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Managing Marijuana: the Role of Data-DrivenRegulationColorado's robust system for tracking the drug and its effects provides a glimpse of abetter system of controls.

BY: Stephen Goldsmith | August 17, 2016

When Colorado voters approved a ballot measure to legalize the sale of recreational marijuana in 2014,state officials knew they would have to quickly develop a robust system to safely and securely control theflow of the drug across the state, and they managed to do just that with the help of advanced tracking anddata analytics. What Colorado is doing provides an impressive example of an emerging, more effectiveregulation model.

To deal with the consequences of marijuana's legalization, Gov. John Hickenlooper appointed AndrewFreedman as director of marijuana coordination, and the legislature created the Marijuana EnforcementDivision (MED) in the state's Department of Revenue. MED drew on the state's experience with itspreexisting medical marijuana regulations, examining what had worked previously to regulate and inventorycontrolled substances.

The widespread legal availability of marijuana and marijuana-infused products, however, presented a host ofnew concerns for Colorado, with those surrounding public health and safety first and foremost. The stateestablished a comprehensive set of goals surrounding health and safety concerns, analyzed the gaps in itsexisting data, and devised a plan to better track and regulate marijuana.

To begin with, the state needed a way to track plants from seed to sale. MED contracted with Franwell, aFlorida-based company, to create a Colorado-specific version of its Marijuana Enforcement TrackingReporting Compliance (Metrc) system. The state requires growers to track each plant with a unique radiofrequency identification tag. The RFID tags allow the plants to be inventoried more quickly without directcontact, and they create data at each step of the supply chain as plants move from growers to shippers tofinal packaging.

The RFID tags, like the sensors that are becoming ubiquitous in the emerging economy of connecteddevices, build regulatory intelligence directly into the regulated object, streamlining enforcement across theboard. The tracking system, for example, can automatically flag facilities that are producing substantiallyless marijuana than expected based on the outputs of comparable growers, which allows state employees tomore easily identify potential illegal diversion. And because the state is able to track the origins of anyproduct, it can easily issue public recalls for specific batches or growers if regulators discover traces ofpotentially harmful pesticides.

This system of constant, real-time tracking allowed Colorado to shift away from an older regulatory model inwhich governments must depend on slow bureaucratic procedures for permitting and licensing. Rather thansimply hoping that procedural factors would prevent noncompliance, the state can respond to problems asthey arise, which increases accountability and allows for better-informed enforcement.

The Colorado Department of Public Health and Environment, for example, analyzed hospital-visit data andfound that marijuana-related visits had tripled after commercialization and that poison control calls had

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doubled. Around the same time, MED noticed that marijuana-infused edibles were comprising significantlymore of the market than expected — fully 50 percent, according to Freeman. As MED discovered, the twowere correlated: Many of the hospital visits and poison-control calls stemmed from a lack of dosinginformation or packaging safeguards.

MED quickly intervened, adopting new requirements that included childproofing edibles and clearly markingdoses on the edibles' packaging. These changes have helped lower the instances of unintentional exposureto edible marijuana products. Colorado has hired a full-time analyst dedicated to deriving similar insightsfrom these new flows of marijuana data.

Whatever one might think of the advisability of legalizing marijuana, there's much to be learned fromColorado's experience in data-driven regulation. While many of the practices Colorado is pioneering can beadopted by other states that may be considering legalizing marijuana, they also could help to broadlyimprove regulatory systems across all levels of government. Colorado is demonstrating how data-drivenregulatory models can enable governments to quickly understand the realities of a market and holdbusinesses accountable — ultimately resulting in stronger, more effective consumer protections.

This article was printed from: http://www.governing.com/blogs/bfc/gov-colorado-data-driven-marijuana-regulation.html

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