公开(公告)号：US20230035564A1

公开(公告)日：2023-02-02

申请号：US17962732

申请日：2022-10-10

Applicant: Humana Inc.

Inventor： Yanting Dong ,  Jing Fan ,  Vinay Chiguluri ,  Vipin Gopal

IPC: G16H10/20 ,  G16H50/20 ,  G16H10/40 ,  G16H50/50 ,  G16H50/30

Abstract: The disclosed computerized system and method facilitates predicting the onset of diabetes or symptom progression in those patients already suffering from the disease. The computerized system and method applies steps to segment the population by predefined member characteristics. Once segmented, the computerized system and method applies a plurality of prediction models to the segmented population data to provide a ranking of members of the population that indicates the likelihood of onset or progression of diabetes for each member.

公开(公告)号：US20160358291A1

公开(公告)日：2016-12-08

申请号：US14152542

申请日：2014-01-10

Applicant: Humana Inc.

Inventor： Sandy Chiu ,  Vipin Gopal

IPC: G06Q50/22 ,  G06Q10/06

CPC classification number: G16H50/30 ,  G16H50/70

Abstract: A computerized back surgery predictive model identifies a risk population for back surgery and assigns a severity level to members of the risk population. High risk members are informed of preference-sensitive surgeries and alternative treatment options. The model focuses on members of the population with back condition related claims and is trained using data for members with primary diagnoses associated with various types of visits, procedures, and treatments for back pain. In an example embodiment, the model is applied to member populations to predict a first back surgery (e.g., spinal fusion, kyphosplasty, vertebroplasty, or decompression surgery) within one year after identified triggers. Predictors are historical risk factors from a broad set of data sources. Members are scored monthly to allow for continuous monitoring of the changing risk of back surgery and to allow timely intervention. The model may be tailored for different populations such as commercial and Medicare populations.

Abstract translation: 计算机化的背景手术预测模型识别背部手术的风险人群，并为风险人群的成员分配严重程度。 高风险成员被告知偏好敏感手术和替代治疗方案。 该模型侧重于具有背部条件相关声明的人群中的成员，并使用与各种类型的访问，手术和背部疼痛治疗相关联的主要诊断的成员的数据进行培训。 在示例性实施例中，将模型应用于成员群体以在确定的触发器后一年内预测第一次背部手术（例如，脊柱融合，脊柱后凸成形术，椎体成形术或减压手术）。 预测因子是来自广泛数据源的历史风险因素。 会员每月获得评分，以便不断监测背部手术风险的变化并及时进行干预。 该模型可能针对不同的人群，如商业和医疗保健人口。

公开(公告)号：US20160357930A1

公开(公告)日：2016-12-08

申请号：US14180717

申请日：2014-02-14

Applicant: Humana Inc.

Inventor： Harpreet Singh ,  Vipin Gopal

IPC: G06F19/00

Abstract: A computerized system and method for automatically estimating the likelihood of having a fall leading to a fracture/dislocation within a specified period is described, and comprises a predictive model for guiding patients to the right course of treatment and encouraging discussions with their doctors for better outcomes. The system and method extracts member's health information from health administrative claims data, including clinical and pharmacy data, and estimates the probability of a fall for that member. Patients with high risk scores are selected for various clinical programs and interventions to manage their health conditions and reduce their likelihood of falling.

Abstract translation: 描述了一种计算机化系统和方法，用于自动估计在特定时期内导致骨折/脱位的可能性的可能性，并且包括用于指导患者正确治疗过程的预测模型，并鼓励与医生讨论以获得更好的结果 。 系统和方法从健康管理索赔数据（包括临床和药学数据）中提取成员的健康信息，并估计该成员的下降概率。 选择具有高风险评分的患者进行各种临床方案和干预措施，以管理其健康状况并降低其下降的可能性。

公开(公告)号：US20160358290A1

公开(公告)日：2016-12-08

申请号：US13863498

申请日：2013-04-16

Applicant: Humana Inc.

Inventor： Sandy Chiu ,  Vipin Gopal

IPC: G06Q50/22 ,  G06F19/00

CPC classification number: G06Q50/22 ,  G06F19/328

Abstract: A computerized health severity score predictive model for assigning a health severity score to a member of a health insurance member population is disclosed. The computerized system and method comprises a predictive model for scoring members. The predictive model is developed based on health insurance claim data. Member claim data may comprise eligibility, demographics, medical claims, pharmacy claims, pharmacy benefit management, laboratory test results, and disease management data. A utilization transition pattern is identified from a comparison of costs observed during a first year and a subsequent year. Members are segmented into groups according to predetermined segmenting rules derived from a segmentation model that applies the utilization transition pattern. The health severity score is thus based on demographic and clinical data as well as utilization transition pattern (or cost transition) data.

