Search

Objectives: This study assesses the use of routinely collected claims data for managed entry agreements (MEA) in the illustrative context of German statutory health insurance (SHI) funds., Methods: Based on a nonsystematic literature review, the data needs of different MEA were identified. A value-based typology to classify MEA on the basis of these data needs was developed. The typology is oriented toward health outcomes and utilization and costs, key components of a new technology's value. For each MEA type, the suitability of claims data in establishing evidence of the novel technology's value in routine care was systematically assessed. Assessment criteria were data availability, completeness, timeliness, confidentiality, reliability, and validity., Results: Claims data are better suited to MEA addressing uncertainty regarding the utilization and costs of a novel technology in routine care. In schemes where safety aspects or clinical effectiveness are assessed, the role of claims data is limited because clinical information is not included in sufficient detail., Conclusions: The suitability of claims data depends on the source of uncertainty and, in consequence, the outcome measures chosen in the agreements. In all schemes, the validity of claims data should be judged with caution as data are collected for billing purposes. This framework may support manufacturers and payers in selecting the most suitable contract type and agreeing on contract conditions. More research is necessary to validate these results and to address remaining medical, economic, legal, and ethical questions of using claims data for MEA.

Given the multitude of newly available genetic tests in the face of limited healthcare budgets, the European Society of Human Genetics assessed how genetic services can be prioritized fairly. Using (health) benefit maximizing frameworks for this purpose has been criticized on the grounds that rather than maximization, fairness requires meeting claims (e.g. based on medical need) equitably. This study develops a prioritization score for genetic tests to facilitate equitable allocation based on need-based claims. It includes attributes representing health need associated with hereditary conditions (severity and progression), a genetic service's suitability to alleviate need (evidence of benefit and likelihood of positive result) and costs to meet the needs. A case study for measuring the attributes is provided and a suggestion is made how need-based claims can be quantified in a priority function. Attribute weights can be informed by data from discrete-choice experiments. Further work is needed to measure the attributes across the multitude of genetic tests and to determine appropriate weights. The priority score is most likely to be considered acceptable if developed within a decision process which meets criteria of procedural fairness and if the priority score is interpreted as "strength of recommendation" rather than a fixed cut-off value., (Copyright © 2014. Published by Elsevier Ireland Ltd.)

The aim of this study was to analyze influences of process- and technology-related characteristics on the outcomes of coverage decisions. Using survey data on 77 decisions from 13 countries, we examined whether outcomes differ by 14 variables that describe components of decision-making processes and the technology. We analyzed the likelihood of committees covering a technology, i.e. positive (including partial coverage) vs. negative coverage decisions. We performed non-parametric univariate tests and binomial logistic regression with a stepwise variable selection procedure. We identified a negative association between a positive decision and whether the technology is a prescribed medicine (p=0.0097). Other significant influences on a positive decision outcome included one disease area (p=0.0311) and whether a technology was judged to be (cost-)effective (p<0.0001). The first estimation of the logistic regression yielded a quasi-complete separation for technologies that were clearly judged (cost-)effective. In uncertain decisions, a higher number of stakeholders involved in voting (odds ratio=2.52; p=0.03) increased the likelihood of a positive outcome. The results suggest that decisions followed the lines of evidence-based decision-making. Despite claims for transparent and participative decision-making, the phase of evidence generation seemed most critical as decision-makers usually adopted the assessment recommendations. We identified little impact of process configurations., (Copyright © 2013 Elsevier Ireland Ltd. All rights reserved.)

Objectives: The role and impact of health technology assessment (HTA) in health policy has been widely discussed. Researchers have started to analyze how decisions on coverage of new technologies are made. Although the involvement of HTA may be an indicator of a well established decision process, this hypothesis requires validation. Also, it is not known whether HTA involvement is associated with other characteristics of decision making like participation or transparency. The primary objective of this study was to develop and test statements on the association between the publication of an HTA and coverage decision making for newborn screening tests in European Union countries., Methods: Five statements were defined on the relative role of HTA during the steps of decision processes: trigger, participation, publication, assessment, and appraisal. For this purpose, data on twenty-two decision processes in the area of newborn screening across Europe were analyzed, defined as a coverage decision for a given disorder in a specific country. Decision processes were compared by whether the decision was accompanied by the publication of an HTA report. To test differences, nonparametric statistical tests were used., Results: The decision steps of trigger, participation and publication differed between the HTA and the non-HTA groups. No clear association between HTA and assessment methods in coverage decision making was identified., Conclusions: It appeared that there is an association between HTA and coverage decision processes that are more explicit, inclusive, and transparent. It is unclear whether HTA is associated with formal evidence reviews and economic evaluations.

Objectives: It has been claimed that gene technology will induce revolutionary changes in healthcare. This paper investigates how and to what extent these changes have been economically assessed., Methods: A generic framework was developed to distinguish between methodologically similar evaluations of healthcare technology. Methodological issues and the current state of economic evidence concerning human DNA technology were extracted from publications within these groups of evaluations., Results: Economic evaluations of "healthcare consisting of gene technology" were identified primarily for in vitro diagnostics for hereditary disease and others for pharmacogenetics and molecular pathology. "Healthcare enabled by gene technology" is far more encompassing and includes, e.g., biotechnology drugs for which various health economic evaluations can be found. Yet here, the impact of gene technology intertwines with the impact of other technologies and is therefore hardly susceptible to evaluation. The fields of evaluation may be classified best according to the two dimensions "purpose" and "stage of development". Current evaluations cover screening, diagnostic and treatment technologies in investigational, new and established stages. Apart from prenatal screening, healthcare consisting of gene technology was cost saving only for genotype tests replacing continuous phenotype tests and for one pharmacogenetic test. Conclusive evidence of favourable cost-effectiveness ratios is available only for few conditions., Conclusion: Hypotheses about the impact of gene technology on healthcare must be explicit about the definition of "genetic" medicine. A general statement regarding healthcare enabled by gene technology is not possible. Based on current evidence, an era of healthcare consisting of gene technology built on widespread predictive testing is not desirable from a health economic viewpoint.

Objectives: The Human Genome Project has led to a multitude of new potential screening targets on the level of human DNA. The aim of this systematic review is to critically summarize the evidence from health economic evaluations of genetic screening in the literature., Methods: Based on an extensive explorative search, an appropriate algorithm for a systematic database search was developed. Twenty-one health economic evaluations were identified and appraised using published quality criteria., Results: Genetic screening for eight conditions has been found to be investigated by health economic evaluation: hereditary breast and ovarian cancer, familial adenomatous polyposis (FAP) colorectal cancer, hereditary nonpolyposis colorectal carcinoma (HNPCC), retinoblastoma, familial hypercholesterolemia, hereditary hemochromatosis, insulin-dependent diabetes mellitus, and cystic fibrosis. Results range from dominated to cost-saving. Population-wide genetic screening may be considered cost-effective with limited quality of evidence only for three conditions. The methodology of the studies was of varying quality. Cost-effectiveness was primarily influenced by mutation prevalence, genetic test costs, mortality risk, effectiveness of treatment, age at screening, and discount rate., Conclusions: Health economic evidence on genetic screening is limited: Only few conditions have properly been evaluated. Based on the existing evidence, healthcare decision makers should consider the introduction of selective genetic screening for FAP and HNPCC. As genetic test costs are declining, the existing evaluations may warrant updating. Especially in the case of hereditary hemochromatosis, genetic population screening may be about to turn from a dominated to a cost-effective or even cost-saving intervention.