Thomas Falasca, physician and author of Physician’s Guide to Better Medical Decision Making: Critical Thinking in Medicine
An instructive case of overlooked breast malignancy is described by Gordon Ownby. (Gordon T. Ownby. Malpractice Case: How Careful Physicians Can Miss Vital Information – Medscape – Dec 05, 2018.)
In this case, mammogram and ultrasound revealed two upper outer quadrant right breast masses in a middle-aged female. The biopsy report noted, “changes suggestive of ruptured cyst.”
The ordering gynecologist did not notice that this comment described only specimen B and that on the preceding page, specimen A was described as showing “morphologic findings of invasive ductal carcinoma.”
Three months later, responding to complaints by the patient of symptoms, the gynecologist examined the area, noted a mass, and then discovered the previous oversight.
This article prompted extensive reader reaction, much of it suggesting the ease of losing significant findings in a plethora of data.
Certainly, the incident seems an example of the search satisfaction bias, whereupon a search is terminated once some result is obtained. However, an effective countermeasure to search satisfaction bias is to conduct the search according to a plan and not to terminate prematurely.
Nevertheless, this is difficult to implement when the quantity of data increases explosively. Consequently, the comments of the readership seem justified.
It would be yet another victory for search satisfaction bias to stop looking for other causative factors in the case of this unfortunate patient. However, while examination of the case continues for other causative factors, it important to understand that the benefits of Big Data are realized only with machine processing of the data and may be counterproductive when human processing is involved.