Abstract
Hospital readmission is a key metric of hospital quality, such as for comparing Veterans Affairs (VA) hospitals to private sector hospitals. To calculate readmission rates, one must first identify individual hospitalizations. However, in the VA Corporate Data Warehouse (CDW), data are organized by “bedded stays,” that is, any stay in a healthcare facility where a patient is provided a bed, not hospitalizations. Thus, CDW data poses several challenges to identifying hospitalizations including: (1) bedded stays include both non-acute inpatient stays (i.e. nursing home, mental health) and acute inpatient hospital care; (2) transfers between VA facilities appear as separate bedded stays; and (3) VA care may also be fragmented by non-VA care. Thus, we sought to develop a rigorous method to identify acute hospitalizations using the VA CDW. We examined all VA bedded stays with an admission date in 2009. Non-acute portions of a stay were dropped. VA to VA transfers were merged when consecutive discharge and admission dates were within one calendar day. Finally, hospitalizations that occurred in a non-VA facility were merged. The 30-day readmission rate was calculated at each step of the algorithm to demonstrate the impact. The total number of VA medical hospitalizations in 2009 with live discharges was 505,861. The 30-day readmission rate after adjusting for VA to VA transfers and incorporating non-VA care was 18.3% (95% confidence interval (CI): 18.2, 18.4%).
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Acknowledgements
This research was supported by the Department of Veteran Affairs, Veterans Health Administration, Health Services Research and Development Services (11-109 and 13-079) and from the National Institutes of Health (K08 GM115859). The views expressed in this article are those of the authors and do not necessarily represent the view of the Department of Veterans Affairs.
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Vincent, B.M., Wiitala, W.L., Burns, J.A. et al. Using Veterans Affairs Corporate Data Warehouse to identify 30-day hospital readmissions. Health Serv Outcomes Res Method 18, 143–154 (2018). https://doi.org/10.1007/s10742-018-0178-3
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DOI: https://doi.org/10.1007/s10742-018-0178-3