Swimming Upstream: Thoughts on the Economics of Preventive Healthcare

Rob Abbott, Chief Executive Officer, ISPOR

Nearly 300 years ago, writing in the Pennsylvania Gazette, Benjamin Franklin coined the phrase “an ounce of prevention is worth a pound of cure.” While his interest at the time was in fire prevention, this type of “upstream” thinking has been widely applied to several other fields, including healthcare. The basic premise is simple, although not necessarily easy: It’s better and less costly to stop a problem from happening (prevention) than to try and fix it after it’s already occurred (cure).

Whenever I’m asked about how we might achieve genuine transformation in healthcare, especially in the United States, I like to highlight 3 things: (1) the need to take a systems-level view of healthcare and avoid focusing on one thing (drug pricing comes to mind), (2) the need to understand the history of how healthcare has evolved and the role of private and public interests in delivering care, and (3) the need to shift our mental model of healthcare from treating people when they become sick to preventing sickness or disability in the first place.

This issue of Value & Outcomes Spotlight focuses very squarely on the third leg of the metaphorical stool I’ve just described. And I couldn’t be happier. In the face of an aging population and shrinking government budgets, it’s absolutely critical that we think creatively and strategically about how we set people on a trajectory of healthy living, keep them as healthy as possible for as long as possible, and target expensive treatment interventions for those who most need them. It’s not an either/or proposition; we need both prevention and treatment. We just need to get the balance right.

Health economics and outcomes research has much to offer in the quest to better balance resources—and scale up preventive measures. That doesn’t mean it will be easy. 

Proving that investments in prevention reduce long-term costs involves demonstrating that those interventions (screenings, vaccinations, counseling, and so on) translate into fewer hospital visits and chronic disease treatments. This can be done through longitudinal studies and cohort comparisons in which large groups (cohorts) are studied over many years, and comparisons are drawn between those receiving preventive care and similar groups not receiving such care. Statistical models are typically an important part of such studies because they allow researchers to adjust for factors such as participant age, socioeconomic status, and preexisting conditions to isolate the effect of prevention. Proving causality, however, is still hard because cost savings often don’t appear until years after the intervention, even advanced statistical analysis can’t control for all factors to pinpoint prevention’s impact, and the very meaning of “prevention” can be confounding (Is it clinical, lifestyle, or both?).

Some preventive actions, however, have proven extraordinarily cost-effective. Vaccines, for example, show lower disease incidence and associated treatment costs. Similarly, research has demonstrated the effectiveness of cancer screening, especially colonoscopies and mammograms, for detecting disease early enough to reduce or avoid late-stage, expensive treatment.

At ISPOR’s recent European conference in Glasgow, I spoke about smoking cessation in Scotland as an extraordinary example of preventive care. This example stands out because it ticks so many boxes on our mental “value for money” checklist:

• By investing in smoking cessation support, Scotland reduced the number of people who developed costly, long-term conditions such as heart disease, cancer, stroke, and lung disease. This, in turn, avoided years of hospital care and medication.
  

• The deployment of strong tobacco control measures in Scotland, such as free cessation services and smoke-free public spaces, led to an immediate decrease in hospital admissions for heart attacks and asthma.
  

• Smoking rates in Scotland were highest in the most resource-deprived communities. Scotland intentionally targeted cessation support in these places, helping to narrow the gap between rich and poor— something that treatment-focused care rarely achieves.
  

• Notwithstanding the up-front investment, the money spent on cessation was significantly less than the estimated cost of treating smoking-related diseases.

Ultimately, a mix of approaches is needed to build a strong, evidence-based case that investing in prevention yields significant long-term financial benefits both for individuals and the healthcare system at large. In general, though, as the papers in this issue of Value & Outcomes Spotlight make clear, targeted investments in healthcare prevention can lower direct healthcare costs (fewer hospitalizations), boost workforce productivity (less absenteeism), increase gross domestic product, and free up resources for other sectors of the economy. That’s a pretty strong economic argument.

The economic argument, while persuasive, is instrumental in nature. Happily, there is more to investing in prevention, and it strikes at the heart of value-based care, or a more thoughtful, holistic approach to health and healthcare decision making. If we prioritize primary care, invest meaningfully in data and technology, address social determinants of health, and engage patients as partners, we have the potential to author a paradigm shift in our collective thinking about health and healthcare.

Many current tools and evaluation methods are insufficient to drive the kind and level of change I'm advocating. We need to develop and prioritize metrics that are outcome-focused and aligned across payers.

A key step forward is shifting incentives from rewarding volume of services (the current fee-for-service model in many countries) to rewarding positive health outcomes. This step is absolutely fundamental. If we can achieve this, we’ll be that much closer to realizing the promise of a proactive healthcare system focused on long-term wellness rather than reactive (and expensive) treatment of advanced illness. I’m personally committed to exploring the efficacy of the argument I’m making here as part of a potential revisioning of healthcare in the United States.

Of course, everything I’ve suggested above is predicated on the availability of tools and methods that allow us to measure the impact of preventive medicine. Many current tools and evaluation methods (incremental cost-effectiveness ratio, quality-adjusted life years, disability-adjusted life years, electronic health records, insurance claims data, manual chart reviews, and so on) are insufficient to drive the kind and level of change I’m advocating. Moving forward, we need to develop and prioritize metrics that are outcome-focused and aligned across payers.

At the same time, we need new evaluation frameworks and modeling techniques to assess the long-term, cumulative effects of prevention. Technologies such as big data, artificial intelligence, genomics, and wearable devices have much to offer researchers with respect to personalized health monitoring and more precise, data-driven measurement of preventive care impact.

ISPOR is already leaning into the articulation of these new ideas, tools and methods, and as your CEO, I pledge that we will continue to advance this “upstream” work. This is new territory for health economists, but I’m excited about the possibilities we can discover together.