Opioid Analytics
Using Data to Fight the South Bend-Elkhart Opioid Epidemic
By this time, the severity of the opioid epidemic in the United States is felt by most individuals through direct and indirect connections as it affects people of all race/ethnicities, ages, genders, and socioeconomic status. In 2016, over 42,000 people were killed by opioid-related overdoses, with 40% of those due to prescription painkillers. Indiana is noted for having inordinately high opioid prescription rates and drug overdose death rates. Varying degrees of culpability are shared by pharmaceutical companies, drug distributors, the FDA, prescribers, and patients, among other accountable parties. As there is still no sign of reduction in this epidemic, it is critical that communities take collaborative and coordinated approaches to counter its prevalence at every stage.
Following this imperative, Beacon Health System has taken steps to address the epidemic in the community that it serves. In the Fall of 2017, Beacon sponsored enFocus to collect and analyze primary and secondary data relating to the impact of the opioid epidemic in the community. enFocus’ goal was to use trends from the analysis to provide recommendations to Beacon and the community for a multifaceted approach in response to the local opioid epidemic.
enFocus began to develop a data-informed perspective of the local problem to accompany the anecdotal evidence and national trends that had been presented. Multiple state and local data sources were identified and integrated, enabling comparison of St. Joseph County to other Indiana counties in measures of opioid prescription rates and drug overdose death rates. enFocus then shifted its scope toward the community served by Beacon Health System, examining the records of approximately 450 opioid-related patient visits through Beacon in 2016. Approximately 44% of those visits were due to opioid abuse and dependence, while the other 56% occurred at the Emergency Department due to acute overdoses. Descriptive and predictive analyses revealed linkages between demographic characteristics, Medicaid beneficiaries, and geography.
To supplement the analysis, enFocus examined various strategies implemented in other communities in efforts to alleviate the burden of the opioid crisis. After rigorous evaluation, along with considerations of local feasibility and potential impact, enFocus presented recommendations regarding prescribing practices, medication assisted therapy, and harm reduction and prevention strategies, such as drug disposal, needle exchange, and abuse education programs. The analysis and recommendations were utilized as the cornerstone of a locally produced documentary on the local impact of the opioid epidemic that included testimonies from victims and those fighting for them. In October 2017, the documentary was showcased with enFocus’ analysis and recommendations report at a community plunge where over 60 local leaders from all sectors gathered to share perspectives and coordinate cohesive strategies to save lives and reduce opioid abuse.
“enFocus’ innovative abilities and use of big data helped us understand the community landscape and showed us how we could best respond to our community’s needs in a targeted way.”- Patty Willaert, Executive Director of Beacon Community Health.
Following enFocus’ work, Beacon immediately responded with education programming in local public high schools. Executive Director of Beacon Community Health, Patty Willaert explained that “with the research and analysis completed by enFocus we were confident in rolling out a new opioid prevention education program in the schools. We’ve had positive outcomes so far and are looking to expand it into Elkhart County next school year.”
enFocus’ engagement allowed Beacon to better understand the current state of the opioid epidemic in its surrounding community, while also providing insight that will continue to drive decision making for strategic interventions for at-risk populations.
You can see the full documentary, “Hidden in Plain Sight”, featuring enFocus below:
