Demographic, Clinical, and Prescribing Characteristics Associated with Future Opioid Use in an Opioid-Naive Population in an Integrated Health System

Dm, Mosen; Ag, Rosales; Mummadi, Raj; Hu, Weixin; Brooks, Neon

doi:10.7812/tpp/19.236

Cited by 3 publications

(3 citation statements)

References 18 publications

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“…Another example is work done in the Kaiser system, which has brought together clinical, dispensing, and socioeconomic data sources to examine opioid-related outcomes across patients in multiple market segments, though the data are limited to Kaiser membership. 21 Finally, in 2017, Governor Eric Holcomb of Indiana established the Management Performance Hub, an agency acting as the hub for data collection, analysis, and exchange for the Indiana state government. The goal of the agency was to implement data-driven policies within state government by creating a focal point for state-level data and providing technical assistance in partnership with state agencies.…”

Section: Introductionmentioning

confidence: 99%

Visual Analytics for Data-Driven Understanding of the Substance Use Disorder Epidemic

Qaurooni,

Herr,

Zappone

et al. 2024

INQUIRY

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The substance use disorder epidemic has emerged as a serious public health crisis, presenting complex challenges. Visual analytics offers a unique approach to address this complexity and facilitate effective interventions. This paper details the development of an innovative visual analytics dashboard, aimed at enhancing our understanding of the substance use disorder epidemic. By employing record linkage techniques, we integrate diverse data sources to provide a comprehensive view of the epidemic. Adherence to responsive, open, and user-centered design principles ensures the dashboard’s usefulness and usability. Our approach to data and design encourages collaboration among various stakeholders, including researchers, politicians, and healthcare practitioners. Through illustrative outputs, we demonstrate how the dashboard can deepen our understanding of the epidemic, support intervention strategies, and evaluate the effectiveness of implemented measures. The paper concludes with a discussion of the dashboard’s use cases and limitations.

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Section: Introductionmentioning

confidence: 99%

Visual Analytics for Data-Driven Understanding of the Substance Use Disorder Epidemic

Qaurooni,

Herr,

Zappone

et al. 2024

INQUIRY

View full text Add to dashboard Cite

show abstract

“…This work has been leveraged to answer many questions, including the 1‐year mortality risk of overdose victims who initially survive, what adverse effects are experienced by seniors inappropriately prescribed opioids, and how often medication for opioid use disorder is prescribed after a nonfatal overdose 7–9 . Another example is work done in the Kaiser system, which has brought together clinical, dispensing, and socioeconomic data sources to examine opioid‐related outcomes across patients in multiple market segments, though the data are limited to Kaiser membership 10 …”

Section: Introductionmentioning

confidence: 99%

“…[7][8][9] Another example is work done in the Kaiser system, which has brought together clinical, dispensing, and socioeconomic data sources to examine opioid-related outcomes across patients in multiple market segments, though the data are limited to Kaiser membership. 10 In this paper, we describe how we linked, at an individual level, numerous public health datasets with all-payer claims data and census data to create a rich administrative dataset that will assess multiple factors affecting opioid-related risk. The project, funded by the National Institute on Drug Abuse, examines the role that individual characteristics, household characteristics, and community characteristics have on an individual's risk of opioid overdose.…”

mentioning

confidence: 99%