Ссылка из Google. Возможно, Вы ее видели (открывается плохо, на всякий случай сделала большую копию). Похоже на то, что observed component years - просто "total number of individual years from implantation":

When developing the methodology in the course of the EUPHORIC project the main question was how to summarise data based on different numbers of cases and follow-up periods in a single figure and make them directly comparable. We finally decided on the indicator ‘Revisions per 100
observed component years’, which was introduced in Orthopaedics by introduced the Australian Joint Replacement Registry.
The formula for the calculation is:
Number of cases of revision surgery for any reason /
Number of observed component years x 100

The concept of ‘Revisions per 100 observed component years’ is a recognised standard in epidemiology (16) and was, for example, used as early as the middle of the 20th century in providing evidence of the association between tobacco consumption and the incidence of lung
cancer (17).
In principle, this method deals with calculating a correlation between the incidence of a potential risk exposure (e.g. cigarette smoking) and a consequential event (e.g. development of lung cancer). It also allows for considering essential influencing factors (e.g. smoking period or number of cigarettes) in the calculation.
Applied to arthroplasty, this means:
• There is a risk for revision from the moment of implantation. The total number of individual years from implantation (= observed component years) are counted.
• The total number of revisions (for any reason) as the failure end-point are documented and
calculated in ‘Revisions per 100 observed component years’.
• Back calculation of the calculated value into the usual way of presentation of Revisions/Time is
possible by means of a linear function.
• A value of 1 represents a 1% revision rate at 1 year and a 10% revision rate at 10 years of follow-up.
• The advantage of this method is that it allows for comparison of datasets adjusted for the two main factors influencing the value of individual cohorts: number of cases and follow-up period.
This concept and the indicator can easily also be used for clinical studies.

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Note added at 2 hrs (2012-09-13 20:40:22 GMT)
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Вот сама ссылка, на всякий случай: http://www.ear.efort.org/downloads/EAR-EFORT QoLA Project.pd...

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Note added at 2 hrs (2012-09-13 20:50:54 GMT)
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И вот, неожиданно, еще одна ссылка, подтверждающая идею первой: http://www.rpa.spot.pt/getdoc/fd857357-8e5f-4599-85b6-9b8395...

(стр. 12-14)