Cheryl
Kraemer Module 2 Week 2
Kahn, M., Baston, D.,
& Schilling, L. (2012). Data Model
Considerations for Clinical Effectiveness Researchers. Medical
Care (50)7, S60-S67.
Why
was this article, blog, post, or multimedia chosen?
I chose this article because the term data
model was in the title and it is a topic for Module 2. It describes considerations needed when
deciding on a data model for healthcare research. I also chose it because while I am familiar
with the term, until reading this article, I didn’t understand what the term
meant.
What
makes it interesting, appropriate, or reputable?
I found it interesting
because it explains what data modeling is and considerations for model
selection at a level that someone new to data models can understand and use. It provides examples of data models and
examines how they would be used in a clinical research setting but also
explains their limitations. It also
differentiates which example is better under certain research circumstances.
Is
it an opinion? Case study? Research study? Product review?
It is a case study about the Scalable
Architecture for Federated Translational Inquiries Network (SAFTINet) to create
a scalable, distributed network to support Comparative Effectiveness Research. Comparative Effectiveness Research (CER) studies
focus on health outcomes, clinical effectiveness, risk and benefits of medical
care in real world clinical settings.
CER uses data from clinical, administrative and billing areas.
What
was the need, problem, issue or trend addressed in the article, blog, post, or multimedia?
The need was to
determine a data model that would meet the needs for storage, processing and
analysis of a vast array of clinical and financial data. There need to be a decision whether to
develop a model from scratch or adopt and modify an existing data model. Factored into the decision was the resources
need to create a new model and the ability to modify an existing model.
What
was the solution for which technology had an answer?
The decision was to
modify an already existing data model as it was felt that it was a better use
of resources. It was also determined to
provide a return benefit to the original data model’s community with the new
modifications.
What
implications might this have in healthcare delivery?
The implications for
healthcare delivery are based upon whether the data model chosen can support
the research. Multidisciplinary teams
comprised of informatics professionals, clinical investigators and
biostatisticians need to evaluate entity relationship diagrams to determine the
data model’s ability to meet the research needs for data storage and querying. An additional consideration is the quality of
the data which is outside the scope of the data model.
What
did you learn from it that might have an application for your practice?
I learned that are better ways to use data
than the way it is currently being done with the data from the systems I
support. I also learned that there are
challenges to both creating a data model from scratch and modifying an existing
data model and the decision must be thoughtfully considered by both the people
creating/modifying and using the data model.
Additionally, futures uses must be considered. The article provided Moody and Shank’s 8
dimensions to be considered when evaluating a data model which will be useful
when reviewing data models.
