Community Socioeconomic Status and Surgical Quality Metrics

• In Event: 2481 - Sociology in Practice Settings Symposium Roundtable Session
  In Informal Discussion Roundtable: Table 04. Methods for Surveys and Administrative Data

Abstract

Importance: Professional and regulatory organizations in medicine establish quality metrics (e.g., mortality rates, readmission rates) for comparing surgery outcomes across hospitals. To fairly identify under-performing hospitals, surgical outcomes are “risk-adjusted” for characteristics such as the type of surgery, specific diagnosis, disease severity, and presence of co-morbidities. Inclusion of socioeconomic status (SES) in risk-adjustment models has become a significant area of controversy, as the emerging consensus that SES influences surgical outcomes is counterweighed by limited data on individual SES available from clinical and administrative sources. We review recent clinical research using community SES data to improve prediction of surgical outcomes, and discuss the need for translating sociological theory on emergence of health disparities into a standardized approach to using SES data in this clinical setting.

Observations: Census Bureau data are frequently used in United States research to predict complications after surgery. However, there is a lack of standardization and methodological justification for the geographical units at which SES is evaluated, the timing of community data collection relative to clinical data collection, or the combination of community SES factors into indices of disadvantage. These inconsistencies are related to a lack of conceptual distinction between community-level causal mechanisms (e.g., under-investment in health care infrastructure) and the use of community SES as a proxy for individual SES. Lastly, existing research has emphasized differences across categories of community SES rather than improvement in the predictive utility of risk-adjustment models resulting from adding SES measures.

Conclusions and relevance: A systematic approach to understanding how community SES influences surgical outcomes could contribute to improving surgical risk-adjustment models by appropriate inclusion of SES data. Sociological research on population health consequences of community socioeconomic disadvantage could inform a better understanding of causal processes, selection of community-level data, and arbitration between multiple measures of SES for this purpose.

Authors

• Dmitry Tumin, Ohio State University

• Emily A. Shrider, Ohio State University

• Martin Kosla, Ohio State University

• Michael David Nau, Ohio State University