Prediction of Medical Device Usability Problems and Use Errors - An Improved Analytical Methodical Approach
The aim of medical care is to make people healthier, and this is pursued with great success today. Unfortunately, medical care also entails injuries to certain patients. Some of these injuries are caused by use errors. Research has shown that lack of usability of medical equipment is a strongly contributing cause of use errors. One way of counteracting use errors and usability problems with medical equipment is to investigate these proactively during the product development process of the equipment. If they are identified early, it is possible to undertake measures in the design to counteract them.
This licentiate thesis focuses on the investigation of use errors and usability problems that arise with medical equipment. The purpose of the work was to improve methods for identifying usability problems and use errors in the development process. The goal was to, based on existing methods, develop an improved Human Factors Engineering method for predicting, identifying and presenting presumed use errors and usability problems.
The method development has been conducted through analysis of user interfaces in real product development projects for medical equipment. Two efforts constituted the method development: formulation of requirements on the new method, and a further refinement of it. These efforts have been made in parallel. The resultant requirements are that the method must be formative, analytical and question-based, and must yield qualitative and semi-quantitative data. The method responds to four questions in the analysis of the interaction between user and equipment: (1) Will the user act correctly? (2) Why does the user act correctly? (3) Which errors can the user commit? (4) Why does the user act incorrectly?
When choosing a method for further refinement, there was no single method that fulfilled the formulated requirements. Hence two methods were selected, Cognitive Walkthrough (CW) and Predictive Human Error Analysis (PHEA). These were modified on the basis of weaknesses and deficiencies identified by personal studies. The method development resulted in two new methods: Enhanced Cognitive Walkthrough (ECW) and Predictive Use Error Analysis (PUEA).
The ECW method works by employing a clearly detailed procedure for simulating the user’s problem-solving process in each step of the interaction with the device. Throughout the interaction, it is checked whether the user’s established goal and previous experience will lead to the next correct action. PUEA employs a detailed process for breaking down the user’s tasks in steps and, for each step, identifying and investigating potential errors of use and their connection to the user’s cognitive processes. Both ECW and PUEA employ matrixes to show the outcome of the analysis. The methods have been applied with expected results (prediction and identification of use errors and usability problems) in analysis of dialysis machines and home care ventilators in real development projects.
The greatest strength of ECW and PUEA is that they can discover presumed use errors and usability problems before any empirical trials with real users are conducted. This simplifies the work in the development process. The principal weakness of ECW and PUEA is that they are more tedious and complicated than the original methods. Nonetheless, ECW and PUEA yield more comprehensive and easily overviewed results when the analysis is finished than do CW and PHEA. To conclude, the method development has resulted in two Human Factors Engineering methods for predicting, identifying and presenting presumed use errors and usability problems.