To ensure fair and impartial distribution of the $1.07 billion that was awarded to Pennsylvania as part of 2021’s massive settlement with opioid manufacturers and distributors, a team of interdisciplinary researchers from Penn State worked with counties across the commonwealth to develop the formula by which funds are being distributed. In a new publication in The Milbank Quarterly, the researchers described the process they followed to select data for decision-making, develop a formula that addressed the needs of all counties, and promote buy-in among counties. The researchers also described factors that other groups should consider when developing similar formulas and discussed lessons learned.
Overdoses have killed more than 900,000 people in the United States since 1999, according to the United States Centers for Disease Control. Eighty-two percent of those deaths were related to synthetic opioids, which research shows have been over-prescribed for pain management. Multiple legal settlements showed that dishonest and illegal practices by companies that make and distribute synthetic opioids fueled the opioid epidemic.
In 2021, four pharmaceutical companies and three distributors reached a $21 billion settlement with 46 states’ Attorneys General. These funds were designated to address the crisis to which the companies’ actions contributed. Pennsylvania, which was hit particularly hard by the opioid epidemic, was awarded $1.07 billion to be paid over 18 years. The Penn State team collaborated with all counties across Pennsylvania to decide how to fairly distribute the money.
Seventy percent of the funds in the settlement are being distributed directly to Pennsylvania’s counties. The settlement stipulates that funds must be used for the abatement of the opioid problem, but each locality has discretion over how funds are spent within their jurisdiction. Legally, the funds may go to a wide range of programs including prevention efforts, treatment and recovery programs and more.
“Pennsylvania has experienced devastating impacts from the opioid epidemic including high rates of mortality and overdoses, strain on the criminal justice system, and burdening of social services,” said Danielle Rhubart, assistant professor of biobehavioral health and demography and lead author on this publication. “The consequences were also very personal. Addiction can affect families along dimensions of food and housing security, employment stability, health and well-being, and more.
“It was critically important that each county get a fair share of money so that they could begin to address this tragedy."
The counties were required to drop any other lawsuits they had filed against the defendants in order to receive money from the settlement. This incentivized counties to participate, and the distribution formula created for this settlement is intended to apply to any future settlements against other defendants.
The researchers stressed that data used in this type of decision-making needs to be publicly available for all counties. Using data that is not captured in every county could mean that the needs of some stakeholders are left underestimated. Similarly, some proprietary or private data — like Medicare data — may contain useful information but could take too much time to acquire and reduce transparency and reproducibility. For these reasons, the researchers recommend that decision-makers in similar situations use publicly available data that cover all affected people and communities.
Any formula used for distributing funds had to be sensitive to stakeholder opinions and needs, according to the researchers. Their first formula relied heavily on overdose-death statistics. That formula was less favorable to some counties because it did not account for costs related to overdoses where the patient may not have died. In response, the researchers incorporated data on the amount of naloxone distributed in each county and the number of overdose-related hospitalizations.
Additionally, the researchers found that they had to consider how rural counties would fair in an allocation formula relative to more populous counties. For the smallest counties, the initial formula would have generated allocations of just a few hundred thousand dollars over the course of 18 years. Even for a small county, this amount of money would likely be insufficient to do any meaningful work to abate the opioid problem. For that reason, the final allocation formula ensured that every county received a minimum amount of money, ensuring that smaller rural counties receive sufficient funds to expand prevention and treatment in their communities.
Once the adjustments were made, all counties agreed to the proposed funding model.
“The situation is complicated, so our job was to be impartial and to develop as simple a model as possible using transparent data,” Rhubart explained. “This was necessary in order to promote buy-in to the model in a timely manner. I hope that other groups working on a model like this can learn from our experience.”
The interdisciplinary team
Dennis Scanlon, distinguished professor of health policy and administration and director of the Center for Health Care and Policy Research, had worked with Pennsylvania’s government before on issues of health policy. He helped construct the team of researchers that included the expertise needed to develop the model.
“This project served an important public purpose while relying on the expertise and impartiality of a team of researchers at Penn State, Pennsylvania's land-grant institution,” said Scanlon. “In service of this important mission, the team worked quickly and directly with the counties and municipalities, their legal counsels, and the Pennsylvania Attorney General's Office. Everyone on the team understood the importance of allocating this huge sum of money fairly, so that Pennsylvania can reverse the tide of the opioid epidemic.”
Members of the research team included Rhubart; Scanlon; Qiushi Chen, assistant professor of industrial and manufacturing engineering; Glenn Sterner, assistant professor of criminal justice; Rob Newton, graduate student of industrial and manufacturing engineering; and Bethany Shaw, assistant director of data accelerator compliance at Penn State’s Evidence-to-Impact Collaborative.