Authors:
Don Roosan
1
;
Mazharul Karim
1
;
Jay Chok
2
and
Moom R. Roosan
3
Affiliations:
1
College of Pharmacy, Western University of Health Science, Pomona, California, U.S.A.
;
2
School of Applied Life Science, Keck Graduate Institute, Claremont, California, U.S.A.
;
3
School of Pharmacy, Chapman University, Irvine, California, U.S.A.
Keyword(s):
Electronic Health Record, Big Data, Visualization, Heatmap, Data Science.
Abstract:
Background: The majority of the electronic health record (EHR) contains a wealth of information, including unstructured notes. Healthcare professionals may be missing substantial portions of essential diagnostic and treatment information by not focusing on unstructured texts. The objective of this study is to present progress notes data using heatmap visualization. Methods: In this study, the research team used the unstructured text from the progress notes of deidentified patient data. The research team conducted qualitative content-coding based on the clinical complexity model and developed a heatmap based on the processed frequency data. Result: The researchers developed a color-coded heatmap focusing on the severity and acuity of patients’ status accumulated through multiple previous patient’s visits. Conclusions: Future research into creating an automated process to generate the heatmap from an unstructured dataset can open up opportunities to operationalize big data in healthcare.