RESOLVING AMBIGUOUS SEARCH QUERIES
    41.
    发明申请

    公开(公告)号:US20230044159A1

    公开(公告)日:2023-02-09

    申请号:US17970785

    申请日:2022-10-21

    摘要: Computerized systems and methods facilitate searches by identifying instances in which search input is an ambiguous query and resolving the ambiguous query. The search system identifies ambiguous queries by querying a common data store prior to querying a patient database. More particularly, when the search system receives search input entered into a search tool, the search system queries the common name data store before querying the patient database to determine if the search input matches a common name and is an ambiguous query. If so, the search system may provide a notification to the user to indicate the search input is an ambiguous query with a common name and prompt the user to enter additional search criteria. In some instances, the search system may prevent a search from being performed on the patient database if the search input matches a common name until additional search criteria is entered.

    EXPRESSION OF CLINICAL LOGIC WITH POSITIVE AND NEGATIVE EXPLAINABILITY

    公开(公告)号:US20230024631A1

    公开(公告)日:2023-01-26

    申请号:US17945873

    申请日:2022-09-15

    IPC分类号: G16H10/60 G16H50/20 G06Q40/08

    摘要: Methods, systems, and computer-storage media are provided for facilitating the management of population health. A parallel processing architecture receives patient population health data from healthcare facilities along with any updated data. A high-level clinical logic is executed against the data to identify, among other things, patients in the population who qualify for health intervention programs. Using this information, healthcare facilities can implement management programs to help care for these patients

    Rule-based low-latency delivery of healthcare data

    公开(公告)号:US11515016B2

    公开(公告)日:2022-11-29

    申请号:US16397804

    申请日:2019-04-29

    IPC分类号: G16H10/60

    摘要: Methods, systems, and computer-readable media are provided for delivering healthcare records with low latency. Healthcare data is collected from various disparate healthcare data sources. The data is filtered in accordance with routing rules to identify healthcare data to deliver to a processing node. The routing rules specify that healthcare data from a particular originating source of a particular data type is to be delivered to a particular processing node. The healthcare data is converted to a local format for use by a computing solution. This system of delivering healthcare data with low latency ensures that the data is delivered to the correct location in the correct format, even if the routing rules change.

    Automated security assessment systems

    公开(公告)号:US11509678B2

    公开(公告)日:2022-11-22

    申请号:US16917234

    申请日:2020-06-30

    IPC分类号: G06F15/173 H04L9/40 G06Q30/00

    摘要: The federal government requires organizations it partners with to comply with a higher level of security requirements and issues guideline detailing vulnerabilities within computer systems, assessments to be conducted, and security requirements. Previously, the security assessments required to be in compliance with the government's security requirements were mostly conducted manually, creating a labor and time intensive process. The present disclosure provides computerized systems and methods that intelligently and dynamically conduct automatic security assessments to determine security compliance for one or more applications. These systems and methods significantly improve the security assessment process and result in significant savings of time, labor, and money. The system receives the security requirements, identifies one or more applications to undergo a security assessment, generates a script comprising commands for conducting an automatic assessment of the one or more applications, conducts the security assessments on the one or more applications, determines whether the one or more application are in compliance with the security requirements and generates a report comprising the security assessment findings.

    Aggregation, partitioning, and management of healthcare data for efficient storage and processing

    公开(公告)号:US11508467B2

    公开(公告)日:2022-11-22

    申请号:US16443550

    申请日:2019-06-17

    IPC分类号: G16H10/60

    摘要: Methods, systems, and computer-readable media are provided for aggregating, partitioning, and storing healthcare data. Healthcare data is collected from various disparate healthcare data sources. The data is aggregated into batches of the same type of data. From here, the data is partitioned according to the data's originating healthcare data source. The aggregated and partitioned healthcare data is then stored in a long term storage data store. This system of storing healthcare data allows for efficient retrieval and processing by computing solutions that need access to batches of healthcare data. The system also reduces costs associated with storing data as duplicate storage is eliminated.

    Dynamically determining risk of clinical condition

    公开(公告)号:US11495354B2

    公开(公告)日:2022-11-08

    申请号:US16601311

    申请日:2019-10-14

    IPC分类号: G16H50/20 G16H50/30 G16H10/60

    摘要: Systems, methods and computer-readable media are provided for facilitating clinical decision support and managing patient population health by health-related entities including caregivers, health care administrators, insurance providers, and patients. Embodiments of the invention provide decision support services including providing timely contextual patient information including condition risks, risk factors and relevant clinical information that are dynamically updatable; imputing missing patient information; dynamically generating assessments for obtaining additional patient information based on context; data-mining and information discovery services including discovering new knowledge; identifying or evaluating treatments or sequences of patient care actions and behaviors, and providing recommendations based on this; intelligent, adaptive decision support services including identifying critical junctures in patient care processes, such as points in time that warrant close attention by caregivers; near-real time querying across diverse health records data sources, which may use diverse clinical nomenclatures and ontologies; improved natural language processing services; and other decision support services.

    Maintaining stability of health services entities treating influenza

    公开(公告)号:US11468996B1

    公开(公告)日:2022-10-11

    申请号:US16866269

    申请日:2020-05-04

    发明人: Douglas S. McNair

    IPC分类号: G16H50/30 G16H50/50 G16H50/80

    摘要: Systems, methods and computer-readable media are provided for determining and mitigating the aggregate loss risk associated with hospitalization for epidemic or pandemic influenza for health insurers, reinsurers, provider organizations, or public policy-makers. An accurate prediction of this risk may be provided, which may be used to determine parameters for reinsurance underwriting or for issuance and trading of catastrophe bonds (“cat bonds”) or other insurance-linked securities (ILS) and derivatives to lay off substantial amounts of such risk to capital markets investors. In particular, one embodiment uses a novel log-expit transformation of the raw data and non-parametric gradient-boosting machine-learning modeling in order to determine a high-claim right-tail risk. Some embodiments further comprise securitizing epidemic or pandemic influenza acute care health services catastrophe risk.

    Pneumonia readmission prevention
    50.
    发明授权

    公开(公告)号:US11468994B2

    公开(公告)日:2022-10-11

    申请号:US16457082

    申请日:2019-06-28

    摘要: A decision support tool is provided for discharging a patient by predicting the probability of a patient's readmission with pneumonia based on information available prior to discharge. The information used to make the prediction may include labs, vitals, diagnoses, and medications from prior encounters and from the current encounter. At least some of this information may be used to compute one or more severity metrics for the patient, such as a cancer score, an epilepsy or seizure score, a pneumococcal pneumonia score, and an instability score, to be input into one or more prediction models. An ensemble of machine learning models may be applied to the patient information to generate a prediction of that patient being readmitted with pneumonia within a future time interval. Based on the prediction, one or more intervening actions may be initiated to reduce the probability of readmission.