TY - JOUR
T1 - Accuracy of the discharge destination field in administrative data for identifying transfer to a long-term acute care hospital
AU - Kahn, Jeremy M.
AU - Iwashyna, Theodore J.
N1 - Funding Information:
Funded by R01 HL096651 from the United States National Institutes of Health (Kahn). Drs. Kahn and Iwashyna are supported by a career development awards from the United States National Institutes of Health (K23 HL096651, Kahn; K08 HL091249, Iwashyna). This study was also funded in part from a grant from the Pennsylvania Department of Health, which specifically disclaims responsibility for any analyses, interpretations or conclusions.
Funding Information:
Dr. Kahn is employed by the University of Pennsylvania, which owns and operates a long-term acute care hospital under a cooperative agreement with Good Sheppard Rehabilitation Network–both are non-profit entities. Dr. Kahn also receives grant funding from the United States National Institutes of Health to study long-term acute care hospitals. Dr. Iwashyna reports no competing financial interests.
PY - 2010
Y1 - 2010
N2 - Background. Long-term acute care hospitals (LTACs) provide specialized care for patients recovering from severe acute illness. In order to facilitate research into LTAC utilization and outcomes, we studied whether or not the discharge destination field in administrative data accurately identifies patients transferred to an LTAC following acute care hospitalization. Findings. We used the 2006 hospitalization claims for United States Medicare beneficiaries to examine the performance characteristics of the discharge destination field in the administrative record, compared to the reference standard of directly observing LTAC transfers in the claims. We found that the discharge destination field was highly specific (99.7%, 95 percent CI: 99.7% - 99.8%) but modestly sensitive (77.3%, 95 percent CI: 77.0% - 77.6%), with corresponding low positive predictive value (72.6%, 95 percent CI: 72.3% - 72.9%) and high negative predictive value (99.8%, 95 percent CI: 99.8% - 99.8%). Sensitivity and specificity were similar when limiting the analysis to only intensive care unit patients and mechanically ventilated patients, two groups with higher rates of LTAC utilization. Performance characteristics were slightly better when limiting the analysis to Pennsylvania, a state with relatively high LTAC penetration. Conclusions. The discharge destination field in administrative data can result in misclassification when used to identify patients transferred to long-term acute care hospitals. Directly observing transfers in the claims is the preferable method, although this approach is only feasible in identified data.
AB - Background. Long-term acute care hospitals (LTACs) provide specialized care for patients recovering from severe acute illness. In order to facilitate research into LTAC utilization and outcomes, we studied whether or not the discharge destination field in administrative data accurately identifies patients transferred to an LTAC following acute care hospitalization. Findings. We used the 2006 hospitalization claims for United States Medicare beneficiaries to examine the performance characteristics of the discharge destination field in the administrative record, compared to the reference standard of directly observing LTAC transfers in the claims. We found that the discharge destination field was highly specific (99.7%, 95 percent CI: 99.7% - 99.8%) but modestly sensitive (77.3%, 95 percent CI: 77.0% - 77.6%), with corresponding low positive predictive value (72.6%, 95 percent CI: 72.3% - 72.9%) and high negative predictive value (99.8%, 95 percent CI: 99.8% - 99.8%). Sensitivity and specificity were similar when limiting the analysis to only intensive care unit patients and mechanically ventilated patients, two groups with higher rates of LTAC utilization. Performance characteristics were slightly better when limiting the analysis to Pennsylvania, a state with relatively high LTAC penetration. Conclusions. The discharge destination field in administrative data can result in misclassification when used to identify patients transferred to long-term acute care hospitals. Directly observing transfers in the claims is the preferable method, although this approach is only feasible in identified data.
UR - https://www.scopus.com/pages/publications/77955549130
UR - https://www.scopus.com/pages/publications/77955549130#tab=citedBy
U2 - 10.1186/1756-0500-3-205
DO - 10.1186/1756-0500-3-205
M3 - Article
AN - SCOPUS:77955549130
SN - 1756-0500
VL - 3
JO - BMC Research Notes
JF - BMC Research Notes
M1 - 205
ER -