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Per governare i tempi di attesa delle prestazioni è imprescindibile utilizzare i dati amministrativi nella pianificazione dell'offerta e nel governo della domanda di servizi. L'articolo illustra l'esperienza della ricerca-intervento realizzata dall'Azienda Sanitaria dell'Alto Adige per la stima dei fabbisogni futuri e l'analisi retrospettiva dei consumi della specialistica ambulatoriale. Viene presentato il modello quantitativo predittivo sviluppato dall'azienda per la definizione del fabbisogno di prestazioni con dettaglio per singola prestazione, e vengono esposte le scelte strategiche aziendali per ridurre i tempi di attesa. Rispetto ad alcune prestazioni di particolare rilevanza sono invece proposte analisi retrospettive per verificare l'appropriatezza dei consumi, con particolare riferimento agli indici di consumo per area di residenza, MMG, o fasce di età; alla mobilità intraprovinciale; alle modalità di accesso alle prestazioni; ai codici di priorità. Tale approccio si presta a esser facilmente applicabile ad altre aziende sul territorio italiano data la semplicità dello strumento e la crescente disponibilità e granularità di dati sul consumo di prestazioni sanitarie a disposizione delle aziende.

Resource modeling aims to explicitly quantify the effects of adopting new health care technologies in settings with capacity-related constraints. The aim of this analysis was to use resource modeling to explore the effects of the uptake of first-line treatment with daratumumab on wait lists and wait times in patients with untreated multiple myeloma. Two formulations were compared: the standard IV formulation (DARA-IV) and a recently approved SC formulation (DARA-SC).First, semi-structured interviews at six oncologic centers were used to retrieve data on the management of patients given a DARA-IV regimen. Second, a discrete event simulation (DES) model was built to estimate the effects on resource consumption, wait lists, and wait times in scenarios with different incident numbers of patients treated with either DARA-IV or DARA-SC.In all of the simulated scenarios with more incident patients initiated on first-line treatment with DARA-IV, the actual capacity of infusion chairs was not enough to meet the demand, leading to increases in wait times and wait lists. In the highest-demand scenario, 17 more infusion chairs per center would be required to avoid such increases. Treatment with DARA-SC would allow centers to meet the demand with their actual capacity.DES modeling can effectively be used to formally explore the effects of different formulations on the use of limited resources, wait lists, and wait times at the facility level. Based on the findings from this analysis, DARA-SC may free up resources and prevent short- and long-term costs to infusion centers.

Health economists have written extensively on the design and implementation of coverage with evidence development (CED) schemes and have proposed theoretical frameworks based on cost-effectiveness modeling and value of information analysis. CED may aid decision-makers when there is uncertainty about the (cost-)effectiveness of a new health technology at the time of reimbursement. Medical devices are potential candidates for CED schemes, as regulatory regimes do not usually require the same level of efficacy and safety data normally needed for pharmaceuticals. The purpose of this research is to assess whether the actual practice of CED for medical devices in Europe meets the theoretical principles proposed by health economists and whether theory and practice can be more closely aligned. Based on decision-makers' perceptions of the challenges associated with CED schemes, plus examples from the schemes themselves, we discuss a series of proposals for assessing the desirability of schemes, their design, implementation, and evaluation. These proposals, while reflecting the practical challenges with developing CED programs, embody many of the principles suggested by economists and should support decision-makers in dealing with uncertainty about the real-world performance of devices.

The blended learning (BL) approach to training health care professionals is increasingly adopted in many countries because of high costs and disruption to service delivery in the light of severe human resource shortage in low resource settings. The Covid-19 pandemic increased the urgency to identify alternatives to traditional face-to-face (f2f) education approach. A four-day f2f antenatal care (ANC) and postnatal care (PNC) continuous professional development course (CPD) was repackaged into a 3-part BL course; 1) self-directed learning (16 hours) 2) facilitated virtual sessions (2.5 hours over 3 days) and 3) 2-day f2f sessions. This study assessed the feasibility, change in healthcare providers’ knowledge and costs of the BL package in Nigeria, Tanzania, and Kenya. A mixed methods design was used. A total of 89 healthcare professionals, were purposively selected. Quantitative data was collected through an online questionnaire and skills assessments, analyzed using STATA 12 software. Qualitative data was collected through key informant interviews and focus group discussions, analysed using thematic analysis.Majority of participants (86%) accessed the online sessions using a mobile phone from home and health facilities. The median (IQR) time of completing the self-directed component was 16 hours, IQR (8, 30). A multi-disciplinary team comprising of 42% nurse-midwives, 28% doctors, 20% clinical officers and 10% other healthcare professionals completed the BL course. Participants liked the BL approach due to its flexibility in learning, highly educative/relevant content, mixing of health worker cadres and CPD points. Aspects that were noted as challenging were related to personal log-in details and network connectivity issues during the self-directed learning and facilitated virtual sessions respectively. The blended learning approach to ANC-PNC in-service training was found to be feasible, cost saving compared to the face-to-face approach and acceptable to health care professionals in LMICs.

