Health economic design for cost, cost-effectiveness and simulation analyses in the HEALing Communities Study

Informing evidence-based medicine for opioid use disorder using pharmacoeconomic studies

INTRODUCTION

The health and economic consequences of inadequately treated opioid use disorder (OUD) are substantial. Healthcare systems in the United States (US) and other countries are facing a growing healthcare crisis due to opioids. Although effective medications for OUD exist, relying solely on clinical information is insufficient for addressing the opioid crisis.

AREAS COVERED

In this review, the role of pharmacoeconomic studies in informing evidence-based medication treatment for OUD is discussed, with a particular emphasis on the US healthcare system, where the economic burden is significantly higher than the global average. The scope/objective of pharmacoeconomics as a distinct scientific research program is briefly defined, followed by a discussion of existing evidence informed by data from systematic reviews, in addition to a convenience sample of recently published pharmacoeconomic studies and protocols. The review also explores the need for methodological advancements in the field.

EXPERT OPINION

Despite the potential of pharmacoeconomic research in shaping evidence-based medicine for OUD, significant challenges limiting its real-world application remain. How to address these challenges are explored, including how to combine cost-effectiveness and budget impact analyses to address the needs of the healthcare system as a whole and specific stakeholders interested in adopting new OUD treatment strategies.

Community-led approaches to making naloxone available in public settings: Implementation experiences in the HEALing communities study

BACKGROUND

Expanding public naloxone access is a key strategy to reduce opioid overdose fatalities. We describe tailored community-engaged, data-driven approaches to install and maintain naloxone housing units (naloxone boxes) in New York State and estimate the cost of these approaches.

METHODS

Guided by the Consolidated Framework for Implementation Research, we collected data from administrative records and key informant interviews that documented the unique processes employed by four counties enrolled in the HEALing Communities Study to install and maintain naloxone housing units. We conducted a prospective micro-costing analysis to estimate the cost of each naloxone housing unit strategy from the community perspective.

RESULTS

While all counties used a coalition to guide action planning for naloxone distribution, we identified unique approaches to implementing naloxone housing units: 1) County-led with technology expansion; 2) County-led grassroots; 3) Small-scale rural opioid overdose prevention program (OOPP) contract and 4) Comprehensive OOPP contract including overdose education and naloxone distribution (OEND) to individuals. The first two county-led approaches had lower cost per naloxone dose disbursed ($28-$38) compared to outsourcing to an OOPP ($183-$266); costs depended on services added to installing and maintaining units, such as OEND. Barriers included competing demands on public health resources (i.e., COVID-19) and stigma toward naloxone and opioid use disorder. Geographic access was a barrier in rural areas whereas existing infrastructure was a facilitator in urban counties. The policy landscape in New York State, which provides free naloxone kits and financial support to OOPPs, facilitated implementation in all counties.

CONCLUSIONS

If a community has the resources, installing and maintaining naloxone housing units in-house can be less expensive than contracting with an outside partner. However, contracts that include OEND may be more effective at reaching target populations. Financial support from health departments and legislative authorization are important facilitators to making naloxone available in public settings.

Cost of start-up activities to implement a community-level opioid overdose reduction intervention in the HEALing Communities Study

BACKGROUND

Communities That HEAL (CTH) is a novel, data-driven community-engaged intervention designed to reduce opioid overdose deaths by increasing community engagement, adoption of an integrated set of evidence-based practices, and delivering a communications campaign across healthcare, behavioral-health, criminal-legal, and other community-based settings. The implementation of such a complex initiative requires up-front investments of time and other expenditures (i.e., start-up costs). Despite the importance of these start-up costs in investment decisions to stakeholders, they are typically excluded from cost-effectiveness analyses. The objective of this study is to report a detailed analysis of CTH start-up costs pre-intervention implementation and to describe the relevance of these data for stakeholders to determine implementation feasibility.

METHODS

This study is guided by the community perspective, reflecting the investments that a real-world community would need to incur to implement the CTH intervention. We adopted an activity-based costing approach, in which resources related to hiring, training, purchasing, and community dashboard creation were identified through macro- and micro-costing techniques from 34 communities with high rates of fatal opioid overdoses, across four states-Kentucky, Massachusetts, New York, and Ohio. Resources were identified and assigned a unit cost using administrative and semi-structured-interview data. All cost estimates were reported in 2019 dollars.

