Sedated in San Diego: Lessons from reporting on opioid addiction

Had I done this project diving into opioid addiction in San Diego County 15 years ago, I probably would have gone to communities like downtown San Diego, City Heights or National City. For years, those urban communities with large low-income and diverse populations were seen as the core of the county’s addiction problem.

But that’s not where the reporting took me. Instead, I met Mark Gagarin in Poway, a relatively affluent community in northern San Diego County. It was at Poway High School that the budding baseball star began experimenting with drugs and alcohol. Eventually, Mark dropped out of high school and for years struggled with addiction, including heroin.

During the last few years of his addiction he was using a Monday-to-Sunday pill case to keep track of drug cocktails that included painkillers like Vicodin and muscle relaxants. Chief among them was the powerful opioid OxyContin.

Aaron Rubin, also a Poway High grad, suffered a devastating overdose from OxyContin in 2005. The ensuing stroke left him a quadriplegic. Today, Aaron and his mom, Sherrie, visit schools sharing their story and the danger of opioids. Mark, now in recovery, has spent years making up for lost time, getting his GED and starting college.

Their stories were key to a reporting project that aimed to blend real people's stories with hard data to understand opioid addiction in San Diego County. The hope was to move the conversation from stereotypes towards a real understanding of the communities and individuals afflicted by addiction.

Here are some key lessons I learned during this project:

Don’t make assumptions

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Wounded by Tanya Momi

One of the goals of this project was to challenge assumptions about drug addiction in San Diego. As a long-time resident of the county, I had my own ideas about where the addiction hotspots might be.

However, in talking to individuals on the ground — health care specialists such as the director of the county’s behavioral health services and law enforcement officials — communities that I had pegged as potential hotspots were never mentioned.

Those experts were also able to react to the data and say when the numbers showed opioid deaths in unexpected places. Even if those conversations never make it into a story, they provided a valuable smell test for the direction the reporting was taking me.

I also fact-checked those assumptions to see how the geography of addiction might have changed over time. For example, four ZIP codes, including the three mentioned earlier in central San Diego, accounted for almost a third of opioid-related deaths in 2000. By 2015, those same communities accounted for less than one-sixth of deaths.

Get to know your local medical examiner

County medical examiner’s offices — or coroner’s offices depending on the local system — have a wealth of information. The data the local examiner’s office provided was central in showing how opioid deaths had increased in communities that had few, if any, opioid deaths in the early 2000s. Take the time to learn how your local agency works, what they track and which deaths they investigate. The annual reports they publish are a good place to start.

These experts also have a good understanding of current trends. Dr. Jonathan Lucas, the deputy medical examiner in San Diego, was one of the first experts to express concern to me about the growing number of fentanyl deaths in the county. Although the numbers were small compared to other opioids, he was able to provide context that showed it was worth looking into.

“(There’s) not only a trend in the number of deaths that are increasing due to fentanyl, but we’re seeing the emergence of these synthetic fentanyls or fentanyl analogs that people are synthesizing to act like fentanyl,” Lucas told me.

ZIP codes are your friend

Geography was a central element in this project. Picking the appropriate geographic level early on will save you a lot of time and energy.

When I was first analyzing the medical examiner’s data, I asked for a grouping of deaths by community. I was told that would take several weeks, if not months, of work from a separate county agency. And unlike my original non-geocoded data, it would not be free. When I modified my request to just add ZIP codes to the existing cases I got a spreadsheet within a couple of hours.

Organizing data by ZIP code is a quick, relatively low-tech way to provide geographic context to numbers. Unlike neighborhoods, they’re not subject to the opinions of residents and realtors. For a county like San Diego with large swaths of unincorporated land, finding boundaries for smaller communities can be nearly impossible. ZIP codes solve that problem.

Using ZIP codes also allowed us to create an interactive map where readers can search their own community for current and historical data about opioid addiction.

All of the above

Using an “all of the above” tack to data can help bolster results. One of the biggest challenges with taking a data-based look at opioid addiction is that there’s no master database. The addict population often overlaps with and blends into legitimate painkiller users.

Multiple independent data sources can bolster the analysis and provide a more nuanced picture of addiction. For example, one of the core findings of this project was that a large share of those addicted to opioids in San Diego were white men.

We saw that in the demographics of opioid deaths from the medical examiner’s office. We also saw the same pattern with data on opioid-related emergency room visits from the California Department of Public Health’s EpiCenter. Those two datasets also revealed unexpected details: Young people represented half of all ER visits but a relatively smaller share of deaths. That helped us provide more nuance about who was using and dying from opioids.

Last but not least, never let the data overshadow the human stories. Data can provide the engine for the project, but your reporting should be driven by the human sources and experts you interview.

If you have any questions about this story or are looking for more information on how we crafted our data requests feel free to email me at leocastaneda@inewsource.org.