Dataset Information

Application of an Opioid Use Disorder Cascade of Care in a Large Public Health System.

ABSTRACT:

Background

Over the past decade, hospitals and health systems have increasingly adopted interventions to address the needs of patients with substance use disorders. The Opioid Use Disorder (OUD) Cascade of Care provides a framework for organizing and tracking patient health milestones over time, and can assist health systems in identifying areas of intervention to prevent overdose and maximize the impact of evidence-based services for patients with OUD. However, detailed protocols are needed to guide health systems in how to operationalize the OUD Cascade and track outcomes using their systems' electronic medical records (EMR).

Objective

In this paper, we describe the process of operationalizing and implementing the OUD Cascade in one large, urban, public hospital system.

Methods

Through this case example, we describe the technical processes around data mining, as well as the decision-making processes, challenges encountered, and lessons learned from compiling patient data and defining stages and outcome measures for the OUD Cascade of Care. The current established framework and process will set the stage for subsequent research studies that quantify and evaluate patient progression through each stage of OUD treatment across the health system and identify target areas for quality improvement initiatives to better engage patients in care and improve health outcomes.

Results

The current paper can therefore serve as a primer for other health systems seeking to implement a data-informed approach to guide more efficient care and improved substance use-related outcomes.

Conclusion

An OUD Cascade of Care must be tailored to local systems based on inherent data limitations and services design.

SUBMITTER: Carter E

PROVIDER: S-EPMC10614983 | biostudies-literature | 2023 Oct

REPOSITORIES: biostudies-literature

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Publications

Application of an Opioid Use Disorder Cascade of Care in a Large Public Health System.

Carter Emily E Schatz Daniel D Isaacs Noah N Garcia Juan J Henry Brandy B Krawczyk Noa N Williams Arthur Robin AR

medRxiv : the preprint server for health sciences 20231019

<h4>Background</h4>Over the past decade, hospitals and health systems have increasingly adopted interventions to address the needs of patients with substance use disorders. The Opioid Use Disorder (OUD) Cascade of Care provides a framework for organizing and tracking patient health milestones over time, and can assist health systems in identifying areas of intervention to prevent overdose and maximize the impact of evidence-based services for patients with OUD. However, detailed protocols are ne ...[more]

PMID: 37905052

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Project description:ImportanceGiven the high number of opioid overdose deaths in the US and the complex epidemiology of opioid use disorder (OUD), systems models can serve as a tool to identify opportunities for public health interventions.ObjectiveTo estimate the projected 3-year association between public health interventions and opioid overdose-related outcomes among persons with OUD.Design, setting, and participantsThis decision analytical model used a simulation model of the estimated US population aged 12 years and older with OUD that was developed and analyzed between January 2019 and December 2023. The model was parameterized and calibrated using 2019 to 2020 data and used to estimate the relative change in outcomes associated with simulated public health interventions implemented between 2021 and 2023.Main outcomes and measuresProjected OUD and medications for OUD (MOUD) prevalence in 2023 and number of nonfatal and fatal opioid-involved overdoses among persons with OUD between 2021 and 2023.ResultsIn a baseline scenario assuming parameters calibrated using 2019 to 2020 data remained constant, the model projected more than 16 million persons with OUD not receiving MOUD treatment and nearly 1.7 million persons receiving MOUD treatment in 2023. Additionally, the model projected over 5 million nonfatal and over 145 000 fatal opioid-involved overdoses among persons with OUD between 2021 and 2023. When simulating combinations of interventions that involved reducing overdose rates by 50%, the model projected decreases of up to 35.2% in nonfatal and 36.6% in fatal opioid-involved overdoses among persons with OUD. Interventions specific to persons with OUD not currently receiving MOUD treatment demonstrated the greatest reduction in numbers of nonfatal and fatal overdoses. Combinations of interventions that increased MOUD initiation and decreased OUD recurrence were projected to reduce OUD prevalence by up to 23.4%, increase MOUD prevalence by up to 137.1%, and reduce nonfatal and fatal opioid-involved overdoses among persons with OUD by 6.7% and 3.5%, respectively.Conclusions and relevanceIn this decision analytical model study of persons with OUD, findings suggested that expansion of evidence-based interventions that directly reduce the risk of overdose fatality among persons with OUD, such as through harm reduction efforts, could engender the highest reductions in fatal overdoses in the short-term. Interventions aimed at increasing MOUD initiation and retention of persons in treatment projected considerable improvement in MOUD and OUD prevalence but could require a longer time horizon for substantial reductions in opioid-involved overdoses.

