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Essays on the Evolution of Health Care Technology


This dissertation looks at health care technology using the tools and methods of economics. The particular focus is on the causes and implications of dynamic changes in health care technology over time. The dissertation utilizes methodologies developed in public finance to consider the effects of policy change on technological innovation and adoption.

I first look at the impact of Medicare's prospective payment system and how it influences which technologies get developed and adopted. This presents an ideal case study because the government implemented the system nationwide in 1983, and there have been many years for innovators to respond to the different financial incentives. Prospective payment theoretically penalizes hospitals for adopting technologies that treat illnesses common among the elderly. This chapter evaluates weather we see empirical evidence that there has been fewer innovative developments targeting illnesses common among the elderly compared to illnesses common among the non-elderly. The data paint a picture that supports the theoretical predictions, and upholds the idea that payment incentives do indeed impact which technologies get developed in the first place.

The next chapter looks at a much smaller government change and its short run effect on hospital behavior. Every year, the government adds a few new procedures to the list of icd-9-cm codes. These codes make it easier for hospitals to bill insurers for procedures. This chapter investigates empirically and finds that there is a sudden jump in the number of procedures performed in the quarter when a new code is introduced and that this jump persists going forward. It also looks at different sub-groups of insurers and hospitals, and finds that patients whose insurers depend most heavily on the icd-9-cm codes have the largest jump in the probability of undergoing the procedure in the quarter when it is introduced. The jump in treatment is non-existent for Medicare patients and self-pay patients, for whom the icd-9-cm procedure code is irrelevant.

The final chapter investigates changes in ADHD medication over time. Understanding these changes is important in understanding the diffusion of new technology. This project looks at a time period, 2001 to 2003, when a long-acting version of ADHD medication was spreading, which makes it interesting from a technological standpoint. The project particularly asks why some counties have higher growth rates in medication than other counties. What factors lead to faster diffusion in a particular geographic region? My co-authors and I find that supply side characteristics, such as physicians per capita and a younger age distribution among physicians, leads to a faster rate of diffusion.

These findings together shed light on some specific key questions about health care technology and how it changes over time. These issues will become increasingly important as health care costs escalate and as policymakers strive to make health care more affordable. Economists have long claimed that new technology plays the biggest role in cost growth. While new technology brings benefits as well as costs, economists will need more tools for evaluating technology cost-effectiveness if cost containment becomes an important enough political goal. This project sheds light on some of the matters that will need to be fleshed out in greater detail if we eventually want to understand innovation's role in rising costs.

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