title: Revenue Potential for Inpatient IR Consultation Services: A Financial Model.
abstract: OBJECTIVE
  Interventional radiology (IR) has historically failed to fully capture the value of evaluation and management services in the inpatient setting. Understanding financial benefits of a formally incorporated billing discipline may yield meaningful insights for interventional practices.
  
  
  METHODS
  A revenue modeling tool was created deploying standard financial modeling techniques, including sensitivity and scenario analyses. Sensitivity analysis calculates revenue fluctuation related to dynamic adjustment of discrete variables. In scenario analysis, possible future scenarios as well as revenue potential of different-size clinical practices are modeled.
  
  
  RESULTS
  Assuming a hypothetical inpatient IR consultation service with a daily patient census of 35 patients and two new consults per day, the model estimates annual charges of $2.3 million and collected revenue of $390,000. Revenues are most sensitive to provider billing documentation rates and patient volume. A range of realistic scenarios-from cautious to optimistic-results in a range of annual charges of $1.8 million to $2.7 million and a collected revenue range of $241,000 to $601,000. Even a small practice with a daily patient census of 5 and 0.20 new consults per day may expect annual charges of $320,000 and collected revenue of $55,000.
  
  
  CONCLUSIONS
  A financial revenue modeling tool is a powerful adjunct in understanding economics of an inpatient IR consultation service. Sensitivity and scenario analyses demonstrate a wide range of revenue potential and uncover levers for financial optimization.
authors.affiliation: Department of Radiology, 55 Fruit St., Gray 2, Boston, MA 02114. Electronic address: amisono@mgh.harvard.edu.
authors.forename: Alexander S
authors.initials: AS
authors.lastname: Misono
authors.affiliation: Department of Radiology, 55 Fruit St., Gray 2, Boston, MA 02114; Division of Interventional Radiology Harvard Medical School, Massachusetts General Hospital, 55 Fruit St., Gray 2, Boston, MA 02114.
authors.forename: Peter R
authors.initials: PR
authors.lastname: Mueller
authors.affiliation: Department of Radiology, 55 Fruit St., Gray 2, Boston, MA 02114; Division of Interventional Radiology Harvard Medical School, Massachusetts General Hospital, 55 Fruit St., Gray 2, Boston, MA 02114.
authors.forename: Joshua A
authors.initials: JA
authors.lastname: Hirsch
authors.affiliation: Department of Radiology, 55 Fruit St., Gray 2, Boston, MA 02114.
authors.forename: Robert M
authors.initials: RM
authors.lastname: Sheridan
authors.affiliation: Department of Radiology, 55 Fruit St., Gray 2, Boston, MA 02114.
authors.forename: Assad U
authors.initials: AU
authors.lastname: Siddiqi
authors.affiliation: Department of Radiology, 55 Fruit St., Gray 2, Boston, MA 02114; Division of Interventional Radiology Harvard Medical School, Massachusetts General Hospital, 55 Fruit St., Gray 2, Boston, MA 02114.
authors.forename: Raymond W
authors.initials: RW
authors.lastname: Liu
mesh_terms: D018588:Fee-for-Service Plans / Q000191:economics; D005251:Fees, Medical / Q000639:trends; D005544:Forecasting; D017048:Health Care Costs / Q000639:trends; D017722:Hospital Charges / Q000639:trends; D006801:Humans; D007182:Income / Q000639:trends; D007297:Inpatients; D018803:Models, Economic; D011216:Practice Management, Medical / Q000191:economics* / Q000639:trends; D015641:Radiography, Interventional / Q000191:economics* / Q000639:trends; D012017:Referral and Consultation / Q000191:economics* / Q000639:trends; D013997:Time Factors; D016526:Workload / Q000191:economics