Tailored Drug Titration through Artificial Intelligence
通过人工智能定制药物滴定
基本信息
- 批准号:9341533
- 负责人:
- 金额:$ 84.9万
- 依托单位:
- 依托单位国家:美国
- 项目类别:
- 财政年份:2017
- 资助国家:美国
- 起止时间:2017-06-01 至 2019-03-31
- 项目状态:已结题
- 来源:
- 关键词:Admission activityAdoptionAdverse effectsAffectAgeAmericanArtificial IntelligenceBlood PressureBusinessesCaringClinicalClinical TrialsComorbidityComputerized Medical RecordCustomDataDiseaseEffectivenessEmergency SituationEmergency department visitEnsureEthnic OriginEventFrequenciesGenderGenerationsGoalsHealthHealth Insurance Portability and Accountability ActHealthcareHealthcare SystemsHeart failureHospital CostsHospitalizationHypersensitivityHypertensionIncidenceIntelligenceIntervention StudiesLaboratoriesLife StyleLogicMeasuresMedicalMedical centerModelingMyocardial InfarctionOffice VisitsPatient CarePatientsPharmaceutical PreparationsPhysiciansPositioning AttributePreventive careProtocols documentationQuality of CareQuality of lifeRandomizedRandomized Clinical TrialsRiskRisk stratificationSan FranciscoScheduleSecureSiteStrokeSurveysSymptomsSystemTechnologyTimeTitrationsUpdateVisitarmbaseblood pressure reductionblood pressure regulationclinical efficacycloud basedcommercial applicationcomputerized data processingcostdesignhealth care deliveryhealth care servicehealth datahypertension treatmentimprovedinnovative technologiesmedication compliancenovelpatient stratificationprimary outcomeresponsescale upsecondary outcomesuccesstoolweb services
项目摘要
Optima Integrated Health Inc. (Optima) proposes to demonstrate the clinical efficacy of the decision support
technology for medication treatment optimization it validated in a pilot clinical trial, optima4BP. optima4BP is
designed as a physician decision/action support aid in timely and safely optimizing medication treatment
independent of in-office visits, for patients with uncontrolled hypertension (HTN). optima4BP is designed to
reduce preventable hospitalizations and the associated incidence of stroke, heart failure (HF) or myocardial
infarction (MI) events resulting from high blood pressure (BP) above goal. Uncontrolled HTN affects 34 million
Americans. The cost of HTN-associated hospitalizations is $113 billion, or 15% of all hospital costs, with >135
million Emergency Dptm. (ED) visits. optima4BP will improve the quality of life for uncontrolled HTN patients,
and reduce this massive burden on the US healthcare system. Our long term objective is to help drive the
transformation from the reactive pay-for-service healthcare paradigm to one that emphasizes preventative care
through personalized health surveillance, assessment, and action via timely and safely optimized medication
treatment. Our specific aims include: Aim (1) demonstrating the efficacy of optima4BP in a randomized clinical
trial (n=300 patients) deployed at UC San Francisco Medical Center. Patients will be randomized to an
enhanced care (EC) arm or an optima4BP arm (O4BP). All patients will use Omron10 BP arm cuff to remotely
measure their BP. For the patients in the EC arm, physicians will be provided with a monthly summary of the
Omron10 data. For patients in the O4BP arm, aside from the BP monthly summary, physicians will receive (a)
a risk stratified patient roster, (b) next step actions in medication optimization for each patient, and (c) access
to optima4BP's secure web-service medication treatment modeling to investigate how changing current patient
data could affect medication choice (e.g., change in medication choice if BP goal is lowered). We will then
examine the BP value reduction between arms (success:>7 mmHg decreased systolic; >4 mmHg decreased
diastolic of O4BP vs. EC), along with secondary outcomes between O4BP and EC: medication treatment
action frequency; ED admissions due to HTN-related symptoms and associated hospitalizations for stroke, HF
or MI; and overall cost of HTN management. Aim (2) optima4BP data processing steps will be optimized to
scale-up its capability to >1000/day patient cases processing power. 3 specific optimization processing tools
will be developed: Optima Extract, Transform, and Load (OETL); Optima Survey Generator (OSG), and Optima
Message Builder (OMB). OETL will provide streamlined scheduling logic to extracting data from Epic® EMR
(electronic medical record), optimize data mapping scripts within optima4BP, and optimize data uploading
protocols. OSG will optimize the current generation protocol for patient surveys, patient response, and
assignment of patient responses to specific processing modules. OMB will ensure streamlined scheduling of
risk stratification updates and scheduled delivery to physician In-Basket messaging system within Epic® EHR.
Optima Integrated Health Inc. (Optima)提出论证决策支持的临床效果
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Gabriela Voskerician其他文献
Gabriela Voskerician的其他文献
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{{ truncateString('Gabriela Voskerician', 18)}}的其他基金
PERSEVERE-PEF: optimizing medical therapy saves lives in heart failure with preserved ejection fraction
PERSEVERE-PEF:优化药物治疗可挽救射血分数保留的心力衰竭患者的生命
- 批准号:
10641684 - 财政年份:2022
- 资助金额:
$ 84.9万 - 项目类别:
PERSEVERE-PEF: optimizing medical therapy saves lives in heart failure with preserved ejection fraction
PERSEVERE-PEF:优化药物治疗可挽救射血分数保留的心力衰竭患者的生命
- 批准号:
10381898 - 财政年份:2022
- 资助金额:
$ 84.9万 - 项目类别:
ARTERY Outcomes: tAilored dRug Titration through artificial intElligence: an inteRventional studY
动脉结果:通过人工智能定制药物滴定:一项干预性研究
- 批准号:
10001603 - 财政年份:2019
- 资助金额:
$ 84.9万 - 项目类别:
optima4heart: pharmacological intervention and transition of care in cardiovascular disease management
optima4heart:心血管疾病管理中的药物干预和护理转变
- 批准号:
9770702 - 财政年份:2019
- 资助金额:
$ 84.9万 - 项目类别:
PROTECT: optima4BP 2.0: prediction of Optimal Treatment and Route to achieve and maintain BP Target
保护:optima4BP 2.0:预测最佳治疗和路线以实现和维持血压目标
- 批准号:
10159301 - 财政年份:2018
- 资助金额:
$ 84.9万 - 项目类别:
PROTECT: optima4BP 2.0: prediction of Optimal Treatment and Route to achieve and maintain BP Target
保护:optima4BP 2.0:预测最佳治疗和路线以实现和维持血压目标
- 批准号:
9901106 - 财政年份:2018
- 资助金额:
$ 84.9万 - 项目类别:
Personal Mobile Diabetes Management System(PMDMS): IN-TRACK
个人移动糖尿病管理系统(PMDMS):IN-TRACK
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8311248 - 财政年份:2012
- 资助金额:
$ 84.9万 - 项目类别:
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