Abstract
Aim: The purpose of this study was to quantify the difference between the current processflow model for a typical patient workup for chest pain and development of a new process flow model thatincorporates DMAIC (define, measure, analyze, improve, control) Six Sigma and evidence-based medicine in a bestpractices model for diagnosis and treatment.
Methods: The first stage, DMAIC Six Sigma, is used tohighlight areas of variability and unnecessary tests in the current process flow for a patient presenting to theemergency department or physician's clinic with chest pain (also known as angina). The nextstage, patient process flow, utilizes DMAIC results in the development of a simulated model that representsreal-world variability in the diagnosis and treatment of a patient presenting with angina. The third and finalstage is used to analyze the evidence-based output and quantify the factors that drive physician diagnosisaccuracy and treatment, as well as review the potential for a broad national evidence-based database.
Results: Because of the collective expertise captured within the computer-oriented evidence-basedmodel, the study has introduced an innovative approach to health care delivery by bringing expert-level care toany physician triaging a patient for chest pain anywhere in the world. Similar models can be created for otherailments as well, such as headache, gastrointestinal upset, and back pain.
Conclusions: This updatedway of looking at diagnosing patients stemming from an evidence-based best practice decision support model mayimprove workflow processes and cost savings across the health care continuum.