Using Publicly Available Data to Understand the Opioid Overdose Epidemic: Geospatial Distribution of Discarded Needles in Boston, Massachusetts

Characteristics of hospital and health system initiatives to address social determinants of health in the United States: a scoping review of the peer-reviewed literature

Background

Despite the incentives and provisions created for hospitals by the US Affordable Care Act related to value-based payment and community health needs assessments, concerns remain regarding the adequacy and distribution of hospital efforts to address SDOH. This scoping review of the peer-reviewed literature identifies the key characteristics of hospital/health system initiatives to address SDOH in the US, to gain insight into the progress and gaps.

Methods

PRISMA-ScR criteria were used to inform a scoping review of the literature. The article search was guided by an integrated framework of Healthy People SDOH domains and industry recommended SDOH types for hospitals. Three academic databases were searched for eligible articles from 1 January 2018 to 30 June 2023. Database searches yielded 3,027 articles, of which 70 peer-reviewed articles met the eligibility criteria for the review.

Results

Most articles (73%) were published during or after 2020 and 37% were based in Northeast US. More initiatives were undertaken by academic health centers (34%) compared to safety-net facilities (16%). Most (79%) were research initiatives, including clinical trials (40%). Only 34% of all initiatives used the EHR to collect SDOH data. Most initiatives (73%) addressed two or more types of SDOH, e.g., food and housing. A majority (74%) were downstream initiatives to address individual health-related social needs (HRSNs). Only 9% were upstream efforts to address community-level structural SDOH, e.g., housing investments. Most initiatives (74%) involved hot spotting to target HRSNs of high-risk patients, while 26% relied on screening and referral. Most initiatives (60%) relied on internal capacity vs. community partnerships (4%). Health disparities received limited attention (11%). Challenges included implementation issues and limited evidence on the systemic impact and cost savings from interventions.

Conclusion

Hospital/health system initiatives have predominantly taken the form of downstream initiatives to address HRSNs through hot-spotting or screening-and-referral. The emphasis on clinical trials coupled with lower use of EHR to collect SDOH data, limits transferability to safety-net facilities. Policymakers must create incentives for hospitals to invest in integrating SDOH data into EHR systems and harnessing community partnerships to address SDOH. Future research is needed on the systemic impact of hospital initiatives to address SDOH.

Risk factors for pediatric intoxications in the prehospital setting. A geospatial survey

Background

Socioeconomic factors and the COVID-19 pandemic influence children's physical and mental health. We aimed to investigate the association between a census tract's median household income [MHI in United States Dollars ($)] and pediatric intoxications in Rhode Island, the smallest state in the United States of America. Geographical hotspots, as well as interactions with the COVID-19 pandemic, should be identified.

Methods

This study is a retrospective analysis of ambulance calls for pediatric (<18 years) intoxication in Rhode Island between March 1st, 2018, and February 28th, 2022. March 1st, 2020 was considered the beginning of the COVID-19 pandemic. Prehospital data were joined with information from the United States Census Bureau. The census tracts' case counts and MHI were examined using Poisson regression. Geographical clusters were identified with the Global Moran's I and local indicators of spatial association tests in ArcGIS Pro (Esri Corporation, Redlands, CA).

Results

Inclusion criteria were met by 208 incidents (48% female, median age 16 (IQR 15 to 17) years). The regression model showed a 0.6% increase (IRR 1.006, 95% CI [1.002, 1.01], p = 0.003) in pediatric intoxications for every $ 1,000 increase in MHI. Interaction analysis showed that the effect of MHI was less pronounced during the pandemic (IRR 0.98, 95% CI [0.964, 0.997], p = 0.02). Thirty-four (14%) of the 244 census tracts contributed to geographical clusters, which changed after the onset of the pandemic.

Conclusion

Higher median household income could be a risk factor for pediatric intoxications. Geographical hotspots changed with the pandemic.

