Repeal of CON Laws and Health Outcomes

Health care costs and quality remain pressing issues for American policymakers and the general public. The US spends more on health care than any other OECD country. As a response to growing concerns about health care costs many states have adopted Certificate of Need (CON) laws. Such laws limit the ability of hospitals to expand capacity, yet have been accused of increasing hospital costs; therefore, some states have repealed their CON laws. In this analysis, we use data from the Healthcare Cost and Utilization Project National Inpatient Survey for the years 1993 to 2011 to examine the effect of CON repeal on a wide array of outcomes.

In 1996, PA repealed its CON law, providing us a natural experiment to identify the effects of this legislation on quality, costs, and access to health care. This repeal yields an ideal identification strategy because it is arguably exogenous — rather than being the result of an affirmative decision based on cost or quality concerns, the law simply expired as PA lawmakers failed to act by a certain deadline (Longwell and Steele, 2007). Neighboring NY and NJ have retained their CON laws; therefore, they serve as our control states.  

Most previous research related to CON laws has focused on Acute Myocardial Infarction; it is often not chosen based on price, and it is one of the most profitable areas in medicine (e.g. Ho, 2006; Ho and Ku-Goto 2013). It is unclear whether the conclusions concerning the effect of (repeal of) CON laws are generalizable. Hence, we expand the literature by examining the effect of this repeal on length of stay, hospital charges, mortality, and hospital-acquired infections (at the individual level) in addition to volume, mortality rate, and infection rate (at the hospital level).  We assess these outcomes within hip and knee replacements, bariatric surgeries, and Neonatal Intensive Care Units.

Our second contribution is our empirical specification and use of panel data. Most previous studies in this area (e.g. Lorch et al., 2011) use only cross-sectional data, which make it difficult to separate causality from correlation. Our empirical approach is similar to that of Ho and Ku-Goto (2013) who, focusing solely on CON provisions related to cardiac procedures, make use of panel data. Specifically, we use a difference-in-differences model for individual, i, of state, s, at hospital, h, in year, t, as follows:

 Y_ihts = PAAFTER96*β₁ + x_its* β₂ + z_hts* β₃ + θ_t + γ_s + δ_h + e_ihts

where PAAFTER96 indicates whether the observation is from PA after the repeal. β₁ is our parameter of interest.  X_its and Z_hts are sets of individual and hospital and market level variables, respectively. θ_t is a time fixed effect; δ_h are hospital dummy variables, and γ_s are time-invariant state fixed effects.

We hypothesize that CON repeal leads to greater competition, translating into lower prices/costs and increased access to services (through more hospitals providing this service and each hospital providing a higher quantity of this service).  This increase in quantity could potentially lead to higher quality.