Estimating the number of usability problems affecting medical devices: modelling the discovery matrix

Vincent Vandewalle (), Alexandre Caron, Coralie Delettrez, Renaud Périchon, Sylvia Pelayo, Alain Duhamel and Benoit Dervaux
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Vincent Vandewalle: MODAL - MOdel for Data Analysis and Learning - LPP - Laboratoire Paul Painlevé - UMR 8524 - Université de Lille - CNRS - Centre National de la Recherche Scientifique - Université de Lille, Sciences et Technologies - Centre Inria de l'Université de Lille - Inria - Institut National de Recherche en Informatique et en Automatique - METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694 - Université de Lille - CHRU Lille - Centre Hospitalier Régional Universitaire [CHU Lille] - Polytech Lille - École polytechnique universitaire de Lille
Alexandre Caron: METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694 - Université de Lille - CHRU Lille - Centre Hospitalier Régional Universitaire [CHU Lille]
Coralie Delettrez: CHU Lille - Direction de la recherche et de l’innovation - CHRU Lille - Centre Hospitalier Régional Universitaire [CHU Lille]
Renaud Périchon: METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694 - Université de Lille - CHRU Lille - Centre Hospitalier Régional Universitaire [CHU Lille]
Sylvia Pelayo: CIC Lille - Centre d'Investigation Clinique - Innovation Technologique de Lille - CIC 1403 - CIC 9301 - INSERM - Institut National de la Santé et de la Recherche Médicale - Université de Lille - CHRU Lille - Centre Hospitalier Régional Universitaire [CHU Lille], METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694 - Université de Lille - CHRU Lille - Centre Hospitalier Régional Universitaire [CHU Lille]
Alain Duhamel: METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694 - Université de Lille - CHRU Lille - Centre Hospitalier Régional Universitaire [CHU Lille], CHU Lille - Direction de la recherche et de l’innovation - CHRU Lille - Centre Hospitalier Régional Universitaire [CHU Lille]
Benoit Dervaux: METRICS - Evaluation des technologies de santé et des pratiques médicales - ULR 2694 - Université de Lille - CHRU Lille - Centre Hospitalier Régional Universitaire [CHU Lille], CHU Lille - Direction de la recherche et de l’innovation - CHRU Lille - Centre Hospitalier Régional Universitaire [CHU Lille]

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Abstract: Background: Usability testing of medical devices are mandatory for market access. The testings' goal is to identify usability problems that could cause harm to the user or limit the device's effectiveness. In practice, human factor engineers study participants under actual conditions of use and list the problems encountered. This results in a binary discovery matrix in which each row corresponds to a participant, and each column corresponds to a usability problem. One of the main challenges in usability testing is estimating the total number of problems, in order to assess the completeness of the discovery process. Today's margin-based methods fit the column sums to a binomial model of problem detection. However, the discovery matrix actually observed is truncated because of undiscovered problems, which corresponds to fitting the marginal sums without the zeros. Margin-based methods fail to overcome the bias related to truncation of the matrix. The objective of the present study was to develop and test a matrix-based method for estimating the total number of usability problems. Methods: The matrix-based model was based on the full discovery matrix (including unobserved columns) and not solely on a summary of the data (e.g. the margins). This model also circumvents a drawback of margin-based methods by simultaneously estimating the model's parameters and the total number of problems. Furthermore, the matrix-based method takes account of a heterogeneous probability of detection, which reflects a real-life setting. As suggested in the usability literature, we assumed that the probability of detection had a logit-normal distribution. Results: We assessed the matrix-based method's performance in a range of settings reflecting real-life usability testing and with heterogeneous probabilities of problem detection. In our simulations, the matrix-based method improved the estimation of the number of problems (in terms of bias, consistency, and coverage probability) in a wide range of settings. We also applied our method to five real datasets from usability testing. Conclusions: Estimation models (and particularly matrix-based models) are of value in estimating and monitoring the detection process during usability testing. Matrix-based models have a solid mathematical grounding and, with a view to facilitating the decision-making process for both regulators and device manufacturers, should be incorporated into current standards. Keywords: Usability testing, Medical device, Missing data, Bayesian statistics, Maximum likelihood

Keywords: Usability testing; Medical device; Missing data; Bayesian statistics; Maximum likelihood (search for similar items in EconPapers)
Date: 2020-09
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Published in BMC Medical Research Methodology, 2020, 20 (1), ⟨10.1186/s12874-020-01091-y⟩

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Persistent link: https://EconPapers.repec.org/RePEc:hal:journl:hal-03117742

DOI: 10.1186/s12874-020-01091-y

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