The utility of Zip4 codes in spatial epidemiological analysis

There are many public health situations within the United States that require fine geographical scale data to effectively inform response and intervention strategies. However, a condition for accessing and analyzing such data, especially when multiple institutions are involved, is being able to preserve a degree of spatial privacy and confidentiality. Hospitals and state health departments, who are generally the custodians of these fine-scale health data, are sometimes understandably hesitant to collaborate with each other due to these concerns. This paper looks at the utility and pitfalls of using Zip4 codes, a data layer often included as it is believed to be "safe", as a source for sharing fine-scale spatial health data that enables privacy preservation while maintaining a suitable precision for spatial analysis. While the Zip4 is widely supplied, researchers seldom utilize it. Nor is its spatial characteristics known by data guardians. To address this gap, we use the context of a near-real time spatial response to an emerging health threat to show how the Zip4 aggregation preserves an underlying spatial structure making it potentially suitable dataset for analysis. Our results suggest that based on the density of urbanization, Zip4 centroids are within 150 meters of the real location almost 99% of the time. Spatial analysis experiments performed on these Zip4 data suggest a far more insightful geographic output than if using more commonly used aggregation units such as street lines and census block groups. However, this improvement in analytical output comes at a spatial privy cost as Zip4 centroids have a higher potential of compromising spatial anonymity with 73% of addresses having a spatial k anonymity value less than 5 when compared to other aggregations. We conclude that while offers an exciting opportunity to share data between organizations, researchers and analysts need to be made aware of the potential for serious confidentiality violations.

Geographic information science and the United States opioid overdose crisis: A scoping review of methods, scales, and application areas

BACKGROUND

The Opioid Overdose Crisis (OOC) continues to generate morbidity and mortality in the United States, outpacing other prominent accident-related reasons. Multiple disciplines have applied geographic information science (GIScience) to understand geographical patterns in opioid-related health measures. However, there are limited reviews that assess how GIScience has been used.

OBJECTIVES

This scoping review investigates how GIScience has been used to conduct research on the OOC. Specific sub-objectives involve identifying bibliometric trends, the location and scale of studies, the frequency of use of various GIScience methodologies, and what direction future research can take to address existing gaps.

METHODS

The review was pre-registered with the Open Science Framework ((https://osf.io/h3mfx/) and followed the PRISMA-ScR guidelines. Scholarly research was gathered from the Web of Science Core Collection, PubMed, IEEE Xplore, ACM Digital Library. Inclusion criteria was defined as having a publication date between January 1999 and August 2021, using GIScience as a central part of the research, and investigating an opioid-related health measure.

RESULTS

231 studies met the inclusion criteria. Most studies were published from 2017 onward. While many (41.6%) of studies were conducted using nationwide data, the majority (58.4%) occurred at the sub-national level. California, New York, Ohio, and Appalachia were most frequently studied, while the Midwest, north Rocky Mountains, Alaska, and Hawaii lacked studies. The most common GIScience methodology used was descriptive mapping, and county-level data was the most common unit of analysis across methodologies.

CONCLUSIONS

Future research of GIScience on the OOC can address gaps by developing use cases for machine learning, conducting analyses at the sub-county level, and applying GIScience to questions involving illicit fentanyl. Research using GIScience is expected to continue to increase, and multidisciplinary research efforts amongst GIScientists, epidemiologists, and other medical professionals can improve the rigor of research.

GAN-Based Approaches for Generating Structured Data in the Medical Domain

Modern machine and deep learning methods require large datasets to achieve reliable and robust results. This requirement is often difficult to meet in the medical field, due to data sharing limitations imposed by privacy regulations or the presence of a small number of patients (e.g., rare diseases). To address this data scarcity and to improve the situation, novel generative models such as Generative Adversarial Networks (GANs) have been widely used to generate synthetic data that mimic real data by representing features that reflect health-related information without reference to real patients. In this paper, we consider several GAN models to generate synthetic data used for training binary (malignant/benign) classifiers, and compare their performances in terms of classification accuracy with cases where only real data are considered. We aim to investigate how synthetic data can improve classification accuracy, especially when a small amount of data is available. To this end, we have developed and implemented an evaluation framework where binary classifiers are trained on extended datasets containing both real and synthetic data. The results show improved accuracy for classifiers trained with generated data from more advanced GAN models, even when limited amounts of original data are available.

