Thematic Categories
The 10th Fall Research Meeting of the Wennberg International Collaborative is organized around six categories, five are specific and the sixth is general:
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Warranted and unwarranted variation in the COVID-19 pandemic
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Novel data and data linkage methods for health care evaluation
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General category for innovative research in population-based health care measurement and variation.
Warranted and unwarranted variation in the COVID-19 pandemic
Theme leaders: Sabina Nuti and Milena Vainieri - Pisa, Italy
The COVID-19 pandemic was a shock to health care systems. Demand for acute and inpatient services increased, leading to relative shortages of ICU and general beds. Attention by patients and providers was diverted from chronic illness and elective procedures to preventative COVID measures and the care of those with acute serious illness. Many providers were forced to triage patients in both outpatient and inpatient settings. Mortality rates surged. While some of these deaths were directly attributed to COVID-19 infections, excess mortality from diffuse causes also substantially increased.
Beyond the immediate and, often obvious, effects on health care systems, COVID-19 also caused changes to the management of other domains of care, raising a number of questions including:
- In some cases the pandemic led to the reduction of geographic differences such as the variation in elective surgery procedures. What happened in the pandemic aftermath?
- To be prepared for the next pandemic or epidemic, many countries have been investing in strengthening primary health care. This will change the relationship among the settings of care. What are the implications for the measurement of geographic variation?
- The shortage of personnel (namely doctors and nurses) has been leading countries to revise the organizational model of care strengthening the skill mix strategies and the policy of task shifting towards new professions as well as towards new technologies. What is the impact on geographic variation? Are these changes opportunities or threads to manage geographic variation?
Health Care Atlases – Future prospects
Theme leader: David Goodman - Hanover, NH USA
In the past 15 years, numerous countries have developed health care atlases reporting unwarranted variation across regions, small areas, and hospitals. The scope and scale of these atlases range from single publications with a limited set of measures to sustained periodic reporting linked to research and/or clinical and policy changes. In this session, several countries will report their experiences with producing health care atlases and their impact on local and national health care systems. We will consider the future of atlases as a means to evaluate and inform health change. Some relevant questions include: Is the Atlas model sustainable? Are there new opportunities to expand data, measures, and inference? Where do we expect the field of health care evaluation to be in another decade? How can we enhance the impact of Atlas-like initiatives?
Novel data and data linkage methods for health care evaluation
Theme leader: Therese Stukel - Toronto, Canada
Population-based health care measurement across regions and providers commonly begins with the analysis of health administrative data that has been collected for billing purposes, but the scope and scale of these data differs across regions, even within the same country. Some countries have access to rich population-based data that is linkable across health care sectors and time as well as across different domains such as health, education and justice. In many places, researchers and policy analysts have access to other rich data sources that can be linked to patients such as clinical registries, patient and provider surveys, and electronic medical data (EMR). In this session, we will explore the use of novel data sources and data linkage methods to enhance our understanding of the causes and consequences of unwarranted variation.
Economic analysis of unwarranted variation examines prices, spending and costs (including travel times)
Theme leaders: Jostein Grytten - Olso, Norway | Zeynep Orr - Paris, France
Economists are often concerned about causality. The gold standard for cause-effect studies is randomized controlled experiments. For several reasons (ethical, financial and political), such experiments are difficult to carry out in studies of practice variation. Typically, these studies rely on observational data, i.e. data in which exposure is determined in a different way than random assignment. Therefore, it is a challenge to draw causal inference from any type of intervention in which observational data has been used.
Causal inference is required to answer questions such as: What is the impact of hospital payment on practice variation? What is the effect of a specific intervention (such as care protocols) in reducing variation in medical practice? To what extent does an increase in the number of beds increase variation?
For this session, we want to call for studies in which strategies for drawing causal inference from observational data have been used. We want to include studies that have used both experimental and quasi-experimental designs. Examples are difference-in-difference, regression discontinuity or instrumental variables methods. These methods can be challenging to use, and their use is not necessarily straightforward. The aim of the session is to discuss the potential benefits and limitations of these methods, as well as the results. We welcome all types of work, both work in progress and work nearly completed. If you have a draft of your work, we may be able to get somebody to give prepared comments.
Systemic causes and remedies to unwarranted variation
Theme leader: Gwyn Bevan - London, UK
Much of the research into unwarranted variation is directed at practices of physicians and surgeons or preferences of patients. We know that unwarranted variations develop in any system of health care (with differences in insurance coverage, user charges, and payments to providers). This theme explores questions of how these differences impact on unwarranted variations and changes to systems that aim to reduce them.