Does Data Drive Policymaking? A Multiple Streams Perspective on the Relationship Between Indicators and Agenda Setting

by Rob A DeLeo & Alex Duarte

The multiple streams framework (MSF) illustrates how policies are formed not through linear processes, but through the convergence of three independent streams: the problem stream, the policy stream, and the political stream. While the MSF offers numerous insights into the often chaotic nature of policy making, prior studies have not fully explored the relationship between problem indicators and agenda setting. In this study, we explore nuanced ways that changes in indicators either shape or fail to influence policy responses.

Within the MSF, changes in problem indicators have the potential to elevate issues on the policy agenda. In addition, indicators that threaten powerful economic or political interests may lead to reduced policy attention. Recognizing the possibility that policymakers might overlook or downplay information that poses risks to their power or that contradicts prevailing policy directions, we introduce the concept of “indicator politicization.” 

We apply the MSF to examine the US Congress’s response to changes in opioid overdose rates. Empirically, we employ a mixed-methods approach to examine the relationship between opioid-related data and policy responses. Drawing on data from congressional hearings and legislative actions from 1999 to 2019, we explore how the changes in opioid-related indicators influenced legislative actions (or inactions). We use negative binomial regression analysis to estimate the effect of opioid indicators–heroin, fentanyl, and prescription opioids–on the congressional agenda. We then provide a case study that investigates the differential patterns of agenda change identified in our quantitative model. 

On one hand, we confirm the substantial impact of indicator change on policy attention, exemplified by marked upticks in policymaker attention to heroin and fentanyl overdose deaths. Policymaker attention was likely magnified by electoral concerns, as the opioid epidemic was a prominent issue during the 2016 election cycle. On the other hand, public awareness and political responses to prescription opioids developed slowly over several years. Indeed, although increases in opioid overdose indicators occasionally spurred congressional attention and led to policy shifts, such responses were inconsistent. A major obstacle is “data politicization”–when data threatens powerful interests, these entities can minimize or downplay the information to turn aside policy scrutiny. When data politicization occurs, it undermines the urgency and attention the issues receive even in the face of an escalating crisis hence the lack of attention to prescription opioids observed in our study.

This study sheds light on data-driven policymaking, with a focus on the constraints imposed by entrenched political interests. Data alone cannot drive policy changes when it conflicts with the interests of powerful stakeholders. We reevaluate the multiple streams framework’s (MSF) initial assumptions, which may overestimate the direct impact of indicators on policy decisions. Practically, we encourage policymakers, scholars, and practitioners to assess the power dynamics that shape policy responses to social issues. This is particularly relevant in crafting effective strategies for public health crises, where ideally, data should inform and guide policy responses. As the opioid crisis continues to evolve, this study underscores the importance of how data is interpreted and used in policy formulation. Moreover, it paves the way for future investigations into other policy areas where data may be underutilized or overlooked, advocating for a broader and more integrated approach to evidence-based policy making. 

You can read the original article in Policy Studies Journal at

DeLeo, Rob A. and Alex Duarte. 2022. “Does Data Drive Policymaking? A Multiple Streams Perspective on the Relationship Between Indicators and Agenda Setting.” Policy Studies Journal, 50(3): 701-724. https://doi.org/10.1111/psj.12419

About the Authors

Rob A. DeLeo is an Associate Professor of Public Policy at Bentley University. A policy process scholar by training, Rob’s work examines policy change in anticipation of emerging hazards, including climate change, novel diseases, and other slow onset events. His research has appeared in Policy Studies Journal, Public Administration Review, Policy & Politics, PNAS Nexus, Publius, Review of Policy Research, Natural Hazards Review as well as various other peer-reviewed journals and edited volumes. Rob’s work has been funded by the National Science Foundation, the National Institutes of Health, and various academic and private organizations. Rob previously held a visiting fellowship at Harvard University’s Kennedy School of Government and is a founding member of the Risk & Social Policy Working Group, an interdisciplinary team of scholars examining the relationship between risk messaging and individual behavior during the COVID-19 pandemic. He was the 2021 co-recipient of the American Political Science Association’s Theodore Lowi Award for the best article written in Policy Studies Journal.

Alex Duarte is a doctoral student at the Heller School for Social Policy. Alex graduated from Bentley University in 2019 and received a dual bachelor degree in public policy and business studies. During his time at Bentley, Alex’s research focused on policy indicators found within the substance abuse policy domain. Alex has also worked at the Peace Corps Headquarters in Washington DC and Project Weber, a Rhode Island-based harm reduction center for male and transgender sex workers.