How Do Bundled Payment Initiatives Account for Differences in Patient Risk Profiles? A Systematic Review

Abstract

Objectives

Bundled payments (BPs) are increasingly being adopted to enable the delivery of high-value care. For BPs to reach their goals, accounting for differences in patient risk profiles (PRPs) predictive of spending is crucial. However, insight is lacking into how this is done in practice. This study aims to fill this gap.

Methods

We conducted a systematic review of literature published until February 2024, focusing on BP initiatives in the Organization for Economic Cooperation and Development countries. We collected data on initiatives’ general characteristics, details on the (stated reasons for) approaches used to account for PRP, and suggested improvements. Patterns within and across initiatives were analyzed using extraction tables and thematic analysis.

Results

We included 95 documents about 17 initiatives covering various conditions and procedures. Across these initiatives, patient exclusion (n = 14) and risk adjustment (n = 12) of bundle prices were the most applied methods, whereas risk stratification was less common (n = 3). Most authors stated mitigating perverse incentives as the primary reason for PRP accounting. Commonly used risk factors included comorbidities and sociodemographic and condition/procedure-specific characteristics. Our findings show that, despite increasingly sophisticated approaches over time, key areas for improvement included better alignment with value and equity goals, and enhanced data availability for more comprehensive corrections for relevant risk factors.

Conclusions

BP initiatives use various approaches to account for PRP differences. Despite a trend toward more sophisticated approaches, most remain basic with room for improvement. To enable cross-initiative comparisons and learning, it is important that stakeholders involved in BPs be transparent about the (reasons for) design choices made.

Authors

Celine M.R. Hendriks Fiona Koster Daniëlle Cattel Marc R. Kok Angelique E.A.M. Weel-Koenders Deirisa Lopes Barreto Frank Eijkenaar

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