Public Health Technology Assessment: niet horen, niet zien en zwijgen!

Oratie uitgesproken op 1 februari 2013 door Prof.dr.mr. Silvia MAA Evers, Maastricht University, Faculty of Health, Medicine and Life Sciences, Maastricht ter aanvaarding van haar bijzonder hoogleraarschap met als titel "Public Health Technology Assessment: niet horen, niet zien en zwijgen!

How to prepare a systematic review of economic evaluations for informing evidence-based healthcare decisions: data extraction, risk of bias, and transferability (part 3/3)

Introduction: This article is part of the series “How to Prepare a Systematic Review (SR) of Economic Evaluations (EE) for Informing Evidence-based Healthcare Decisions” in which a five-step-approach for conducting a SR of EE is proposed. Areas covered: This paper explains the data extraction process, the risk of bias assessment and the transferability of EEs by means of a narrative review and expert opinion. SRs play a critical role in determining the comparative cost-effectiveness of healthcare interventions. It is important to determine the risk of bias and the transferability of an EE. Expert commentary: Over the past decade, several criteria lists have been developed. This article aims to provide recommendations on these criteria lists based on the thoroughness of development, feasibility, overall quality, recommendations of leading organizations, and widespread use

Methods for think-aloud interviews in health-related resource-use research:the PECUNIA RUM instrument

The think-aloud (TA) approach is a qualitative research method that allows for gaining insight into thoughts and cognitive processes. It can be used to incorporate a respondent’s perspective when developing resource-use measurement (RUM) instruments. Currently, the application of TA methods in RUM research is limited, and so is the guidance on how to use them. Transparent publication of TA methods for RUM in health economics studies, which is the aim of this paper, can contribute to reducing the aforementioned gap. Methods for conducting TA interviews were iteratively developed by a multi-national working group of health economists and additional qualitative research expertise was sought. TA interviews were conducted in four countries to support this process. A ten-step process was outlined in three parts: Part A ‘before the interview’ (including translation, recruitment, training), Part B ‘during the interview’ (including setting, opening, completing the instrument, open-ended questions, closing), and part C ‘after the interview’ (including transcription and data analysis, trustworthiness). This manuscript describes the step-by-step approach for conducting multi-national TA interviews with potential respondents of the PECUNIA RUM instrument. It increases the methodological transparency in RUM development and reduces the knowledge gap of using qualitative research methods in health economics.</p

Value of information analysis of an early intervention for subthreshold panic disorder: Healthcare versus societal perspective

Background Panic disorder is associated with high productivity costs. These costs, which should be included in cost-effectiveness analyses (CEA) from a societal perspective, have a considerable impact on cost-effectiveness estimates. However, they are often omitted in published CEAs. It is therefore uncertain whether choosing a societal perspective changes priority setting in future research as compared to a healthcare perspective. Objectives To identify research priorities regarding the cost-effectiveness of an early intervention for subthreshold panic disorder using value of information (VOI) analysis and to investigate to what extent priority setting depends on the perspective. Methods We calculated the cost-effectiveness of an early intervention for panic disorder from a healthcare perspective and a societal perspective. We performed a VOI analysis, which estimates the expected value of eliminating the uncertainty surrounding cost-effectiveness estimates, for both perspectives. Results From a healthcare perspective the early intervention was more effective at higher costs compared to usual care (€17,144 per QALY), whereas it was cost-saving from a societal perspective. Additional research to eliminate parameter uncertainty was valued at €129.7 million from a healthcare perspective and €29.5 million from a societal perspective. Additional research on the early intervention utility gain was most valuable from a healthcare perspective, whereas from a societal perspective additional research would generate little added value. Conclusions Priority setting for future research differed substantially according to the perspective. Our study underlines that the health-economic perspective of CEAs on interventions for panic disorder must be chosen carefully in order to avoid inappropriate choices in research priorities

Design of an RCT on cost-efectiveness of group schema therapy versus individual schema therapy for patients with Cluster-C personality disorder: the QUEST-CLC study protocol

