A state-transition Markov model was constructed to determine the clinical and economic impact of the alternative follow-up strategies. A seven-year time horizon was specified and the authors stated that the study perspective was that of the Australian health service.
The clinical data for the rates of total hip arthroplasty and subsequent revision surgery were from the Australian Orthopaedic Association's National Joint Replacement Registry. The probability of delayed revision was based on four values estimated by experts and each of these values was tested to assess its impact on the results. The key clinical parameters were the number of procedures, number of revisions, mortality, and quality of life.
Monetary benefit and utility valuations:
The utility estimates were from a published study of the effectiveness of knee and hip replacement (Rasanen, et al. 2007, see ‘Other Publications of Related Interest’ below for bibliographic details). The estimates were assessed using the 15-dimension health-related quality of life (15D) questionnaire.
Measure of benefit:
The benefit measure was the number of quality-adjusted life-years (QALYs), which were discounted at a rate of 3% per year.
The analysis included the direct medical costs of follow-up of patients after surgery, including consultations, X-rays, out-patient visits, and revisions. These costs were from Australian Medicare benefits schedules and Australian national cost data. The currency was Australian dollars (AUD) and an annual discount rate of 3% was applied.
Analysis of uncertainty:
Probabilistic sensitivity analysis was performed to assess the impact of the uncertainty around the key transition probabilities and the utility estimates for the health states in the model.