Our job as Real World Data programmers is to put the whole patient data, usually spread across multiple tables, into one coherent history. This might lead to some surprising discoveries such as: patients with records before birth/after death, patients changing sexes multiple times, and finding non-valid codes. Such discrepancies are usually pretty easy to classify as data issues and are easy to handle. On the other hand we might encounter real world data events that cannot be as easily classified and need special approaches such as; patient receiving multiple Rx’s for the same drug on one day, or receiving a new Rx’s before the previous runs out, patients visiting the Doctor’s office / Emergency Room during their hospital stays, patients changing wards/level of care multiple times during one hospital visit, and finding valid but non-billable codes in insurance claims data. In this post we share some commonly encountered problems (and our solutions) related to Real World Data analysis.