More evidence that changes in smoking drop heath care costs quickly

Jim Lightwood and I have published a series of papers on the short-term (one year) medical care cost savings associated with drops in smoking.  The most recent of these showed an elasticity between changes in smoking and changes in medical care costs of 0.11.  What this means is that a 10% relative drop in smoking (about 1.5% drop in absolute prevalence) would lead to a 1% drop in aggregate health care costs the following year.  This has powerful policy implications because this is a big effect in terms of dollars, policy makers are looking for ways to lower medical costs, and this change is fast.

For example, I used this elasticity to estimate the immediate (one year) savings on state-by-state Medicaid expenditures of a 1% absolute drop in smoking prevalence; the total savings for all states totaled $2.6 billion (in 2017 dollars). Each state saved a median (interquartile range) of $25 million ($8 million to $35 million).

One limitation of most such analyses like this is that the same data are used to estimate the effects and make predictions.  Jim Lightwood, Steve Anderson and I have now published “Predictive validation and forecasts of short-term changes in healthcare expenditure associated with changes in smoking behavior in the United States” in PLOS ONE that substantially advances the validation of this estimate.  In this new paper we use the earlier model to predict subsequent changes in medical costs over the next few years and show that the 0.11 elasticity hold up.  This makes policy predictions using this elasticity even more reliable.

For example, a 5% relative drop in smoking prevalence (about a 0.87% reduction in absolute prevalence) combined with a 5% drop in consumption per remaining smoker (about 16 packs/year) would be followed by a $31.5 billion reduction in healthcare expenditure (in 2014 dollars).

Here is the abstract:

Objectives: Out-of-sample forecasts are used to evaluate the predictive adequacy of a previously published national model of the relationship between smoking behavior and real per capita health care expenditure using state level aggregate data. In the previously published analysis, the elasticities between changes in state adult current smoking prevalence and mean cigarette consumption per adult current smoker and healthcare expenditures were 0.118 and 0.108 This new analysis provides evidence that the model forecasts out-of-sample well.

Methods.  Out-of-sample predictive performance was used to find the best specification of trend variables and the best model to bridge a break in survey data used in the analysis. Monte-Carlo simulation was used to calculate forecast intervals for the effect of changes in smoking behavior on expected real per capita healthcare expenditures.

Results.  The model specification produced good-out-of-sample forecasts and stable recursive regression parameter estimates spanning the break in survey methodology. In 2014, a 1% relative reduction in adult current smoking prevalence and mean cigarette consumption per adult current smoker decreased real per capita healthcare expenditure by 0.104% and 0.113% the following year, respectively (elasticity). A permanent relative reduction of 5% reduces expected real per capita healthcare expenditures $99 (95% CI $44, $154) in the next year and $31.5 billion for the entire US (in 2014 dollars), holding other factors constant. The reductions accumulate linearly for at least five years following annual permanent decreases of 5% each year. Given the limitations of time series modelling in a relatively short time series, the effect of changes in smoking behavior may occur over several years, even though the model contains only one lag for the explanatory variables.

Conclusion.  Reductions in smoking produce substantial savings in real per capita healthcare expenditure in short to medium term. A 5% relative drop in smoking prevalence (about a 0.87% reduction in absolute prevalence) combined with a 5% drop in consumption per remaining smoker (about 16 packs/year) would be followed by a $31.5 billion reduction in healthcare expenditure (in 2014 dollars).

The full citation is: Lightwood J, Anderson S, Glantz SA (2020) Predictive validation and forecasts of short-term changes in healthcare expenditure associated with changes in smoking behavior in the United States. PLOS ONE 2020; 15(1): e0227493. https://doi.org/10.1371/journal.pone.0227493.  In is available for free here.