Improving Cardiovascular Drug Safety With Automated Bleeding Classification
Improving Cardiovascular Drug Safety With Automated Bleeding Classification
批准号:
9899862
负责人:
Rashmee U. Shah
金额:
$16.31万
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
项目状态:
已结题
起止时间:
2017-04-01 至 2021-11-30
关键词:
AccountingAddressAdultAdverse eventAffectAgeAlgorithmsAnticoagulantsAtrial FibrillationBiomedical ResearchCardiologyCardiovascular AgentsCardiovascular DiseasesClassificationClinicalCodeComparative Effectiveness ResearchCompetenceComplicationComputer AssistedComputerized Medical RecordDataData ScienceDevelopment PlansDevicesDiagnosisEnsureEventFoundationsFutureGoalsHealthcareHemorrhageIncidenceInstitutionInterdisciplinary StudyK-Series Research Career ProgramsKnowledgeLeadLeadershipLearningLettersLinkManualsMeasuresMentorsMentorshipMethodologyMethodsModelingMonitorNatural Language ProcessingOralPatientsPharmaceutical PreparationsPharmacotherapyPopulationPragmatic clinical trialPrevalenceProviderQuality of lifeRaceRecordsReproducibilityResearchResearch MethodologyResearch PersonnelResearch TrainingRiskSafetySeveritiesSiteStandardizationStrokeStroke preventionSystemTechniquesTestingTextTrainingUnited States Centers for Medicare and Medicaid ServicesUtahValidationVital Statusacute coronary syndromeadvanced analyticsaging populationanalytical methodbasebiomedical informaticscareercareer developmentclinically relevantcohortimprovedinterdisciplinary approachmedication compliancemedication safetymortalityneglectnovelnovel therapeuticspatient safetypersonalized medicineportabilitypublic health relevancescreeningsexskillsstroke riskstroke therapytool
中文摘要
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英文摘要
PROJECT SUMMARY
Atrial fibrillation (AF) treatment often includes drug therapy with oral anticoagulants (OAC) to prevent stroke.
Bleeding, however, is a common complication of these drugs, affecting up to one in four patients. The Center
for Medicare and Medicaid Services recently prioritized OAC-related drug safety as a key quality measure.
Currently, however, no method exists to accurately identify bleeding events and severity in large populations.
Prior methods use diagnoses codes, which lack sensitivity and clinical detail, or manual chart review, which
cannot be implemented in large populations. The proposed research aims address this knowledge gap by
applying a natural language processing (NLP)-based approach to identify bleeding events and classify severity
in a real-world AF population. The tools will be validated in patients treated at a different institution, to ensure
reproducibility across provider settings. In addition, we will apply the bleeding classification tool to evaluate the
association between bleeding severity and mortality. Dr. Shah is an emerging young investigator whose career
development plan is focused on acquiring the biomedical informatics skills to needed to accurately identify and
reduce patient harm. Her training plan focuses on learning core competencies in natural language processing,
with the goal of turning the wealth of data in the electronic medical record into useable knowledge. She will
combine mentorship from established experts and targeted coursework to acquire skills in biomedical
informatics, data science, advanced analytic methods, and research leadership. Completion of these research
and training aims will create a platform for future R01 proposals by: (i) enabling safety focused comparative
effectiveness research in AF (ii) setting the stage to identify bleeding complications in other cardiovascular
diseases and (iii) developing a skill set that allows leadership of a multidisciplinary research team. Through this
career development plan, Dr. Shah will build upon her prior training in clinical cardiology and research
methodology and lay a strong foundation for a high impact research career.
期刊论文(17)
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DOI:
10.1001/jamanetworkopen.2020.35782
发表时间:
2021-01-04
期刊:
JAMA network open
影响因子:
13.8
作者:
[Matheny ME, Ricket I, Goodrich CA, Shah RU, Stabler ME, Perkins AM, Dorn C, Denton J, Bray BE, Gouripeddi R, Higgins J, Chapman WW, MacKenzie TA, Brown JR]
通讯作者:
Brown JR
Data and Information in the Sea of Electronic Health Records.
电子健康记录海洋中的数据和信息。
DOI:
10.1161/circoutcomes.118.005247
发表时间:
2018
期刊:
Circulation. Cardiovascular quality and outcomes
影响因子:
--
作者:
[Shah,RashmeeU, Matheny,MichaelE]
通讯作者:
Matheny,MichaelE
Peri-procedural complications in women: an alarming and consistent trend.
女性围手术期并发症:一个令人震惊且一致的趋势。
DOI:
10.1093/eurheartj/ehz193
发表时间:
2019
期刊:
European heart journal
影响因子:
39.3
作者:
[Wang,Libo, Selzman,KimberlyA, Shah,RashmeeU]
通讯作者:
Shah,RashmeeU
Modeling reductions in SARS-CoV-2 transmission and hospital burden achieved by prioritizing testing using a clinical prediction rule.
通过使用临床预测规则优先进行测试,对 SARS-CoV-2 传播和医院负担的减少进行建模。
DOI:
10.1101/2020.07.07.20148510
发表时间:
2020
期刊:
medRxiv : the preprint server for health sciences
影响因子:
--
作者:
[Reimer,JodyR, Ahmed,ShariaM, Brintz,Benjamin, Shah,RashmeeU, Keegan,LindsayT, Ferrari,MatthewJ, Leung,DanielT]
通讯作者:
Leung,DanielT
DOI:
10.1016/j.jbi.2021.103851
发表时间:
2021-08
期刊:
Journal of biomedical informatics
影响因子:
4.5
作者:
[Reeves RM, Christensen L, Brown JR, Conway M, Levis M, Gobbel GT, Shah RU, Goodrich C, Ricket I, Minter F, Bohm A, Bray BE, Matheny ME, Chapman W]
通讯作者:
Chapman W
共 11 条
Healthcare Impact of Consumer-Driven Atrial Fibrillation Detection
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批准号:9980996
-
项目类别:
-
资助金额:$7.63万
-
财政年份:2019
-
负责人:Rashmee U. Shah
-
依托单位:
Healthcare Impact of Consumer-Driven Atrial Fibrillation Detection
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批准号:9809717
-
项目类别:
-
资助金额:$7.63万
-
财政年份:2019
-
负责人:Rashmee U. Shah
-
依托单位:
海外基金