A qualitative study of big data and the opioid epidemic: recommendations for data governance

Public Involvement and Engagement in Big Data Research: Scoping Review

BACKGROUND

The success of big data initiatives depends on public support. Public involvement and engagement could be a way of establishing public support for big data research.

OBJECTIVE

This review aims to synthesize the evidence on public involvement and engagement in big data research.

METHODS

This scoping review mapped the current evidence on public involvement and engagement activities in big data research. We searched 5 electronic databases, followed by additional manual searches of Google Scholar and gray literature. In total, 2 public contributors were involved at all stages of the review.

RESULTS

A total of 53 papers were included in the scoping review. The review showed the ways in which the public could be involved and engaged in big data research. The papers discussed a broad range of involvement activities, who could be involved or engaged, and the importance of the context in which public involvement and engagement occur. The findings show how public involvement, engagement, and consultation could be delivered in big data research. Furthermore, the review provides examples of potential outcomes that were produced by involving and engaging the public in big data research.

CONCLUSIONS

This review provides an overview of the current evidence on public involvement and engagement in big data research. While the evidence is mostly derived from discussion papers, it is still valuable in illustrating how public involvement and engagement in big data research can be implemented and what outcomes they may yield. Further research and evaluation of public involvement and engagement in big data research are needed to better understand how to effectively involve and engage the public in big data research.

INTERNATIONAL REGISTERED REPORT IDENTIFIER (IRRID)

RR2-https://doi.org/10.1136/bmjopen-2021-050167.

Benefits and challenges of geographic information systems (GIS) for data-driven outreach in black communities experiencing overdose disparities: results of a stakeholder focus group

BACKGROUND

Black individuals in the U.S. face increasing racial disparities in drug overdose related to social determinants of health, including place-based features. Mobile outreach efforts work to mitigate social determinants by servicing geographic areas with low drug treatment and overdose prevention access but are often limited by convenience-based targets. Geographic information systems (GIS) are often used to characterize and visualize the overdose crisis and could be translated to community to guide mobile outreach services. The current study examines the initial acceptability and appropriateness of GIS to facilitate data-driven outreach for reducing overdose inequities facing Black individuals.

METHODS

We convened a focus group of stakeholders (N = 8) in leadership roles at organizations conducting mobile outreach in predominantly Black neighborhoods of St. Louis, MO. Organizations represented provided adult mental health and substance use treatment or harm reduction services. Participants were prompted to discuss current outreach strategies and provided feedback on preliminary GIS-derived maps displaying regional overdose epidemiology. A reflexive approach to thematic analysis was used to extract themes.

RESULTS

Four themes were identified that contextualize the acceptability and utility of an overdose visualization tool to mobile service providers in Black communities. They were: 1) importance of considering broader community context; 2) potential for awareness, engagement, and community collaboration; 3) ensuring data relevance to the affected community; and 4) data manipulation and validity concerns.

CONCLUSIONS

There are several perceived benefits of using GIS to map overdose among mobile providers serving Black communities that are overburdened by the overdose crisis but under resourced. Perceived potential benefits included informing location-based targets for services as well as improving awareness of the overdose crisis and facilitating collaboration, advocacy, and resource allocation. However, as GIS-enabled visualization of drug overdose grows in science, public health, and community settings, stakeholders must consider concerns undermining community trust and benefits, particularly for Black communities facing historical inequities and ongoing disparities.

Development of a Real-Time Dashboard for Overdose Touchpoints: User-Centered Design Approach

BACKGROUND

Overdose Fatality Review (OFR) is an important public health tool for shaping overdose prevention strategies in communities. However, OFR teams review only a few cases at a time, which typically represent a small fraction of the total fatalities in their jurisdiction. Such limited review could result in a partial understanding of local overdose patterns, leading to policy recommendations that do not fully address the broader community needs.

OBJECTIVE

This study explored the potential to enhance conventional OFRs with a data dashboard, incorporating visualizations of touchpoints-events that precede overdoses-to highlight prevention opportunities.

METHODS

We conducted 2 focus groups and a survey of OFR experts to characterize their information needs and design a real-time dashboard that tracks and measures decedents' past interactions with services in Indiana. Experts (N=27) were engaged, yielding insights on essential data features to incorporate and providing feedback to guide the development of visualizations.

RESULTS

The findings highlighted the importance of showing decedents' interactions with health services (emergency medical services) and the justice system (incarcerations). Emphasis was also placed on maintaining decedent anonymity, particularly in small communities, and the need for training OFR members in data interpretation. The developed dashboard summarizes key touchpoint metrics, including prevalence, interaction frequency, and time intervals between touchpoints and overdoses, with data viewable at the county and state levels. In an initial evaluation, the dashboard was well received for its comprehensive data coverage and its potential for enhancing OFR recommendations and case selection.

CONCLUSIONS

The Indiana touchpoints dashboard is the first to display real-time visualizations that link administrative and overdose mortality data across the state. This resource equips local health officials and OFRs with timely, quantitative, and spatiotemporal insights into overdose risk factors in their communities, facilitating data-driven interventions and policy changes. However, fully integrating the dashboard into OFR practices will likely require training teams in data interpretation and decision-making.

