Medical big data has generated much excitement in recent years and for good reason. It can be an invaluable resource for researchers in general and insurers in particular. This Article, however, argues that users of medical big data must proceed with caution and recognize the data’s considerable limitations and shortcomings. These include data errors, missing information, lack of standardization, record fragmentation, software problems, and other flaws. This Article analyzes a variety of data quality problems and then formulates recommendations to address these deficiencies, including data audits, workforce and technical solutions, and regulatory approaches.
Hoffman, Sharona, "Medical Big Data and Big Data Quality Problems" (2014). Connecticut Insurance Law Journal. 141.