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dc.contributor.authorRuetsch, Charles
dc.contributor.authorVelligan, Dawn
dc.contributor.authorRobinson, Delbert
dc.contributor.authorJaeger, Chris
dc.contributor.authorCarpenter, William
dc.contributor.authorDavis, Tigwa
dc.contributor.authorLiberman, Joshua N
dc.contributor.authorClerie, Jennifer
dc.contributor.authorWaters, Heidi
dc.contributor.authorForma, Felicia
dc.date.accessioned2021-06-28T14:46:53Z
dc.date.available2021-06-28T14:46:53Z
dc.date.issued2021-05-10en_US
dc.identifier.urihttp://hdl.handle.net/10713/16097
dc.description.abstractBACKGROUND: Psychiatric prescribers typically assess adherence by patient or caregiver self-report. A new digital medicine (DM) technology provides objective data on adherence by using an ingestible event monitoring (IEM) sensor embedded within oral medication to track ingestion. Despite likely clinical benefit, adoption by prescribers will in part depend on attitudes toward and experience with digital health technology, learning style preference (LSP), and how the technology s utility and value are described. OBJECTIVE: is to identify attitudes, experiences, and proclivities toward DM platforms that may affect adoption of the IEM platform and provide direction on tailoring educational materials to maximize adoption. Methods A survey of prescribers treating seriously mentally ill patients was conducted to assess drivers/barriers to IEM adoption. Factor analysis was performed on 13 items representing prior experience with and attitudes toward DM. Factor scores were correlated with prescriber characteristics including attitude and experience with digital technologies, LSP, and level of focus on healthcare cost. RESULTS: A total of 127 prescribers (56% female, 76% physicians, mean age 48.1yrs.) completed the survey. Over 90% agreed medication adherence is important, visits allow enough time to monitor adherence (84.1%), and tailoring treatment to level of adherence would be beneficial (92.9%). The majority (65.9%) preferred relying upon outcomes data as their learning style while 15.9% preferred opinion leader recommendations and 18.3% information about how the technology would affect practice efficiency. Factor analysis revealed four dimensions: Level of comfort with EHR; Concern over current ability to monitor medication adherence; Attitudes about value of DM applications; and Benefits vs cost of DM for payers. Women scored higher on attitudes about the value of digital applications (p<0.01). Providers who perceive non-adherence as costly, and those who believe DM could benefit providers and patients scored higher on the value of DM (p<.05). Those whose LSP focuses on improving efficiency and prescribers with a higher proportion of Medicaid/ uninsured patients displayed concern about their ability to monitor adherence (p<0.05). Willingness to be a Beta Test site for DM applications was positively correlated with concern about their ability to monitor adherence and attitudes about the value of DM (p <0.01). CONCLUSIONS: Prescriber characteristics including LSP, focus on healthcare costs, and attitudes toward DM may be related to adoption of the IEM platform. Those with more Medicaid/ uninsured patients were more concerned about ability to monitor adherence while those focused-on cost and benefit to providers and patients viewed DM as part of a solution for managing outcomes and cost. Overall, LSP, patient panel size by payer type, and focus on healthcare cost containment should be considered when developing IEM provider training materials. FUNDING: Otsuka Pharmaceutical Development & Commercialization, Inc.en_US
dc.description.urihttps://doi.org/10.1017/S109285292000228Xen_US
dc.language.isoenen_US
dc.publisherCambridge University Pressen_US
dc.relation.ispartofCNS Spectrumsen_US
dc.subjectdigital medicine platformsen_US
dc.subject.meshAttitude of Health Personnelen_US
dc.subject.meshDigital Technologyen_US
dc.subject.meshMedication Adherenceen_US
dc.subject.meshPsychotropic Drugsen_US
dc.titlePsychiatric Prescriber Attitudes, Experiences, and Proclivities Toward Digital Medicine and How They Influence Adoption of Digital Medicine Platformsen_US
dc.typeArticleen_US
dc.identifier.doi10.1017/S109285292000228X
dc.identifier.pmid34127104
dc.source.volume26
dc.source.issue2
dc.source.beginpage144
dc.source.endpage145
dc.source.countryUnited States


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