Over the past two decades, healthcare delivery in the United States has been transformed by technology. From remote monitoring tools that detect cardiac events in real time to digital platforms that expand access to mental health care, technological innovation in healthcare has improved efficiency, saved money, and increased access to care. As the application of technology extends into harm reduction, it offers the same promise of improved reach and effectiveness of interventions to combat the overdose crisis.
However, to maximize this promise, it’s important to remove barriers to innovation and adoption. In practice, this includes scaling tools like drug-checking technologies, digital overdose-prevention platforms, and emerging artificial intelligence (AI)-based prediction systems that can detect risk earlier and support faster, more targeted responses.
These technologies are not magic-bullet solutions nor a substitute for structural reforms that address the underlying drivers of drug dependence, overdose risk, poverty, housing insecurity, and limited access to care. What they can do, however, is help shift overdose prevention and response away from approaches that rely primarily on arrests, seizures, and drug interdiction, and toward more pragmatic and effective harm-reduction strategies. These approaches better reflect how risk and drug-related harms are actually experienced and managed in people’s everyday lives.
A brief history of harm reduction
Born from a philosophical position of steadfast pragmatism, “harm reduction” is a framework that accommodates innovation in addressing the overdose crisis. Approaches include syringe service programs, which provide sterile injection to reduce the transmission of HIV, hepatitis C, and other bloodborne infections while serving as points of contact for healthcare, drug testing, and treatment referrals. They also include overdose prevention centers, which offer supervised environments where individuals can use previously obtained substances under medical oversight, allowing for immediate intervention in the event of an overdose and connection to health and social services. Naloxone distribution is another core component, involving the widespread availability of a medication that reverses opioid overdoses in community settings. Collectively, these services are designed to and are effective in preventing avoidable deaths, reducing strain on emergency systems, and maintaining engagement with individuals who are not reached by traditional healthcare models.
Federal efforts under the Great American Recovery Initiative emphasize coordinated recovery and treatment models, including partnerships with faith-based organizations, many of which prioritize abstinence-based approaches in their funding structures, program requirements, and outcome metrics. While effective for some individuals, this emphasis may unintentionally constrain the development of complementary harm-reduction interventions needed to reach populations not engaged in abstinence-based care. As state policymakers plan for the coming months and years, they will have access to a steady stream of opioid settlement funds that could be used to enable innovation in harm reduction and treatment. This moment creates space for a long-overdue question to be asked: What role might technology play in how we diversify, scale, and deliver care to those who need it most?
As technology begins to enter harm-reduction settings, it brings real potential to expand access and improve overdose response. But particularly in the drug harm-reduction space, uptake is shaped as much by trust as by technical performance. Many people who use drugs have learned, often through experience, to be cautious about systems that collect personal or behavioral data, especially when those systems overlap with policing or criminal justice. This pushes many away from programs or seeking care at all. Without clear limits on how information is used, even well-designed tools are likely to be ignored or avoided.
Drug-checking technology
In the 1920s, Americans didn’t stop drinking when alcohol was prohibited; they simply lost the ability to know what they were drinking. During Prohibition, people regularly purchased alcohol that was, in fact, industrial spirits adulterated with methanol or other toxic additives, sometimes indistinguishable by taste or smell. Thousands were poisoned or killed simply because they drank something fundamentally different from what they believed they had purchased. The danger lay not in intoxication itself, but in supply-side market volatility and a lack of transparency created by prohibition. This is the current reality for Americans who consume drugs from today’s unregulated drug markets. Drug-checking technologies offer a direct response to this volatility. Tools such as fentanyl and xylazine test strips, portable Fourier transform infrared (FTIR) spectrometers, and mail-in drug checking services allow people to identify what is actually present in their drug sample.
In New York City, a recent drug-checking pilot program operated within community harm-reduction centers, allowing trained technicians to test small samples voluntarily brought in by participants. Using various testing methods and laboratory confirmation, the program provided participants with real-time information about the contents of their drugs and connected them to harm-reduction education and services. Over its first two years of operation, analysis of more than 1,600 samples revealed widespread fentanyl contamination, including in drugs not typically associated with opioids. Crucially, as the testing program was located within an overdose prevention center, trained health professionals were then able to equip clients with actionable information based on participants’ real-world drug use, enabling them to make informed decisions about whether, how, and when to use, inherently reducing risk by allowing them to discard contaminated supplies, encouraging smaller doses, avoiding using alone, or ensuring they have Narcan—the antidote to an opioid overdose—when they use opioids.
