Missing Data Masks Scale of Opioid Epidemic

The U.S. opioid epidemic has exacted an enormous human toll and economic burden. It is important that the epidemic is tracked as accurately as possible so that available resources can be allocated effectively, according to authors of a study recently published in the Journal of American Medical Informatics Association.

The study was conducted by Andrew J. Boslett, Alina Denham and  Elaine L. Hill of the Department of Public Health Sciences, University of Rochester School of Medicine and Dentistry, Rochester, New York, and Meredith C. B. Adams, Department of Anesthesiology, Wake Forest Baptist Health, Winston-Salem, North Carolina.

About 20% of drug overdoses in the U.S. mortality data is missing information on specific drugs involved, thus impacting understanding of the scale of the epidemic, according to the study authors. They wanted to examine whether individual, geographic, and economic phenotypes predict missing data on specific drug involvement in overdose deaths, manifesting inequities in overdose mortality data, which is a key data source used in measuring the opioid epidemic.

They combined national data sources (mortality, demographic, economic, and geographic) from 2014–2016 in a multi-method analysis of missing drug classification in the overdose mortality records (as defined by the use of ICD-10 T50.9 on death certificates). They examined individual disparities in decedent-level multivariate logistic regression models, geographic disparities in spatial analysis (heat maps), and economic disparities in a combination of temporal trend analyses (descriptive statistics) and both decedent- and county-level multivariate logistic regression models.

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Results of the study found higher rates of missing information on drug involvement in fatal overdoses for decedents of female gender, White race, non-Hispanic ethnicity, with college education, age between 30–59, married, and those from poorer counties. Racial and ethnic minorities are less likely to have an unclassified drug overdose: black decedents are 17.6%, Asians 20.9%, American Indians 18.8% less likely than white decedents, and Hispanic decedents are 15.4% less likely than non-Hispanic decedents to have missing drug information.

Also, there are striking differences both across and within states: missing drug information is particularly common in Alabama, Arkansas, Indiana, Louisiana, Mississippi, Missouri, Pennsylvania, Delaware, Montana, and Nebraska.

Despite the fact that unclassified drug overdose death rates have reduced over time, gaps persist between the richest and poorest counties. Decedents from higher-income counties are less likely to have an unclassified drug overdose.

To improve data collection of the opioid epidemic, we must enhance understanding of data collection itself, extraction challenges and missing data patterns, the authors say. Healthcare executives must be aware of the missing patterns of information in drug overdoses and understand how advanced informatics methods and modeling will play a role in the emerging challenges of mining and analyzing opioid-related data.

Their findings on health inequities in missing data on specific drug involvement can inform more targeted interventions and an associated allocation of resources across communities and geographies, they say.