Refining Knowledge: How Data Categorization Efforts Contribute to the Making of An Opioid Overdose Crisis

• In Event: 30669 - Knowledge #1: Data, Risk, and Knowledge in Health Policy

Abstract

What is a knowledge crisis? How does it revolve around an “actual” public crisis? This paper examines how the Centers for Disease Control and Prevention (CDC) and related government agencies categorize, collect, and interpret drug-related public health data from 1982 to 2023. Based on 659 documents from CDC Archives, 265 CDC Morbidity and Mortality Weekly Reports (MMWR), 69 Data Briefs from the National Center for Health Statistics (NCHS), and current publicly available information on the CDC website, it shows how technological innovations and infrastructural changes, such as the Mortality Medical Indexing, Classification, and Retrieval System (MICAR) and the Prescription Behavior Surveillance System (PBSS), improved the accuracy and efficiency of collecting nationally representative data on drug use. On the other hand, the logic and mechanism in generating quantifiable data – agglomeration and counting – resonate with the data collected – mortality cases and emergency department visits – to reinforce a focus on types of drugs causing overdose death. In turn, they contributed to the emphasis on quick response in recent programs, such as the Overdose Data to Action (OD2A). Complementing sociological and STS studies on knowledge crisis with the Foucauldian concept of problematization, this paper offers a conceptual framework for understanding how data categories, public policies, and government agencies shape the outlook of a crisis and transform expertise. By presenting the opioid crisis as an anti-crisis – a knowledge crisis demarcated and designated by existing knowledge networks instead of driven by epistemic contests, it shows how moments of truth – collective recognition of a social problem – are conditioned by available data telling the truth.

Author

• Xinyan Wu, The University of Texas Medical Branch