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Volume 47 Number 8, 2010
   Pages 709 — 718

Abstract —  Mental illness-related disparities in length of stay: Algorithm choice influences results

Susan M. Frayne, MD, MPH;1-3* Eric Berg, MS;1-2 Tyson H. Holmes, PhD;4 Kaajal Laungani, BA;1 Dan R. Berlowitz, MD, MPH;5 Donald R. Miller, ScD;5 Leonard Pogach, MD, MBA;6Valerie W. Jackson, MPH;1-2 Rudolf Moos, PhD1,3-4

1Center for Health Care Evaluation, Department of Veterans Affairs (VA) Palo Alto Health Care System, Palo Alto, CA; 2Division of General Internal Medicine, Stanford University, Palo Alto, CA; 3Center for Primary Care and Outcomes Research, Stanford University, Palo Alto, CA; 4Department of Psychiatry and Behavioral Sciences, Stanford University, Palo Alto, CA; 5Center for Health Quality, Outcomes, and Economic Research, Edith Nourse Rogers Memorial Veterans Hospital, Bedford, MA; and Boston University School of Public Health, Boston, MA; 6Center for Healthcare Knowledge Management, VA New Jersey Health Care System, East Orange, NJ; and University of Medicine and Dentistry of New Jersey-New Jersey Medical School, Newark, NJ

Abstract — Methodological challenges arise when one uses various Veterans Health Administration (VHA) data sources, each created for distinct purposes, to characterize length of stay (LOS). To illustrate this issue, we examined how algorithm choice affects conclusions about mental health condition (MHC)-related differences in LOS for VHA patients with diabetes nationally (n = 784,321). We assembled a record-level database of all fiscal year (FY) 2003 inpatient care. In 10 steps, we sequentially added instances of inpatient care from various VHA sources. We processed databases in three stages, truncating stays at the beginning and end of FY03 and consolidating overlapping stays. For patients with MHCs versus those without MHCs, mean LOS was 17.7 versus 13.6 days, respectively (p < 0.001), for the crudest algorithm and 37.2 versus 21.7 days, respectively (p < 0.001), for the most refined algorithm. Researchers can improve the quality of data applied to VHA systems redesign by applying methodological considerations raised by this study to inform LOS algorithm choice.

Key words: algorithms, databases, Department of Veterans Affairs, episode of care, healthcare disparities, health services research, human, length of stay, mental disorders, outcome and process assessment, patient discharge, physician's practice patterns, rehabilitation, reproducibility of results, veterans, veterans hospitals.

View HTML  ¦  View PDF  ¦  Contents Vol. 47, No. 8
This article and any supplementary material should be cited as follows:
Frayne SM, Berg E, Holmes TH, Laungani K, Berlowitz DR, Miller DR, Pogach L, Jackson VW, Moos R. Mental illness-related disparities in length of stay: Algorithm choice influences results. J Rehabil Res Dev. 2010:47(8): 709-18.

Last Reviewed or Updated  Wednesday, October 27, 2010 1:48 PM

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