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Do we need to use race in assessing renal function?
July 14, 2020
Stimulated by recent events there has been a very active debate among physicians about the role of race in medicine, we took a look at whether using race in the eGFR equation was useful in predicting renal failure events.
New start date announced for Kidney Care Choices models
June 10, 2020
Last week the The Centers for Medicare & Medicaid Services Innovation (CMMI) Center announced that it would be pushing ahead with the new Kidney Care Choices (KCC) payment models, with launch date of April 1, 2021. pulseData has been developing new tools to help practices deliver value based care and succeed under these new models.
Impact of COVID-19 on patients with CKD and ESRD
April 1, 2020
Article discussing the impact of the COVID-19 outbreak and patients with CKD and ESRD.
CMS Interoperability final ruling and why it matters
March 10, 2020
Our thoughts on the recently announced Final Interoperability Ruling
How Kidney Care Choices impacts your revenue
January 9, 2020
pulseData has crunched the numbers to help nephrology practices understand how the KCC models will impact on revenue
Exploring Benefits Enhancements in Kidney Care Choices
January 2, 2020
The new payment model Kidney Care Choices offer benefits enhancements that nephrology practices have not explored in depth. Let's explore useful benefits outlined in the current model.
pulseData at Kidney Week 2019
November 25, 2019
Kidney Week 2019 Wrap-up from pulseData! Learn about our Kidney Week experience.
Join us at ASN Kidney Week 2019
November 4, 2019
Urine luck! We've got a lot going on this week down in DC and would love for you to join us. A talk, poster sessions and a happy hour! Get in on the fun.
With PEAK Program, artificial intelligence helps build smooth transition to dialysis, encouraging home modalities
September 2, 2019
Risk prediction of end stage renal disease (ESRD) for population management and care intervention is both a research priority and unmet public health need. The use of electronic medical records (EMR) can be leveraged for improved assessment of ESRD onset. However, traditional risk scoring may not provide accurate risk prediction or complete population coverage if EMR data is incomplete. To handle missing data we developed a machine learning (ML) approach and compared it to traditional risk scoring in two EMR cohorts.
A machine learning approach to identifying patients at risk of developing incident CKD
November 8, 2018
Chronic Kidney Disease (CKD) is an under-identified condition and current methodology for identifying patients at risk of developing incident CKD is limited. Identifying patients who are high risk for CKD can improve awareness while delaying onset and progression of CKD. Machine learning algorithms can be used to stratify risk of those likely to develop incident CKD. Previous work has defined CKD using ICD codes or a limited number of eGFR readings.
Using machine learning to predict optimal renal replacement therapy starts in patients with advanced renal function loss
November 8, 2018
Building on our previous work using machine learning techniques to identify patients at risk of progression to End Stage Renal Disease (ESRD), we focused this model more precisely on identifying patients with advanced kidney function loss who should plan for optimal renal replacement therapy. The most recent USRDS data indicates that more than 80% of patients begin hemodialysis with a catheter and only 2.5% receive preemptive renal transplants.
Case Study: The Rogosin Institute’s Initiative to Promote Health Literacy
October 1, 2018
This case study describes The Rogosin Institute’s (Rogosin’s) experience in implementing a health literacy initiative focused on chronic kidney disease (CKD).
A machine learning approach to predicting renal failure
November 9, 2017
Abstract submitted for ASN Kidney Week 2017

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