No abstract

annual total cost per subject in relation to disease severity (GOLD) was: €783 (mild), €2,567 (moderate), €6,818 (severe), and €19,927 (very severe). Indirect costs were higher than direct costs in all severity stages. For direct costs, main cost drivers were hospitalizations in severe and very severe disease, and drugs in mild and moderate COPD, respectively. The main cost driver in indirect costs was productivity loss due to early retirement, except in mild disease where the driver was sick-leave. In comparison with a similar study performed in 1999 a numerical increase in mean annual total costs per subject was observed (ns). The total costs of COPD in 2010 could be estimated to about €1212-1469 million, with indirect costs accounting for about 70% of the total costs. CONCLUSIONS: The costs of COPD are still high in Sweden, and the costs increase considerably by disease severity.

Objectives: Very little information is available about the demand from CONITEC, the Brazilian HTA agency, for real-world evidence (RWE), moreover, few real-world data (RWD) sources are available. The objective of this study was to examine reports from CONITEC to identify patters of RWE and sources being used. MethOds: The reports from CONITEC are publicly available at the Ministry of Health (MoH). All reports from January to September of 2015 were reviewed for RWE and RWD information. In total, 37 seven reports were analyzed in this research. The assessed variables included type of technology, therapeutic area (TA), source of demand, final decision, RWE and RWD sources. Results: In total, there were 33 inclusion demand and 4 were exclusion. The most frequently technology requested were drugs, 31 out of 37. Infectious disease (8), immunobiologics (6), and cancer (4) were the most frequent TAs. A total of 24 demands were from organizations within MoH. Among external demands the majority were from pharmaceutical industries. Brazilian Unified Health System (SUS) database, the DATASUS, was the RWD source most frequently quoted in the final reports (19), and epidemiology, resources used and treatment patterns were the most used RWE. Drug costs were more frequently quoted (17) from the official MoH Journal (DOU). Observational studies were quoted in 12 reports, including chart reviews, and non-randomized interventional trials were used to support the decisions. Surveys were used in two reports to identify treatment patterns. cOnclusiOns: CONITEC is increasingly demanding RWE in the reports. By expanding the use of existing RWD, as DATASUS, a new concern arises with the way RWE are being retrieved and statistically adjusted in the reports. It is noticeable the concentration of RWE in MoH demands compared to other claimants. From demands without RWE, estimations and assumptions were taken into account. PHP168Not ready for tHe real world? tHe role of NoN-rCt evideNCe iN HealtH teCHNology assessmeNt

OBJECTIVES:To estimate annual health care utilization and costs of pneumonia across age cohorts in the United State (US) from an all-payer perspective. METHODS: A retrospective cross-sectional study was conducted using the 2008 Medical Expenditure Panel Survey (MEPS) database, a nationally representative annual survey of the civilian non-institutionalized population of the US. Pneumonia patients were identified as those with a Clinical Classification Code for pneumonia (code with 122). Resources used and expenditures incurred by patients with pneumonia that were directly attributable to pneumonia treatment (physician office visits, emergency room visits, outpatients visits, inpatient visits, other medical visits, and medications) were estimated. Health care costs per year per person (PYPP) were assessed across five age cohorts (Ͻ5, 5-Ͻ18, 18-Ͻ50, 50-Ͻ64, and Ն65 years old) and reported in 2008 US dollars. RESULTS: A total of 297 patients (representing 3.1 million persons) reported using medical resources or incurring expenditures due to pneumonia. Direct medical costs attributable to pneumonia were estimated at $2,763 (standard error [SE] Ϯ 344) per patient. Approximately 86% ($2,394) of this estimate was generated by inpatient hospitalizations for pneumonia, which were experienced by 26.9% of pneumonia patients, with an average of 0.31 admissions per patient. Physician office visits and home health visits were the next largest categories of expenditure, contributing $153 (5.5%) and $113 (4.1%), respectively. By age cohort, mean attributable costs PYPP for patients Ͻ5 (nϭ47), 5-Ͻ18 (nϭ38), 18-Ͻ50 (nϭ41), 50-Ͻ64 (nϭ108), and Ն65 years old (nϭ63)

To estimate the budget impact of adding omalizumab to standard therapy (ST) in patients with uncontrolled severe allergic asthma, from the perspective of the Brazilian private health care system, over a 5-year time horizon. METHODS: A budget impact model was developed to calculate the budget impact for Brazil, based on local epidemiological and drug cost data. The eligible population was based on the following inputs: 2013 population estimate (age ≥6 years): 183 million; prevalence of asthma: 10%; proportion of patients diagnosed and receiving treatment: 6.5%; percentage with allergic asthma: 69%; percentage with immunoglobulin E (IgE) ≥30 IU/mL: 78.7%; percentage with uncontrolled, severe disease: 2.4%; proportion of population using the private health care system and medications: 25.1%. For the following years, an annual population growth rate of 1.17% was assumed. Average doses, resource utilization per exacerbation and proportion of patients who respond to omalizumab were obtained from the INNOVATE trial. Direct costs, including omalizumab purchase and the costs of health care consumption related to exacerbations and routine visits. These costs were calculated from the perspective of the private health care payer. Omalizumab uptake was assumed to be 17%, 35%, 55%, 75% and 95% of eligible population for years 1 to 5, respectively. RESULTS: The number of patients eligible for add-on omalizumab therapy that met the eligibility criteria was estimated to be around 3,887 in the first year. The annual budget impact of omalizumab was approximately BRL25 million, BRL50 million, BRL77 million, BRL104 million and BRL131 million for years 1 to 5, respectively (BRL1=USD0.492). CONCLUSIONS: The budget impact for the private health care system in Brazil of adding omalizumab to ST was approximately BRL131 million at the end of year-5. Considering that the total population using the private health care system in Brazil is around 45.4 million, this represents a relatively small impact on the payer's budget, of BRL2.90 per beneficiary.