At the state level, more advanced spectrometry tools also serve a broader public health function by detecting emerging trends in the toxic adulterants, like xylazine, that are present in the drug supply in near-real time. More dispersed approaches, such as mail-in drug-checking programs, can also assist in early identification of shifts in the wider drug supply while preserving individuals’ privacy and allowing states to issue targeted alerts to communities and service providers. This capacity for rapid surveillance is vastly different from traditional overdose data systems that often lag weeks or months behind trends on the ground.
As Amber Lashbaugh, a Georgetown University addiction policy graduate student and researcher, explains, most states still rely on ambulance call-out and toxicology reports that arrive long after harm has already occurred, limiting their ability to proactively protect people. In contrast, drug-checking programs use portable testing devices and rapid screening strips to analyze street drugs on-site, identify dangerous contaminants within minutes, and share this information with health officials and service providers. This allows services to issue timely warnings that can prevent overdoses and reduce avoidable emergency hospitalizations.
According to the Pew Research Center, the number of U.S. states allowing drug-checking has risen from just a handful in 2018 to 45 by 2024. Although the specifics vary among state programs, in practice, individuals and organizations can possess and distribute various forms of drug checking equipment (primarily rapid test strips). Despite this, legal and regulatory barriers continue to limit these programs’ ability to scale up. For example, many states maintain anti-drug paraphernalia laws that criminalize possession of drug-checking equipment in public, leaving its legality ambiguous and discouraging providers from offering these tools widely. These laws also dissuade people who use drugs from carrying take-home equipment in public spaces. Clarifying the legal status of drug checking services, supporting open data sharing between counties and states, encouraging technological innovation within this sector, and integrating these technologies into existing harm reduction services would all be relatively low-cost policy moves that could yield high returns when comparing the cost of overdose deaths and the cost of the fentanyl test strips themselves.
Digital overdose-prevention platforms
An estimated 69% of fatal overdoses occur when people are alone. This happens across both urban and rural communities, often in private homes or other unsupervised settings. These deaths are almost always preventable if Narcan is available, even if administered by untrained bystanders. This insight underpins the rationale for supervised consumption sites and overdose prevention centers, so rather than using alone, users can remain in the presence of trained professionals capable of addressing any potential complications from their use.
Digital overdose-prevention platforms have provided new ways to connect drug users with supervision and services that can save their lives in the event of overdose. From apps to telehealth services, newly emerging platforms range from “spotting” call-in services, in which trained operators stay on the line with individuals using drugs and can dispatch emergency help if needed, to smartphone apps that monitor vital signs or automatically trigger alerts when overdose symptoms emerge.
One example is SafeSpot, a 24/7 national overdose “spotting” hotline that connects people using drugs with trained operators ready to respond if the caller becomes unresponsive. To date, SafeSpot has supervised more than 32,000 use events, handled over 12,800 calls, and facilitated at least 33 overdose detections requiring emergency response. This is just one example of how virtual monitoring can reduce the risks associated with solitary drug use.
Even in jurisdictions that authorize in-person supervised consumption sites, practical and logistical barriers continue to prevent widespread access to facilities, such as disability, limited operating hours, geographic isolation, and transportation challenges. To address these barriers to physical supervised consumption spaces, Canada has encouraged the development of virtual supervised consumption services. Canada’s National Overdose Response Service (NORS), a peer-run community-based service, provides a model for how virtual supervised consumption could be implemented in the United States. Rather than functioning as a traditional emergency hotline, NORS is staffed by trained peers with lived experience in using drugs who remain on the line during drug use and coordinate emergency response only when needed, offering a low-threshold alternative for people who face barriers to accessing physical supervised consumption sites.
Complementing this, digital tools such as British Columbia’s Lifeguard App, launched by the Provincial Health Services Authority, allow users to initiate a timed virtual safety check before drug use, triggering an alert to emergency responders if the user does not respond in time. Beyond phone lines and apps, Canadian researchers and companies are also developing wearable overdose detection devices, such as a wrist-worn vital-sign monitor being created in partnership with Simon Fraser University and ODEN Health Solutions—a medical device company—that autonomously tracks physiological indicators of overdose and notifies emergency services when critical thresholds of overdose symptoms are crossed.
