CP3 - PATIENTS-INTERVENTION-COMPARATORS-OUTCOMES-SETTINGS-TIME-EFFECTS-SENSITIVITY (PICOSTEPS): REPRESENTING EVIDENCE-BASED HEALTH ECONOMIC EVALUATIONS (EBHEE) IN THE ORDER OF IMPORTANCE

Abstract

Evidence-based medicine (EBM) defines clinical questions in terms of the Patients/population-Intervention-Comparators-Outcomes, i.e. PICO. PICO has important role in EBM and is commonly applied in evidence assembly for systematic literature reviews, meta-analyses and clinical care guidelines (e.g. the Finnish Current Care Criteria, CCC, http://www.kaypahoito.fi/web/english/home). However, PICO alone is less suitable for representing the information of evidence-based health economic evaluations (EBHEE). To extend PICO to cover the crucial elements of EBHEEs. A systematic literature review was done to study the applicability of published HEEs for psoriatic arthritis treatments (http://www.kaypahoito.fi/web/kh/suositukset/suositus?id=nix02465&suositusid=hoi50062, http://www.terveysportti.fi/xmedia/nix/nix02465liitteet.pdf) during the work by the Finnish psoriasis CCC working group (http://www.kaypahoito.fi/web/kh/suositukset/suositus?id=hoi50062). During the study, international and Finnish guidelines for HEE were reviewed. Based on the review, Patients, Intervention, Comparators, Outcomes, Settings, Time, Effects and Sensitivity (PICOSTEPS) framework for EBHEEs was established and applied. In comparison to EBM-PICO, the PICOSTEPS Outcomes can include e.g. incremental cost-effectiveness ratios, net benefit, expected value of perfect information, net budget impact or burden avoided depending on the methods and settings applied. The Settings can be incremental, average or summing; depicted e.g. as cost effectiveness/utility, cost benefit, value of information, budget impact or burden of disease/treatment. The Time can vary, from a short within-trial horizon to a lifetime modelling. The Effects are commonly applied based on the trial, meta-analysis or real-world clinical effects, quality of life, resource use and/or productivity loss. The Sensitivity analyses applied for the assessment of uncertainty include e.g. one/multiway deterministic scenarios, probabilistic sensitivity analyses and expected value of partial perfect/sample information. PICOSTEPS has the potential to define HEE in more clinician-familiar way (vs. common HEE guidelines or checklists), and can demonstrate if the minimum information of EBHEE has been reported. PICOSTEPS is being successfully applied to EBHEEs and it represents their crucial information in the potential order of importance.