Data collecting and processing

Recorded implant data

In an arthroplasty Register, the date of the operation (primary or revision) and information such as diagnosis or reasons for reoperation, type of revision, approach, use of bone transplant, prostheses, cement, and antibiotic prophylaxis, are necessary. The Norwegian Arthroplasty Register collect data on the proximal (e.g. cup), distal (e.g. stem), and intermediate (e.g. head) prosthesis components separately and on a catalogue number level. In this way, results for the different implant designs, can be calculated separately, both for proximal and distal components. To ensure accurate information on the implant, the surgeons may use stickers with catalogue numbers of the implants supplied by the manufacturers.(see also the classification of the endoprosthetic implants types.

Collection of data

As register studies usually cover longer time periods and contain larger numbers of surgeons and patients than most other study approaches, a few principles should be emphasized at this point:

1. Correct and complete reporting are most easily achieved if the reporting is performed by the surgeon immediately after the operation has been performed.

2. It is important to use short and simple forms, since the level of dedication may vary among the participants.

3. As cases with incomplete information usually cannot be included in the statistical analyses, only information that is essential and easily available for the reporting surgeons should be asked for.

The general opinion is that, at present, the reporting to registers is more practical by the use of paper forms. In some registries, such as the Swedish hip registry the data are reported by e-mail, but this method is not safe, and the patients' data mustn't be sent through an unsafe medium.

Data analysis

In order to handle the large amounts of data in a register study, a statistical program package is needed. The statistical packages most commonly used by the authors are the SPSS (SPSS Inc., Chicago, IL, USA) and the S-PLUS (Statistical Sciences Inc., Seattle, WA, USA), althought others are both available and suitable (e.g.: SAS, SAS Institute, Cary, NC, USA).

Descriptive statistical data analysesmust be carriedout, and follow-up times and demographic data for the different compared treatment groups should be given. Survival analyses have most commonly been used in arthroplasty registers, but they are applicable also to other fields of orthopaedic surgery, especially in studies where groups of patients with certain treatments are followed until an outcome (response) such as healing or a complication.

Survival analyses

The different methods for calculation of survival have in common that they analyse the length of time to a response (death, failure). the possibility to include data from patients in which the response has not yet occured distinguishes survival analyses from other statistical methods.

Such data are called 'incomplete' or 'censored', and they may arise from loss to follow-up, death, or no response (failure) before the end of the study. The survival function is the probability that, for any specific survival time, a subject will survive at least for that long or longer.

Source: "Outcome Measures in Orthopaedics and Orthopaedic Trauma" by Paul Pynsent, Jeremy Fairbank &Andrew Carr