Abstract for: Modeling opioid addiction treatment policies using system dynamics
Treatment of opioid addiction has historical employed an opioid drug called Methadone that is dispensed in liquid form at treatment facilities. Drawbacks to this treatment include social stigma and relatively high risk due to the pharmacological properties of methadone and also its side effects. A newer therapy uses another opioid drug called Buprenorphine, which is safer and has less social stigma because it can be prescribed and dispensed in tablet form. Policy makers have been cautious, however, and have place a cap on the number of patients that a physician can treat using Buprenorphine, leading to a concern that even though it is safer, people seeking treatment might not be able to locate a physician and access the treatment because of the cap. An SD model was developed to represent the flows of opioid abusers into and out of treatment with Buprenorphine, as well as the number of physicians certified to treat with Buprenorphine. Treatment is constrained by the cap and also by the amount of budget available for subsidizing treatment. The main finding is the treatment budget is by far the most influential policy variable, and that changing the cap would probably not make much difference.