Annual conferences, educational courses, and other meetings draw a diverse community of individuals, yet also create a unique environment without the traditional guard rails. Unlike events held at one's home institution, clear rules and jurisdiction have not been universally established. To promote the open exchange of ideas, as well as an environment conducive to professional growth of all participants, the leading neurosurgical professional organizations joined forces to delineate the expectations for anyone who participates in sponsored events. The One Neurosurgery Summit Taskforce on Professionalism and Harassment developed a foundational policy that establishes common expectations for behavior and a unified roadmap for the prompt response to untoward events. We hope that publishing this policy will inspire other medical organizations to establish their own meeting and conference policies. More importantly, we wish to bring greater attention to everyone's responsibility for ensuring a safe and respectful space for education, scientific debate, and networking during organized events.

Background

The Centers for Medicare and Medicaid Services (CMS) hierarchical condition category (HCC) coding is a risk adjustment model that allows for the estimation of risk-and cost-associated with health care provision. Current models may not include key factors that fully delineate the risk associated with spine surgery.

Objective

To augment CMS HCC risk adjustment methodology with socioeconomic data to improve its predictive capabilities for spine surgery.

Methods

The National Inpatient Sample was queried for spinal fusion, and the data was merged with county-level coverage and socioeconomic status variables obtained from the Brookings Institute. We predicted outcomes (death, nonroutine discharge, length of stay [LOS], total charges, and perioperative complication) with pairs of hierarchical, mixed effects logistic regression models-one using CMS HCC score alone and another augmenting CMS HCC scores with demographic and socioeconomic status variables. Models were compared using receiver operating characteristic curves. Variable importance was assessed in conjunction with Wald testing for model optimization.

Results

We analyzed 653 815 patients. Expanded models outperformed models using CMS HCC score alone for mortality, nonroutine discharge, LOS, total charges, and complications. For expanded models, variable importance analyses demonstrated that CMS HCC score was of chief importance for models of mortality, LOS, total charges, and complications. For the model of nonroutine discharge, age was the most important variable. For the model of total charges, unemployment rate was nearly as important as CMS HCC score.

Conclusion

The addition of key demographic and socioeconomic characteristics substantially improves the CMS HCC risk-adjustment models when modeling spinal fusion outcomes. This finding may have important implications for payers, hospitals, and policymakers.