RESULTS

State-level average and median start-up cost (representing 8-10 communities per state) were $268,657 and $175,683, respectively. Hiring and training represented 40%, equipment and infrastructure costs represented 24%, and dashboard creation represented 36% of the total average start-up cost. Comparatively, hiring and training represented 49%, purchasing costs represented 18%, and dashboard creation represented 34% of the total median start-up cost.

CONCLUSION

We identified three distinct CTH hiring models that affected start-up costs: hospital-academic (Massachusetts), university-academic (Kentucky and Ohio), and community-leveraged (New York). Hiring, training, and purchasing start-up costs were lowest in New York due to existing local infrastructure. Community-based implementation similar to the New York model may have lower start-up costs due to leveraging of existing infrastructure, relationships, and support from local health departments.

Establishing a Protocol for Determining the Costs of an Integrated Set of Evidence-based Practices Aimed at Reducing Opioid Overdose Deaths

OBJECTIVES

In the midst of the opioid overdose crisis, local jurisdictions face a choice of public health interventions. A significant barrier when considering evidence-based practices (EBPs) is the lack of information regarding their implementation cost. This protocol paper provides the methodological foundation for the economic cost evaluations of community-wide strategies on the scale of a national study. It can serve as a resource for other communities, local policymakers, and stakeholders as they consider implementing possible public health strategies in their unique settings.

METHODS

We present a protocol that details (1) the process of identifying, reviewing, and analyzing individual strategies for study-funded and non-study-funded costs; (2) prospective costing tool designation, and; (3) data collection. To do this, we set up working groups with community stakeholders, reviewed financial invoices, and surveyed individuals with detailed knowledge of their community implementation.

DISCUSSION

There were 3 main challenges/limitations. The first was the lack of a standard structure for documenting nonfunded costs associated with each strategy. The second was the need for timely implementation of cost data. The third was generalizability because our study designed its strategies for selected communities due to their high opioid overdose mortality rates. Future steps include more tailored questions to ask during the categorization/filter process and establishing realistic expectations for organizations regarding documenting.

CONCLUSIONS

Data collected will provide a critical methodological foundation for costing large community-based EBP strategies and provide clarity for stakeholders on the cost of implementing EBP strategies to reduce opioid overdose deaths.

Protocol for community-driven selection of strategies to implement evidence-based practices to reduce opioid overdoses in the HEALing Communities Study: a trial to evaluate a community-engaged intervention in Kentucky, Massachusetts, New York and Ohio

INTRODUCTION

Opioid-involved overdose deaths continue to surge in many communities, despite numerous evidence-based practices (EBPs) that exist to prevent them. The HEALing Communities Study (HCS) was launched to develop and test an intervention (ie, Communities That HEAL (CTH)) that supports communities in expanding uptake of EBPs to reduce opioid-involved overdose deaths. This paper describes a protocol for a process foundational to the CTH intervention through which community coalitions select strategies to implement EBPs locally.

METHODS AND ANALYSIS

The CTH is being implemented in 67 communities (randomised to receive the intervention) in four states in partnership with coalitions (one per community). Coalitions must select at least five strategies, including one to implement each of the following EBPs: (a) overdose education and naloxone distribution; expanded (b) access to medications for opioid use disorder (MOUD), (c) linkage to MOUD, (d) retention in MOUD and (e) safer opioid prescribing/dispensing. Facilitated by decision aid tools, the community action planning process includes (1) data-driven goal setting, (2) discussion and prioritisation of EBP strategies, (3) selection of EBP strategies and (4) identification of next steps. Following review of epidemiologic data and information on existing local services, coalitions set goals and discuss, score and/or rank EBP strategies based on feasibility, appropriateness within the community context and potential impact on reducing opioid-involved overdose deaths with a focus on three key sectors (healthcare, behavioural health and criminal justice) and high-risk/vulnerable populations. Coalitions then select EBP strategies through consensus or majority vote and, subsequently, suggest or choose agencies with which to partner for implementation.

