Users as designers: how people cope with poor HCI design in computer-based medical devices.

In this paper we examine how users interact with a computer-based infusion device adapted for terbutaline infusion to treat preterm labor in women experiencing high-risk pregnancies. This study examines (a) the human-computer interaction (HCI) deficiencies in the device as related to this context of use, (b) how the device characteristics increase the potential for error, and (c) the tailoring strategies developed by users to insulate themselves from failure. Interviews with nurses and tests of the behavior of the infusion device in different conditions identified several classic HCI deficiencies: complex and arbitrary sequences of operation, mode errors caused by poor differentiation of multiple operating modes intended for different contexts, ambiguous alarms, getting lost in multiple displays, and poor feedback on device state and behavior.

Empirical evaluation of the transfusion medicine tutor.

Previous research during the development of Antibody IDentification Assistant (AIDA) revealed that many medical technology students and other laboratory personnel have serious difficulties in determining the specificity of blood group alloantibodies, especially weak or multiple antibodies. Based on these previous results, AIDA was modified to provide a teaching environment for medical technology students. We report the results of a rigorous, objective evaluation of the resultant system, the Transfusion Medicine Tutor (TMT). The results show that the students who were taught by an instructor using TMT to provide the instructional environment went from 0 percent correct on a pretest case to 87 percent correct on posttests (n = 15). This increase compares with an improvement rate of 20 percent by a control group (n = 15) who used a passive version of the system with the tutoring functions turned off.

Dealing with brittleness in the design of expert systems for immunohematology.

In recent years, there has been increased discussion about the potential of expert systems to support medical decision-making tasks, including applications in clinical laboratory settings. This study provides data regarding the cognitive errors that technologists make on an important problem-solving task: the identification of antibodies in a patient's blood. It explores alternative designs for expert systems developed to reduce such errors. It also evaluates the effects of these alternative designs on the ability of the users to effectively stay "in the loop," applying their own expertise and judgment while using the computer as a tool to assist with their analyses. A pilot study was conducted involving 32 certified medical technologists, which compared two alternative roles for the computer: (1) use of the computer to automatically complete subtasks upon request, and (2) use of the computer as a monitoring device to critique technologists as they completed the analyses themselves. The system design that automatically completed subtasks for the technologist induced a 29 percent increase in errors relative to the design that critiqued technologists as they completed the analyses themselves.