A Practical Approach for Calculating Reliable Cost Estimates from Observational Data: Application to Cost Analyses in Maternal and Child Health
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Comparative effectiveness research (CER) and cost-effectiveness analysis are valuable tools for informing health policy and clinical care decisions. Despite the increased availability of rich observational databases with economic measures, few researchers have the skills needed to conduct valid and reliable cost analyses for CER.
The objectives of this paper are to (i) describe a practical approach for calculating cost estimates from hospital charges in discharge data using publicly available hospital cost reports, and (ii) assess the impact of using different methods for cost estimation in maternal and child health (MCH) studies by conducting economic analyses on gestational diabetes (GDM) and pre-pregnancy overweight/obesity.
In Florida, we have constructed a clinically enhanced, longitudinal, encounter-level MCH database covering over 2.3 million infants (and their mothers) born alive from 1998 to 2009. Using this as a template, we describe a detailed methodology to use publicly available data to calculate hospital-wide and department-specific cost-to-charge ratios (CCRs), link them to the master database, and convert reported hospital charges to refined cost estimates. We then conduct an economic analysis as a case study on women by GDM and pre-pregnancy body mass index (BMI) status to compare the impact of using different methods on cost estimation.
Over 60 % of inpatient charges for birth hospitalizations came from the nursery/labor/delivery units, which have very different cost-to-charge markups (CCR = 0.70) than the commonly substituted hospital average (CCR = 0.29). Using estimated mean, per-person maternal hospitalization costs for women with GDM as an example, unadjusted charges ($US14,696) grossly overestimated actual cost, compared with hospital-wide ($US3,498) and department-level ($US4,986) CCR adjustments. However, the refined cost estimation method, although more accurate, did not alter our conclusions that infant/maternal hospitalization costs were significantly higher for women with GDM than without, and for overweight/obese women than for those in a normal BMI range.
Cost estimates, particularly among MCH-related services, vary considerably depending on the adjustment method. Our refined approach will be valuable to researchers interested in incorporating more valid estimates of cost into databases with linked hospital discharge files.
The authors acknowledge the following organizations and individuals for contributing to this project: the Agency for Healthcare Research and Quality (AHRQ) for promoting the enhancement of statewide, hospital-based, encounter-level databases (Grant Number R01HS019997); Social and Scientific Systems, Inc. for their coordination and direction of enhanced state data grants; and the staff of the Florida Department of Health and the Agency for Health Care Administration for providing access to the hospital discharge and vital statistics data used in this project.
This project was supported by grant number R01HS019997 from the AHRQ. The content is solely the responsibility of the authors and does not necessarily represent the official views of the AHRQ, or the University of South Florida. The authors do not have any relevant financial interest in this manuscript.
The introduction was written by JLS, MMC, and KC. The methodology for the project was written by JLS, MMC, and HMS. The results section, tables, and figures were prepared by JLS and MFM. The discussion section was written by JLS and HMS with support from the other authors. All authors contributed to the conceptualization and planning of the work that led to this manuscript.
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