ETHICS AND DISSEMINATION

The HCS protocol was approved by a central Institutional Review Board (Advarra). Results of the action planning process will be disseminated in academic conferences and peer-reviewed journals, online and print media, and in meetings with community stakeholders.

TRIAL REGISTRATION NUMBER

NCT04111939.

Marginal modeling in community randomized trials with rare events: Utilization of the negative binomial regression model

BACKGROUND/AIMS

This work is motivated by the HEALing Communities Study, which is a post-test only cluster randomized trial in which communities are randomized to two different trial arms. The primary interest is in reducing opioid overdose fatalities, which will be collected as a count outcome at the community level. Communities range in size from thousands to over one million residents, and fatalities are expected to be rare. Traditional marginal modeling approaches in the cluster randomized trial literature include the use of generalized estimating equations with an exchangeable correlation structure when utilizing subject-level data, or analogously quasi-likelihood based on an over-dispersed binomial variance when utilizing community-level data. These approaches account for and estimate the intra-cluster correlation coefficient, which should be provided in the results from a cluster randomized trial. Alternatively, the coefficient of variation or R coefficient could be reported. In this article, we show that negative binomial regression can also be utilized when communities are large and events are rare. The objectives of this article are (1) to show that the negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model and to explain why the estimates may differ; (2) to derive formulas relating the negative binomial overdispersion parameter k with the intra-cluster correlation coefficient, coefficient of variation, and R coefficient; and (3) analyze pre-intervention data from the HEALing Communities Study to demonstrate and contrast models and to show how to report the intra-cluster correlation coefficient, coefficient of variation, and R coefficient when utilizing negative binomial regression.

METHODS

Negative binomial and over-dispersed binomial regression modeling are contrasted in terms of model setup, regression parameter estimation, and formulation of the overdispersion parameter. Three specific models are used to illustrate concepts and address the third objective.

RESULTS

The negative binomial regression approach targets the same marginal regression parameter(s) as an over-dispersed binomial model, although estimates may differ. Practical differences arise in regard to how overdispersion, and hence the intra-cluster correlation coefficient is modeled. The negative binomial overdispersion parameter is approximately equal to the ratio of the intra-cluster correlation coefficient and marginal probability, the square of the coefficient of variation, and the R coefficient minus 1. As a result, estimates corresponding to all four of these different types of overdispersion parameterizations can be reported when utilizing negative binomial regression.

CONCLUSION

Negative binomial regression provides a valid, practical, alternative approach to the analysis of count data, and corresponding reporting of overdispersion parameters, from community randomized trials in which communities are large and events are rare.

Revisiting Healing Environments: Islamic Interior Elements in Hospital Rooms in North Africa

BACKGROUND

A predominant notion among researchers is that hospital room design and decor are subject to the designer's expression of self, which is contrary to evidence-based studies showing that design and decor can impact patient health. The aim of this study was to examine whether improvement in quality of healthcare provided in hospitals could be achieved through the convergence of expertise of healthcare professionals and hospital room designers.

METHODS

This was a prospective study to identify the impact of hospital interior design features with a focus on single occupancy rooms. Volunteers were recruited through advertisements and the study was conducted at the Tripoli Medical Center. Responses were analyzed using a three-dimensional computer-aided design software to help respondents accurately map their preferences and visualize outcomes.

RESULTS

Participants preferred an aesthetically pleasing hospital room environment that included art and bright colors, window views, and the need for personalization, technology, mobility, and flexibility, all of which improved satisfaction and happiness. Of these, participants' preference for technology as a cause for satisfaction and happiness was a novel finding.

CONCLUSION

Designers of hospital room interiors should plan and create an appealing single occupancy room for increasing user satisfaction and patient wellness.

The HEALing (Helping to End Addiction Long-term SM) Communities Study: Protocol for a cluster randomized trial at the community level to reduce opioid overdose deaths through implementation of an integrated set of evidence-based practices

BACKGROUND

Opioid overdose deaths remain high in the U.S. Despite having effective interventions to prevent overdose deaths, there are numerous barriers that impede their adoption. The primary aim of the HEALing Communities Study (HCS) is to determine the impact of an intervention consisting of community-engaged, data-driven selection, and implementation of an integrated set of evidence-based practices (EBPs) on reducing opioid overdose deaths.