Examining the spatial risk environment tied to the opioid crisis through a unique public health, EMS, and academic research collaborative: Lowell, Massachusetts, 2008–2018

Between 2015 and 2018, Lowell Massachusetts experienced outbreaks in opioid overdoses, HIV, and hepatitis C virus infections (HCV) among people who inject drugs. Through an innovative collaboration between emergency medical services (EMS), public health, and academic partners, we assessed the geographic distribution of opioid-related risks to inform intervention efforts. We analyzed data from three unique data sources for publicly discarded syringes, opioid-related incidents (ORIs), and fatal opioid overdoses in Lowell between 2008 and 2018. We assessed the risk environment over time using a geographic information system to identify and characterize hotspots and noted parallel trends within the syringe discard and ORI data. We identified two notable increases in ORIs per day: the first occurring between 2008 and 2010 (from 0.3 to 0.5), and the second between 2011 and 2014 (from 0.9 to 1.3), following the introduction of fentanyl within local drug markets. We also identified seasonal patterns in the syringe discard, ORI, and overdose data. Through our spatial analyses, we identified significant clusters of discarded syringes, ORIs, and fatal overdoses (p < 0.05), and neighborhoods where high densities of these outcomes overlapped. We found that areas with the highest densities shifted over time, expanding beyond the epicenter of the Downtown neighborhood. Data sharing and analyses among EMS, public health, and academic partners can foster better assessments of local risk environments. Our work, along with new public health efforts in Lowell, led to a city-funded position to improve pick-up and proper disposal of publicly discarded syringes, and better targeted harm reduction services.

Assessing open science and citizen science in addictions and substance use research: A scoping review

BACKGROUND

The EU promotes 'Open Science' as a public good. Complementary to its implementation is Citizen Science, which redefines the relationship between the scientific community, civic society and the individual. Open Science and Citizen Science poses challenges for the substance use and addictions research community but may provide positive opportunities for future European addiction research. This paper explores both current barriers and potential facilitators for the implementation of Open Science and Citizen Science in substance use and addictions research.

METHODOLOGY

A scoping review was used to examine barriers and facilitators identified in the substance use and addiction research literature for the adoption of Open Science and Citizen Science.

RESULTS

'Technical' facilitators included the pre-registration of study protocols; publication of open-source datasets; open peer review and online tools. 'Motivational' facilitators included enhanced reputation; embracing co-creation; engaged citizenship and gamification. 'Economic' facilitators included the use of free tools and balanced remuneration of crowdworkers. 'Political' facilitators included better informed debates through the 'triple helix' approach and trust-generating transparency. 'Legal' facilitators included epidemiologically informed law enforcement; better policy surveillance and the validation of other datasets. 'Ethical' facilitators included the 'democratisation of science' and opportunities to explore new concepts of ethics in addiction research.

CONCLUSION

Open Science and Citizen Science in substance use and addictions research may provide a range of benefits in relation to the democratisation of science; transparency; efficiency and the reliability/validity of data. However, its implementation raises a range of research integrity and ethical issues that need be considered. These include issues related to participant recruitment; privacy; confidentiality; security; cost and industry involvement. Progressive journal policies to support Open Science practices; a shift in researcher norms; the use of free tools and the greater availability of methodological and ethical standards are likely to increase adoption in the field.

Spatiotemporal trends in discarded needle reports near schools in Boston, Massachusetts, between 2016-2019

BACKGROUND

Childhood exposures to discarded needles pose a direct risk for infection with blood-borne pathogens and psychological trauma for caregivers and children. Little is known about environmental predictors of discarded needles relative to areas where children are frequent, such as schools.

OBJECTIVE

We investigated spatiotemporal trends in discarded needle reports and the density near schools in Boston, Massachusetts, between 2016 and 2019.

METHODS

We used the kernel density estimation (KDE) and a relative risk function (RRF) to explore their spatial distribution and temporal changes of discarded needles reported through the 311 service request system in Boston. The density of needle pick-up requests around schools was investigated by using Thiessen polygons.

RESULTS

Between January 2016 and December 2019, 18,272 discarded needle reports were made. Publicly reported discarded needles in Boston sharply increased over the 4 years and the highest density of needles was found in 2 central neighborhoods. The density of reports of discarded needles near schools increased among the majority of schools. About 30% of schools demonstrated an increase of 100% or more in reports of discarded needles.

CONCLUSION

This analysis provides insight into potential risk of exposure to needle stick injuries for children based on utilizing publicly available crowd-sourced data. Monitoring the density of discarded needles near schools may be a novel approach to improve public health efforts to distribute safe needle disposal locations and reduce injection drug use in public.