Abstract translation: 公开了一种用于将健康严重程度分数分配给健康保险成员人员的计算机健康严重性评分预测模型。 计算机化系统和方法包括评分成员的预测模型。 预测模型是基于健康保险索赔数据开发的。 会员索赔数据可能包括资格，人口统计，医疗索赔，药房索赔，药房福利管理，实验室检测结果和疾病管理数据。 从第一年和随后一年观察到的成本比较可以确定利用过渡模式。 根据从应用利用过渡模式的分割模型导出的预定分段规则，成员被分割成组。 因此，健康严重程度评分基于人口统计学和临床​​数据以及利用过渡模式（或成本转换）数据。

公开(公告)号：US20160357923A1

公开(公告)日：2016-12-08

申请号：US15057091

申请日：2016-02-29

Applicant: Humana Inc.

Inventor： Yanting Dong ,  Vipin Gopal

IPC: G06F19/00 ,  G06N7/00

CPC classification number: G06N7/005 ,  G06N3/02 ,  G06N5/003 ,  G06N20/20 ,  G16H50/20

Abstract: The present invention is a method of predicting the likelihood that chronic kidney disease will result in end stage renal disease requiring dialysis. The method uses various indicators comprising information specific to an individual as well as information representing characteristics of a population including demographic information, health care and prescription insurance claims, and involvement in various programs designed to improve the health of a user. The method applies a predictive algorithm to these indicators in order to derive a risk score indicating an individual's risk of dialysis.

Abstract translation: 本发明是预测慢性肾脏疾病将导致需要透析的终末期肾病的可能性的方法。 该方法使用包括个人信息的各种指标以及表示人口特征的信息，包括人口统计信息，医疗保健和处方保险索赔，以及参与旨在改善用户健康状况的各种程序。 该方法对这些指标应用预测算法，以便得出指示个人透析风险的风险评分。

公开(公告)号：US20230084308A1

公开(公告)日：2023-03-16

申请号：US17951718

申请日：2022-09-23

Applicant: Humana Inc.

Inventor： Harpreet Singh ,  Vipin Gopal

IPC: G16H50/30 ,  G16H50/70

Abstract: Systems and methods for automated interventions to persons identified as being of risk of falling are provided. A subset of members is identified which are associated with at least one of a plurality of falls predictors. At least one falls prediction algorithm is applied to a subset of said medical claims data associated with the subset of members to generate a falls risk score for each of member of the subset. At least one intervention is assigned to each of member of the subset having an assigned risk score above any of several predetermined risk score thresholds which are automatically and electronically initiated based, at least in part, on member data.

公开(公告)号：US20200152334A1

公开(公告)日：2020-05-14

申请号：US16743747

申请日：2020-01-15

Applicant: Humana Inc.

Inventor： Harpreet Singh ,  Vipin Gopal

IPC: G16H50/30 ,  G16H50/70

Abstract: A computerized system and method for automatically estimating the likelihood of having a fall leading to a fracture/dislocation within a specified period is described, and comprises a predictive model for guiding patients to the right course of treatment and encouraging discussions with their doctors for better outcomes. The system and method extracts member's health information from health administrative claims data, including clinical and pharmacy data, and estimates the probability of a fall for that member. Patients with high risk scores are selected for various clinical programs and interventions to manage their health conditions and reduce their likelihood of falling.

公开(公告)号：US10540478B2

公开(公告)日：2020-01-21

申请号：US14180717

申请日：2014-02-14

Applicant: Humana Inc.

Inventor： Harpreet Singh ,  Vipin Gopal

IPC: G16H50/30 ,  G16H50/70 ,  G06F19/00

Abstract: A computerized system and method for automatically estimating the likelihood of having a fall leading to a fracture/dislocation within a specified period is described, and comprises a predictive model for guiding patients to the right course of treatment and encouraging discussions with their doctors for better outcomes. The system and method extracts member's health information from health administrative claims data, including clinical and pharmacy data, and estimates the probability of a fall for that member. Patients with high risk scores are selected for various clinical programs and interventions to manage their health conditions and reduce their likelihood of falling.

公开(公告)号：US20160357934A1

公开(公告)日：2016-12-08

申请号：US14942592

申请日：2015-11-16

Applicant: Humana Inc.

Inventor： Yanting Dong ,  Jing Fan ,  Vinay Chiguluri ,  Vipin Gopal

IPC: G06F19/00

CPC classification number: G16H10/20 ,  G16H10/40 ,  G16H50/20 ,  G16H50/30 ,  G16H50/50

Abstract: The disclosed computerized system and method facilitates predicting the onset of diabetes or symptom progression in those patients already suffering from the disease. The computerized system and method applies steps to segment the population by predefined member characteristics. Once segmented, the computerized system and method applies a plurality of prediction models to the segmented population data to provide a ranking of members of the population that indicates the likelihood of onset or progression of diabetes for each member.

Abstract translation: 所公开的计算机化系统和方法有助于预测已经患有该疾病的患者的糖尿病发作或症状进展。 计算机化的系统和方法应用步骤，通过预定义的成员特征分割群体。 一旦细分，计算机化系统和方法将多个预测模型应用于分割的群体数据，以提供群体成员的排名，其指示每个成员发生或进展糖尿病的可能性。