METHODS

The HCS is a four year multi-site, parallel-group, cluster randomized wait-list controlled trial. Communities (n = 67) in Kentucky, Massachusetts, New York and Ohio are randomized to active intervention (Wave 1), which starts the intervention in Year 1 or the wait-list control (Wave 2), which starts the intervention in Year 3. The HCS will test a conceptually driven framework to assist communities in selecting and adopting EBPs with three components: 1) a community engagement strategy with local coalitions to guide and implement the intervention; 2) a compendium of EBPs coupled with technical assistance; and 3) a series of communication campaigns to increase awareness and demand for EBPs and reduce stigma. An implementation science framework guides the intervention and allows for examination of the multilevel contexts that promote or impede adoption and expansion of EBPs. The primary outcome, number of opioid overdose deaths, will be compared between Wave 1 and Wave 2 communities during Year 2 of the intervention for Wave 1. Numerous secondary outcomes will be examined.

DISCUSSION

The HCS is the largest community-based implementation study in the field of addiction with an ambitious goal of significantly reducing fatal opioid overdoses.

Introduction to the special issue on the HEALing Communities Study

The severity of the overdose epidemic underscores the urgent need for innovative and high impact interventions that promote the rapid penetration and scale up of evidence-based practices (EBPs) in communities profoundly affected by fatal opioid overdose. This special issue shares scientific advancements in implementation research design and evaluation of a novel data-driven community-based intervention. The HEALing (Helping End Addiction Long-Term) Communities Study (HCS) is a four-year study that is designed to examine the effectiveness of the Communities That HEAL (CTH) intervention. The CTH intervention supports the dissemination of EBPs in 67 communities across four high-burdened states-Kentucky, Massachusetts, New York, and Ohio. The diversity in these communities in terms of rural-urban status, race-ethnicity and other social determinants of health facilitates generalizability of results to other communities across the US. The nine papers in this special issue describe critical elements that constitute the HCS framework and design. This includes the implementation of EBPs that have a substantial impact on fatal and non-fatal opioid overdose, the Opioid-overdose Reduction Continuum of Care Approach, communication campaigns to increase awareness and demand for EBPs and reduce stigma against people with OUD and MOUD interventions, and the process of community engagement. This includes how to form community coalitions and gain their commitment, and steps taken to mobilize coalitions to pursue EBP implementation and ensure EBPs are adapted for community needs. The collective papers in this issue demonstrate that the design of any complex study must adapt to unanticipated temporal events, including the rapidly emerging COVID-19 crisis. Readers will learn about the scientific process of the design and implementation of a community-engaged intervention, its methodologies, guiding conceptual models, and research implementation strategies that can be applied to address other health issues.

Model and approach for assessing implementation context and fidelity in the HEALing Communities Study

BACKGROUND

In response to the U.S. opioid epidemic, the HEALing (Helping to End Addiction Long-term^SM) Communities Study (HCS) is a multisite, wait-listed, community-level cluster-randomized trial that aims to test the novel Communities That HEAL (CTH) intervention, in 67 communities. CTH will expand an integrated set of evidence-based practices (EBPs) across health care, behavioral health, justice, and other community-based settings to reduce opioid overdose deaths. We present the rationale for and adaptation of the RE-AIM/PRISM framework and methodological approach used to capture the CTH implementation context and to evaluate implementation fidelity.

METHODS

HCS measures key domains of the internal and external CTH implementation context with repeated annual surveys and qualitative interviews with community coalition members and key stakeholders. Core constructs of fidelity include dosage, adherence, quality, and program differentiation-the adaptation of the CTH intervention to fit each community's needs. Fidelity measures include a monthly CTH checklist, collation of artifacts produced during CTH activities, coalition and workgroup attendance, and coalition meeting minutes. Training and technical assistance delivered by the research sites to the communities are tracked monthly.

DISCUSSION

To help attenuate the nation's opioid epidemic, the adoption of EBPs must be increased in communities. The HCS represents one of the largest and most complex implementation research experiments yet conducted. Our systematic examination of implementation context and fidelity will significantly advance understanding of how to best evaluate community-level implementation of EBPs and assess relations among implementation context, fidelity, and intervention impact.