What drives variation in spending for breast cancer patients within geographic regions?

Health Serv Res. 2019 Feb;54(1):97-105. doi: 10.1111/1475-6773.13068. Epub 2018 Oct 14.

Abstract

Objective: To estimate and describe factors driving variation in spending for breast cancer patients within geographic region.

Data source: Surveillance, Epidemiology, and End Results (SEER)-Medicare database from 2009-2013.

Study design: The proportion of variation in monthly medical spending within geographic region attributed to patient and physician factors was estimated using multilevel regression models with individual patient and physician random effects. Using sequential models, we estimated the contribution of differences in patient and disease characteristics or use of cancer treatment modalities to patient-level and physician-level variance in spending. Services associated with high spending physicians were estimated using linear regression.

Data extraction method: A total of 20 818 women with a breast cancer diagnosis in 2010-2011.

Principal findings: We observed substantial between-patient and between-provider variation in spending following diagnosis and at the end-of-life. Immediately following diagnosis, 48% of between-patient and 31% of between-physician variation were driven by differences in delivery of cancer treatment modalities to similar patients. At the end-of-life, patients of high spending physicians had twice as many inpatient days, double the chemotherapy spending, and slightly more hospice days.

Conclusions: Similar patients receive very different treatments, which yield significant differences in spending. Efforts to reduce unwanted variation may need to target treatment choices within patient-doctor discussions.

Keywords: breast cancer; spending; variation.

Publication types

  • Research Support, Non-U.S. Gov't

MeSH terms

  • Breast Neoplasms / economics*
  • Breast Neoplasms / metabolism*
  • Breast Neoplasms / therapy
  • Female
  • Health Care Costs / statistics & numerical data*
  • Health Expenditures / statistics & numerical data*
  • Humans
  • Medical Oncology / economics
  • Quality of Health Care / economics*
  • Regional Health Planning / economics
  • United States