By using a case-study on a fall-prediction device for elderly patients with orthostatic hypotension we aim to demonstrate how the MAFEIP tool, developed as part of the European Innovation Programme on Active and Healthy Ageing (EIP on AHA), can be used to inform manufacturers on their product development based on a cost-effectiveness criterion. Secondly, we critically appraise the tool and suggest further improvements that may be needed for a larger-scale adoption of MAFEIP within and beside the EIP on AHA initiative. The model was implemented using the MAFEIP tool. Within the tool one way sensitivity analyses were performed to assess the robustness of the model against the relative effectiveness of the fall-prevention device at different price levels. The MAFEIP tool was applied to a novel fall-prediction device and used to estimate the expected cost-effectiveness and perform threshold analysis. In our case study, the device produced estimated gains of 0.035 QALYs per patient and incremental costs of £ 518 (incremental cost-effectiveness ratio £14,719). Based on the one-way sensitivity analysis, the maximum achievable price at a willingness to pay threshold of £20,000 per QALY is estimated close to £900. The MAFEIP allows to quickly create early economic models, and to explore model uncertainty by performing deterministic sensitivity analysis for single parameters. However, the integration within the MAFEIP of common analytical tools such as probabilistic sensitivity analysis and Value of information would greatly contribute to its relevance for evaluating innovative technologies within and beside the EIP on AHA initiative.

Objectives A recent debate in health economics and outcomes research community identified option value as one of the elements warranting consideration in the assessment of medical technologies. To conduct a scoping review of contributions on option value in the healthcare sector and identify relevant conceptual aspects and methods used to incorporate it in standard economic evaluations. Methods A systematic search was conducted up to July 2020 to identify contributions from electronic bibliographic database and gray literature. Data on the proposed definitions of option value, theoretical implications of its use in economic evaluations, and methods used to estimate it were extracted and analyzed. Results We found 57 eligible studies. Three different definitions emerged: insurance value, real option value, and option value of survival. Focusing on the latter (24 studies), we analyzed in depth 8 empirical applications across 7 therapeutic areas. The most relevant methodological challenges were on the perspective used in economic evaluations and how to robustly manage forecasting uncertainty, update cost-effectiveness thresholds, and avoid double-counting issues. For empirical studies assessing the total value of the technology, including option value, estimates ranged from +7% to +469% of its conventional value. Conclusions This review synthesizes theoretical and empirical aspects on option value of healthcare technologies and proposes a terminology to distinguish 3 different concepts identified. Future work should focus primarily on agreeing on whether option value should be included in economic evaluations and, if so, on developing and validating reliable methods for its ex-ante estimation.

Experiences with coverage with evidence development (CED) schemes are fairly limited in Central and Eastern European (CEE) countries, which are usually late adopters of new health technologies. Our aim was to put forward recommendations on how CEE health technology assessment bodies and payer organizations can apply CED to reduce decision uncertainty on reimbursement of medical devices, with a particular focus on transferring the structure and data from CED schemes in early technology adopter countries in Western Europe. Structured interviews on the practices and feasibility of transferring CED schemes were conducted and subsequently, a draft tool for the systematic classification of decision alternatives and recommendations was developed. The decision tool was reviewed in a focus group discussion and validated within a wider group of CEE experts in a virtual workshop. Transferability assessment is needed in case of (1) joint implementation of a CED scheme; (2) transferring the structure of an existing CED scheme to a CEE country; (3) reimbursement decisions that are linked to outcomes of an ongoing CED scheme in another country and (4) real-world evidence transferred from completed CED schemes. Efficient use of available resources may be improved by adequately transferring evidence and policy tools from early technology adopter countries.

Si l’on parle aujourd’hui de l’inondation de 1966 à Florence, on ne le doit qu’à l’entêtement des Florentins qui, bien qu’ayant déjà expérimenté trois fois « quelle était la force du vindicatif Arno, voulurent toutefois en garder auprès de leurs maisons une partie plus grande encore, en réduisant à bon terme, autour de 1324, la troisième et jusqu’alors plus ample enceinte de la cité ». La Bibliothèque nationale vue de la Piazza Poggi Cliché Adriano Bartolozzi, coll. Archives photographiques ...