Project description:ImportanceDigital health technologies may expand organizational capacity to treat opioid use disorder (OUD). However, it remains unclear whether these technologies serve as substitutes for or complements to traditional substance use disorder (SUD) treatment resources in health care organizations.ObjectiveTo characterize the use of patient-facing digital health technologies for OUD by US organizations with accountable care organization (ACO) contracts.Design, setting, and participantsThis cross-sectional study analyzed responses to the 2022 National Survey of Accountable Care Organizations (NSACO), collected between October 1, 2021, and June 30, 2022, from US organizations with Medicare and Medicaid ACO contracts. Data analysis was performed between December 15, 2022, and January 6, 2023.ExposuresTreatment resources for SUD (eg, an addiction medicine specialist, sufficient staff to treat SUD, medications for OUD, a specialty SUD treatment facility, a registry to identify patients with OUD, or a registry to track mental health for patients with OUD) and organizational characteristics (eg, organization type, Medicaid ACO contract).Main outcomes and measuresThe main outcomes included survey-reported use of 3 categories of digital health technologies for OUD: remote mental health therapy and tracking, virtual peer recovery support programs, and digital recovery support for adjuvant cognitive behavior therapy (CBT). Statistical analysis was conducted using descriptive statistics and multivariable logistic regression models.ResultsOverall, 276 of 505 organizations responded to the NSACO (54.7% response rate), with a total of 304 respondents. Of these, 161 (53.1%) were from a hospital or health system, 74 (24.2%) were from a physician- or medical group-led organization, and 23 (7.8%) were from a safety-net organization. One-third of respondents (101 [33.5%]) reported that their organization used at least 1 of the 3 digital health technology categories, including remote mental health therapy and tracking (80 [26.5%]), virtual peer recovery support programs (46 [15.1%]), and digital recovery support for adjuvant CBT (27 [9.0%]). In an adjusted analysis, organizations with an addiction medicine specialist (average marginal effect [SE], 32.3 [4.7] percentage points; P < .001) or a registry to track mental health (average marginal effect [SE], 27.2 [3.8] percentage points; P < .001) were more likely to use at least 1 category of technology compared with otherwise similar organizations lacking these capabilities.Conclusions and relevanceIn this cross-sectional study of 276 organizations with ACO contracts, organizations used patient-facing digital health technologies for OUD as complements to available SUD treatment capabilities rather than as substitutes for unavailable resources. Future studies should examine implementation facilitators to realize the potential of emerging technologies to support organizations facing health care practitioner shortages and other barriers to OUD treatment delivery.

Project description:BACKGROUND:In light of the accelerating and rapidly evolving overdose crisis in the United States (US), new strategies are needed to address the epidemic and to efficiently engage and retain individuals in care for opioid use disorder (OUD). Moreover, there is an increasing need for novel approaches to using health data to identify gaps in the cascade of care for persons with OUD. METHODS AND FINDINGS:Between June 2018 and May 2019, we engaged a diverse stakeholder group (including directors of statewide health and social service agencies) to develop a statewide, patient-centered cascade of care for OUD for Rhode Island, a small state in New England, a region highly impacted by the opioid crisis. Through an iterative process, we modified the cascade of care defined by Williams et al. for use in Rhode Island using key national survey data and statewide health claims datasets to create a cross-sectional summary of 5 stages in the cascade. Approximately 47,000 Rhode Islanders (5.2%) were estimated to be at risk for OUD (stage 0) in 2016. At the same time, 26,000 Rhode Islanders had a medical claim related to an OUD diagnosis, accounting for 55% of the population at risk (stage 1); 27% of the stage 0 population, 12,700 people, showed evidence of initiation of medication for OUD (MOUD, stage 2), and 18%, or 8,300 people, had evidence of retention on MOUD (stage 3). Imputation from a national survey estimated that 4,200 Rhode Islanders were in recovery from OUD as of 2016, representing 9% of the total population at risk. Limitations included use of self-report data to arrive at estimates of the number of individuals at risk for OUD and using a national estimate to identify the number of individuals in recovery due to a lack of available state data sources. CONCLUSIONS:Our findings indicate that cross-sectional summaries of the cascade of care for OUD can be used as a health policy tool to identify gaps in care, inform data-driven policy decisions, set benchmarks for quality, and improve health outcomes for persons with OUD. There exists a significant opportunity to increase engagement prior to the initiation of OUD treatment (i.e., identification of OUD symptoms via routine screening or acute presentation) and improve retention and remission from OUD symptoms through improved community-supported processes of recovery. To do this more precisely, states should work to systematically collect data to populate their own cascade of care as a health policy tool to enhance system-level interventions and maximize engagement in care.

Dataset Information

Application of an Opioid Use Disorder Cascade of Care in a Large Public Health System.

Background

Objective

Methods

Results

Conclusion

Publications

Application of an Opioid Use Disorder Cascade of Care in a Large Public Health System.

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