Go your own way? The importance of environment in the formation of - PowerPoint PPT Presentation

Go your own way? The importance of environment in the formation of physician practice styles Avdic, Ivets and Sriubaite Discussion by Amitabh Chandra

Highest Performance Lowest Performance Source: Chandra, Staiger and Skinner (IOM, 2010)

Stents are Highly Cost-Effective for some Marginal Benefit from Treatment Primary PCI Cost per PCI Stable Angina # Patients

But less so for the marginal patient Marginal Benefit from Treatment Cost per PCI Total Cost # Patients X’

Small Differences in Beliefs have large cost-implications Marginal Benefit from Treatment Different beliefs about benefits Cost per PCI Total Cost # Patients X Z

The New Yorker 1950-55 Collection “By all means, dear – buy it if you really want it. We’ll find the money for it somehow”

Average who say yes: 57%

Our Enterprise • Are Physician Factors Independent of Hospital/Environment factors? • What is the mechanism behind differences in physician factors • Peers versus capacity? • Peers versus environment? • Peers versus training? • Peer versus beliefs? • Is there heterogeneity across physicians in these factors? • What is the impact of this variation on patient outcomes?

Id Identification ∆ j =Time-invariant difference between a migrating cardiologist’s origin ( O ) and destination ( D ) hospitals’ risk -adjusted cath rates Using data on dates and peers, can be redefined as difference between a migrating cardiologist’s peers in origin and destination Diff-in-Diff : How much does a physician change her practice style after migrating? Coefficient of 1 means that 1 pp change in physician’s environment corresponds to a 1 pp change in physician behavior

Three suggestions • Approximately 160 cardiologists per year and 40 movers per year. So lots of noise in CATH rates • Even more noise in difference in CATH rates (subtracting signal+noise from signal + noise = noise) • Maybe use empirical bayes for shrinkage • Not sure whether peer effects are genuine peer effects or something else- maybe downplay these or show that they have variation above and beyond hospital level variation • Use simple theory to help understand null results on patient outcomes

Predictions of Hospital 30-day AMI Mortality, 2000 Example Empirical Bayes predictions of hospital mortality rate in 2000, accounting for volume and drift, using data from 1992-1999 & 2003-2013 13 Hospital Closures and Patient Mortality

Prototypical Roy Model of Treatment How one gets treated depends on X’s, hurdle, TFP and comparative advantage

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