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Primary sources of data to create a QI Data Registry lie primarily in the hands of the end users. This means their word docs, spreadsheets, emails and shared conversations with colleagues. Doing primary data collection in this population of end users may be an additional data entry burden. The user’s are primarily seen as clinical staff, Nurses, Pharmacists, Residents, and Doctors. This population’s daily requirements for electronic data entry is already very high. In order to minimize an already high data entry burden, this system proposes to keep the data entry for this phase of CQI Approver to a minimum. Our primary goal is to collect just enough information to answer the basic questions of who is doing which CQI project, what department are they from and what are the most basic details about the type of project and who is involved. This user population is already incented to perform a CQI project, but they are not necessarily incented to try to find an existing project to join or to commit the details of their proposed new project to a data registry for others to find. We propose to create an incentive mechanism to encourage end users to provide the data needed to create the QI Data Registry; an approval certificate. This ‘Approval Certificate’, similar to how UF HIPAA Training issued certificates, will be a token to allow the bearer access to services and resources from the QI Team. For example, an ‘Approval Certificate’ could be required to get a free BMJ publishing tool license or to access to Data Sets from the QI team. The ‘Approval Certificate’, will also serve as a means to proceed with your project with no further human approvals. The ‘CQI Approver’ app, will contain the ‘CQI Approver Algorithm’. The CQI Approver Algorithm, based on a tool developed by the QI team, will programmatically and algorithmically determine the end users approval status. This status may be ‘approved’ or ‘IRB protocol required’. ‘Approved’ will provide them with a certificate. The ‘IRB protocol required’ status will inform the end user about the aspects of their project that require IRB approval and then direct them to the entry point for the IRB process. The ‘CQI Approver’ will be a web based data driven application that will feed and retrieve data from the database we will call the ‘QI Data Registry’ (https://github.com/ctsit/qipr).

#Support This work has been supported in part by the UF Health Sebastian Ferrero Office of Clinical Quality & Patient Safety, a pilot grant from the AAMC and the University of Florida Clinical and Translational Science Institute, which is funded in part by the National Institutes of Health Clinical and Translational Science Award program, grants UL1TR001427, KL2TR001429 and TL1TR001428.

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At minimum, a citation should include: Clinical and Translational Science Informatics and Technology group at the University of Florida

Our suggested acknowledgement is (select one or more items within the braces, as appropriate): The authors acknowledge the Clinical and Translational Science Informatics and Technology group at the University of Florida for providing {Python software library, code, examples} resources that have contributed to the research results reported within this paper. URL: http://www.ncbi.nlm.nih.gov/pubmed/20306566

#Special Thanks to: Style Guide for Module project structure: http://docs.python-guide.org/en/latest/writing/structure/ https://github.com/kennethreitz/samplemod http://www.kennethreitz.org/essays/repository-structure-and-python

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