In real-world Lynch syndrome management, incomplete clinical follow-up was the major barrier to do genetic testing. Targeted screening costs 2- to 7.5-fold less than universal and rarely misses Lynch syndrome cases. Future changes in testing costs will likely change the optimal algorithm.
With advances in organ matching and preventing acute graft-versus-host-disease (aGvHD), chronic graft-versus-host disease (cGvHD) following allogeneic hematopoietic stem cell transplantation (HSCT) has become a focus of transplant-related morbidity and mortality. Given that cGvHD often presents years following a transplant, our objective was to estimate its burden of cost resulting from allogeneic HSCT based on published estimates of incidence, morbidity, the value of lost work time and survivorship. Our choice of a ten-year time horizon is novel to the field of rare disease and was determined to be meaningful after consultations with present co-authors, including five physicians, one of whom is a transplant surgeon. A total of 44 450 cGvHD patients in the United States were estimated to require treatment over the next decade (from 2015 to 2025). This estimate is based on the last 5 years of trends reported in the transplant registries. What is not reported in any registry is that these patients will accrue a total of 605 631 years of lost wages, a collective lost productivity that will cost society over $27 Billion in the decade ahead: more than five times ($27B vs. $5.2B) the estimated ten-year cost of treating the condition.
Background: End Stage Renal Disease (ESRD) accounts for 9% of Medicare spending, with the beneficiaries suffering from ESRD costing 7-9 times more than the average. This population is expected to continue to grow as a portion of Medicare beneficiaries. To provide clinicians and administrators with a greater understanding of the combined costs associated with the multiple critical care pathways for End Stage Renal Disease we have developed a model to predict ESRD populations through 2020.
Methods: A system dynamics model was designed to project the prevalence and total costs of ESRD treatment for the United States through 2020. Incidence, transplant and mortality rates were modeled for 35 age and primary diagnosis subgroups coursing through different ESRD critical care pathways. Using a web interface that allows users to alter certain combinations of parameters, several demonstration analysis were run to predict the impact of three policy interventions on the future of ESRD care.
Results: The model was successfully calibrated against the output of United States Renal Data System’s (USRDS) prior predictions and tested by comparing the output to historical data. Our model predicts that the ESRD patient population will continue to rise, with total prevalence increasing to 829,000 by 2020. This would be a 30% increase from the reported 2010 prevalence.
Conclusions: Findings suggest that clinical care and policy changes can be leveraged to more effectively and efficiently manage the inevitable growth of ESRD patient populations. Patients can be shifted to more effective treatments, while planning integrating systems thinking can save Medicare’s ESRD program billions over the next decade.
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