IChoose Kidney: A Clinical Decision Aid for Kidney Transplantation Versus Dialysis Treatment. Issue 3 (March 2016) - Patzer, Rachel E.; Basu, Mohua; Larsen, Christian P.; Pastan, Stephen O.; Mohan, Sumit; Patzer, Michael; Konomos, Michael; McClellan, William M.; Lea, Janice; Howard, David; Gander, Jennifer; Arriola, Kimberly Jacob
Abstract : Background: Despite a significant survival advantage of kidney transplantation compared with dialysis, nearly one third of end-stage renal disease (ESRD) patients are not educated about kidney transplantation as a treatment option at the time of ESRD diagnosis. Access to individualized, evidence-based prognostic information is needed to facilitate and encourage shared decision making about the clinical implications of whether to pursue transplantation or long-term dialysis. Methods: We used a national cohort of incident ESRD patients in the US Renal Data System surveillance registry from 2005 to 2011 to develop and validate prediction models for risk of 1- and 3-year mortality among dialysis versus kidney transplantation. Using these data, we developed a mobile clinical decision aid that provides estimates of risks of death and survival on dialysis compared with kidney transplantation patients. Results: Factors included in the mortality risk prediction models for dialysis and transplantation included age, race/ethnicity, dialysis vintage, and comorbidities, including diabetes, hypertension, cardiovascular disease, and low albumin. Among the validation cohorts, the discriminatory ability of the model for 3-year mortality was moderate (c statistic, 0.7047; 95% confidence interval, 0.7029-0.7065 for dialysis and 0.7015; 95% confidence interval, 0.6875-0.7155 for transplant). We used these risk prediction models to develop an electronic, user-friendly, mobile (iPad, iPhone, and website) clinical decision aid called iChoose Kidney. Conclusions: The use of a mobile clinical decision aid comparing individualized mortality risk estimates for dialysis versus transplantation could enhance communication between ESRD patients and their clinicians when making decisions about treatment options. Abstract : The investigators use USRDS data to develop a mathematical model that was used subsequently to develop an electronic, user-friendly, mobile (iPad, iPhone, and website) clinical decision aid called "iChoose Kidney" to help patients with ESRD decide whether or not to seek a kidney transplant. Supplemental digital content is available in the text.