Program evaluations suggest that these virtual monitoring platforms can be effective not only in preventing overdose deaths but also in generating public savings by reducing avoidable emergency responses and hospitalizations (with savings estimated at around $1.53 – $15.28 per dollar spent on programs). At the same time, researchers note that these services raise unresolved legal and operational risks, including liability in cases of delayed response or device malfunction, as well as concerns about quality assurance and safety standards for these emerging technologies. In addition, many services rely on sensitive location, health, and drug-use data to coordinate emergency responses, creating ongoing risks to both service providers and users related to data security, informed consent, and data access by law enforcement or third parties. Without clear regulatory frameworks, licensing standards, and explicit protections for providers and users, these legal and privacy vulnerabilities may limit broader adoption of these potentially life-saving technologies. Strengthening liability safeguards, data governance rules, and confidentiality protections are therefore essential for digital harm reduction tools to be scaled up responsibly in the United States.
AI-assisted overdose prediction
While drug checking services and digital supervision platforms focus on reducing risk at the time of use, emerging AI systems may be able to anticipate overdose risk before it becomes fatal. Chicago, Los Angeles, and New York are among several U.S. jurisdictions that have already begun integrating machine learning and automated data processing into their overdose surveillance and response modelling. In practice, these systems combine multiple related datasets to model where emergency services, harm reduction providers, and drug treatment programs should focus for the greatest impact. Inputs typically include real-time emergency service call-out data, emergency department visits for overdose, medical examiner and toxicology reports, prescription drug monitoring program records, and hospital discharge data. These databases are updated far more frequently than traditional annual mortality statistics. Some models also incorporate drug-checking alerts, naloxone distribution records, wastewater analysis, and law enforcement seizure data to capture sudden changes in the drug supply, such as adulteration with dangerous contaminants like fentanyl or xylazine.
Once these data sets are combined, machine-learning techniques analyze them simultaneously to identify patterns and correlations that are not visible in isolation. This allows public health agencies to detect and forecast short-term overdose spikes, as well as identify neighbourhoods or populations at rapidly increasing risk. Rather than producing a single prediction, many of these systems generate dynamic risk scores or heat maps that can be updated daily to support operational decisions, such as where to deploy outreach teams and the selection of ambulance staging locations, where to extend supervised consumption hours or increase naloxone availability, when and where to issue targeted drug alerts, as well as helping health departments prioritize funding and staffing during periods of elevated risk.
In Canada, researchers at the University of Alberta have developed a machine learning model using anonymized health-system data from millions of residents that, in combination with personal data, can predict individual risk of future opioid overdose. The model draws on health system records, including treatment encounters for substance use, prescription histories, and co-occurring mental health conditions, and demonstrates strong prospective performance, with balanced accuracy ranging from 83 to 85 percent across multiple years.
Although these models are still relatively new, and outcome data from real-world implementation are not yet available, their significance lies in their ability to move beyond retrospective surveillance towards accurate current and future predictive modelling. If integrated thoughtfully, such tools could support clinicians and wider care teams to proactively engage patients before an overdose unfolds, again, provided they are paired with voluntary, supportive, and non-punitive interventions.
Finally, AI is also increasingly being embedded in wearable and sensor-based overdose detection technologies. Researchers at the University of Washington have developed and tested a wearable injector system that continuously monitors breathing and movement to detect signs of overdose. When signs appear and respiratory arrest is detected, the device automatically delivers naloxone to the wearer. The prototype integrates on-body sensors with a real-time detection algorithm and a commercially available injector platform, creating a closed-loop system that can intervene instantly without waiting for outside assistance or naloxone administration.
Despite the potential of AI technologies within this sector (which have been publicly recognised in recent statements by both the Department of Health and Human Services and the Centers for Disease Control and Prevention), experts have warned that these tools raise concerns about privacy, surveillance, data governance, and algorithmic bias, especially when public health data intersects with systems historically used by law enforcement and the wider criminal justice system. Without transparent safeguards in place and explicit protections against civilian data being repurposed for policing, the “predictive” promise of AI could deter engagement with services that use these technologies, or exacerbate inequities in who is targeted for care. For these technologies to fulfill their promise, a serious challenge for both public health systems and the companies creating these technologies will be building trust.
Looking to the future
The U.S. has routinely deployed new technologies to prevent heart attacks, manage diabetes, and predict infectious disease outbreaks. At the same time, the overdose crisis claims a comparably staggering number of lives annually, yet these tools have not been systematically integrated into the public health response with the same speed or coordination seen in other areas of medicine. The tools discussed in this article can allow us to detect risk earlier and respond more efficiently. However, policymakers must be willing to embrace experimentation, remove outdated legal and regulatory barriers, and align market incentives towards investment in this sector.
For drug-related deaths to continue along the post-pandemic downward trajectory, irrespective of changes in the drug supply, these technologies need to be integrated into an infrastructure of housing, mental health care, low-barrier drug treatment, and continued support for traditional, evidence-based harm reduction services.