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1.
Am J Transplant ; 12(8): 2106-14, 2012 Aug.
Article in English | MEDLINE | ID: mdl-22702349

ABSTRACT

With the shortage of standard criteria donor (SCD) kidneys, efficient expanded criteria donor (ECD) kidney utilization has become more vital. We investigated the effects of the ECD label on kidney recovery, utilization and outcomes. Using data from the Scientific Registry of Transplant Recipients from November 2002 to May 2010, we determined recovery and transplant rates, and modeled discard risk, for kidneys within a range of kidney donor risk index (KDRI) 1.4-2.1 that included both SCD and ECD kidneys. To further compare similar quality kidneys, these kidneys were again divided into three KDRI intervals. Overall, ECD kidneys had higher recovery rates, but lower transplant rates. However, within each KDRI interval, SCD and ECD kidneys were transplanted at similar rates. Overall, there was increased risk for discard for biopsied kidneys. SCD kidneys in the lower two KDRI intervals had the highest risk of discard if biopsied. Pumped kidneys had a lower risk of discard, which was modulated by KDRI for SCD kidneys but not ECD kidneys. Although overall ECD graft survival was worse than SCD, there were no differences within individual KDRI intervals. Thus, ECD designation adversely affects neither utilization nor outcomes beyond that predicted by KDRI.


Subject(s)
Kidney Transplantation , Tissue Donors , Biopsy , Female , Graft Rejection , Humans , Male , Risk Assessment , Survival Analysis
2.
Am J Transplant ; 10(4 Pt 2): 1081-9, 2010 Apr.
Article in English | MEDLINE | ID: mdl-20420654

ABSTRACT

The evolution of communication as donor data flows from organ procurement organization to transplant centers has evolved with the incorporation of DonorNet 2007 into the UNet(SM) system. The ensuing study looks at DonorNet's impact on this process. We established defined time periods for comparison purposes. The study looked at match number for organ placement and overall organ utilization with a focus on ischemia time and graft outcomes. The results of the study demonstrate no significant change in the median match number of organ placement in liver or kidney transplantation. Changes in discard rates were varied amongst transplanted organs and there were noticeable changes in organ sharing with an increase in local allocation for kidney and liver and an ensuing decrease in regional and national distribution. There were no significant differences in the outcomes of livers and kidneys with low offer numbers compared with those with high offer numbers. Overall the study suggests a modest impact by DonorNet on organ placement and utilization, but a longer term study would need to be done to fully evaluate its impact.


Subject(s)
Kidney Transplantation/statistics & numerical data , Kidney , Tissue Donors/supply & distribution , Tissue Donors/statistics & numerical data , Humans , Risk Factors , Treatment Outcome
3.
Am J Transplant ; 9(4 Pt 2): 959-69, 2009 Apr.
Article in English | MEDLINE | ID: mdl-19341418

ABSTRACT

Continuous quality improvement efforts have become a central focus of leading health care organizations. The transplant community has been a pioneer in periodic review of clinical outcomes to ensure the optimal use of limited donor organs. Through data collected from the Organ Procurement and Transplantation Network (OPTN) and analyzed by the Scientific Registry of Transplant Recipients (SRTR), transplantation professionals have intermittent access to specific, accurate and clinically relevant data that provides information to improve transplantation. Statistical process control techniques, including cumulative sum charts (CUSUM), are designed to provide continuous, real-time assessment of clinical outcomes. Through the use of currently collected data, CUSUMs can be constructed that provide risk-adjusted program-specific data to inform quality improvement programs. When retrospectively compared to currently available data reporting, the CUSUM method was found to detect clinically significant changes in center performance more rapidly, which has the potential to inform center leadership and enhance quality improvement efforts.


Subject(s)
Transplantation/standards , Humans , Kidney Transplantation/mortality , Kidney Transplantation/statistics & numerical data , Liver Transplantation/mortality , Liver Transplantation/statistics & numerical data , Quality Assurance, Health Care , Risk Assessment , Survival Analysis , Survivors , Tissue Donors/statistics & numerical data , Tissue and Organ Procurement/standards , Transplantation/mortality , Transplantation/statistics & numerical data , Transplantation, Homologous/mortality , Transplantation, Homologous/statistics & numerical data , Treatment Failure , Treatment Outcome
4.
Am J Transplant ; 8(4 Pt 2): 1012-26, 2008 Apr.
Article in English | MEDLINE | ID: mdl-18336703

ABSTRACT

Differences in outcomes indeed exist among transplant programs and organ procurement organizations (OPO). A growing set of tools are available from the Scientific Registry of Transplant Recipients (SRTR) to measure and assess these outcomes in the different phases of the transplant process. These tools are not intended to compare two individual programs, rather to help identify programs whose practices may need further scrutiny, to be either avoided, corrected or emulated. To understand which differences in outcomes might be due to underlying differences in populations served and which might be due to differences in treatment, it is important to compare outcomes to 'risk-adjusted' expected values. Further, it is important to recognize and assess the role that random chance may play in these outcomes by considering the p-value or confidence interval of each estimate. We present the reader with a basic explanation of these tools and their interpretation in the context of reading the SRTR Program-Specific Reports. We describe the intended audience of these reports, including patients, monitoring and process improvement bodies, payers and others such as the media. Use of these statistics in a way that reflects a basic understanding of these concepts and their limitations is beneficial for all audiences.


Subject(s)
Organ Transplantation/statistics & numerical data , Adult , Age Factors , Aged , Humans , Middle Aged , Models, Statistical , Organ Transplantation/mortality , Proportional Hazards Models , Registries , Regression Analysis , Survival Analysis , Tissue and Organ Procurement/statistics & numerical data , Treatment Outcome , United States
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