Objectives Medical devices are potentially good candidates for coverage with evidence development (CED) schemes, as clinical data at market entry are often sparse and (cost-)effectiveness depends on real-world use. The objective of this research was to explore the diffusion of CED schemes for devices in Europe, and the factors that favour or hamper their utilization. Methods We conducted structured interviews with 25 decision-makers from 22 European countries to explore the characteristics of existing CED programmes for devices, and how decision makers perceived 13 pre-identified challenges associated with initiating and operating CED schemes for devices. We also collected data on individual schemes that were either initiated or still ongoing in the last 5 years. Results We identified seven countries with CED programmes for devices and 78 ongoing schemes. The characteristics of CED programmes varied across countries, including eligibility criteria, roles and responsibilities of stakeholders, funding arrangements, and type of decisions being contemplated at the outset of each scheme. We observed a high variability in how decision makers perceived CED-related challenges possibly reflecting country-specific arrangements and different experiences with CED. One general finding across all countries was that relatively little attention was paid to the evaluation of schemes, both during and at their completion. Conclusions CED programmes for devices with different characteristics exist in Europe. Decision-makers’ perceptions differ on the challenges associated with these schemes. More exchange of knowledge and experience will help decision makers anticipate the likely challenges in CED schemes for devices, and to learn from good practices existing elsewhere.

Differing contexts have greatly influenced HTA development in various countries, with considerable effort recently made by international HTA networks (e.g., EUnetHTA) and the European Union (EU) to make HTA a more coherent, equal, and efficient process. Medical devices (MDs) present particular challenges for HTA because of frequent, rapid innovation, outcomes influenced by end-user competence, dynamic pricing and often low-quality scientific evidence. Our objective is to describe the development, structure and governance of a National HTA Program for MDs (PNHTADM) in Italy, a highly participatory, stakeholder-engaged, evidence-based process to reform a fragmented system of appraisal and approval. Based largely on EUnetHTA methods, the resulting process delineates a standardized system for proposing MDs by any stakeholders, accrediting HTA producers, setting criteria for prioritization and appraisals, and innovatively linking recommendations with coverage, reimbursement and procurement of MDs. Expected benefits include reduced disparities in pricing and reimbursement policies and improved access to new technologies across 21 regional healthcare systems in Italy's decentralized, universal system, complete with provisions to require additional evidence collection and centrally monitor diffusion. Though devised for Italy, the design, resources and underlying analysis provide a framework for other nations seeking to consolidate HTA initiatives, particularly in light of new EU regulation.

INTRODUCTION: Performance-based risk-sharing agreements (PBRSAs), between payers, health care providers, and technology manufacturers can be useful when there is uncertainty about the (cost-) effectiveness of a new technology or service. However, they can be challenging to design and implement. AREAS COVERED: A total of 18 performance-based agreements were identified through a literature review. All but two of the agreements identified were pay-for-performance schemes, agreed between providers and payers at the national level. No examples were found of agreements between health care providers and manufacturers at the local level. The potential for these local agreements was illustrated by hypothetical case studies of water quality management and an integrated chronic kidney disease program. EXPERT OPINION: Performance-based risk-sharing agreements can work to the advantage of patients, health care providers, payers, and technology manufacturers, particularly if they facilitate the introduction of technologies or systems of care that might not have been introduced otherwise. However, the design, conduct, and implementation of PBRSAs in renal care pose a number of challenges. Efforts should be made to overcome these challenges so that more renal care patients can benefit from technological advances and new models of care.

Early Feasibility Studies (EFS) are among the pre-market clinical investigations allowed by the International Standard for Clinical investigation of medical devices (MD) for human subjects. The Food and Drug Administration (FDA) introduced an EFS program in the US in 2013. The European Union (EU) MD Regulation, that entered into force in May 2021, opened the possibility of EFS in the EU. However, European countries at present have no standardized procedural framework for EFS. In this paper, we address the desirability of a European EFS program.Characteristics of EFS conducted so far are reviewed, and perceptions of an expert, multidisciplinary panel of key stakeholders are explored regarding desirability and feasibility of a European EFS program and critical factors favoring or hampering its implementation.Implementing an EFS program in the EU would contribute to creating a favorable environment for early-stage clinical investigations, with positive effects on the quality and timeliness of clinical evidence for novel MDs, and attractiveness of the European system for pre- and post-market clinical research. Based on discussion with experts, also leveraging on the US experience, three dimensions should be considered for effective design and implementation: process, resources, and ethical issues.

In the drive towards faster patient access to treatments, health technology assessment (HTA) agencies are increasingly faced with reliance on evidence from surrogate endpoints, leading to increased decision uncertainty. This study undertook an updated survey of methodological guidance for using surrogate endpoints across international HTA agencies. We reviewed HTA and economic evaluation methods guidance from European, Australian and Canadian HTA agencies. We considered how guidelines addressed the methods for handling surrogate endpoints, including (1) level of evidence, (2) methods of validation, and (3) thresholds of acceptability. Across the 73 HTA agencies surveyed, 29 (40%) had methodological guidelines that made specific reference to consideration of surrogate outcomes. Of the 45 methods documents analysed, the majority [27 (60%)] were non-technology specific, 15 (33%) focused on pharmaceuticals and three (7%) on medical devices. The principles of the European network for Health Technology Assessment (EUnetHTA) guidelines published in 2015 on the handling of surrogate endpoints appear to have been adopted by many European HTA agencies, i.e. preference for final patient-relevant outcomes and reliance on surrogate endpoints with biological plausibility and epidemiological evidence of the association between the surrogate and final endpoint. Only a small number of HTA agencies (UK National Institute for Care and Excellence; the German Institute for Medical Documentation and Information and Institute for Quality and Efficiency in Health Care; the Australian Pharmaceutical Benefits Advisory Committee; and the Canadian Agency for Drugs and Technologies in Health) have developed more detailed prescriptive criteria for the acceptance of surrogate endpoints, e.g. meta-analyses of randomised controlled trials showing strong association between the treatment effect on the surrogate and final outcomes. As the decision uncertainty associated with reliance on surrogate endpoints carries a risk to patients and society, there is a need for HTA agencies to develop more detailed methodological guidance for consistent selection and evaluation of health technologies that lack definitive final patient-relevant outcome evidence at the time of the assessment.

