Use Of Quantitative Evidence Research Articles

Synthetic Data and Public Policy: supporting real-world policymakers with algorithmically generated data

Good policy is best developed by drawing on a wide array of high-quality evidence. The rapid growth of data science and the emergence of big datasets has materially advanced the supply and use of quantitative evidence. However, some key constraints remain, including that available datasets are still not big enough for some analytical purposes. There are also privacy and data security risks. Synthetic data is an emerging area of data science that can potentially support policy decision making through enabling research to work faster and with fewer errors while also ensuring privacy and security.

Equity in HTA: what doesn\u2019t get measured, gets marginalised

When making recommendations about the public funding of new health technologies, policy makers typically pay close attention to quantitative evidence about the comparative effectiveness, cost effectiveness and budget impact of those technologies – what we might call “efficiency” criteria. Less attention is paid, however, to quantitative evidence about who gains and who loses from these public expenditure decisions, and whether those who gain are better or worse off than the rest of the population in terms of their health – what we might call “equity” criteria. Two studies recently published in this journal by Shmueli and colleagues suggest that this efficiency-oriented imbalance in the use of quantitative evidence may have unfortunate consequences – as the old adage goes: “what gets measured, gets done”. The first study, by Shmueli, Golan, Paolucci and Mentzakis, found that health policy makers in Israel think equity considerations are just as important as efficiency considerations – at least when it comes to making hypothetical technology funding decisions in a survey. By contrast, the second study – by Shmueli alone – found that efficiency rules the roost when it comes to making real decisions about health technology funding in Israel. Both studies have limitations and potential biases, and more research is needed using qualitative methods and more nuanced survey designs to determine precisely which kinds of equity consideration decision makers think are most important and why these considerations do not appear to be given much weight in decision making. However, the basic overall finding from the two studies seems plausible and important. It suggests that health technology funding bodies need to pay closer attention to equity considerations, and to start making equity a quantitative endpoint of health technology assessment using the methods of equity-informative economic evaluation that are now available.

How Did Youth Mental Health Make It Onto Australia’s 2011 Federal Policy Agenda?

The 2011 Australian federal budget included a large investment in youth mental health and early intervention services. In this article, we focus on the critical role of agenda setting in the preceding 4 years to examine how and why these services were given such a high priority at this time. We undertook a systematic review of relevant literature, including parliamentary Hansard transcripts from the House of Representatives and Senate, the final reports of all available parliamentary committees, government policy documents, other pertinent documents held by the Commonwealth Department of Health and Aging, and media reports from five widely circulated Australian publications/news outlets. We used Kingdon’s multiple streams framework to structure analysis. We highlight three factors that were influential in getting youth mental health issues onto the policy agenda: (a) the strategic use of quantitative evidence to create a publicly visible “problem,” (b) the marshalling of the “public” to create pressure on government, and (c) the role of serendipity. Overall, we found the decision to prioritize youth mental health resulted from a combination of advocacy for a well-articulated policy solution by high-profile, influential policy entrepreneurs, and political pressure caused by an up swell of national support for mental health reform. Our findings highlight the socio-political factors that influence agenda setting and health policy formulation. They raise important ethical and strategic issues in utilizing research evidence to change policy.

Conceptualization of category-oriented likelihood ratio: a useful tool for clinical diagnostic reasoning

BackgroundIn the diagnostic reasoning process medical students and novice physicians need to be made aware of the diagnostic values of the clinical findings (including history, signs, and symptoms) to make an appropriate diagnostic decision. Diagnostic reasoning has been understood in light of two paradigms on clinical reasoning: problem solving and decision making. They advocate the reasoning strategies used by expert physicians and the statistical models of reasoning, respectively. Evidence-based medicine (EBM) applies decision theory to the clinical diagnosis, which can be a challenging topic in medical education.This theoretical article tries to compare evidence-based diagnosis with expert-based strategies in clinical diagnosis and also defines a novel concept of category-oriented likelihood ratio (LR) to propose a new model combining both aforementioned methods.DiscussionEvidence-based medicine advocates the use of quantitative evidence to estimate the probability of diseases more accurately and objectively; however, the published evidence for a given diagnosis cannot practically be utilized in primary care, especially if the patient is complaining of a nonspecific problem such as abdominal pain that could have a long list of differential diagnoses. In this case, expert physicians examine the key clinical findings that could differentiate between broader categories of diseases such as organic and non-organic disease categories to shorten the list of differential diagnoses. To approach nonspecific problems, not only do the experts revise the probability estimate of specific diseases, but also they revise the probability estimate of the categories of diseases by using the available clinical findings.SummaryTo make this approach analytical and objective, we need to know how much more likely it is for a key clinical finding to be present in patients with one of the diseases of a specific category versus those with a disease not included in that category. In this paper, we call this value category-oriented LR.

Evidence-Based Health Care: Benefits and Barriers

The evidence-based policy approach – the view that social policy ought to be based upon supporting evidence that the policy works (and why it works) – is currently in vogue. In this article we reflect upon one aspect of the evidence-based approach: the use of quantitative evidence in health care decision-making. In particular, we discuss both the potential usefulness of quantitative evidence in this context, and the barriers to the appropriate use of such evidence at the decision-making level.

The Case Method as a Strategy for Teaching Policy Analysis to Undergraduates

The case method is presented as a means to motivate students in an introductory level undergraduate course in international economics to learn theory, to teach them to apply theory, to enhance their skills in the use of quantitative evidence, and to show them the limits of economic analysis in the study of policy issues.

The Use of Quantitative Evidence in Research: A Comparative Study of Two Literatures

Random samples of 50 articles each were selected from the education and health sciences literatures to compare their use of quantitative evidence. While proportionally fewer articles from the educational literature cited quantitative evidence in support of research questions and conclusions, the study designs and approaches to analysis represented by these samples were similar. Our results do not provide convincing evidence to support the idea that educational research is somehow less “rigorous” than that of the health sciences.

The Use of Quantitative Evidence in Research: A Comparative Study of Two Literatures

The Use of Quantitative Evidence in Research: A Comparative Study of Two Literatures

Public Finance and the Industrialization of Prussia, 1815–1866: A Correction

My article on Prussian public finance in the December 1966 issue of this Journal contained some errors of calculation which partially affect the arguments I advanced there and which provide an excellent object lesson in the hasty use of quantitative evidence. After unaccountably converting current prices into constant ones by multiplication instead of division, I rushed the results off to the editors without checking them.