311 service requests as indicators of neighborhood distress and opioid use disorder

Opioid use disorder and overdose deaths is a public health crisis in the United States, and there is increasing recognition that its etiology is rooted in part by social determinants such as poverty, isolation and social upheaval. Limiting research and policy interventions is the low temporal and spatial resolution of publicly available administrative data such as census data. We explore the use of municipal service requests (also known as "311" requests) as high resolution spatial and temporal indicators of neighborhood social distress and opioid misuse. We analyze the spatial associations between georeferenced opioid overdose event (OOE) data from emergency medical service responders and 311 service request data from the City of Columbus, OH, USA for the time period 2008-2017. We find 10 out of 21 types of 311 requests spatially associate with OOEs and also characterize neighborhoods with lower socio-economic status in the city, both consistently over time. We also demonstrate that the 311 indicators are capable of predicting OOE hotspots at the neighborhood-level: our results show code violation, public health, and street lighting were the top three accurate predictors with predictive accuracy as 0.92, 0.89 and 0.83, respectively. Since 311 requests are publicly available with high spatial and temporal resolution, they can be effective as opioid overdose surveillance indicators for basic research and applied policy.

Spatiotemporal Trends in Discarded Needle Reports in San Francisco Over a 10-year Period, 2010-2019

BACKGROUND

To describe the geographic and spatiotemporal distribution of needle reports in San Francisco, and examine spatial relationships between needle reports and needle disposal boxes, needle disposal kiosks, and homeless shelters.

METHODS

We conducted multiple geospatial analyses of a crowdsourced database of non-emergency service requests. We describe changes in discarded needle and bulky item reports across San Francisco between 2010 and 2019, and compared changes in the reporting patterns of these items, while 200-meter Euclidean buffers captured needle reports in close proximity to needle deposit boxes, needle deposit kiosks, and homeless shelters in 2019.

RESULTS

34,912 needle reports were included. Yearly needle reports increased by 3827.1%, with a markedly different geospatial distribution from bulky item reports. 45.6% of needle reports originated in the five downtown neighborhoods with the highest needle report density, and 33.8% were identified within 200 meters of boxes, kiosks, or homeless shelters.

CONCLUSIONS

Reports of discarded needles in San Francisco increased dramatically over the last decade, and more than one third of 2019 reports were adjacent to harm reduction and homeless shelter locations. Needle reports provide an opportunity to understand changes in public injection drug use and target harm reduction services.

The ecology of overdose mortality in Philadelphia

Fatal drug overdose represents a significant public health threat in Philadelphia, but substantial variation exists across its communities. This study uses negative binomial longitudinal regression to model ZIP code overdose fatalities over a seven-year period. Model covariates indicate that structural inequality, police arrest activity, and features of the built environment are associated with increased mortality across ZIP codes. Additionally, fatalities are spatially concentrated in select geographies of the city. These findings emphasize the pertinence of community ecological features in the production of stratified within-city health outcomes, and inform the geographic distribution of harm reduction interventions.

Opioid use disorder research and the Council for the Advancement of Nursing Science priority areas

BACKGROUND

Chronic diseases, such as opioid use disorder (OUD) require a multifaceted scientific approach to address their evolving complexity. The Council for the Advancement of Nursing Science's (Council) four nursing science priority areas (precision health; global health, determinants of health, and big data/data analytics) were established to provide a framework to address current complex health problems.

PURPOSE

To examine OUD research through the nursing science priority areas and evaluate the appropriateness of the priority areas as a framework for research on complex health conditions.

METHOD

OUD was used as an exemplar to explore the relevance of the nursing science priorities for future research.

FINDINGS

Research in the four priority areas is advancing knowledge in OUD identification, prevention, and treatment. Intersection of OUD research population focus and methodological approach was identified among the priority areas.

DISCUSSION

The Council priorities provide a relevant framework for nurse scientists to address complex health problems like OUD.

Engineering Approaches for Addressing Opioid Use Disorder in the Community

Many communities in the United States are struggling to deal with the negative consequences of illicit opioid use. Effectively addressing this epidemic requires the coordination and support of community stakeholders in a change process with common goals and objectives, continuous engagement with individuals with opioid use disorder (OUD) through their treatment and recovery journeys, application of systems engineering principles to drive process change and sustain it, and use of a formal evaluation process to support a learning community that continuously adapts. This review presents strategies to improve OUD treatment and recovery with a focus on engineering approaches grounded in systems thinking.

