The Critical Reader: Data Sources

Abstract

Imagine that you are embarking on a week-long road trip with your family, looking at potential colleges with your son or daughter. One stop of particular interest is your alma mater. While in the official college bookstore of your alma mater, you find some cool gifts. You wish to mail these as a surprise to your old housemates. All you need is their home addresses, which you plan to find using social media.While using your favorite social media application later that day, you easily find an ''overview'' and ''places lived'' tab for each of your old housemates, which lists towns and cities. But no matter how many tabs you click, you cannot find the detail needed to mail a small package to a specific physical address. Unfortunately, your old housemates are responsible and do not share their home addresses publicly. And it seems people do not post photos of their mailboxes, street signs, or mail. Despite sifting through digital tons of information, you cannot extract a 2-line mailing address for any of them. The social media application was not intended for that purpose.Similarly, medical researchers can use data from sources that were not intended for that research purpose. In orthopaedic sports medicine, these studies typically involve either large databases of generalized information or publicly available injury data of athletes.A large database study has been defined as a study of any large collection of data that encompasses records at a state, multistate, or national level reporting on more than one procedure or subspecialty. 10 Large databases contain generalized information such as demographic characteristics and diagnosis codes, which are typically derived from administrative, billing, or discharge records. These databases are markedly different than registries, which obtain detailed information specific to a diagnosis or procedure. 10 Some common examples of large databases include Nationwide Inpatient Sample (NIS), National Surgical Quality Improvement Project (NSQIP), statewide billing or discharge records, PearlDiver, Medicare claims and enrollment records, and National Hospital Discharge Survey.The strength of a large database study is the quantity of data. A large database study can report on rare patient