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AHRQ Research Studies
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Research Studies is a compilation of published research articles funded by AHRQ or authored by AHRQ researchers.
Results
1 to 3 of 3 Research Studies DisplayedTraino HM, Nonterah CW, Cyrus JW
Disparities in the completion of steps to kidney transplantation: protocol for a systematic review.
This review will catalogue disparities in the steps to transplantation as well as the barriers and facilitators to completion of each step identified in the extant literature. The results of the review will be used to generate recommendations for future research to improve equity in access to kidney transplantation.
AHRQ-funded; HS018113.
Citation: Traino HM, Nonterah CW, Cyrus JW .
Disparities in the completion of steps to kidney transplantation: protocol for a systematic review.
BMJ Open 2015 Sep 08;5(9):e008677. doi: 10.1136/bmjopen-2015-008677.
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Keywords: Disparities, Transplantation, Kidney Disease and Health, Access to Care, Guidelines
Davis AE, Mehrotra S, Friedewald JJ
Improving geographic equity in kidney transplantation using alternative kidney sharing and optimization modeling.
The authors analyzed current kidney allocation and developed an alternative kidney sharing strategy using a multiperiod linear optimization model, KSHARE, which aims to improve geographic equity in kidney transplantation while also respecting transplant system constraints and priorities. They used Organ Procurement and Transplant Network data to determine that enhancing the practice of sharing kidneys by the KSHARE model may increase geographic equity in kidney transplantation.
AHRQ-funded; HS021078.
Citation: Davis AE, Mehrotra S, Friedewald JJ .
Improving geographic equity in kidney transplantation using alternative kidney sharing and optimization modeling.
Med Decis Making 2015 Aug;35(6):797-807. doi: 10.1177/0272989x14557696.
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Keywords: Access to Care, Disparities, Health Services Research (HSR), Social Determinants of Health, Transplantation
Toro-Diaz H, Mayorga ME, Barritt AS
Predicting liver transplant capacity using discrete event simulation.
The researchers constructed a discrete event simulation model informed by current donor characteristics to predict future liver transplant trends through the year 2030. They found that by altering assumptions about the future donor pool, their model can be used to develop policy interventions to prevent a further decline in this lifesaving therapy.
AHRQ-funded; HS019468.
Citation: Toro-Diaz H, Mayorga ME, Barritt AS .
Predicting liver transplant capacity using discrete event simulation.
Med Decis Making 2015 Aug;35(6):784-96. doi: 10.1177/0272989x14559055.
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Keywords: Access to Care, Health Services Research (HSR), Policy, Transplantation