Date of Award

Spring 5-2019

Degree Name

Doctor of Philosophy (PhD)

Advisor(s)

FRANCES LEE REVERE, PHD, MS

Second Advisor

OSAMA I. MIKHAIL, PHD, MBA, MS

Third Advisor

JOSE-MIGUEL YAMAL, PHD, MA

Abstract

Bundled payments have the opportunity to promote care standardization and coordination while incentivizing efficiency and value-based healthcare delivery. However, bundled payments have been scrutinized due to challenges with defining the bundled lengths (also known as the episode of care period), limited inclusion/exclusion criteria, the absence of IT systems to support new payment models, and the lack of federal support. The objective of this study was to develop a profile for head and neck cancer, including descriptive statistics, risk assessment and bundled payment pricing recommendations using a large national claims database. The ability to assess pricing risks associated with head and neck cancer bundled payments across the US from a large claims database can provide evidence to either support or discredit the feasibility of bundled payment reform. The results of the study highlighted the total episode costs for head and neck cancer from start of treatment and a transparent bundled payment methodology. The results are as follows: 1) head and neck episode cancer costs on average $164,332 with a standard deviation of $106,500, and median episode costs of $143,806; 2) bundled payments were developed using a complete-linked hierarchical clustering analysis of 2 possible bundling approaches of either 3 bundled payment groups or 4 bundled payment groups; 3) a monte carlo simulation resulted in recommendations that pricing negotiations not start at the 50th percentile of the bundled payment group cost as suggested by previous studies but rather at the 75th percentile; 4) study aims were summarized and displayed in a visual framework to provide a practical ‘how-to guide’ for organizations looking to start modeling bundled payments. This analysis proves bundled payment grouping is feasible and viability, albeit dependent on an organization’s ability to control healthcare spending costs and negotiate bundled payment prices above costs. The results of this work demonstrate the use of statistical and financial models to support price models and sensitivity analyses. Healthcare leaders can use these models to better understand their expected costs/ profits and leverage their negotiations; however, it should be noted that this research does not suggest all bundled payment methodologies are profitable.

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