MMI 402 – Introduction to Clinical Thinking

Course Description:

This course provides students with insight into the clinical care process. It is designed for students not previously involved in clinical medicine as a nurse, pharmacist, or physician, as well as those trained in medicine outside the U.S. Course content will include some basic medical terminology and introductory psychophysiology. Topics include eliciting information from patients, synthesizing the history and physical examination, decision making for ordering tests, establishing diagnoses, treatment planning, integrating evidence-based medicine, and using an intelligent medical record in a complex environment.
Professor: David M. Liebovits, MD Medical Director, Information Systems, Northwestern Memorial Hospital
Term: Summer 2010
Grade: A
Text: Cutler, P. M. (1998). Problem Solving in Clinical Medicine: From Data to Diagnosis (Third Edition). Baltimore, Maryland: Williams & Wilkins.

Learning Objectives:

  • Understand the clinical environment in which problem solving occurs.
  • Understand the process of acquiring both narrative and structured content and assimilating both into a medical record.
  • Understand the techniques used by clinicians to formulate clinical hypotheses when caring for patients
  • Understand how precise use of an electronic medical record facilitates clinical thought and decision making.
  • Stimulate thought for how future technologies and care approaches may better utilize information management
  • Use these new skills in practice scenarios.
  • Use PubMed and master searching techniques to do medical research using MeSH database.
  • Gain familiarity with diagnosis tools and clinical decision support systems (CDSS) such as DXPlain

What I Learned:

Similar to MedInf 401, this class was required for students entering the MMI program without prior clinical experience. I found the class to be very informative with its primary focus centered on clinical diagnosis of disease. I learned about the clinical encounter and the dialog that occurs between a patient and a physician. Namely, it is a guided process whereby the physician establishes a trusting relationship and guides the patient to discuss presenting symptoms, while prompting for clues that help determine a diagnosis. While the dialog is occurring, the physician is at the same time performing an analysis on the information available in order to understand the problem so that a proper diagnosis can be determined. The analysis process starts with a review of the patient’s history, their chief complaint, and physical symptoms. I appreciated having an MD as an instructor, as I learned first-hand from his years of experience. It is interesting to learn that while physicians receive a great deal of book training, interpersonal skills are not a focus of their formal training, and that this is learned mostly in practicing.

A key take away for me was the realization of how much demand we place on our practicing physicians. Primary care physicians (PCPs) especially play such a critical role in our healthcare delivery as they are the most direct means to care that most individuals have. With the growing demand for healthcare services, the time that a physician has to spend with a patient is limited. On average, most interactions are between 15-20 minutes. Thus, in order to be effective in collection and review of all the clues, a physician must leverage healthcare IT tools such as electronic medical records (EMR), computerized physician order entry (CPOE), and clinical decision support systems (CDSS). This ignited my passion in Medical Informatics, and it gave me a perspective on how I could contribute to the industry by using my valuable technical background to bridge the clinical and technical worlds.

I also enjoyed learning about diagnostic tools such as Dxplain, MedCalc and WebMD. I also gained a greater appreciation for the complexity that goes into development of tools like these, and their value in terms of evidence based medicine practices. By leveraging integration with these tools between EMRs, CPOE and CDSS, I discovered that the industry could really increase the effectiveness of our primary care physicians. I was also given an introductory exposure to biostatistical principles, and I learned about 2×2 tables, sensitivity, specificity, prevelance, and predictive modeling. Biostatistical theory is all encompassed in the types of tools that aim to predict diagnosis of a disease and specifically used to minimize misdiagnosis.

After gaining a better understanding of the diagnosis process and science behind it, it became easier for me to understand how medical error occurs. Many of the readings, in fact, focused the consequences of misdiagnosis and underscored the importance quality outcomes.

After completing the course, I felt I had a well laid foundation on the clinical side, and better appreciation for the clinicians I would work alongside with for the remainder of the program. In retrospect, I found myself frequently referring back to the journal articles and texts that were covered in this course. Indeed, the biostatistical focus was of critical importance later when it aided me to understand MedInf 403 andMedInf 409Additionally, I received my first exposure to the Galter Health Sciences Library available through the Feinberg School of Medicine in this class. Through the library, I was taught how to do medical research and to explore research like other clinical professionals using PubMed, Ovid ,Medline and the MeSH databases. These critical research skills would add to the fundamental skills that all Medical Informaticists need, and it helped me further to be successful in the program via my many class research papers.

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