Four Ways to Conceptualize and Study Policy in Implementation Science Research

Jonathan Purtle, DrPH, MSc
New York University

ABSTRACT:
This presentation will offer a typology of four ways to conceptualize policy in implementation science research: 1) Policy as something to adopt, 2) Policy as something to implement, 3) Policy as context to understand, and 4) Policy as strategy to use. Examples will be provided of studies that have conceptualized policy in these different ways in the area of behavioral health.

Bridging policy research and implementation science

Beth McGinty, PhD, MS
Weill Cornell Medicine

ABSTRACT:
Policy implementation is a key but often-ignored aspect of policy effectiveness. Public policy research typically considers the effects of having versus not having a policy on outcomes, without considering whether and how the policy was implemented – even though the effects of policies on their intended outcome depend upon degree of implementation. Experimental approaches to studying policy dissemination and implementation are challenging, given that policies are difficult to randomly assign, but not impossible. Natural experiments in policy implementation abound, as states, localities, and organizations consider, adopt, and implement – with varying degrees of implementation success, and intensity – a range of policies over time. Rigorous nonexperimental methods for studying policy dissemination and implementation in these types of natural experiments are critical, but methodological advances are needed. This presentation will motivate the importance of studying policy implementation, provide examples of current approaches, and discuss promising future directions.

Reducing Opioid Use Disorder and Overdose in the United States: Model Development and Policy Analysis

Mohammad Jalali, PhD
Harvard University

Wayne Wakeland, PhD
Portland State University

ABSTRACT:
The opioid crisis is one of the most pressing public health issues in the U.S. today. Opioid overdoses are the proverbial “tip of the iceberg,” arising within a complex adaptive system characterized by rapidly changing dynamics combined with significant time lags and large uncertainties in the data. System dynamics modeling is a critical tool to guide policymaking and avoid unintended consequences. We developed a simulation model of the opioid system, spanning from medical use of prescription opioids to opioid misuse and heroin use, use disorder, treatment, and remission. The model aims to help policymakers address the crisis by aiding in policy analysis and decision-making under uncertainty. We project the effects of several policies to reduce opioid use disorder and overdose, and analyze intended and unintended effects of the policies over the next 10 years. Model simulations suggest most policies implemented on their own will achieve only modest reduction in either fatal overdoses or prevalence of OUD.