Friday, August 11, 2017

Can Technology Help?

State and local governments collect a lot of health data, but as it turns out, there are many roadblocks to putting that data to its highest and best use. Building a bridge, however, could create the potential for its use in battling the U.S. opioid epidemic, which is taking its toll in every corner of the country, across all ages and socioeconomic backgrounds. Just how could digging a little deeper into this data help to uncover the hidden facets of this epidemic?

Mining for Gold

Law enforcement, the healthcare sector, and human services collect a wide assortment of data when it comes to opioids, tracking sales through prescription drug monitoring programs, post-addiction treatment, overdoses, and deaths. While this data sometimes helps identify doctor shopping and over-prescribing, it does little to thwart addiction. Typically, little information is shared with other entities, or nationally, except as required by law. However in a few states, this data is being used for a higher purpose – compiled into a richer picture of the crisis in the hopes of taking control via a proactive, not reactive approach to the crisis – and neighboring states are taking notice.

Imitation is the Highest Form of Flattery


In Indiana, the state recently rolled out an opioid ‘crime dashboard,’ compiling data on overdoses from area health professionals and forensic labs. Used to deploy law enforcement, it is helping deliver aid to the areas hardest hit, ensuring enough anti-opioid prescriptions on-hand to counter the effects of the drugs and save lives. Massachusetts is now engaging in a similar attempt with their own available data.

Stepping Things Up a Notch


Bridging the divide between states, technological firms are also stepping-in – and stepping things up in the communications arena, to join forces nationwide. Meeting in Portland for a panel discussion, companies such as Massachusetts-based company Biobot Labs, whose human waste analytics can determine where drugs are being abused in particular areas, are teaming-up with others such as Chicago-based Triggr, designer of data-driven, personalized addiction-recovery systems that combine a mobile app with human interaction to identify and thwart relapse, and looking to ways their diverse skill and data sets can contribute to fighting the epidemic. The end goal? Making the shift from thwarting fatal overdoses, to that of early detection and overdose prevention.

Tearing Down the Walls


As history has shown in this epidemic, simply collecting and storing relevant data is not enough. Data must be better analyzed and integrated to produce positive results. Future collaborations such as these will be integral in making impactful decisions and better allocating resources. Multi-stakeholder organizations – a joint committee or joint taskforce – will be key, as no network yet exists between state and local governments. Law enforcement, alongside the healthcare and IT arena must work together to breakdown current barriers, unifying – not isolating – via a cohesive strategy. Though this will be no small task, the sharing of such data on a national level is crucial. If the trend continues, tens-of-thousands of American lives could depend on it in the coming years.
About the Author: Anthony Sambucini is a founding principal and the Chief Executive Officer of ANS Solutions. Anthony specializes in bridging the goals of clinical innovation and business strategy that have helped propel ANS Solutions into a national leader in Pharmacotherapy Review Services for workers’ comp insurers and ANS Pharmacotherapy Review Program is the most advanced, results-oriented drug utilization review program in the industry. As a consultant to insurance carriers and attorneys, Anthony customizes services based on the particular needs of the client and oversees all activities related to business development and company operations. For more information about ANS Solutions visit http://ans-solutions.com/.
Original content posted on http://ans-solutions.com/can-technology-help/

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