Project SIGNAL: A Dashboard for Supporting Community Confidence in Making Data-Driven Decisions.

Context: Data dashboards have emerged as critical tools for surveillance and informing resource allocation. Despite their utility and popularity during COVID-19, there is a growing need to understand what tools and training are tailored to nonprofit community-based organizations that may partner with public health officials.

Program: In June 2021, the Rhode Island Department of Health and Brown University partnered to create Project SIGNAL (Spatiotemporal Insights to Guide Nuanced Actions Locally), which utilizes spatiotemporal analytics to identify Rhode Island's largest disparities in COVID-19-related outcomes (eg, testing, diagnosis, vaccinations) at the neighborhood level.

Patients presenting to the ED with nonfatal drug overdose: Self-reported history of overdose and naloxone use.

Background: In the context of polysubstance use and fentanyl detection in non-opioid drugs supplies (e.g., cocaine, methamphetamine), it is important to re-evaluate and expand our understanding of which populations are at high risk for fatal drug overdoses.

Public Health Dashboards in Overdose Prevention: The Rhode Island Approach to Public Health Data Literacy, Partnerships, and Action.

As the field of public health rises to the demands of real-time surveillance and rapid data-sharing needs in a postpandemic world, it is time to examine our approaches to the dissemination and accessibility of such data. Distinct challenges exist when working to develop a shared public health language and narratives based on data. It requires that we assess our understanding of public health data literacy, revisit our approach to communication and engagement, and continuously evaluate our impact and relevance.

PROVIDENT: Development and Validation of a Machine Learning Model to Predict Neighborhood-level Overdose Risk in Rhode Island.

Background: Drug overdose persists as a leading cause of death in the United States, but resources to address it remain limited. As a result, health authorities must consider where to allocate scarce resources within their jurisdictions. Machine learning offers a strategy to identify areas with increased future overdose risk to proactively allocate overdose prevention resources.

Comprehensive testing and rapid dissemination of local drug supply surveillance data in Rhode Island.

Background: The North American overdose crisis has continued at unprecedented rates with more than 100,000 overdose deaths estimated to have occurred in the United States in 2022. Regional variations in overdose rates signify differences in local drug supplies. State-level drug supply surveillance systems have been limited in their ability to document and communicate the rapidly changing drug supplies which can hinder harm reduction efforts at the community level.

Comparison of a national commercial pharmacy naloxone data source to state and city pharmacy naloxone data sources-Rhode Island, Massachusetts, and New York City, 2013-2019.

Objective: Accurate naloxone distribution data are critical for planning and prevention purposes, yet sources of naloxone dispensing data vary by location, and completeness of local datasets is unknown. We sought to compare available datasets in Massachusetts, Rhode Island, and New York City (NYC) to a commercially available pharmacy national claims dataset (Symphony Health Solutions).

Data Sources And Study Setting: We utilized retail pharmacy naloxone dispensing data from NYC (2018-2019), Rhode Island (2013-2019), and Massachusetts (2014-2018), and pharmaceutical claims data from Symphony Health Solutions (2013-2019).

Translating Predictive Analytics for Public Health Practice: A Case Study of Overdose Prevention in Rhode Island.

Prior applications of machine learning to population health have relied on conventional model assessment criteria, limiting the utility of models as decision support tools for public health practitioners. To facilitate practitioners' use of machine learning as a decision support tool for area-level intervention, we developed and applied 4 practice-based predictive model evaluation criteria (implementation capacity, preventive potential, health equity, and jurisdictional practicalities). We used a case study of overdose prevention in Rhode Island to illustrate how these criteria could inform public health practice and health equity promotion.

Comparing Projected Fatal Overdose Outcomes and Costs of Strategies to Expand Community-Based Distribution of Naloxone in Rhode Island.

Importance: In 2021, the state of Rhode Island distributed 10 000 additional naloxone kits compared with the prior year through partnerships with community-based organizations.

Objective: To compare various strategies to increase naloxone distribution through community-based programs in Rhode Island to identify one most effective and efficient strategy in preventing opioid overdose deaths (OODs).

Design, Setting, And Participants: In this decision analytical model study conducted from January 2016 to December 2022, a spatial microsimulation model with an integrated decision tree was developed and calibrated to compare the outcomes of alternative strategies for distributing 10 000 additional naloxone kits annually among all individuals at risk for opioid overdose in Rhode Island.

Identifying Predictors of Opioid Overdose Death at a Neighborhood Level With Machine Learning.

Predictors of opioid overdose death in neighborhoods are important to identify, both to understand characteristics of high-risk areas and to prioritize limited prevention and intervention resources. Machine learning methods could serve as a valuable tool for identifying neighborhood-level predictors. We examined statewide data on opioid overdose death from Rhode Island (log-transformed rates for 2016-2019) and 203 covariates from the American Community Survey for 742 US Census block groups.

