Validation of kidney transplantation using administrative data
| dc.contributor.author | Lam, Ngan N | |
| dc.contributor.author | McArthur, Eric | |
| dc.contributor.author | Kim, S J | |
| dc.contributor.author | Knoll, Gregory A | |
| dc.date.accessioned | 2015-11-23T15:42:08Z | |
| dc.date.available | 2015-11-23T15:42:08Z | |
| dc.date.issued | 2015-05-18 | |
| dc.date.updated | 2015-11-19T13:06:27Z | |
| dc.description.abstract | Abstract Background Administrative data are increasingly being used to assess outcomes in kidney transplant recipients. Objective To assess the validity of transplant data in healthcare administrative databases compared to the reference standard of information collected directly from transplant centres. Design Retrospective cohort study. Setting One of three major transplant centres in Ontario (Toronto General Hospital, University Hospital – London, and Ottawa Hospital). Patients Recipients who received a kidney-only transplant between 2008 and 2011. Measurements For each data source, we identified kidney transplants performed. We calculated the sensitivity and positive predictive value (PPV) of the administrative data for the reference standard data. Methods The data collected from transplant centres were compared with data from the Canadian Organ Replacement Register (CORR) database, a hospital procedural code from the Canadian Institute for Health Information Discharge Abstract Database (CIHI-DAD), and provincial physician billing claims from the Ontario Health Insurance Plan (OHIP) database. Results During the study period, the three centres reported a total of 1112 kidney transplants performed. The probability of identifying kidney transplant recipients in CORR, CIHI, and OHIP, given they were identified by the transplant centres (sensitivity), was 96%, 98%, and 98% respectively. The probability that the database code correctly identified a transplant recipient (positive predictive value) in CORR, CIHI, and OHIP was 98%, 98%, and 96% respectively. Limitations We validated the information from 2008 to 2011 and cannot attest to the reliability of the data beyond the study period. Specifically, we would not regard this as evidence that applies to the earlier years, shortly after the inception of the databases. Secondly, we were unable to distinguish between first and repeat transplantation. Conclusions Codes in CORR, CIHI, and OHIP each operate well in the detection of kidney transplant recipients. These data sources can be used to efficiently identify and follow kidney transplant recipients for post-transplant outcomes. | |
| dc.identifier.citation | Canadian Journal of Kidney Health and Disease. 2015 May 18;2(1):20 | |
| dc.identifier.uri | http://dx.doi.org/10.1186/s40697-015-0054-9 | |
| dc.identifier.uri | http://hdl.handle.net/10393/33310 | |
| dc.language.rfc3066 | en | |
| dc.rights.holder | Lam et al.; licensee BioMed Central. | |
| dc.title | Validation of kidney transplantation using administrative data | |
| dc.type | Journal Article |