In this commentary, we discuss early stage assessments of innovative medical technologies both in terms of methods applied as well as their use in healthcare decision-making. We argue that cost-effectiveness alone may be too reductive if taken as the only decision rule, and it would benefit from being used within a broader evaluation framework. We discuss innovative methods which may contribute to better estimate the potential costs and consequences of a technology in the absence of solid clinical data, as frequently the case in early assessments. Finally, we comment on the potential synergies which may take place should early economic models be used not only by technology developers alone but as a negotiating base during early dialogues with health technology assessment (HTA) bodies.

Payers and manufacturers can disagree on the appropriate level of evidence that is required for new medical devices, resulting in high societal costs due to decisions taken with sub‐optimal information. A cost‐effectiveness model of a hypothetical total artificial heart was built using data from the literature and the (simulated) results of a pivotal study. The expected value of perfect information (EVPI) was calculated from both the payer and manufacturer perspectives, using net monetary benefit and the company's return on investment respectively. A function was also defined, linking effectiveness to market shares. Additional constraints such as a minimum clinical difference or maximum budget impact were introduced into the company's decisions to simulate additional barriers to adoption. The difference in the EVPI between manufacturers and payers varied greatly depending on the underlying decision rules and constraints. The manufacturer's EVPI depends on the probability of being reimbursed, the uncertainty on the (cost‐)effectiveness of the technology, as well as other parameters relating to initial investments, operating costs and market dynamics. The use of Value of information for both perspectives can outline potential misalignments and can be particularly useful to inform early dialogs between manufacturers and payers, or negotiations on conditional reimbursement schemes.

Health economic modeling of novel technology at the early stages of a product lifecycle has been used to identify technologies that are likely to be cost-effective. Such early assessments are challenging due to the potentially limited amount of data. Modelers typically conduct uncertainty analyses to evaluate their effect on decision-relevant outcomes. Current approaches, however, are limited in their scope of application and imposes an unverifiable assumption, i.e., uncertainty can be precisely represented by a probability distribution. In the absence of reliable data, an approach that uses the fewest number of assumptions is desirable. This study introduces a generalized approach for quantifying parameter uncertainty, i.e., probability bound analysis (PBA), that does not require a precise specification of a probability distribution in the context of early-stage health economic modeling. We introduce the concept of a probability box (p-box) as a measure of uncertainty without necessitating a precise probability distribution. We provide formulas for a p-box given data on summary statistics of a parameter. We describe an approach to propagate p-boxes into a model and provide step-by-step guidance on how to implement PBA. We conduct a case and examine the differences between the status-quo and PBA approaches and their potential implications on decision-making.

IntroductionAn iterative, life-cycle approach to the evaluation of healthcare technologies requires that clinical and economic evidence is collected since the initial stages of diffusion. Nevertheless, early cost-effectiveness models are challenging mainly due to the difficulties in estimating model parameters and faithfully characterizing parameter uncertainty. This is especially true with AI-based diagnostics, where attribution of effects on costs and patient-relevant outcomes is more challenging. Empirical applications of early-models are useful to identify the main challenges of iterative modelling and provide recommendations on best-practices. Here, we reported on a case study on a machine learning-derived hypotension predictive index (HPI), that predicts the onset of intraoperative hypotension and trigger corrective measures.MethodsA hybrid decision-tree/Markov model was developed comparing an HPI-based intervention protocol to standard-of-care intervention protocol during gynecological procedures. A short-term component of the model was populated using data from individual patients collected at one hospital in Italy. An historical control group was also defined using propensity score matching. Long-term costs and consequences of HPI were modelled using secondary data. A probabilistic version of the headroom approach was used to determine the maximum achievable price of HPI based on available evidence. Value of Information analysis was also conducted to identify the parameters that contribute the most to the overall uncertainty, and to identify optimal future study designs. Extensive deterministic and probabilistic sensitivity analyses were conducted to characterize the uncertainty over the cost-effectiveness of HPI.ResultsThe preliminary results of the analysis suggest that HPI has potential to improve patients’ outcomes and generate efficiency gains by reducing hypotension events and permanent complications, such as acute kidney injury. The link between reduction in hypotension and the rate of complications, or the long-term effects on healthcare costs and patients’ quality of life are the parameters that contribute the most to model uncertainty.ConclusionsEarly cost-effectiveness models are a valuable tool to inform further product development and evidence requirements, but characterization of uncertainty and transparency in modelling assumptions are key.

