Visibility Is Not Control: Construct Separation and Variable Attribution in Surgical Reimbursement Policy
Andrew M Klapper1, Anthony N Dardano1, Michael Risin2
1Plastic and Reconstructive Surgery, Florida Atlantic University Charles E. Schmidt College of Medicine, Boca Raton, USA.
Cureus
|July 22, 2026
Summary
Surgical reimbursement figures often conflate distinct economic concepts. This report introduces a framework to separate these constructs and attribute accountability based on operative control, not just visibility, for better policy decisions.
Area of Science:
- Health Economics
- Health Policy Analysis
- Healthcare Management
Background:
- Current surgical reimbursement policies often treat diverse financial metrics as equivalent, despite differences in their economic construction and purpose.
- Attribution of accountability in healthcare disputes frequently mistakes patient visibility for operative control, leading to misassigned responsibility.
Purpose of the Study:
- To propose a framework for distinguishing the economic constructs measured by reimbursement figures.
- To develop a method for attributing accountability based on control of operative variables, rather than patient-facing visibility.
Main Methods:
- Introduction of a construct-separation and variable-attribution framework.
- Presentation of two operational checks: a five-filter construct-separation test and a six-question variable-attribution test.
- Application of the framework to various reimbursement scenarios, including physician charges, payer benchmarks, and network adequacy.
Main Results:
- The framework provides a structured method for interpreting diverse reimbursement figures and evaluating network adequacy.
- Distinguishes functional specialist availability as a distinct construct from mere directory enrollment.
- Highlights the need to define measurement boundaries and identify operative control before assigning accountability.
Conclusions:
- A disciplined approach to measurement, focusing on construct definition and variable attribution, is essential before policy judgments.
- The framework aids clinicians, policymakers, payers, and regulators in interpreting reimbursement data and assigning accountability accurately.
- Accurate interpretation of reimbursement figures and network adequacy requires understanding the underlying economic constructs and control variables.
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