Data to support patient care comes from a variety of sources that contain differing data types. Key activities to use clinical data include identifying the sources of data, understanding the data types and associated methods to work with the data, and identifying the necessary resources to complete your IT project.
The scope of your IT project will determine the level of data access required and the associated data storage needs. Data used in multisite projects will require IRB oversight and often require the execution of a DUA if transferring data outside of the institution or receiving data from another institution.
Identifying and assembling an adequate project team is based on the needs of the project. At a minimum, you will need to include frontline staff that will use the product, a data analyst capable of completing the ETL process on the data, and potentially statisticians to conduct appropriate model building and outcomes analyses.
There are multiple approaches to analyzing data. AI is the latest advance in machine learning approaches that include supervised, in which data is labeled and the algorithm is guided with statistical considerations, and unsupervised, in which unlabeled data is used to infer meaning. While robust, machine learning approaches require interdisciplinary teams and large resource dedication to complete.
review and potential revision over time. Follow-up and review of implemented programs should be included in the initial planning stages and resource allocation decisions at project inception.
Let us consider the following for the quality improvement project:
You are a new manager on your Heart Failure/Cardiac step-down unit and have high hopes for your floor.
Identify several IT projects that you as the nurse manager of a nursing unit could develop to support the operations of the nursing floor to promote compliance with daily weights for your HF patients.
As you do your RCA analysis you realize that compliance to many of the issues causing experiences on your floor is due to the poor health data literacy within your nursing staff. Why is it important for nurse leaders to develop health data literacy?
As you begin to form your team for your IT projects you question yourself as to who will comprise the team.
Who are the various team members to consider adding to the team? Identify their roles and contributions to the project.