Introduction: Specific guidance and examples for health technology assessment (HTA) of medical devices are scarce in medical device development. A more intense dialogue of competent authorities, HTA agencies, and manufactures may improve evidence base on clinical and cost-effectiveness. Especially as the new Medical Device Regulation requires more clinical evidence. Methods: We explore the perceptions of manufacturers, competent authorities, and HTA agencies towards such dialogues and investigate how they should be designed to accelerate the translational process from development to patient access using semi-structured interviews. We synthesized the evidence from manufacturers, competent authorities, and HTA agencies from 14 different jurisdictions across Europe. Results: Eleven HTA agencies, four competent authorities, and eight manufacturers of high-risk devices expressed perceptions on the current situation and the expected development of three types of early dialogues. Discussion: The MDR has to be taken into account when designing the early dialogue processes. Transferring insights from medicinal product regulation is limited as the regulatory pathways differ substantially. Conclusion: Early dialogues promise to accelerate the translational process and to provide faster access to innovative medical devices. However, health policy-makers should promote and fully establish regulatory and HTA early dialogues before introducing parallel early dialogues of regulatory, HTA agencies, and manufacturers. For initiating change, the legislator must create the legal basis and set the appropriate incentives for manufacturers.

Objectives Early rescue surfactant therapy using less invasive surfactant administration (LISA) can reduce the need for mechanical ventilation and avoid complications in preterm infants with respiratory distress syndrome. The purpose of this study was to estimate the budget impact of LISA compared with management based on continuous positive airway pressure (CPAP) alone and rescue surfactant therapy in case of CPAP failure. Methods A budget impact model was built comparing LISA with CPAP alone in order to estimate the potential resource consumption and budget impact from the perspective of the National Health Service in England. A literature review was conducted to populate the model. Deterministic and probabilistic sensitivity analyses were conducted to characterise the existing uncertainty and to explore the contribution of individual model parameters to the overall budget impact. Results Early rescue with LISA is expected to reduce resource consumption and costs compared with conservative therapy based on CPAP alone for preterm infants born at 25–32 weeks gestation. Savings are higher for preterm infants of 25–28 weeks (expected budget impact −£5146 per case, 95% credible interval (CrI) −£22 403 to £13, probability of being cost saving 97.4%) than for preterm infants of 29–32 weeks (−£176, 95% CrI −£4279 to £339, probability of being cost saving 85%). The impact of bronchopulmonary dysplasia (BPD) and intraventricular haemorrhage on resource consumption and the expected reduction in the incidence of BPD with LISA are the most influential parameters on the budget. Conclusions Early rescue with LISA used in preterm infants with respiratory distress syndrome and fraction of inspired oxygen ≥0.3 is expected to be cost saving compared with management based on CPAP alone, particularly in those born at 25–28 weeks gestation.

Background\ud \ud : Nutrition interventions have specific features that might warrant modifications to the methods used for economic evaluations of healthcare interventions.\ud \ud \ud Aim\ud \ud : The aim of the article is to identify these features and when they challenge the use of cost-utility analysis (CUA).\ud \ud \ud Methods\ud \ud : A critical review of the literature is conducted and a 2 by 2 classification matrix for nutrition interventions is proposed based on 1) who the main party responsible for the implementation and funding of the intervention is; and 2) who the target recipient of the intervention is. The challenges of conducting economic evaluations for each group of nutrition interventions are then analysed according to four main aspects: attribution of effects, measuring and valuing outcomes, inter-sectorial costs and consequences and equity considerations.\ud \ud \ud Results and conclusions\ud \ud : CUA is appropriate for nutrition interventions when they are funded from the healthcare sector, have no (or modest) spill-overs to other sectors of the economy and have only (or mainly) health consequences. For other interventions, typically involving different government agencies, with cost implications for the private sector, with important wellbeing consequences outside health and with heterogeneous welfare effects across socio-economic groups, other economic evaluation methods need to be developed in order to offer valid guidance to policy making. For these interventions, checklists for critical appraisal of economic evaluations may require some substantial changes.

