POINT: Is ICD-10 Diagnosis Coding Important in the Era of Big Data? Yes.

[1]  David A Chambers,et al.  Big Data and Large Sample Size: A Cautionary Note on the Potential for Bias , 2014, Clinical and Translational Science.

[2]  Morris F. Collen,et al.  Secondary Medical Research Databases , 2012 .

[3]  J. Newhouse,et al.  Using medicare data for comparative effectiveness research: opportunities and challenges. , 2011, The American journal of managed care.

[4]  C. Steiner,et al.  Comorbidity measures for use with administrative data. , 1998, Medical care.

[5]  L. Patak,et al.  A Shared Opportunity for Improving Electronic Medical Record Data. , 2017, Anesthesia and analgesia.

[6]  Uwe Siebert,et al.  Good research practices for comparative effectiveness research: approaches to mitigate bias and confounding in the design of nonrandomized studies of treatment effects using secondary data sources: the International Society for Pharmacoeconomics and Outcomes Research Good Research Practices for Retr , 2009, Value in health : the journal of the International Society for Pharmacoeconomics and Outcomes Research.

[7]  R. Deyo,et al.  Adapting a clinical comorbidity index for use with ICD-9-CM administrative databases. , 1992, Journal of clinical epidemiology.

[8]  F. Cunningham,et al.  US Government Claims Databases , 2012 .

[9]  M A Hlatky,et al.  Using databases to evaluate therapy. , 1991, Statistics in medicine.

[10]  Ellwood Pm,et al.  Shattuck Lecture--outcomes management. A technology of patient experience. 1988. , 1997, Archives of pathology & laboratory medicine.

[11]  Todd W Rice,et al.  Flash mob research: a single-day, multicenter, resident-directed study of respiratory rate. , 2013, Chest.

[12]  Raman Khanna,et al.  Characterizing the Source of Text in Electronic Health Record Progress Notes , 2017, JAMA internal medicine.