The adoption and utilization of healthcare technologies significantly affect the quality and cost of healthcare services. Understanding the factors that influence diffusion of incremental innovations will ultimately contribute to understanding and addressing health disparities and cost escalations arising from distortions in technology diffusion patterns. The proposed study analyzes how access to information, organizational characteristics, reimbursement policies, and the regulatory environment impact healthcare providers technology adoption and utilization decisions. More specifically, this study focuses on the diffusion of incremental surgical innovations in hospitals. Most health technology diffusion studies focus on large expensive medical devices such as magnetic resonance imaging (MRI) and computer assisted tomography (CT) machines, while paying less attention to small incremental medical innovations. Small incremental innovations may not have similar upfront costs but their cumulative impact on the health care costs and outcomes are significant. The proposed study uses the diffusion of coronary drug-eluting stents (DES) in hospitals as case to analyze diffusion of incremental innovations. They resulted from incremental enhancements to an existing device, the coronary bare-metal stents (BMS). DES are an ideal case for the following reasons. First, the medical determinants of using DES as opposed BMS is minimal. Most medical technology diffusion studies either ignore or poorly control for such determinants. Second, due to Center for Medicare and Medicaid Services (CMS) National Coverage Determination (NCD), DES is subject to uniform insurance coverage policies across public and most employer-provided health insurance plans. In the absence of such a coverage decision, it would be almost impossible to control for the regional variation of insurance coverage given the fragmented nature of the insurance sector. Most technology diffusion studies focus on a limited phase of the diffusion process, such as the initial decision to adopt a new technology. However, when analyzing incremental innovations, the shift to a new technology is much more gradual. The proposed study utilizes event-history analysis to estimate the impact of aforementioned factors on the probability and time taken by hospitals to initially adopt DES and eventually replace BMS. This analysis utilizes Agency for Health care Research and Quality (AHRQ) National In-patient Sample (NIS 2003-2005), a nationally representative sample of hospital in-patient discharges, to test the hypothesis that access to information and organizational characteristics influence the probability and time taken to initially adopt incremental innovations, and that reimbursement and regulatory policies have a larger impact on the probability and time taken for hospitals to eventually phase out BMS.