Suspected heroin-related overdoses incidents in Cincinnati, Ohio: A spatiotemporal analysis

BACKGROUND

Opioid misuse and deaths are increasing in the United States. In 2017, Ohio had the second highest overdose rates in the US, with the city of Cincinnati experiencing a 50% rise in opioid overdoses since 2015. Understanding the temporal and geographic variation in overdose emergencies may help guide public policy responses to the opioid epidemic.

METHODS AND FINDINGS

We used a publicly available data set of suspected heroin-related emergency calls (n = 6,246) to map overdose incidents to 280 census block groups in Cincinnati between August 1, 2015, and January 30, 2019. We used a Bayesian space-time Poisson regression model to examine the relationship between demographic and environmental characteristics and the number of calls within block groups. Higher numbers of heroin-related incidents were found to be associated with features of the built environment, including the proportion of parks (relative risk [RR] = 2.233; 95% credible interval [CI]: [1.075-4.643]), commercial (RR = 13.200; 95% CI: [4.584-38.169]), manufacturing (RR = 4.775; 95% CI: [1.958-11.683]), and downtown development zones (RR = 11.362; 95% CI: [3.796-34.015]). The number of suspected heroin-related emergency calls was also positively associated with the proportion of male population, the population aged 35-49 years, and distance to pharmacies and was negatively associated with the proportion aged 18-24 years, the proportion of the population with a bachelor's degree or higher, median household income, the number of fast food restaurants, distance to hospitals, and distance to opioid treatment programs. Significant spatial and temporal heterogeneity in the risks of incidents remained after adjusting for covariates. Limitations of this study include lack of information about the nature of incidents after dispatch, which may differ from the initial classification of being related to heroin, and lack of information on local policy changes and interventions.

CONCLUSIONS

We identified areas with high numbers of reported heroin-related incidents and features of the built environment and demographic characteristics that are associated with these events in the city of Cincinnati. Publicly available information about opiate overdoses, combined with data on spatiotemporal risk factors, may help municipalities plan, implement, and target harm-reduction measures. In the US, more work is necessary to improve data availability in other cities and states and the compatibility of data from different sources in order to adequately measure and monitor the risk of overdose and inform health policies.

Hepatitis C treatment outcomes among homeless-experienced individuals at a community health centre in Boston

BACKGROUND

Hepatitis C virus (HCV) infection prevalence is high among adults who experience homelessness but data on HCV treatment outcomes are limited in this population. We examined HCV treatment engagement and outcomes in a cohort of homeless-experienced adults treated through an innovative community-based primary care program in Boston, Massachusetts, USA.

METHODS

We conducted a retrospective chart review of individuals referred for HCV treatment at Boston Health Care for the Homeless Program (BHCHP) from January 2014 to March 2017. We assessed HCV treatment initiation, treatment completion, sustained virologic response (SVR), and reinfection rates. We conducted univariate and multivariable logistic regression analyses to examine the predictors of these outcomes.

RESULTS

Of 510 referred for HCV treatment, 210 (41.1%) did not initiate treatment, principally because of being lost to follow-up (N = 93) or having superseding social issues (N = 49). Of 300 who initiated treatment, 80% were male, 52.3% were non-white, and 29% were homeless. Over half (58.6%) had a history of opioid use disorder (OUD). Twenty percent had cirrhosis. Treatment was completed by 285 (95.0%) individuals, and 255 (85.0%) achieved SVR. In multivariable analyses, individuals with bipolar disorder (OR 0.38, 95% CI 0.15-0.99), treated (OR 0.36, 95% CI 0.14-0.96) or untreated (OR 0.18, 95% CI 0.05-0.57) OUD, or on-treatment insurance change (OR 0.16, 95% CI 0.04-0.67) were less likely to achieve SVR, while individuals living with HIV (OR 10.43, 95% CI 1.33-81.96) were more likely to achieve SVR. Among 126 individuals with post-SVR follow-up data, 27 reinfections were identified during 206 person-years of follow up (rate 13.1 per 100 person-years).

CONCLUSION

Homeless-experienced individuals initiating HCV treatment in a community-based program achieved high rates of treatment completion and SVR, but a large proportion did not initiate treatment. Individuals with OUD experienced lower but still substantial rates of cure. Treatment strategies targeting homeless-experienced people should focus on improving initial engagement and minimizing reinfection risk following treatment.