ESHELMAN , Syamanthaka BALAKRISHNAN , Vikram SHIVANNA
IPC: G16H40/20
Abstract: A method and system for generating real time workload balancing recommendations comprising receiving transition data, medical data, and staffing data; determining a transition probability for each of a plurality of patients; determining a predicted workload to be generated by each of the plurality of patients; simulating the predicted workload to be generated by each of the plurality of patients, the future workload for each of a plurality of units in the hospital; generating staffing recommendations; and displaying the generated staffing recommendations on a user display of the workload balancing system.
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公开(公告)号：US20210073629A1
公开(公告)日：2021-03-11
申请号：US16772425
申请日：2018-12-24
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Xin WANG , Eran SIMHON , Reza SHARIFI SEDEH , Amir ABDOLAHI , Cecilia MEIJER
Abstract: The present disclosure pertains to a system configured to prepare and use prediction models for socioeconomic data and missing value prediction. Some embodiments may: extract, from received population segment data, a training set of socioeconomic parameter values for each population segment; provide, to a prediction model as input, first parameter values of the respective training set for the prediction of additional parameter values of the training set such that the prediction of the additional parameter values is performed without reliance on the additional parameter values; provide, for each of the training sets, the additional parameter values to the prediction model as reference feedback for the prediction model's prediction of the additional parameter values to train the prediction model; and predict, based on a working set of parameter values for a population segment, additional values for the working set using the prediction model subsequent to its training.
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Patent Agency Ranking
公开(公告)号：US20190287659A1
公开(公告)日：2019-09-19
申请号：US16287307
申请日：2019-02-27
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Eran SIMHON , Reza SHARIFI SEDEH
Abstract: The present disclosure pertains to a system for providing model-based patient assignment to care managers. In some embodiments, the system (i) receives a collection of health information related to a plurality of individuals residing in a predetermined region and known to have similar social determinants of health; (ii) extracts and provides one or more care management-related features of the plurality of individuals and one or more care management activities provided to the individuals to a machine learning model to train the machine learning model; (iii) obtains and provides health information of an individual residing in the predetermined region to the machine learning model to predict an amount of care management time for the individual; (iv) assigns, based on the predicted amount of care management time, the individual to a care manager; and (v) effectuates presentation of a list of assigned individuals to the care manager.
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公开(公告)号：US20210265050A1
公开(公告)日：2021-08-26
申请号：US17253387
申请日：2019-06-19
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Eran SIMHON , Reza SHARIFI SEDEH
Abstract: A care plan system, including: a key performance indicator (KPI) model configured to predict the value of a KPI for a specific patient based upon patient data and care plan elements; cost data indicating the cost of the care plan elements; a graphical user interface (GUI) configured to receive first suggested care plan elements, to provide a first predicted value of the KPI and a first care plan cost associated with the first suggested care plan elements using the KPI model, and to present the first predicted KPI value and first care plan cost.
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公开(公告)号：US20210201202A1
公开(公告)日：2021-07-01
申请号：US17125308
申请日：2020-12-17
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Eran SIMHON
IPC: G06N20/00
Abstract: In certain embodiments, graphical representations of factors for risk adjustment of a key performance indicator may be presented, and a user selection of a factor subset may be received. Training information may be provided as input to a machine learning model to predict values of the key performance indicator for the selected factor subset. The training information may indicate values of the factor subset associated with a provider. Reference feedback may then be provided to the machine learning model, the reference feedback comprising historic values of the key performance indicator for the provider based on the values of the factor subset that are associated with the provider. The machine learning model may then update portions of the machine learning model based on the reference feedback. The values of the factor subset may then be provided to the updated machine learning model to obtain predicted values of the key performance indicator.
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公开(公告)号：US20200082918A1
公开(公告)日：2020-03-12
申请号：US16565533
申请日：2019-09-10
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Eran SIMHON , Reza SHARIFI SEDEH
IPC: G16H10/20 , G06Q40/06 , G06F3/0482 , G06N20/00
Abstract: A patient selection tool for selecting patients for a social-behavioral determinants of health (SBDoH) program, including: a graphical user interface (GUI) module configured to present a GUI to a user, receive inputs from the user including a SBDoH factor, and to select patient cohort data based upon the inputs received from the user, a machine-learning model configured to predict a key performance indicator (KPI) for each patient based upon the patient cohort data and the SBDoH factor, a success rate module configured to predict the probability of success of the SBDoH program for each patient in the patient cohort; a return on investment (ROI) module configured to determine the cost savings associated with the SBDoH program for each patient in the patient cohort based upon the cost associated with the KPI, the probability of success of the SBDoH program, and a change in the KPI associated with the SBDoH factor, and a patient selection module configured to select patients for the SBDoH program based upon the determined cost saving associated with the SBDoH program for each patient in the patient cohort.
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10.发明申请公开(公告)号：US20190180851A1
公开(公告)日：2019-06-13
申请号：US16203822
申请日：2018-11-29
Applicant: KONINKLIJKE PHILIPS N.V.
Inventor： Eran SIMHON , Reza SHARIFI SEDEH
Abstract: In one embodiment, a computer system and method is disclosed for providing a social determinates of health model which correlates socio-economic factors with the non-adherence risk of an individual to a proscribed task such as care plan compliance, medication dosing, physical therapy or exercise routine, office visit, or test appointment.
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