Logic Regression for Provider Effects on Kidney Cancer Treatment Delivery. (27th March 2014)

• Record Type: Journal Article
• Authors: Banerjee, Mousumi; Filson, Christopher; Xia, Rong; Miller, David C.
• Other Names: Jia Zhenyu Academic Editor.
• Is Part Of: Computational and mathematical methods in medicine. Volume 2014(2014)
• Publication Date: 2014-03-27
• Subjects: Medicine -- Computer simulation -- Periodicals; Medicine -- Mathematical models -- Periodicals; 610.11
• DOI: 10.1155/2014/316935
• Languages: English
• ISSNs: 1748-670X

Abstract

Abstract : In the delivery of medical and surgical care, often times complex interactions between patient, physician, and hospital factors influence practice patterns. This paper presents a novel application of logic regression in the context of kidney cancer treatment delivery. Using linked data from the National Cancer Institute's (NCI) Surveillance, Epidemiology, and End Results (SEER) program and Medicare we identified patients diagnosed with kidney cancer from 1995 to 2005. The primary endpoints in the study were use of innovative treatment modalities, namely, partial nephrectomy and laparoscopy. Logic regression allowed us to uncover the interplay between patient, provider, and practice environment variables, which would not be possible using standard regression approaches. We found that surgeons who graduated in or prior to 1980 despite having some academic affiliation, low volume surgeons in a non-NCI hospital, or surgeons in rural environment were significantly less likely to use laparoscopy. Surgeons with major academic affiliation and practising in HMO, hospital, or medical school based setting were significantly more likely to use partial nephrectomy. Results from our study can show efforts towards dismantling the barriers to adoption of innovative treatment modalities, ultimately improving the quality of care provided to patients with kidney cancer.