Reconciling fragmented sectors of health research regulation: toward an ecosystem of processual regulation

The delivery of good outcomes from human health research is entirely dependent on the proper functioning of the attendant regulatory systems. This article focuses on the processes of regulation themselves, and how these might be better understood, so that regulators and other stakeholders have a strong normative basis upon which to pursue the regulatory objective of achieving outcomes with maximum social value. The argument is made that the concept of ‘processual regulation’—which promotes a whole systems approach to regulation—can assist greatly in the design, implementation, and review of human health research. This moves beyond the current often-fragmented approach to regulation towards a joined-up, reflective, and responsive system that has fitness-for-purpose at its core.

Parameter Reliability and Understanding Enzyme Function

Knowledge of the Michaelis–Menten parameters and their meaning in different circumstances is an essential prerequisite to understanding enzyme function and behaviour. The published literature contains an abundance of values reported for many enzymes. The problem concerns assessing the appropriateness and validity of such material for the purpose to which it is to be applied. This review considers the evaluation of such data with particular emphasis on the assessment of its fitness for purpose.

Evolving Access to Educational Materials

The purpose of this paper is to interrogate the ways in which the selection of educational materials results in implications that impact access to these materials. This is necessary considering the evolving nature of educational materials offered by traditional publishers, and the increase in the availability of online learning materials, among those, open educational resources. I begin by reviewing the existing literature on emerging problems and barriers to learners’ access to educational materials including textbooks, online learning resources, and open educational resources. The findings from the literature review confirm that learners are now engaging with an increasingly complex ecosystem of educational materials, both print and digital, in a multitude of differing forms and formats, with various terms of use and durations of sustained access. Educators have a variety of choices to make when considering the educational materials to be used in their courses, and while fitness for purpose still dominates as the most important selection criterion, ease and persistence of access are becoming important considerations. A model which encapsulates the findings considering the variety of educational materials is presented alongside a discussion about the specific considerations for each.

Considerations for Performance Metrics of Metagenomic Next Generation Sequencing Analyses

Background: Evaluating the performance of metagenomics analyses has proven a challenge, due in part to limited ground-truth standards, broad application space, and numerous evaluation methods and metrics. Application of traditional clinical performance metrics (i.e. sensitivity, specificity, etc.) using taxonomic classifiers do not fit the “one-bug-one-test” paradigm. Ultimately, users need methods that evaluate fitness-for-purpose and identify their analyses’ strengths and weaknesses. Within a defined cohort, reporting performance metrics by taxon, rather than by sample, will clarify this evaluation.Results: For a complete assessment, estimated limits of detection, positive and negative control samples, and true positive and negative true results are necessary criteria for all investigated taxa. Use of summary metrics should be restricted to comparing results of similar, or ideally the same, cohorts and data, and should employ harmonic means and continuous products for each performance metric rather than arithmetic mean. Conclusions: Organism-centric analysis and reporting will enable clear performance assessment and meaningful comparisons between methods in evaluating fitness for purpose of metagenomic analyses with their intended applications.

A Pipeline DNA Approach Within Fitness-For-Purpose Assessments

Establishing a robust knowledge of material properties forms the basis of any FFP assessment. In light of the revised Federal Pipeline Safety Regulations in the US, operators of gas transmission pipelines are required to possess Traceable, Verifiable and Complete (TVC) records for input into FFP assessments and to support MAOP. ROSEN has been engaged by several operators to reconfirm the MAOP along the full pipeline length using the Engineering Critical Assessment (ECA) approach. This is a data integration approach using multiple ILI technologies to detect, identify and quantify the inputs required for a robust FFP assessment. A crucial aspect was the use of TVC material properties in the ECA, in which the RoMat Pipe Grade Sensor (PGS) service was used as the foundation for material property verification, ensuring accurate material properties are used in the ECA. Traditionally, ILI has not been able to provide strength data. However, with the addition of ROSEN’s Pipe Grade Sensor (PGS) technology, pipe populations; defined as a group of pipes with shared material properties and characteristics, can now be reliably identified and a strength grade assigned to each population. New NDT technologies already available on the market allow us to increase the confidence within the population assessment as well as further characterize the populations of pipes. This “Pipeline DNA” approach, incorporating both the PGS technology and in-field material property verification, ensures accurate or representative material properties are used in any future integrity studies. This paper describes the ROSEN approach to “Pipeline DNA”, and how it can be used in combination with material verification as a foundation for FFP assessments in an effort to reconfirm MAOP.