Background Given the high prevalence of Cluster-C Personality Disorders (PDs) in clinical populations, disease burden, high societal costs and poor prognosis of comorbid disorders, a major gain in health care can be achieved if Cluster-C PDs are adequately treated. The only controlled cost-effectiveness study published so far found Individual Schema Therapy (IST) to be superior to Treatment as Usual (TAU). Group ST (GST) might improve cost-effectiveness as larger numbers can be treated in (>50%) less time compared to IST. However, to date there is no RCT supporting its (cost-) effectiveness. The overall aim of this study is to assess the evidence for GST for Cluster-C PDs and to improve treatment allocation for individual patients. Three main questions are addressed: 1) Is GST for Cluster-C PDs (cost-) effective compared to TAU? 2) Is GST for Cluster-C PDs (cost-) effective compared to IST? 3) Which patient-characteristics predict better response to GST, IST, or TAU? Methods In a multicenter RCT, the treatment conditions GST, IST, and TAU are compared in 378 Cluster-C PD patients within 10 sites. GST and IST follow treatment protocols and are completed within 1 year. TAU is the optimal alternative treatment available at the site according to regular procedures. Severity of the Cluster-C PD is the primary outcome, assessed with clinical interviews by independent raters blind for treatment. Functioning and wellbeing are important secondary outcomes. Assessments take place at week 0 (baseline), 17 (mid-GST), 34 (post-GST), 51 (postbooster sessions of GST), and 2 years (FU). Patient characteristics predicting better response to a specifc treatment are studied, e.g., childhood trauma, autistic features, and introversion. A tool supporting patients and clinicians in matching treatment to patient will be developed. An economic evaluation investigates the cost-effectiveness and costutility from a societal perspective. A process evaluation by qualitative methods explores experiences of participants, loved ones and therapists regarding recovery, quality of life, and improving treatment. Discussion This study will determine the (cost-)effectiveness of treatments for Cluster-C PDs regarding treatment type as well as optimal matching of patient to treatment and deliver insight into which aspects help Cluster-C-PD patients recover and create a fulfilling life. Trial registration Dutch Trial Register: NL9209. Registered on 28-01-2021

The Relative Importance of Education and Criminal Justice Costs and Benefits in Economic Evaluations

Objectives Mental and behavioural disorders (MBDs) and interventions targeting MBDs lead to costs and cost savings in the healthcare sector, but also in other sectors. The latter are referred to as intersectoral costs and benefits (ICBs). Interventions targeting MBDs often lead to ICBs in the education and criminal justice sectors, yet these are rarely included in economic evaluations. This study aimed to investigate the attitudes held by health economists and health technology assessment experts towards education and criminal justice ICBs in economic evaluations and to quantify the relative importance of these ICBs in the context of MBDs. Methods An online survey containing open-ended questions and two best–worst scaling object case studies was conducted in order to prioritise a list of 20 education ICBs and 20 criminal justice ICBs. Mean relative importance scores for each ICB were generated using hierarchical Bayes analysis. Results Thirty-nine experts completed the survey. The majority of the respondents (68%) reported that ICBs were relevant, but only a few (32%) included them in economic evaluations. The most important education ICBs were “special education school attendance”, “absenteeism from school”, and “reduced school attainment”. The most important criminal justice ICBs were “decreased chance of committing a crime as a consequence/effect of mental health programmes/interventions”, “jail and prison expenditures”, and “long-term pain and suffering of victims/victimisation”. Conclusions This study identified the most important education and criminal justice ICBs for economic evaluations of interventions targeting MBDs and suggests that it could be relevant to include these ICBs in economic evaluations

Correction to: Design of an international multicentre RCT on group schema therapy for borderline personality disorder

Correction to: BMC Psychiatry 14, 319 (2014)..

The impact of the Trauma Triage App on pre-hospital trauma triage: design and protocol of the stepped-wedge, cluster-randomized TESLA trial

Abstract Background Field triage of trauma patients is crucial to get the right patient to the right hospital within a particular time frame. Minimization of undertriage, overtriage, and interhospital transfer rates could substantially reduce mortality rates, life-long disabilities, and costs. Identification of patients in need of specialized trauma care is predominantly based on the judgment of Emergency Medical Services professionals and a pre-hospital triage protocol. The Trauma Triage App is a smartphone application that includes a prediction model to aid Emergency Medical Services professionals in the identification of patients in need of specialized trauma care. The aim of this trial is to assess the impact of this new digital approach to field triage on the primary endpoint undertriage. Methods The Trauma triage using Supervised Learning Algorithms (TESLA) trial is a stepped-wedge cluster-randomized controlled trial with eight clusters defined as Emergency Medical Services regions. These clusters are an integral part of five inclusive trauma regions. Injured patients, evaluated on-scene by an Emergency Medical Services professional, suspected of moderate to severe injuries, will be assessed for eligibility. This unidirectional crossover trial will start with a baseline period in which the default pre-hospital triage protocol is used, after which all clusters gradually implement the Trauma Triage App as an add-on to the existing triage protocol. The primary endpoint is undertriage on patient and cluster level and is defined as the transportation of a severely injured patient (Injury Severity Score ≥ 16) to a lower-level trauma center. Secondary endpoints include overtriage, hospital resource use, and a cost-utility analysis. Discussion The TESLA trial will assess the impact of the Trauma Triage App in clinical practice. This novel approach to field triage will give new and previously undiscovered insights into several isolated components of the diagnostic strategy to get the right trauma patient to the right hospital. The stepped-wedge design allows for within and between cluster comparisons. Trial registration Netherlands Trial Register, NTR7243. Registered 30 May 2018, https://www.trialregister.nl/trial/7038