Constructing episodes of inpatient care: data infrastructure for population-based research
Databases used to study the care of patients in hospitals and Intensive Care Units (ICUs) typically contain a separate entry for each segment of hospital or ICU care. However, it is not uncommon for patients to be transferred between hospitals and/or ICUs, and when transfers occur it is necessary to combine individual entries to accurately reconstruct the complete episodes of hospital and ICU care. Failure to do so can lead to erroneous lengths-of-stay, and rates of admissions, readmissions, and death.
This study used a clinical ICU database and administrative hospital abstracts for the adult population of Manitoba, Canada from 2000–2008. We compared five methods for identifying patient transfers and constructing hospital episodes, and the ICU episodes contained within them. Method 1 ignored transfers. Methods 2–5 considered the time gap between successive entries (≤1 day vs. ≤2 days), with or without use of data fields indicating inter-hospital transfer. For the five methods we compared the resulting number and lengths of hospital and ICU episodes.
During the study period, 48,551 hospital abstracts contained 53,246 ICU records. For Method 1 these were also the number of hospital and ICU episodes, respectively. Methods 2–5 gave remarkably similar results, with transfers included in approximately 25% of ICU-containing hospital episodes, and 10% of ICU episodes. Comparison with Method 1 showed that failure to account for such transfers resulted in overestimating the number of episodes by 7-10%, and underestimating mean or median lengths-of-stay by 9-30%.
In Manitoba is it not uncommon for critically ill patients to be transferred between hospitals and between ICUs. Failure to account for transfers resulted in inaccurate assessment of parameters relevant to researchers, clinicians, and policy-makers. The details of the method used to identify transfers, at least among the variations tested, made relatively little difference. In addition, we showed that these methods for constructing episodes of hospital and ICU care can be implemented in a large, complex dataset.
- Garland, A (2005) Improving the Intensive Care Unit. Part 1. Chest 127: pp. 2151-2164 CrossRef
- Wunsch, H, Angus, DC, Harrison, DA, Collange, O, Fowler, R, Hoste, EAJ, de Keizer, NF, Kersten, A, Linde-Zwirble, WT, Sandiumenge, A (2008) Variation in critical care services across North America and Western Europe. Crit Care Med 36: pp. 2787-2793 CrossRef
- Garland, A, Fransoo, R, Olafson, K, Ramsey, C, Yogendren, M, Chateu, D, McGowan, K (2012) The Epidemiology and Outcomes of Critical Illness in Manitoba. Manitoba Centre for Health Policy, Winnipeg, Manitoba
- Garland, A, Yogendran, M, Olafson, K, Scales, DC, McGowan, K-L, Fransoo, R (2012) The Accuracy of Administrative Data for Identifying the Presence and Timing of Admission to Intensive Care Units in a Canadian Province. Med Care 50: pp. e1-e6 CrossRef
- Longobardi, T, Bernstein, CN (2006) Health Care Resource Utilization in Inflammatory Bowel Disease. Clin Gastroenterol Hepatol 4: pp. 731-743 CrossRef
- Rosenberg, A, Hofer, T, Hayward, R, Strachan, C, Watts, C (2001) Who bounces back? Physiologic and other predictors of intensive care unit readmission. Crit Care Med 29: pp. 511-518 CrossRef
- The pre-publication history for this paper can be accessed here:http://www.biomedcentral.com/1471-2288/12/133/prepub
- Constructing episodes of inpatient care: data infrastructure for population-based research
- Open Access
- Available under Open Access This content is freely available online to anyone, anywhere at any time.
BMC Medical Research Methodology
- Online Date
- September 2012
- Online ISSN
- BioMed Central
- Additional Links
- Author Affiliations
- 1. Department of Community Health Sciences, University of Manitoba, Winnipeg, MB, Canada
- 3. The Manitoba Centre for Health Policy, University of Manitoba, Winnipeg, MB, Canada
- 2. Department of Community Medicine, University of Manitoba, Winnipeg, MB, Canada