Method, system and program for improved health care
Inventors
Assignees
Publication Number
US-10592501-B2
Publication Date
2020-03-17
Expiration Date
2032-03-08
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Abstract
A platform accessible by a user from a web browser/HMO's electronic medical record (EMR) for providing the user with information regarding a patient's drug regimen as well as generating alerts concerning potential adverse effects to a patient from taking a cluster including a plurality of pharmaceutical preparations and various food supplements/herbals may be in data communication with and configured to obtain information from at least two databases and at least one tool for processing the cluster of pharmaceutical preparations in accordance with the information to generate the alerts to the user.
Core Innovation
The invention provides a platform accessible via a web browser or an electronic medical record (EMR) system, designed to assist users, typically physicians, by supplying comprehensive information regarding a patient's drug regimen. The platform generates alerts concerning potential adverse effects arising from the patient's use of a combination, termed a drug cluster, which includes multiple pharmaceutical preparations and possibly various food supplements or herbals. The platform integrates data communication with at least two databases and employs tools to analyze the drug cluster in accordance with the retrieved information, thereby generating alerts for the user.
The problem addressed arises from the complexity of poly-pharmacy, where aging patients or those with multiple chronic conditions require treatment involving numerous drugs. This often leads to unwarranted drug-drug interactions, adverse side effects, toxicity, and lack of efficacy. Existing databases and programs provide some support for prescribing, but physicians face time constraints in accessing and synthesizing relevant information rapidly. There is a need for more effective treatments, cost savings, and faster prescription of appropriate drug regimens while minimizing risk.
The platform, referred to as the DDI+, overcomes these challenges by providing a system and method that amalgamates clinical, genetic, and metabolic data from various databases, including commercial ones like GENELEX™ and FIRST DATABANK™. The system analyzes drug-drug and gene-drug interactions including effects on serum drug levels and shared side effects, predicts healthcare burdens such as hospital admissions and diagnostic costs, and suggests alternative drugs. It features user-configurable rules and alerts, operates in the background to avoid interfering with clinical workflows, and presents results in a clear and intuitive graphical user interface for efficient decision making.
Claims Coverage
The patent includes several independent claims covering both methods and systems for generating patient-specific alerts on drug-related adverse reactions.
Method for generating patient-specific drug-related adverse reaction alerts
Receiving data about current and candidate drug prescriptions and patient-specific parameters, determining potential drug-related adverse reaction alerts caused by drug-drug, drug-to-patient, and drug-food interactions, applying a decision algorithm to select alerts relevant to the patient's elevated risk status, and outputting these alerts to a graphical user interface with real-time updating based on parameter changes.
System for determining and displaying patient-specific drug-related adverse reaction alerts
A system with a processor and computer memory configured to receive current drug intake data, patient parameters, and candidate drug data; determine drug-related adverse reaction alerts with respect to drug interactions and patient-specific risk; apply decision logic to identify relevant alerts; and output these alerts to a graphical user interface with dynamic updates upon changes to patient parameters.
Computer-readable medium encoded with instructions for alert determination and display
Non-transitory storage medium storing instructions to implement the method of receiving drug and patient data, calculating drug-related adverse reaction alerts based on interactions and patient risk, dynamically updating alerts based on changes, and outputting the alerts to a user interface.
The claims cover a comprehensive method, system, and storage medium that integrate patient-specific parameters with current and candidate drug information to identify and display relevant drug-related adverse reaction alerts by applying a decision algorithm that considers drug interactions and patient elevated risk, thus enabling personalized alerting in clinical decision making.
Stated Advantages
Improves poly-pharmaceutical treatment by providing concise, patient-specific alerts that facilitate quicker, more effective prescription decisions.
Reduces healthcare costs by predicting not only drug interactions but also the associated healthcare burden including hospitalizations and diagnostic procedures.
Supports physician workflow by integrating with EMR systems and operating in the background with user-configurable rules, minimizing disruption and alert fatigue.
Offers alternative drug suggestions that are pre-screened to minimize adverse interactions and alerts, enhancing safe prescribing options.
Incorporates patient genetic profiles and other personal factors for personalized drug interaction analysis, going beyond one-size-fits-all approaches.
Documented Applications
Use in healthcare provider settings such as HMOs to support physicians in prescribing drug regimens safely and efficiently.
Integration with electronic medical records (EMR) to provide real-time alerts and drug regimen optimization during clinical consultations.
Application for reducing adverse drug reactions and healthcare expenditures by predicting and managing complex drug-drug and gene-drug interactions in poly-pharmacy.
Providing decision support through accessible web-based platforms usable on computers, tablets, and mobile devices by clinicians.
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