Dalbavancin is a new innovative long-acting antimicrobial treatment that allows clinicians to endorse an early discharge program for patients suffering from acute bacterial skin and skin structure Infections (ABSSSI). The aim of this study was to develop a spending predictor model for evaluating the direct costs associated with the management of ABSSSI from the National Health Service (NHS) perspective of Italy, Spain, and Romania. The main purpose is to compare the hospitalization and drug costs due to the treatment of ABSSSI patients treated with standard antibiotics therapy or innovative long-acting treatment dalbavancin.

A decision-analytic model was performed to evaluate the diagnostic and clinical pathways of ABSSSI patients in the hospital, based on clinicians’ expert opinion. The standard of care scenario was compared with the dalbavancin scenario. The epidemiological and cost parameters were extrapolated from national administrative databases (hospital information system) and from a systematic literature review for each country. Only direct costs in the national payer's perspective were considered. Probabilistic sensitivity analysis (PSA) and one-way sensitivity analysis (OSA) were performed to check the robustness of the model assumptions.

Overall, the model estimated an average annual number of patients with ABSSSI equal to around 50,000 in Italy, Spain, and Romania. The introduction of dalbavancin reduced the length of stay of, on average, 3.3 days per ABSSSI patient. From the economic point of view, dalbavancin did not incur any additional cost from the NHS perspective with homogenous results between countries. The PSA and OSA demonstrated the robustness of the results.

The preliminary results highlight that the introduction of dalbavancin could generate a significant reduction in term of length of stay with no incremental cost from the NHS perspective. This model could represent a good tool for policymakers to provide information on the early discharge approach in the ABSSSI management.

The objectives of this study were to estimate the economic burden of human papillomavirus (HPV) in Italy, accounting for total direct medical costs associated with nine major HPV-related diseases, and to provide a measure of the burden attributable to HPV 6, 11, 16, 18, 31, 33, 45, 52, 58 infections.

A cost-of-illness incidence-based model was developed to estimate the incidences and costs of invasive cervical cancer, cervical dysplasia, cancer of the vulva, vagina, anus, penis, oropharyngeal, anogenital warts, and recurrent respiratory papillomatosis (RRP) in the context of the Italian National Health System (NHS). We used data from hospital discharge records (HDRs) of an Italian region and conducted a systematic literature review to estimate the lifetime cost per case, the number of incident cases, the prevalence of HPV9 types. Costs of therapeutic options not included in the diagnosis-related group (DRG) tariffs were estimated through a scenario analysis.

The total annual direct costs were EUR 540.7 million, with a range of EUR 338.3 – EUR 789.7 million. These costs could increase considering innovative therapies for cancers treatment (range EUR 16.2 – EUR 37.6 million). The fraction attributable to the HPV9 genotypes without innovative cancers treatment was EUR 329.2 million (range EUR 150.1 – EUR 576.7 million), accounting for sixty-one percent of the total annual burden of HPV-related diseases in Italy. Of this amount, EUR 136.7 million (forty-two percent) was related to men, accounting for sixty-four percent of the costs associated with non-cervical conditions.

The infections by HPV9 strains and the economic burden of non-cervical HPV-related diseases in men were found to be the main drivers of direct costs. The fraction of the total direct lifetime costs attributable to infections by HPV9 strains and the economic burden of non-cervical HPV-related diseases in men were found to be the main drivers of direct costs.

Budget Impact Analysis (BIA) is an integral element of a comprehensive Health Technology Assessment. Prior systematic reviews showed significant methodological dissimilarities in BIAs published from 2002 to 2015 (1,2). Aimed to improve the generalisability and transferability of outcomes, a guidance on methods was updated in 2014 (3). The objective of this study was to measure the adherence to Principles of Good Practice of BIAs published after the release of the updated guidelines.

Fifteen features representative of methodological appropriateness were identified from the Principles of Good Practice. A systematic review of the extant literature was conducted to identify BIAs published from January 2015 to December 2016. The adherence of each BIA to the Principles of Good Practice was defined by the number of representative characteristics taken into consideration as a percent of the total.

The full study protocol is available online: http://www.crd.york.ac.uk/PROSPERO/display_record.asp?ID=CRD42016049287

A sample of thirty-nine published BIAs were included in the analysis. The mean adherence of BIAs to the Principles of Good Practice was 69 percent (10.4 representative features out of 15). The highest adherence was 87 percent, while the lowest was 33 percent. The distribution of the scores was highly concentrated around the mean value, with thirty-four BIAs (87 percent of total sample) showing a level of adherence ≥ 60 percent. Only two BIAs reported an adherence < 50 percent (5 percent of total sample). Six representative features showed a level of adherence < 50 percent: off-label use (0 percent); uncertainty (26 percent); validation (33 percent); choice of computing framework (44 percent); eligible population (44 percent) and relevant features of healthcare system (49 percent).

Compared to the Principles of Good Practice, the BIAs included in the systematic review were overcomplicated and deterministic, ignoring the impact of possible scenarios relevant to budget holders. The research advocates a wider use of scenario planning as a tool to link uncertainty to the economic assessment of new interventions.