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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 &lt; 0.001), for the crudest algorithm and 37.2 versus 21.7 days, respectively (p &lt; 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.

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