Dataset Information

Rapid Cycle Evaluation and Adaptation of an Inpatient Tobacco Treatment Service at a U.S. Safety-Net Hospital.

ABSTRACT:

Background

To address disparities in smoking rates, our safety-net hospital implemented an inpatient tobacco treatment intervention: an "opt-out" electronic health record (EHR)-based Best Practice Alert + order-set, which triggers consultation to a Tobacco Treatment Consult (TTC) service for all hospitalized patients who smoke cigarettes. We report on development, implementation, and adaptation of the intervention, informed by a pre-implementation needs assessment and two rapid-cycle evaluations guided by the Consolidated Framework for Implementation Research (CFIR) and Expert Recommendations for Implementing Change (ERIC) compilation.

Methods

We identified stakeholders affected by implementation and conducted a local needs assessment starting 6 months-pre-launch. We then conducted two rapid-cycle evaluations during the first 6 months post-implementation. The CFIR informed survey and interview guide development, data collection, assessment of barriers and facilitators, and selection of ERIC strategies to implement and adapt the intervention.

Results

Key themes were: (1) Understanding the hospital's priority to improving tobacco performance metrics was critical in gaining leadership buy-in (CFIR Domain: Outer setting; Construct: External Policy and Incentives). (2) CFIR-based rapid-cycle evaluations allowed us to recognize implementation challenges early and select ERIC strategies clustering into 3 broad categories (conducting needs assessment; developing stakeholder relationships; training and educating stakeholders) to make real-time adaptations, creating an acceptable clinical workflow. (3) Minimizing clinician burden allowed the successful implementation of the TTC service. (4) Demonstrating improved 6-month quit rates and tobacco performance metrics were key to sustaining the program.

Conclusions

Rapid-cycle evaluations to gather pre-implementation and early-implementation data, focusing on modifiable barriers and facilitators, allowed us to develop and refine the intervention to improve acceptability, adoption, and sustainability, enabling us to improve tobacco performance metrics in a short timeline. Future directions include spreading rapid-cycle evaluations to promote implementation of inpatient tobacco treatment programs to other settings and assessing long-term sustainability and return on investment of these programs.

SUBMITTER: Kathuria H

PROVIDER: S-EPMC9981890 | biostudies-literature | 2021 Jan-Dec

REPOSITORIES: biostudies-literature

ACCESS DATA

Publications

Rapid Cycle Evaluation and Adaptation of an Inpatient Tobacco Treatment Service at a U.S. Safety-Net Hospital.

Kathuria Hasmeena H Herbst Nicole N Seth Bhavna B Clark Kristopher K Helm Eric D ED Zhang Michelle M O'Donnell Charles C Fitzgerald Carmel C Itchapurapu Indira Swetha IS Waite Meg M Wong Carolina C Swamy Lakshmana L Olson Jen J Mishuris Rebecca G RG Wiener Renda Soylemez RS

Implementation research and practice 20210101

<h4>Background</h4>To address disparities in smoking rates, our safety-net hospital implemented an inpatient tobacco treatment intervention: an "opt-out" electronic health record (EHR)-based Best Practice Alert + order-set, which triggers consultation to a Tobacco Treatment Consult (TTC) service for all hospitalized patients who smoke cigarettes. We report on development, implementation, and adaptation of the intervention, informed by a pre-implementation needs assessment and two rapid-cycle eva ...[more]

PMID: 37089992

Similar Datasets

Project description:BackgroundHospital admissions involving substance use disorders are increasing and represent an opportunity to engage patients in substance use treatment. Addiction medicine consultation services improve access to medications for opioid use disorder (MOUD) and patient outcomes. However, as hospitals continue to adopt addiction medicine consultation services it is important to identify where disparities may emerge in the process of care.ObjectiveTo describe addiction medicine consultation service use by race and ethnicity as well as substance to identify opportunities to reduce substance use treatment disparities.DesignRetrospective cohort study using 2016-2021 Electronic Health Record data from a large Midwest safety-net hospital.ParticipantsHospitalized adults aged 18 or older, with one or more substance use disorders.Main measuresConsultation orders placed, patient seen by consult provider, and receipt of MOUD by self-reported race.Key resultsBetween 2016 and 2021, we identified 16,895 hospitalized patients with a substance use disorder. Consultation orders were placed for 6344 patients and 2789 were seen by the consult provider. Black patients were less likely (aOR = 0.58; 95% CI: 0.53-0.63) to have an addiction medicine consultation order placed and, among patients with a consultation order, were less likely (aOR = 0.74; 95% CI: 0.65-0.85) to be seen by the consult provider than White patients. Overall, Black patients with OUD were also less likely to receive MOUD in the hospital (aOR = 0.63; 95% CI: 0.50-0.79) compared to White patients. However, there were no differences in MOUD receipt among Black and White patients seen by the consult provider.ConclusionsUsing Electronic Health Record data, we identified racial and ethnic disparities at multiple points in the inpatient addiction medicine consultation process. Addressing these disparities may support more equitable access to MOUD and other substance use treatment in the hospital setting.