Artificial Intelligence (AI) systems using symptoms/signs to detect respiratory diseases may improve diagnosis especially in limited resource settings. Heterogeneity in such AI systems creates an ongoing need to analyse performance to inform future research. This systematic literature review aimed to investigate performance and reporting of diagnostic AI systems using machine learning (ML) for pneumonia detection based on symptoms and signs, and to provide recommendations on best practices for designing and implementing predictive ML algorithms. This article was conducted following the PRISMA protocol, 876 articles were identified by searching PubMed, Scopus, and OvidSP databases (last search 5th May 2021). For inclusion, studies must have differentiated clinically diagnosed pneumonia from controls or other diseases using AI. Risk of Bias was evaluated using The STARD 2015 tool. Information was extracted from 16 included studies regarding study characteristics, ML-model features, reference tests, study population, accuracy measures and ethical aspects. All included studies were highly heterogenous concerning the study design, setting of diagnosis, study population and ML algorithm. Study reporting quality in methodology and results was low. Ethical issues surrounding design and implementation of the AI algorithms were not well explored. Although no single performance measure was used in all studies, most reported an accuracy measure over 90%. There is strong evidence to support further investigations of ML to automatically detect pneumonia based on easily recognisable symptoms and signs. To help improve the efficacy of future research, recommendations for designing and implementing AI tools based on the findings of this study are provided.

Objectives: Coverage with evidence development (CED) schemes are particularly relevant for medical devices (MDs), since clinical evidence is often limited at the time of launch and their long-term (cost- ) effectiveness heavily depends on how they are adopted into routine clinical practice. The objective of this study was to identify and describe the challenges that payers and manufacturers might face when assessing the desirability of, choosing the research design for, implementing, and evaluating CED schemes for MDs. Methods: A systematic literature review was performed on six databases following PRISMA guidelines. Two independent reviewers assessed the eligibility of studies based on predefined criteria and extracted data from the included articles by using a pre-defined extraction template. The data were synthesised in a narrative review. Results: The systematic search yielded 4293 articles of which 27 were eligible for inclusion. We identified 20 challenges that are associated with CED schemes for MDs. Five of these challenges relate directly to the characteristics of MDs, and hence are specific to MDs. These challenges concern deciding on whether a CED scheme is required, understanding the relevant uncertainties and risks, identifying meaningful out- comes, defining an adequate duration for a scheme, and market entry of new technologies. Conclusions: Payers and manufacturers of MDs have to address the identified challenges to improve a CED scheme’s chance of success. This can be further improved by public sharing of information about the outcome of applied schemes and way in which stakeholders have addressed the challenges they faced when applying a CED scheme.

Managing the adoption and diffusion of technological innovation is a key challenge for healthcare systems. In 2015, Italy has started designing and implementing a National Health Technology Assessment (HTA) Programme for Medical Devices (MDs), a network aimed at promoting the use of HTA tools, and safety, effectiveness and cost-effectiveness principles in the decision-making process of medical technologies. Since 2017, all the relevant stakeholders involved in HTA (i.e., patients and citizens’ representatives, scientific organizations, industry, healthcare organizations, academic researchers) are supporting a Steering Committee active at the Ministry of Health in the design and implementation of the Programme. Several working groups were established, one of them - based on a review of best practices - was instructed (i) to develop methods and procedures to integrate the results of HTA into decisions of procurement and clinical pathways and (ii) to propose a purchase request form template to be used by health care professionals. The final goal of the HTA Program is to reduce the heterogeneity across practices which translate into uneven access to innovative health technologies. This work provides an overview of the rationale and participatory process undertaken in Italy, and illustrates the working group main findings and recommendations.

Health technology assessment (HTA) is a recognized paradigm used worldwide to support funding, coverage, reimbursement, and, recently, procurement decisions globally. In its bare essence, the HTA paradigm supports systematic generation and collection of the evidence to understand the value of new and existing technologies in order to inform decision-making, at different levels, in health care. HTA appraisals are commonly structured around several dimensions ranging from the health problem addressed, the technology’s safety and effectiveness profiles, and its value for money to other aspects related to the expected organizational, ethical, social, and legal issues associated with the use of the technology within the health system. Several countries have adopted a formal and structured process for the HTA of innovative health technologies including initial identification and priority setting, the methods and processes for the assessment and appraisal phases, and final dissemination of results and translation into policy.

Objectives:Current health technology assessment (HTA) methods guidelines for medical devices may benefit from contributions by biomedical and clinical engineers. Our study aims to: (i) review and identify gaps in the current HTA guidelines on medical devices, (ii) propose recommendations to optimize the impact of HTA for medical devices, and (iii) reach a consensus among biomedical engineers on these recommendations.Methods:A gray literature search of HTA agency Web sites for assessment methods guidelines on devices was conducted. The International Federation of Medical and Biological Engineers (IFMBE) then convened a structured focus group, with experts from different fields, to identify potential gaps in the current HTA guidelines, and to develop recommendations to fill these perceived gaps. The thirty recommendations generated from the focus group were circulated in a Delphi survey to eighty-five biomedical and clinical engineers.Results:Thirty-two panelists, from seventeen countries, participated in the Delphi survey. The responses showed a strong agreement on twenty-seven of thirty recommendations. Some uncertainties remain about the methods to accurately assess the effectiveness and safety, and interoperability of a medical device with other devices or within the clinical setting.Conclusions:As medical devices differ from drug therapies, current HTA methods may not accurately reflect the conclusions of their assessment. Recommendations informed by the focus group discussions and Delphi survey responses aimed to address the perceived gaps, and to provide a more integrated approach in medical device assessments in combining engineering with other perspectives, such as clinical, economic, patient, human factors, ethical, and environmental.

