Analytical approach:
: A decision-tree model was used to compare the short-term cost and effectiveness data for the treatment of constipation in a clinical setting. The time horizon was six months and the authors stated that the perspective was that of the UK NHS.
Effectiveness data:
The evidence came from The Health Independent Network (THIN) database of medical records from UK primary care consultations. The efficacy of macrogol had been demonstrated in clinical trials and the authors wanted to evaluate it for a real clinical setting. The data for 1,000 patients, aged 18 years or older and treated with macrogol, were randomly selected from the database. The inclusion criteria for the population were clearly reported. These patients were matched, to 1,000 patients treated with lactulose, for age, gender and time between starting treatment and the previous laxative. Patients were not matched for co-morbidities, but these were on the whole comparable. The main clinical parameter was the percentage of patients who were successfully treated, defined by the discontinuation of laxative treatment by six months following commencement of treatment.
Monetary benefit and utility valuations:
The utility estimates were based on the preferences of a sample of the UK general public, collected using the standard gamble method (Guest, et al. 2008, see ‘Other Publications of Related Interest' below for bibliographic details).
Measure of benefit:
The measure of benefit was quality-adjusted life-years (QALYs) gained.
Cost data:
The direct costs and resource consumption included laxative prescriptions, clinic visits, admissions to hospital, accident and emergency attendances, laboratory tests, and diagnostic procedures. The constipation-related resource use was from the 2,000 patient records in THIN database, which were used for the effectiveness estimates. The unit costs for resources were provided in UK pounds sterling (£) and in 2007 to 2008 prices. They were from the Drug Tariff and the British National Formulary.
Analysis of uncertainty:
Probabilistic sensitivity analyses were conducted, by simultaneously varying the key outcome probabilities, the unit costs, the use of resources, and the utility estimates. One-way deterministic sensitivity analyses were conducted.