Project description:ImportanceNo consensus exists on how to define safety-net hospitals (SNHs) for research or policy decision-making. Identifying which types of hospitals are classified as SNHs under different definitions is key to assessing policies that affect SNH funding.ObjectiveTo examine characteristics of SNHs as classified under 3 common definitions.Design, setting, and participantsThis cross-sectional analysis includes noncritical-access hospitals in the Healthcare Cost and Utilization Project State Inpatient Databases from 47 US states for fiscal year 2015, linked to the Centers for Medicare & Medicaid Services Hospital Cost Reports and to the American Hospital Association Annual Survey. Data were analyzed from March 1 through September 30, 2018.ExposuresHospital characteristics including organizational characteristics, scope of services provided, and financial attributes.Main outcomes and measuresDefinitions of SNH based on Medicaid and Medicare Supplemental Security Income inpatient days historically used to determine Medicare Disproportionate Share Hospital (DSH) payments; Medicaid and uninsured caseload; and uncompensated care costs. For each measure, SNHs were defined as those within the top quartile for each state.ResultsThe 2066 hospitals in this study were distributed across the Northeast (340 [16.5%]), Midwest (587 [28.4%]), South (790 [38.2%]), and West (349 [16.9%]). Concordance between definitions was low; 269 hospitals (13.0%) or fewer were identified as SNHs under any 2 definitions. Uncompensated care captured smaller (200 of 523 [38.2%]) and more rural (65 of 523 [12.4%]) SNHs, whereas DSH index and Medicaid and uncompensated caseload identified SNHs that were larger (264 of 518 [51.0%] and 158 of 487 [32.4%], respectively) and teaching facilities (337 of 518 [65.1%] and 229 of 487 [47.0%], respectively) that provided more essential services than non-SNHs. Uncompensated care also distinguished remarkable financial differences between SNHs and non-SNHs. Under the uncompensated care definition, median (interquartile range [IQR]) bad debt ($27.1 [$15.5-$44.3] vs $12.8 [$6.7-$21.6] per $1000 of operating expenses; P < .001) and charity care ($19.9 [$9.3-$34.1] vs $9.1 [$4.0-$18.7] per $1000 of operating expenses) were twice as high and median (IQR) unreimbursed costs ($32.6 [$12.4-$55.4] vs $23.6 [$9.0-$42.7] per $1000 of operating expenses; P < .001) were 38% higher for SNHs than for non-SNHs. Safety-net hospitals defined by uncompensated care burden had lower median (IQR) total (4.7% [0%-9.9%] vs 5.8% [1.2%-11.2%]; P = .003) and operating (0.3% [-8.0% to 7.2%] vs 2.3% [-3.9% to 8.9%]; P < .001) margins than their non-SNH counterparts, whereas differences between SNH and non-SNH profit margins generally were not statistically significant under the other 2 definitions.Conclusions and relevanceDifferent SNH definitions identify hospitals with different characteristics and financial conditions. The new DSH formula, which accounts for uncompensated care, may lead to redistributed payments across hospitals. Our results may inform which types of hospitals will experience funding changes as DSH payment policies evolve.

Dataset Information

Rapid Cycle Evaluation and Adaptation of an Inpatient Tobacco Treatment Service at a U.S. Safety-Net Hospital.

Background

Methods

Results

Conclusions

Publications

Rapid Cycle Evaluation and Adaptation of an Inpatient Tobacco Treatment Service at a U.S. Safety-Net Hospital.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets