System Dynamics Modeling Can be Leveraged to Predict Critical Care Pathways and Costs for End Stage Renal Disease: US Population to 2020

**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 wi...

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Main Authors: Luca Fernandez, Christopher Koliba, Asim Zia, Katharine Cheung, Richard Solomon, Christopher Jones
Format: Article
Language:English
Published: Columbia Data Analytics, LLC
Series:Journal of Health Economics and Outcomes Research
Online Access:http://jheor.scholasticahq.com/article/9839-system-dynamics-modeling-can-be-leveraged-to-predict-critical-care-pathways-and-costs-for-end-stage-renal-disease-us-population-to-2020.pdf
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spelling doaj-c136155179cb4bb3b014b5febb32b0302020-11-25T02:14:20ZengColumbia Data Analytics, LLCJournal of Health Economics and Outcomes Research2327-2236System Dynamics Modeling Can be Leveraged to Predict Critical Care Pathways and Costs for End Stage Renal Disease: US Population to 2020Luca FernandezChristopher KolibaAsim ZiaKatharine CheungRichard SolomonChristopher Jones**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.http://jheor.scholasticahq.com/article/9839-system-dynamics-modeling-can-be-leveraged-to-predict-critical-care-pathways-and-costs-for-end-stage-renal-disease-us-population-to-2020.pdf
collection DOAJ
language English
format Article
sources DOAJ
author Luca Fernandez
Christopher Koliba
Asim Zia
Katharine Cheung
Richard Solomon
Christopher Jones
spellingShingle Luca Fernandez
Christopher Koliba
Asim Zia
Katharine Cheung
Richard Solomon
Christopher Jones
System Dynamics Modeling Can be Leveraged to Predict Critical Care Pathways and Costs for End Stage Renal Disease: US Population to 2020
Journal of Health Economics and Outcomes Research
author_facet Luca Fernandez
Christopher Koliba
Asim Zia
Katharine Cheung
Richard Solomon
Christopher Jones
author_sort Luca Fernandez
title System Dynamics Modeling Can be Leveraged to Predict Critical Care Pathways and Costs for End Stage Renal Disease: US Population to 2020
title_short System Dynamics Modeling Can be Leveraged to Predict Critical Care Pathways and Costs for End Stage Renal Disease: US Population to 2020
title_full System Dynamics Modeling Can be Leveraged to Predict Critical Care Pathways and Costs for End Stage Renal Disease: US Population to 2020
title_fullStr System Dynamics Modeling Can be Leveraged to Predict Critical Care Pathways and Costs for End Stage Renal Disease: US Population to 2020
title_full_unstemmed System Dynamics Modeling Can be Leveraged to Predict Critical Care Pathways and Costs for End Stage Renal Disease: US Population to 2020
title_sort system dynamics modeling can be leveraged to predict critical care pathways and costs for end stage renal disease: us population to 2020
publisher Columbia Data Analytics, LLC
series Journal of Health Economics and Outcomes Research
issn 2327-2236
description **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.
url http://jheor.scholasticahq.com/article/9839-system-dynamics-modeling-can-be-leveraged-to-predict-critical-care-pathways-and-costs-for-end-stage-renal-disease-us-population-to-2020.pdf
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