Patient-reported outcomes (PROs) are any report of the status of a patient's health condition that comes directly from the patient (or in some cases from a caregiver or surrogate responder), without interpretation by a practitioner or anyone else. PROs are increasingly used as a valuable source of data in different domains of health care, including research, clinical practice, health care management, and decision making on the regulation, coverage, and reimbursement of new technologies. Several factors must be considered when selecting which PRO measure to use to ensure their appropriate use and interpretation as well as their relevance for decision makers. The increasing availability of PRO data, its integration with other data sources, and the improvements in data analytics offer a valuable opportunity to place the patient at the center of any health care process. However, several issues need to be addressed, including interoperability, data governance, security, privacy, and ethics, to realize an effective, integrated, standardized, real-time assessment of PROs in the health care systems.

Purpose Electrochemotherapy is increasingly entering into national and international guidelines, requiring formal evaluation of treatment costs and cost-effectiveness to ensure that its uptake provides value to budget-constrained health care systems. This study analyzed the early cost-effectiveness of electrochemotherapy in patients with Stage IIIc/IV skin melanoma in clinical practice in Slovenia. The costs of electrochemotherapy were compared to those of the standard of care, consisting of palliative treatment and therapy for symptoms. Methods wThe study enrolled 23 patients treated with electrochemotherapy at the Institute of Oncology (Ljubljana, Slovenia). The mean cost of electrochemotherapy was estimated using patient-specific cost data on electrochemotherapy procedures and subsequent follow-up. Quality-adjusted life-years (QALYs) were estimated by collecting EQ-5D-3L questionnaires at baseline, after complete or partial response following the treatment, and after a relapse of skin lesions. A discrete-time Markov model was built to estimate the lifetime costs and consequences of using electrochemotherapy compared to standard of care, from the perspective of the Slovenian health care system. The analysis was conducted separately in the whole patient sample and in the subset of patients with bleeding lesions. Deterministic and probabilistic sensitivity analyses were conducted to test model assumptions and to characterize the uncertainty around model parameters. Findings In the whole patient population, electrochemotherapy for skin melanoma Stage IIIc/IV was expected to increase QALYs by 0.29 (95% credible interval [CrI], 0.10–0.50), at the higher cost of 6568 EUR (95% CrI, 4593–8928) in comparison to the standard of care. At the cost-effectiveness threshold of 20,000 EUR/QALY, the estimated probabilities of electrochemotherapy being cost-effective compared to standard of care were 0.30 and 0.91 in the whole patient sample and in patients with bleeding lesions, respectively. In the whole sample population, a 50% reduction in the price of the electrodes was expected to increase the probability of electrochemotherapy being cost-effective from 0.30 to ~0.64. Implications The findings from this cost-effectiveness analysis of data from clinical practice were based on a small sample size (ie, 23 patents), which made the subgroup of patients with bleeding lesions very small. Therefore, the findings in this patient population should be carefully interpreted.

Introduction This study systematically reviews costing studies of seasonal influenza-like illness (ILI) in high-income countries. Existing reviews on the economic impact of ILI do not report information on drug consumption and its costs, nor do they provide data on the overall cost per episode. Methods The PRISMA-P checklist was used to design the research protocol. Studies included were cost of illness analysis (COI) and modeling studies that estimated the cost of ILI episodes. Records were searched from January 2000 to December 2016 in electronic bibliographic databases including Medline, Embase, Science Direct, the Cochrane Library, the Centre for Reviews and Disseminations of the University of York, and Google scholar. References from the included studies were hand-searched for completion. Abstract screening, full-text analysis and data extraction were performed by two reviewers independently and discrepancies were resolved by discussion with a third reviewer. A standardized, pre-piloted form was used for data extraction. All costs were converted to 2015 US$ Purchasing Power Parities. Results The literature search identified 5,104 records. After abstract and title screening, 76 studies were analyzed full-text and 27 studies were finally included in the review. Full estimates of the cost per episode range from US$19 in Korea to US$323 in Germany. Particularly, the cost per episode of laboratory confirmed influenza cases was estimated between US$64 and US$73. Inpatient and outpatient services account for the majority of the costs. Differences in the estimates may reflect country-specific characteristics, as well as other study-specific features including study design, identification strategy of ILI cases, study populations and types of costs included in the analysis. Children usually register higher costs, whereas evidence for the elderly is less conclusive. Patients risk-profile, co-morbidities and complications are the other important cost-drivers. None of the papers considered appropriateness in resource use (e.g. abuse of antibiotics). Despite cost of illness studies have ultimately a descriptive role, evidence on (in)appropriateness is useful for policy-makers.

