State public health departments are on the front lines of providing effective responses to challenging problems. To be successful in this, accurate information about which activities are supported by relevant evidence must be available and used by decision makers. The extent to which this occurs is determined by a complex interplay of organizational structure, capacity, culture and priorities. Correcting any of these can be expensive, time-consuming, and risk unintended negative consequences. Thus, together with our colleagues at the Prevention Research Center at the University of Washington, we used an advanced computational simulation model to identify ways that state public health departments can make changes that increase their effectiveness.
State public health departments play an essential role in responding to a myriad of problems, from the ongoing opioid crisis to chronic diseases like diabetes. Recently, however, they have faced increasing challenges both in terms of the scale of the problems they face and the politicization of their work; this was particularly highlighted by the recent “stress test” of the COVID-19 pandemic.
As the United States works to invest in and support critical public health infrastructure to meet current and future challenges, there are opportunities to reexamine how such departments are structured and managed. Empirical evidence from the last decade shows considerable room for improvement in the allocation of resources due to what we call ‘misperformance’, i.e. discontinuing activities whose effectiveness is supported by evidence or continuing activities that are not. In a study recently published in the American Journal of Preventive Medicine, we explore why this may be happening and how instances of maladministration can be significantly reduced as part of rebuilding our nation’s public health capacity.
Research by us and others shows that premature termination of evidence-based activities is mainly due to lack of funding. Overall funding is largely outside the control of public health officials in the short to medium term. The reasons underlying the continuation of ineffective programs are less clear and are the central focus of our new study. Cutting out inefficient activities can free up space in budgets for things that have a positive impact and make public health more effective.
We developed a computational simulation of a representative public health department, examining how organizational structure, training, information sharing, and leadership practices shape decision-making about which programs to pursue. This animation illustrates the computational model we use and its main findings:
Based on the computational simulation results, there is little motivation to invest in evidence-based assessment training or collaborative communication strategies beyond the levels currently found in health departments. However, a large increase in the effectiveness of active programs and interventions can be achieved by changing the way management makes decisions about continuation. Most of this gain comes from simply removing the duration of the intervention from consideration during the decision-making process. That is, apart from other considerations, there is a tendency to continue programs that have been active for longer based on an implicit or explicit assumption that this in itself is evidence of effectiveness. Instead, it would be helpful for management to always look at interventions with “fresh eyes” when deciding whether to continue them.
Fortunately, there is a wide range of learning resources that can help leaders avoid the “sunk cost fallacy” when making decisions that lead to ineffective organizational momentum. Based on our research, we recommend that health departments devote time and resources to this relatively easy and potentially high-impact fix.
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