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This paper proposes a method to analyze statistically maintenance data for complex medical devices with censoring and missing information. It presents a classification of the different types of failures and establishes policies for analyzing data at the system and component levels taking into account the failure types. The results of this analysis can be used as basic assumptions in the development of a maintenance/inspection optimization model. As a case study, we present the reliability analysis of a general infusion pump from a hospital.

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Background:The aim of screening is to detect a cancer in the preclinical state. However, a false-positive or a false-negative test result is a real possibility.Methods:We describe invasive breast cancer progression in the Canadian National Breast Screening Study and construct progression models with and without covariates. The effect of risk factors on transition intensities and false-negative probability is investigated. We estimate the transition rates, the sojourn time and sensitivity of diagnostic tests for women aged 40–49 and 50–59.Results:Although younger women have a slower transition rate from healthy state to preclinical, their screen-detected tumour becomes evident sooner. Women aged 50–59 have a higher mortality rate compared with younger women. The mean sojourn times for women aged 40–49 and 50–59 are 2.5 years (95% CI: 1.7, 3.8) and 3.0 years (95% CI: 2.1, 4.3), respectively. Sensitivity of diagnostic procedures for older women is estimated to be 0.75 (95% CI: 0.55, 0.88), while women aged 40–49 have a lower sensitivity (0.61, 95% CI: 0.42, 0.77). Age is the only factor that affects the false-negative probability. For women aged 40–49, ‘age at entry', ‘history of breast disease' and ‘families with breast cancer' are found to be significant for some of the transition rates. For the age-group 50–59, ‘age at entry', ‘history of breast disease', ‘menstruation length' and ‘number of live births' are found to affect the transition rates.Conclusion:Modelling and estimating the parameters of cancer progression are essential steps towards evaluating the effectiveness of screening policies. The parameters include the transition rates, the preclinical sojourn time, the sensitivity, and the effect of different risk factors on cancer progression.