BE IMMUNE: Behavioral Economics to Improve and Motivate vaccination Using Nudges through the EHR
Project Number5R33AG068945-05
Former Number4R61AG068945-03
Contact PI/Project LeaderMEHTA, SHIVAN JATIN Other PIs
Awardee OrganizationUNIVERSITY OF PENNSYLVANIA
Description
Abstract Text
PROJECT SUMMARY/ABSTRACT
Vaccine-preventable diseases such as influenza, pneumococcal disease, and shingles lead to significant rates of illness,
hospitalization, and death among older adults. In the United States, vaccination rates have been mostly unchanged for a
decade with lower rates among racial and ethnic minority groups. New and scalable approaches are needed to address this
important public health issue.
Nudges are changes to the way choices are offered or information is framed that can have outsized effects on behavior.
For example, default options are the path of least resistance and the action that takes place if no alternatives are selected.
Active choice is a method that prompts a decision-making now, rather than waiting for stakeholders to recognize the need
to make the decision on their own. Our groups at the University of Pennsylvania (Penn Medicine) and the University of
Washington (UW Medicine) have formed behavioral design teams embedded within the operations of our health systems
and have demonstrated how these types of nudges can improve health care value and patient outcomes. Since electronic
health records (EHRs) have been adopted by more than 90% of clinicians in the US, this scalable technology platform is
an optimal environment to implement and deploy these types of nudges.
In this study, we propose to design, test, and implemented personalized nudges to clinicians and patients to target barriers
among high-risk subgroups to improve vaccination rates. We will pilot this at two health systems and then implement a
pragmatic trial at those health systems and sites in the VA Health System. In the R61 phase, we will focus on the
following aims at Penn Medicine and UW Medicine. Aim 1: To use EHR data and analytical methods to identify high-risk
groups of older adults with suboptimal vaccination rates for influenza, pneumococcal disease, and herpes zoster. Aim 2:
To assess the feasibility of implementing different types of personalized nudges to clinicians and patients to target the
identified groups to improve vaccination rates among older adults. Aim 3: To pilot test ways to personalize promising
nudges to clinicians and patients for improving vaccination among older adults.
In the R33 phase, we will focus on the following aims at Penn Medicine, UW Medicine, and the VA Health System. Aim
1: To conduct a 12-month, multisite, cluster randomized, pragmatic trial to evaluate the effectiveness of personalized
nudges to clinicians and patients relative to control to improve vaccination rates among older adults. Aim 2: To evaluate
the effectiveness of the intervention on reducing disparities in vaccination rates related to race/ethnicity and
socioeconomic factors. Aim 3: To evaluate heterogeneity in treatment effect across clinician, patient, and practice
characteristics to further tailor approaches in future intervention design.
Public Health Relevance Statement
PROJECT NARRATIVE
Many older adults are at risk of illness, hospitalization, and death from vaccine-preventable diseases. Moreover, there are
significant racial and ethnic disparities in care with even lower vaccination rates among African Americans, Hispanics,
and Asians. In this study, we will use analytical methods to identify high-risk subgroups, test personalized nudges to
address barriers among these groups, and then implement a pragmatic, multisite trial to evaluate the effectiveness of
personalized nudges to clinicians and patients to improve vaccination rates among older adults and reduce disparities in
care.
NIH Spending Category
No NIH Spending Category available.
Project Terms
AddressAdoptedAfrican American populationAsian populationBehaviorBehavioralCategoriesCessation of lifeCharacteristicsClinicalCluster randomized trialDataDecision MakingDiseaseEffectiveness of InterventionsElectronic Health RecordEnvironmentEnvironmental Risk FactorEthnic OriginFoundationsFutureHealth systemHealthcareHerpes zoster diseaseHeterogeneityHispanic PopulationsHospitalizationImmuneInfluenzaInfluenza vaccinationInterventionLeadMachine LearningMedicalMedical centerMedicineMethodsModelingPatient-Focused OutcomesPatientsPatternPennsylvaniaPhasePneumococcal InfectionsPredictive FactorPreventive Health ServicesPreventive carePrimary Care PhysicianPublic HealthPublic Health InformaticsRaceRandomizedResistanceRiskScreening for cancerSiteSocioeconomic FactorsSubgroupTestingUnited StatesUnited States Department of Veterans AffairsUniversitiesVaccinationVaccinesVendorVeterans Health AdministrationVisitWashingtonWorkWorkloadanalytical methodbehavioral economicsdesigndisparity reductioneffectiveness evaluationethnic disparityethnic minority populationhealth care disparityhealth service usehigh riskhigh risk populationimprovedmulti-site trialmultidisciplinaryolder adultoperationpeerpersonalized approachpilot testpragmatic trialprescription opioidprimary care clinicianprimary care practiceracial disparityracial minority populationresponsestatisticstechnology platformtherapy designtreatment effectunvaccinated
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