ObjectivesTo explore treatment behaviours in a cohort of Italian patients with hereditary angioedema due to complement C1-inhibitor deficiency (C1-INH-HAE), and to estimate how effects and costs of treating attacks in routine practice differed across available on-demand treatments.DesignCost analyses and survival analyses using attack-level data collected prospectively for 1 year.SettingNational reference centre for C1-INH-HAE.Participants167 patients with proved diagnosis of C1-INH-HAE, who reported data on angioedema attacks, including severity, localisation and duration, treatment received, and use of other healthcare services.InterventionsAttacks were treated with either icatibant, plasma-derived C1-INH (pdC1-INH) or just supportive care.Main outcome measuresTreatment efficacy in reducing attack duration and the direct costs of acute attacks.ResultsOverall, 133 of 167 patients (79.6%) reported 1508 attacks during the study period, with mean incidence of 11 attacks per patient per year. Only 78.9% of attacks were treated in contrast to current guidelines. Both icatibant and pdC1-INH significantly reduced attack duration compared with no treatment (median times from onset 7, 10 and 47 hours, respectively), but remission rates with icatibant were 31% faster compared with pdC1-INH (HR 1.31, 95% CI 1.14 to 1.51). However, observed treatment behaviours suggest patterns of suboptimal dosing for pdC1-INH. The average cost per attack was €1183 (SD €789) resulting in €1.58 million healthcare costs during the observation period (€11 912 per patient per year). Icatibant was 54% more expensive than pdC1-INH, whereas age, sex and prophylactic treatment were not associated to higher or lower costs.ConclusionsBoth icatibant and pdC1-INH significantly reduced attack duration compared with no treatment, however, icatibant was more effective but also more expensive. Treatment behaviours and suboptimal dosing of pdC1-INH may account for the differences, but further research is needed to define their role.

Background Unhealthy diet is a risk factor for adverse health outcomes. Reformulation of processed foods has the potential to improve population diet, but evidence of its impact is limited. The purpose of this review was to explore the impact of reformulation on nutrient intakes, health outcomes and quality of life; and to evaluate the quality of modelling studies on reformulation interventions. Methods A systematic review of peer-reviewed articles published between January 2000 and December 2017 was performed using MEDLINE, ScienceDirect, Embase, Scopus, Cochrane, and the Centre for Reviews and Dissemination of the University of York. Additional studies were identified through informal searches on Google and specialized websites. Only simulation studies modelling the impact of food reformulation on nutrient intakes and health outcomes were included. Included articles were independently extracted by 2 reviewers using a standardized, pre-piloted data form, including a self-developed tool to assess study quality. Results A total of 33 studies met the selected inclusion criteria, with 20, 5 and 3 studies addressing sodium, sugar and fats reformulation respectively, and 5 studies addressing multiple nutrients. Evidence on the positive effects of reformulation on consumption and health was stronger for sodium interventions, less conclusive for sugar and fats. Study features were highly heterogeneous including differences in methods, the type of policy implemented, the extent of the reformulation, and the spectrum of targeted foods and nutrients. Nonetheless, partial between-study comparisons show a consistent relationship between percentages reformulated and reductions in individual consumption. Positive results are also shown for health outcomes and quality of life measures, although comparisons across studies are limited by the heterogeneity in model features and reporting. Study quality was often compromised by short time-horizons, disregard of uncertainty and time dependencies, and lack of model validation. Conclusions Reformulation models highlight relevant improvements in diets and population health. While models are valuable tools to evaluate reformulation interventions, comparisons are limited by non-homogeneous designs and assumptions. The use of validated models and extensive scenario analyses would improve models’ credibility, providing useful insights for policy-makers. Review Registration A research protocol was registered within the PROSPERO database (ID number CRD42017057341). Electronic supplementary material The online version of this article (10.1186/s40795-018-0263-6) contains supplementary material, which is available to authorized users.

Over the last decades, the fast pace of innovation, high profile regulatory failures and updates in the medical devices directives, together with intrinsic or environmental characteristics of the products and industry, have turned the attention to the evaluation of medical devices. Medical devices are recognized to be different from drug technologies, however it is still not entirely clear whether these differences really matter with respect to their evaluation. In the title we ask the question of whether we are getting closer to solve the puzzle of the evaluation of medical devices. Thanks to years of research work, debates, discussion, experimentation and learning from errors, we have certainly made progress and developed a better understanding of what it is needed for a better evaluation of medical technologies. In this manuscript we present innovative approaches and promising trends, from in silico trials to early HTA, parallel submissions and, overall, adaptive pathways to evidence generation that could enable better, safer, and faster regulatory and patient access to devices. In the next future, it will be important to monitor the development and diffusion of these approaches and assess their impact. If the regulatory and HTA evaluation of medical devices is to continue to improve, establishing inter-disciplinary collaborations between clinicians and engineers, policy makers, patients and industry representatives will become key.