Literature DB >> 29921451

The Role of Big Data in the Development and Evaluation of US Dialysis Care.

Kevin F Erickson1, Samaya Qureshi2, Wolfgang C Winkelmayer2.   

Abstract

Rapid growth in electronic communications and digitalization, combined with advances in data management, analysis, and storage, have led to an era of "Big Data." The Social Security Amendments of 1972 turned end-stage renal disease (ESRD) care into a single-payer system for most patients requiring dialysis in the United States. As a result, there are few areas of medicine that have been as influenced by Big Data as dialysis care, for which Medicare's large administrative data sets have had a central role in the evaluation and development of public policy for several decades. In the 1970/1980s, Medicare data helped identify concerning trends in costs, access to dialysis care, and quality of care delivered. As the research community and policymakers made Medicare's administrative data increasingly accessible for investigation, analyses of Medicare claims have had a large role in facilitating policy synthesis and refinement. Efforts to address the skyrocketing cost of injectable drugs in the 1990s and 2000s exemplify this expanded role of Big Data. Although there are opportunities for large government and nongovernmental administrative data sets to continue serving a critical role in the evaluation and development of ESRD policies, it is important to understand challenges and limitations associated with their use.
Copyright © 2018 National Kidney Foundation, Inc. Published by Elsevier Inc. All rights reserved.

Entities:  

Keywords:  Administrative datasets; Medicare; US Renal Data System (USRDS); United States; data analysis; dialysis; drug costs; end-stage renal disease (ESRD); erythropoietin-stimulating agent (ESA); health policy; medical costs; reimbursement rates

Mesh:

Year:  2018        PMID: 29921451     DOI: 10.1053/j.ajkd.2018.04.007

Source DB:  PubMed          Journal:  Am J Kidney Dis        ISSN: 0272-6386            Impact factor:   8.860


  3 in total

Review 1.  Big Data in Nephrology.

Authors:  Navchetan Kaur; Sanchita Bhattacharya; Atul J Butte
Journal:  Nat Rev Nephrol       Date:  2021-06-30       Impact factor: 28.314

2.  Quantifying The Costs of Creating and Maintaining Hemodialysis Access in An All-Payer Rate-Controlled Health System.

Authors:  Rebecca Sorber; Joseph K Canner; Christopher J Abularrage; Paula K Shireman; Dorry L Segev; James H Black Iii; Karen Woo; Caitlin W Hicks
Journal:  Ann Vasc Surg       Date:  2021-06-18       Impact factor: 1.607

3.  A Rare Cause of Persistent Blood Loss after Continuous Ambulatory Peritoneal Dialysis Catheter Placement.

Authors:  T Natroshvili; T Elling; S A Dam; M Vd Berg; R R H Nap; R J Hissink
Journal:  Case Rep Surg       Date:  2020-02-20
  3 in total

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