Preventing Overdose Using Information and Data from the Environment (PROVIDENT): protocol for a randomized, population-based, community intervention trial.

Background And Aims: In light of the accelerating drug overdose epidemic in North America, new strategies are needed to identify communities most at risk to prioritize geographically the existing public health resources (e.g. street outreach, naloxone distribution efforts).

Targeting community-based naloxone distribution using opioid overdose death rates: A descriptive analysis of naloxone rescue kits and opioid overdose deaths in Massachusetts and Rhode Island.

Background: Rates of fatal opioid overdose in Massachusetts (MA) and Rhode Island (RI) far exceed the national average. Community-based opioid education and naloxone distribution (OEND) programs are effective public health interventions to prevent overdose deaths. We compared naloxone distribution and opioid overdose death rates in MA and RI to identify priority communities for expanded OEND.

Toxicological and pharmacologic sex differences in unintentional or undetermined opioid overdose death.

Intro: Understanding sex differences in toxicological etiologies of opioid-related drug overdose death could inform future sex- and gender-specific approaches to prevention and treatment.

Methods: A retrospective review of accidental or undetermined opioid-involved overdose deaths in Rhode Island 2016-2019 was performed using the Rhode Island Department of Health State Unintentional Drug Overdose Reporting System (SUDORS) database. Decedent toxicology data was linked with state Prescription Drug Monitoring Program (PDMP) records.

Machine learning takes a village: Assessing neighbourhood-level vulnerability for an overdose and infectious disease outbreak.

Background: Multiple areas in the United States of America (USA) are experiencing high rates of overdose and outbreaks of bloodborne infections, including HIV and hepatitis C virus (HCV), due to non-sterile injection drug use. We aimed to identify neighbourhoods at increased vulnerability for overdose and infectious disease outbreaks in Rhode Island, USA. The primary aim was to pilot machine learning methods to identify which neighbourhood-level factors were important for creating "vulnerability assessment scores" across the state.

US drug overdose mortality: 2009-2018 increases affect young people who use drugs.

Purpose: Drug overdose mortality remains a public health concern in many countries globally. In the US, overdoses involving synthetic opioids are the primary contributor to overdose mortality. We aimed to assess trends in overdose death due to synthetic opioids among young people and describe key demographic and temporal changes.

Opioid Overdose Deaths with Buprenorphine Detected in Postmortem Toxicology: a Retrospective Analysis.

Background: Buprenorphine is a unique μ-opioid receptor partial agonist with avid receptor binding, nominal euphoric reward, and a ceiling effect on sedation and respiratory depression. Despite a pharmacologic profile that enhances safety, cases of fatal opioid overdose with buprenorphine on postmortem toxicology are reported, but details of these cases in the literature are limited.

Methods: A retrospective review of opioid-involved drug overdose fatalities in Rhode Island (RI) from 2016 to 2018 using the RI Department of Health State Unintentional Drug Overdose Reporting System (SUDORS) database.

Analysis of Pharmaceutical Industry Marketing of Stimulants, 2014 Through 2018.

This study examines the number and dollar amount of payments to physicians from companies marketing prescription stimulant medications.

Defining a recovery-oriented cascade of care for opioid use disorder: A community-driven, statewide cross-sectional assessment.

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.

Suspected involvement of fentanyl in prior overdoses and engagement in harm reduction practices among young adults who use drugs.

From 2011 to 2016, the United States has experienced a 55% increase in overall overdose deaths and a 260% increase in fatal fentanyl-related overdoses. Increasing engagement in harm reduction practices is essential to reducing the rate of fentanyl-related overdoses. This study sought to examine the uptake of harm reduction practices among young adults who reported recent drug use and who were recruited for a study to assess the utility and acceptability of rapid fentanyl test strips.

Perspectives on rapid fentanyl test strips as a harm reduction practice among young adults who use drugs: a qualitative study.

Background: In 2016, drug overdose deaths exceeded 64,000 in the United States, driven by a sixfold increase in deaths attributable to illicitly manufactured fentanyl. Rapid fentanyl test strips (FTS), used to detect fentanyl in illicit drugs, may help inform people who use drugs about their risk of fentanyl exposure prior to consumption. This qualitative study assessed perceptions of FTS among young adults.

Use of rapid fentanyl test strips among young adults who use drugs.

Background: The overdose epidemic has been exacerbated by a dramatic increase in deaths involving illicitly manufactured fentanyl (IMF). Drug checking is a novel strategy to identify IMF in illicit drugs. We examined the uptake and acceptability of rapid fentanyl test strips among young adults.

Association of Pharmaceutical Industry Marketing of Opioid Products to Physicians With Subsequent Opioid Prescribing.

This database analysis examines the extent to which pharmaceutical industry marketing of opioid products to physicians during 2014 was associated with opioid prescribing during 2015.