Visual Analytics for Data-Driven Understanding of the Substance Use Disorder Epidemic

The substance use disorder epidemic has emerged as a serious public health crisis, presenting complex challenges. Visual analytics offers a unique approach to address this complexity and facilitate effective interventions. This paper details the development of an innovative visual analytics dashboard, aimed at enhancing our understanding of the substance use disorder epidemic. By employing record linkage techniques, we integrate diverse data sources to provide a comprehensive view of the epidemic. Adherence to responsive, open, and user-centered design principles ensures the dashboard's usefulness and usability. Our approach to data and design encourages collaboration among various stakeholders, including researchers, politicians, and healthcare practitioners. Through illustrative outputs, we demonstrate how the dashboard can deepen our understanding of the epidemic, support intervention strategies, and evaluate the effectiveness of implemented measures. The paper concludes with a discussion of the dashboard's use cases and limitations.

Big data-driven public health policy making: Potential for the healthcare industry

The use of healthcare data analytics is anticipated to play a significant role in future public health policy formulation. Therefore, this study examines how big data analytics (BDA) may be methodically incorporated into various phases of the health policy cycle for fact-based and precise health policy decision-making. So, this study explores the potential of BDA for accurate and rapid policy-making processes in the healthcare industry. A systematic review of literature spanning 22 years (from January 2001 to January 2023) has been conducted using the PRISMA approach to develop a conceptual framework. The study introduces the emerging topic of BDA in healthcare policy, goes over the advantages, presents a framework, advances instances from the literature, reveals difficulties and provides recommendations. This study argues that BDA has the ability to transform the conventional policy-making process into data-driven process, which helps to make accurate health policy decision. In addition, this study contends that BDA is applicable to the different stages of health policy cycle, namely policy identification, agenda setting as well as policy formulation, implementation and evaluation. Currently, descriptive, predictive and prescriptive analytics are used for public health policy decisions on data obtained from several common health-related big data sources like electronic health reports, public health records, patient and clinical data, and government and social networking sites. To effectively utilize all of the data, it is necessary to overcome the computational, algorithmic and technological obstacles that define today's extremely heterogeneous data landscape, as well as a variety of legal, normative, governance and policy limitations. Big data can only fulfill its full potential if data are made available and shared. This enables public health institutions and policymakers to evaluate the impact and risk of policy changes at the population level.

Use of Big Data and Ethical Issues for Populations With Substance Use Disorder

With expanding data availability and computing power, health research is increasingly relying on big data from a variety of sources. We describe a state-level effort to address aspects of the opioid epidemic through public health research, which has resulted in an expansive data resource combining dozens of administrative data sources in Massachusetts. The Massachusetts Public Health Data Warehouse is a public health innovation that serves as an example of how to address the complexities of balancing data privacy and access to data for public health and health services research. We discuss issues of data protection and data access, and provide recommendations for ethical data governance. Keeping these issues in mind, the use of this data resource has the potential to allow for transformative research on critical public health issues.

Commentary on Adams et al.: using administrative big data for the public good

Adams et al demonstrate why US states should learn from Massachusetts on how to build “administrative big data” warehouses for the public good. However, these and other existing data resources must include detailed information on criminal-legal-carceral experiences. Offering buprenorphine treatment in syringe service programs would remove healthcare obstacles and save lives.

Advancing a Data Justice Framework for Public Health Surveillance

BACKGROUND

Bioethical debates about privacy, big data, and public health surveillance have not sufficiently engaged the perspectives of those being surveilled. The data justice framework suggests that big data applications have the potential to create disproportionate harm for socially marginalized groups. Using examples from our research on HIV surveillance for individuals incarcerated in jails, we analyze ethical issues in deploying big data in public health surveillance.

METHODS

We conducted qualitative, semi-structured interviews with 24 people living with HIV who had been previously incarcerated in county jails about their perspectives on and experiences with HIV surveillance, as part of a larger study to characterize ethical considerations in leveraging big data techniques to enhance continuity of care for incarcerated people living with HIV.

RESULTS

Most participants expressed support for the state health department tracking HIV testing results and viral load data. Several viewed HIV surveillance as a violation of privacy, and several had actively avoided contact from state public health outreach workers. Participants were most likely to express reservations about surveillance when they viewed the state's motives as self-interested. Perspectives highlight the mistrust that structurally vulnerable people may have in the state's capacity to act as an agent of welfare. Findings suggest that adopting a nuanced, context-sensitive view on surveillance is essential.

CONCLUSIONS

Establishing trustworthiness through interpersonal interactions with public health personnel is important to reversing historical legacies of harm to racial minorities and structurally vulnerable groups. Empowering stakeholders to participate in the design and implementation of data infrastructure and governance is critical for advancing a data justice agenda, and can offset privacy concerns. The next steps in advancing the data justice framework in public health surveillance will be to innovate ways to represent the voices of structurally vulnerable groups in the design and governance of big data initiatives.