To precisely define the utility of tests in a clinical pathway through data-driven analysis of the electronic medical record (EMR).
Materials and Methods
The information content was defined in terms of the entropy of the expected value of the test related to a given outcome. A kernel density classifier was used to estimate the necessary distributions. To validate the method, we used data from the EMR of the gastrointestinal department at a university hospital. Blood tests from patients undergoing surgery for gastrointestinal surgery were analyzed with respect to second surgery within 30 days of the index surgery.
The information content is clearly reflected in the patient pathway for certain combinations of tests and outcomes. C-reactive protein tests coupled to anastomosis leakage, a severe complication show a clear pattern of information gain through the patient trajectory, where the greatest gain from the test is 3–4 days post index surgery.
We have defined the information content in a data-driven and information theoretic way such that the utility of a test can be precisely defined. The results reflect clinical knowledge. In the case we used the tests carry little negative impact. The general approach can be expanded to cases that carry a substantial negative impact, such as in certain radiological techniques.
Citation: Stein Olav Skrøvseth, Knut Magne Augestad, Shahram Ebadollahi . Data-driven approach for assessing utility of medical tests using electronic medical records DOI: http://dx.doi.org/10.1016/j.jbi.2014.11.011
Received: June 29, 2014 Accepted: November 23, 2014 Published: December 03, 2014
Copyright: © 2014 The Authors. Published by Elsevier Inc.
User License: Creative Common License / Open access funded by the Author(s)
Competing Interests: MS is Chair of the SAB and Founder of Organ-I and Consultant for Immucor, Bristol Meyers Squibb, UCB, ISIS, Genentech; SR was a Consultant for Organ-I; TS and NS are Consultants for Organ-I, Immucor; FV has research grants with Astellas Pharma, Bristol Myers Squibb, Alexion, Pfizer, Novartis, Genentech.
We have shown how to quantify the information content in medical tests based on data available in the EMR. For the case of surgery for colorectal cancer, the information content of blood test results reflect clinical reality well. We quantify the expected value of the test at different clinical phases. It is possible to expand the methodology to other clinical scenarios and other types of tests where the impact of the test is larger.
SOS and KMA are supported by Tromsø Telemedicine Laboratory (TTL) funded by the Research Council of Norway Grant No. 174934 . SOS is supported by the Regional Health Authority of North Norway research Grant No. HST1182-14 .
The authors acknowledge surgeons at University Hospital of North Norway, Rolv-Ole Lindsetmo, Arthur Revhaug and Kim Erlend Mortensen who performed the majority of surgeries studied here and who are essential for the data generation. Kristian Hindberg is thanked for his role in data extraction and data management.