Using a predicting Risky Opioid-Benzodiazepine Trajectory e-Care Tool (PROTeCT) to identify high-risk regions
Using a predicting Risky Opioid-Benzodiazepine Trajectory e-Care Tool (PROTeCT) to identify high-risk regions
批准号:
10170668
负责人:
Wei-Hsuan Lo-Ciganic
金额:
$7.63万
依托单位:
依托单位国家:
美国
项目类别:
财政年份:
2019
资助国家:
美国
项目状态:
已结题
起止时间:
2019-05-01 至 2021-01-31
关键词:
Administrative SupplementAdultAnxietyArizonaBenzodiazepinesCaringClinicalDataDoseElderlyEventFeedbackFloridaFocus GroupsFractureFundingFutureGuidelinesHealthHealthcareHealthcare SystemsHigh PrevalenceInformation SystemsInfrastructureInterventionIntuitionLifeLiteratureMeasuresMedicaidMedicareMedicare claimMedicare/MedicaidMental HealthModelingNeeds AssessmentNurse PractitionersOpioidOutcomeOverdosePainParentsPatient riskPatientsPatternPharmaceutical PreparationsPhysician AssistantsPhysiciansPoliciesPredictive ValuePrescription opioid overdosePrevalenceProbabilityProcessPublic Health InformaticsResearchResearch PersonnelRiskRisk EstimateRisk FactorsSamplingSleeplessnessSoftware EngineeringStructureSubgroupSubstance Use DisorderTimeUnited States Centers for Medicare and Medicaid ServicesUpdateValidationWorkadvanced analyticsadverse outcomeagedbasecare providerschronic painful conditionclinical careclinical decision-makingclinical practicecostdesigneffective interventionexperiencefallshigh riskimprovedineffective therapiesinnovationoperationopioid mortalityopioid useoverdose riskpatient subsetsprescription opioidpreventprogramsprospectiveprototyperisk mitigationstructured datatoolusabilityuser centered designyoung adult
中文摘要
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英文摘要
Prescription opioid overdose deaths have increased markedly in the past two decades, with a third of these
fatalities involving concurrent benzodiazepine (BZD) use. Despite clinical guidelines and FDA black-box
warnings cautioning against concurrent opioid (OPI) and BZD use (hereafter OPI-BZD use), the number of
patients using OPI-BZD increased by 41% between 2002 and 2014. OPI-BZD use increases the risk of overdose
and other adverse outcomes, especially among older adults. However, little is known about the thresholds of
duration and dose or patterns of OPI-BZD use profiles most associated with the risk of overdose and other
adverse outcomes among older adults. Prior studies have defined OPI-BZD use with arbitrary thresholds (e.g.,
≥1 day overlapped supply) and focused only on duration or dose alone rather than combinations of duration and
dose of concurrent use. Applying arbitrary and broad thresholds without evidence and validation to all patients
imposes challenges in tailoring clinical care, and leads to ineffective therapies and interventions involving OPI-
BZD use. Alternatively, advanced group-based trajectory models (GBTMs) can be used to better characterize
OPI-BZD use in clinical practice. GBTMs have the ability to account for dynamic medication use, identify
subgroups with similar changes over time, and simultaneously examine dose and duration thresholds or other
patterns most relevant to outcomes to better aid clinical decision-making.
The parent R21 aims at developing an innovative, real-time “Predicting Risky Opioid-Benzodiazepine Trajectory
e-Care Tool (PROTeCT)” for efficiently identifying and predicting subgroups of older adults with distinct and
potentially unsafe patterns of OPI-BZD use. Because Medicare and Medicaid enrollees are experiencing an
increased number of chronic pain conditions, mental health/substance use disorders, and prescription OPI use,
Medicare and Medicaid are ideal settings for developing the PROTeCT tool. Using national Medicare claims and
Arizona (AZ) and Florida (FL) Medicaid data from 2013-2016, Aim 1 focuses on identifying distinct trajectories
of OPI-BZD use. We will also identify predictors associated with specific trajectories or patterns. In Aim 2, we
will identify the distinct trajectories or patterns of OPI-BZD use that are the most closely associated with two
separate outcomes (i.e., overdoses; falls and fractures). Finally, we propose to develop a prototype of a real-
time PROTeCT platform capable of prospectively and iteratively predicting patients with unsafe patterns of OPI-
BZD use by prospectively analyzing more recent data using 2017-2019 AZ and FL Medicaid data. In order to
help Dr. Lo-Ciganic to successfully complete this R21 after her recent critical life event, this supplement requests
funds to mainly support a specialized program coordinator’s effort and include two additional investigators with
health informatics expertise for Aim 3. The infrastructure of our findings and tool may be generalizable to
Medicare, Medicaid programs in other states, or other healthcare data systems with similar data structures.
期刊论文(2)
专著(0)
科研奖励(0)
会议论文
DOI:
10.1111/add.15189
发表时间:
2021-04
期刊:
Addiction (Abingdon, England)
影响因子:
--
作者:
[Zhou L, Bhattacharjee S, Kwoh CK, Tighe PJ, Reisfield GM, Malone DC, Slack M, Wilson DL, Chang CY, Lo-Ciganic WH]
通讯作者:
Lo-Ciganic WH
Developing and Evaluating a Machine-Learning Opioid Prediction & Risk-Stratification E-Platform (DEMONSTRATE)
-
批准号:10442365
-
项目类别:
-
资助金额:$65.46万
-
财政年份:2021
-
负责人:Wei-Hsuan Lo-Ciganic
-
依托单位:
Developing and Evaluating a Machine-Learning Opioid Prediction & Risk-Stratification E-Platform (DEMONSTRATE)
-
批准号:10597698
-
项目类别:
-
资助金额:$63.48万
-
财政年份:2021
-
负责人:Wei-Hsuan Lo-Ciganic
-
依托单位:
Developing a Real-Time Trajectory Tool to Identify Potentially Unsafe Concurrent Opioid and Benzodiazepine Use among Older Adults
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批准号:9923531
-
项目类别:
-
资助金额:$19.39万
-
财政年份:2019
-
负责人:Wei-Hsuan Lo-Ciganic
-
依托单位:
海外基金