Planning and Reporting Method Validation Studies Print Email. A Supplement to the Eurachem Guide «The Fitness for Purpose of Analytical Methods»

Ukrainian translation of The Fitness for Purpose of Analytical Methods - A Laboratory Guide to Method Validation and Related Topics (2nd ed.), which was published in 2014, is offered. Since Document publication the Method Validation Working Group has identified areas where extra guidance would be appropriate. This extra guidance has been prepared in the form of supplementary documents, which should be used in conjunction with the Guide. Original Document is published on the Euracem website. https://www.eurachem.org/index.php/publications/guides/planning-validation-studies

Development and Actionability of the Dutch COVID-19 Dashboard: Descriptive Assessment and Expert Appraisal Study (Preprint)

BACKGROUND Web-based public reporting by means of dashboards has become an essential tool for governments worldwide to monitor COVID-19 information and communicate it to the public. The actionability of such dashboards is determined by their fitness for purpose—meeting a specific information need—and fitness for use—placing the right information into the right hands at the right time and in a manner that can be understood. OBJECTIVE The aim of this study was to identify specific areas where the actionability of the Dutch government’s COVID-19 dashboard could be improved, with the ultimate goal of enhancing public understanding of the pandemic. METHODS The study was conducted from February 2020 to April 2021. A mixed methods approach was carried out, using (1) a descriptive checklist over time to monitor changes made to the dashboard, (2) an actionability scoring of the dashboard to pinpoint areas for improvement, and (3) a reflection meeting with the dashboard development team to contextualize findings and discuss areas for improvement. RESULTS The dashboard predominantly showed epidemiological information on COVID-19. It had been developed and adapted by adding more in-depth indicators, more geographic disaggregation options, and new indicator themes. It also changed in target audience from policy makers to the general public; thus, a homepage was added with the most important information, using news-like items to explain the provided indicators and conducting research to enhance public understanding of the dashboard. However, disaggregation options such as sex, socioeconomic status, and ethnicity and indicators on dual-track health system management and social and economic impact that have proven to give important insights in other countries are missing from the Dutch COVID-19 dashboard, limiting its actionability. CONCLUSIONS The Dutch COVID-19 dashboard developed over time its fitness for purpose and use in terms of providing epidemiological information to the general public as a target audience. However, to strengthen the Dutch health system’s ability to cope with upcoming phases of the COVID-19 pandemic or future public health emergencies, we advise (1) establishing timely indicators relating to health system capacity, (2) including relevant data disaggregation options (eg, sex, socioeconomic status), and (3) enabling interoperability between social, health, and economic data sources.

Putting numbers to a metaphor: Soil Quality, Health or Fitness?

Soil Quality or Soil Health are terms adopted by the scientific community as a metaphor for the effects of differing land management practices on the properties and functions of soil. Many other terms and metaphors are in use that defy neat quantification: human health, for example. Our challenge is to understand the importance of using such metaphors, but without compromising the underlying scientific understanding upon which they are based. We present here an approach based on expert elicitation in the field of soil quality and management, which offers a universal way of putting numbers to the metaphor. Like humans, soils differ and so do the ways in which they become unhealthy. We structure experts’ views of the extent to which soil delivers the functions expected of it within Bayesian Belief Networks anchored by measurable properties of soil. With these networks, we deduce the value of additional data to the precision of estimates of soil quality and health and infer the likely state of soil at locations in England & Wales. We conclude that the value of soil is best scored as its fitness for purpose or its utility. Our methodology has general applicability and could be deployed elsewhere or in other disciplines.

Assessing fitness-for-purpose and comparing the suitability of COVID-19 multi-country models for local contexts and users

Background: Mathematical models have been used throughout the COVID-19 pandemic to inform policymaking decisions. The COVID-19 Multi-Model Comparison Collaboration (CMCC) was established to provide country governments, particularly low- and middle-income countries (LMICs), and other model users with an overview of the aims, capabilities and limits of the main multi-country COVID-19 models to optimise their usefulness in the COVID-19 response. Methods: Seven models were identified that satisfied the inclusion criteria for the model comparison and had creators that were willing to participate in this analysis. A questionnaire, extraction tables and interview structure were developed to be used for each model, these tools had the aim of capturing the model characteristics deemed of greatest importance based on discussions with the Policy Group. The questionnaires were first completed by the CMCC Technical group using publicly available information, before further clarification and verification was obtained during interviews with the model developers. The fitness-for-purpose flow chart for assessing the appropriateness for use of different COVID-19 models was developed jointly by the CMCC Technical Group and Policy Group. Results: A flow chart of key questions to assess the fitness-for-purpose of commonly used COVID-19 epidemiological models was developed, with focus placed on their use in LMICs. Furthermore, each model was summarised with a description of the main characteristics, as well as the level of engagement and expertise required to use or adapt these models to LMIC settings. Conclusions: This work formalises a process for engagement with models, which is often done on an ad-hoc basis, with recommendations for both policymakers and model developers and should improve modelling use in policy decision making.