A Framework for Effective Promotion of a Medicaid Tobacco Cessation Benefit.

Health Promot Pract

Vermont Department of Health, Burlington, VT, USA.

Published: July 2020

Tobacco burden is significantly greater among those insured by Medicaid, with a smoking prevalence about twice as high as the national average (28% vs. 15%). Over the past decade, smoking prevalence among those insured by Medicaid has remained relatively unchanged while overall smoking prevalence in the United States and among other insurance groups decreased. This indicates need for targeting tobacco control strategies to those insured by Medicaid. In response, the Vermont Tobacco Control Program (VTCP) set out to implement best practice by making its Medicaid cessation benefit more comprehensive and raising awareness and use of the benefit to support members in quitting. The VTCP collaborated with its Medicaid and health department leadership to implement this initiative, learning and adapting processes along the way. The VTCP identified a framework and considerations for programs implementing best practice to expand access and utilization of cessation supports. Elements of success include collaboration, data sharing, and promotion. As a result, the VTCP created an infrastructure that increases access, awareness, and use of cessation supports among Medicaid members and providers. Between 2013 and 2017, the quit ratio among Vermont Medicaid members increased from 8% to 13% and the smoking rate decreased from 36% to 31%.

Download full-text PDF

Source
http://dx.doi.org/10.1177/1524839919829452DOI Listing

Publication Analysis

Top Keywords

insured medicaid
12
smoking prevalence
12
medicaid
8
cessation benefit
8
tobacco control
8
best practice
8
cessation supports
8
medicaid members
8
framework effective
4
effective promotion
4

Similar Publications

The island of Guam is a U.S. territory in the Western Pacific with a population of approximately 174,000.

View Article and Find Full Text PDF

Dementia Care Practice.

Alzheimers Dement

December 2024

University of Pennsylvania, Philadelphia, PA, USA.

Background: Systematic approaches are essential for adapting and tailoring implementation strategies to specific dementia care settings if we are to move evidence-based practice into 'real world' care that reaches most persons living with dementia. Care of Persons with Dementia in their Environments (COPE) is an evidence-based dementia care program that provides families with skills to maximize functional abilities and quality of life of persons with dementia and reduce difficulties managing day-to-day care challenges for family caregivers. The COPE in PACE study was a national non-inferiority trial that involved the implementation of COPE in Programs of All-Inclusive Care of the Elderly (PACE)- which provide support for nursing home eligible Medicaid and Medicare enrollees (NCT04165213).

View Article and Find Full Text PDF

Background And Objectives: Soft tissue sarcomas (STSs) are rare but can be devastating. Paradigm shifts in adjuvant treatment have expanded the availability of limb salvage; however, a subset of patients still require amputation. The aim of this study was to examine the impact of patient, disease, and practice-related factors on rates of amputation in STS.

View Article and Find Full Text PDF

Importance: Pregnant people with opioid use disorder (OUD) are at high risk for potentially avoidable maternal morbidity. The majority of pregnant people with OUD receive health insurance through state Medicaid programs, but there is little comprehensive data on the burden of severe maternal morbidity (SMM)-a composite measure of adverse maternal health outcomes-among this high-risk group.

Objective: To estimate rates of SMM among Medicaid-enrolled pregnant people with OUD from 2016 to 2018.

View Article and Find Full Text PDF

Objective: Measurement of health-related social needs (HRSNs) is complex. We sought to develop and validate computable phenotypes (CPs) using structured electronic health record (EHR) data for food insecurity, housing instability, financial insecurity, transportation barriers, and a composite-type measure of these, using human-defined rule-based and machine learning (ML) classifier approaches.

Materials And Methods: We collected HRSN surveys as the reference standard and obtained EHR data from 1550 patients in 3 health systems from 2 states.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!