Redefining success in fighting addiction

Getting people who use drugs to abstain has long been the goal for successful treatment of substance use disorder.

But that’s changing.

When it comes to addiction to stimulants like cocaine or methamphetamines, reduced use can make a difference in the health of people with the disorder, even if they don’t achieve abstinence, a new federally funded study shows.

Reducing stimulant use by as little as one day a month — such as going from five days a month to between one and four days — was linked to lower levels of drug craving, depression and other challenges compared with no change in drug use, according to an analysis published Wednesday in the journal Addiction.

How so? Scientists at the Johns Hopkins Bloomberg School of Public Health and the National Institute on Drug Abuse, which funded the study, looked at data from 13 clinical trials that examined treatment for stimulant use disorders involving methamphetamine and cocaine.

Why it matters: There are no licensed treatments for stimulant addiction — at a time when an estimated 110,000 people died of a drug overdose in the U.S. in 2022, a record high.

While the illicit opioid fentanyl has driven most deaths, at least one stimulant was detected in just over 57 percent of deaths, according to the CDC.

This is where we explore the ideas and innovators shaping health care.

Could swallowing a vibrating capsule be the next weight loss treatment? The device nearly halved food consumption for pigs but experts are not sure it will work for people, Science reports.

Share any thoughts, news, tips and feedback with Carmen Paun at [email protected], Daniel Payne at [email protected], Ruth Reader at [email protected] or Erin Schumaker at [email protected].

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The Food and Drug Administration, the nation’s regulator of food, medical devices and medicines, is the obvious candidate to lead in setting the rules for AI in health care.

But it’s going to need help.

That’s what FDA Commissioner Robert Califf said at the Consumer Electronic Show in Las Vegas on Wednesday.

Building a system capable of monitoring the algorithms that undergird AI products as they evolve would require doubling the agency’s size.

But Califf doesn’t foresee that and said he’s working to enlist a “community of entities” to assess and certify algorithms.

“There’s a lot at stake as to whether we can develop societal accountability for this,” he said.

What’s next? Califf said the certification process should aim to root out bias in algorithms in all its potential forms involving race, sex, geography and wealth.

Even so: Califf’s not a doomsayer. He foresees AI shedding light on deficiencies in the health care system and helping to fix them.

“One of the greatest opportunities in AI is to get the gatekeepers out of the way right now who are suppressing a lot of information that would show the problems,” he said.

So-called social determinants — from employment to housing to a lack of transportation — are linked to significant differences in health outcomes.

Researchers say in a new study that AI could help doctors identify the risks and counteract the danger they pose.

How so? AI systems can take information from doctors’ notes and turn it into structured data that helps determine who needs help with basic needs, said Dr. Danielle Bitterman, a radiation oncologist at Dana-Farber Cancer Institute who was a study author.

The research published today in npj Digital Medicine relied on a specialized language model that could identify nearly 94 percent of patients in situations that negatively impacted their health, the authors said. In comparison, current diagnostic codes included that information for about 2 percent of patients.

By reviewing the data, doctors could connect their at-risk patients to resources, the researchers suggested.

Without having structured data, trying to find information can often be “a little bit of a needle-in-a-haystack” search, said Bitterman.

Even so: The tools could perpetuate or exacerbate bias in the health system without proper oversight, Bitterman said.

By working to fine-tune the model to find social determinants of health, researchers are getting a better sense of how bias is put into systems — and perhaps how to better address it, she said.