Estimating the Cost of Care for Emergency Department Syncope Patients: Comparison of Three Models
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Estimating the Cost of Care for Emergency Department Syncope Patients: Comparison of Three Models

  • Author(s): Probst, Marc
  • McConnell, John
  • Weiss, Robert
  • Laurie, Amber
  • Yagapen, Annick
  • Lin, Michelle
  • Caterino, Jeffrey
  • Shah, Manish
  • Sun, Benjamin
  • et al.
Abstract

Introduction: We sought to compare three hospital cost estimation models for patients undergoing evaluation for unexplained syncope with hospital cost data. Developing such a model would allow researchers to assess the value of novel clinical algorithms for syncope management.

Methods: Complete health services data, including disposition, testing, and length of stay (LOS), were collected on 67 adult patients (age 60 years and older) who presented to the Emergency Department (ED) with syncope at a single hospital. Patients were excluded if a serious medical condition was identified. Three hospital cost estimation models were created to estimate facility costs: V1, unadjusted Medicare payments for observation and/or hospital admission, V2: modified Medicare payment, prorated by LOS in calendar days, and, V3: modified Medicare payment, prorated by LOS in hours. Total hospital costs included unadjusted Medicare payments for diagnostic testing and estimated facility costs. These estimates were plotted against actual cost data from the hospital finance department. Correlation and regression analyses were performed.

Results: Of the three models, V3 consistently outperformed the others with regard to correlation and goodness of fit. The Pearson correlation coefficient for V3 was 0.88 (95% Confidence Interval 0.81, 0.92) with an R-square value of 0.77 and a linear regression coefficient of 0.87 (95% Confidence Interval 0.76, 0.99).

Conclusion: Using basic health services data, it is possible to accurately estimate hospital costs for older adults undergoing a hospital-based evaluation for unexplained syncope. This methodology could help assess the potential economic impact of implementing novel clinical algorithms for ED syncope. 

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