A health economic evaluation of screening and treatment in patients with adolescent idiopathic scoliosis

Abstract

Summary of background data: Adolescent idiopathic scoliosis can progress and affect the health related quality of life of the patients. Research shows that screening is effective in early detection, which allows for bracing and reduced surgical rates, and may save costs, but is still controversial from a health economic perspective.

Study design: Model based cost minimisation analysis using hospital's costs, administrative data, and market prices to estimate costs in screening, bracing and surgical treatment. Uncertainty was characterised by deterministic and probabilistic sensitivity analyses. Time horizon was 6 years from first screening at 11 years of age.

Objective: To compare estimated costs in screening and non-screening scenarios (reduced treatment rates of 90%, 80%, 70% of screening, and non-screening Norway 2012).

Methods: Data was based on screening and treatment costs in primary health care and in hospital care settings. Participants were 4000, 12-year old children screened in Norway, 115190 children screened in Hong Kong and 112 children treated for scoliosis in Norway in 2012. We assumed equivalent outcome of health related quality of life, and compared only relative costs in screening and non-screening settings. Incremental cost was defined as positive when a non-screening scenario was more expensive relative to screening.

Results: Screening per child was € 8.4 (95% CrI 6.6 to10.6), € 10350 (8690 to 12180) per patient braced, and € 45880 (39040 to 55400) per child operated. Incremental cost per child in non-screening scenario of 90% treatment rate was € 13.3 (1 to 27), increasing from € 1.3 (-8 to 11) to € 27.6 (14 to 44) as surgical rates relative to bracing increased from 40% to 80%. For the 80% treatment rate non-screening scenario, incremental cost was € 5.5 (-6 to 18) when screening all, and € 11.3 (2 to 22) when screening girls only. For the non-screening Norwegian scenario, incremental cost per child was € -0.1(-14 to 16). Bracing and surgery were the main cost drivers and contributed most to uncertainty.

Conclusions: With the assumptions applied in the present study, screening is cost saving when performed in girls only, and when it leads to reduced treatment rates. Cost of surgery was dominating in non-screening whilst cost of bracing was dominating in screening. The economic gain of screening increases when it leads to higher rates of bracing and reduced surgical rates.

Keywords: Cost minimisation analysis; Health related quality of life; Scoliosis screening; Scoliosis treatment.

Figures

Figure 1

Tornado diagram (sensitivity analysis) for comparing the 80% treatment rate of Lee et al. non-screening scenario to screening.

Figure 2

Incremental cost estimations in four non-screening scenarios compared to screening both boys and girls. Incremental costs increase from left to right looking at the top of the curves. Incremental cost was lowest in non- screening 70% treatment rate of Lee et al (red), followed by Norway (purple) 80% treatment rate of Lee et al (blue), and 90% treatment rate of Lee et al (green). Incremental costs were highest with higher treatment rate non-screening scenarios and lower in low treatment rate non- screening scenarios compared to screening of both boys and girls. The areas under the curves to the right of zero equals the probabilities of incremental costs being >0.

Figure 3

Incremental cost estimations in four non-screening scenarios compared to screening of girls only. Incremental costs increase from left to right looking at the top of the curves. Incremental cost was lowest (cost saving) in the 70% treatment rate of Lee et al (red), followed by non-screening Norway (purple), the 80% treatment rate of Lee et. al non screening scenario (blue), and the 90% treatment rate of Lee et al. non-screening scenario (green) compared to screening girls only. The areas under the curves to the right of zero equals the probabilities of incremental costs >0 which are considerably higher when comparing non-screening scenarios to screening of girls only than when comparing non-screening scenarios to screening of both boys and girls (Figure 2).