The synchronized emergence and merge of electronic medical records (EMRs) and data science led to the evolution of other sciences that started to re-shape the healthcare research. Precision medicine, predictive analytics, evidence based medicine (EBM) were all results of this synergetic merge. Accordingly, the emergence of those new sciences led to re-shaping the policies of the healthcare insurance and medical industry.
Big data could be of great benifit to medical insurance companies and insurers thorugh tracking and monitoring the employees. Even the public sectors can make use of the big data concepts.
Companies started to hire special firms who can predict (through big data analytics) sickness possibilities of the employees or the possibility of their pregnancy. Those firms provide employers with such reports after analysing employees medical claims, prescription drugs they use, search queries, and birth-control forms.
Such monitoring and tracking can help in the employees health needs prediction, sickness suscpetibility, possible absentism from work.
Tracking and monitoring process can lead to not only sickness prediction but also to choosing the best treatment plans or prophylactic measures.
In addition, it can support claims denials/approvals.
Untill now there is no rules governing such data manipulation (employees tracking process). There is no control over firms who gather such type of data about the employees’ health or what they can do with it. Such analyzed data can not be covered by HIPAA, especially if they are not including employees’ names.
New technological methodolgies facilitated the “anonymization” or “de-identification” of EMRs and so could comply with HIPAA standards.
There is a great debate about the use of the risk factors (age, sex, social status, family history, … etc.) in estimating the prices of healthcare services.
