Randomized trials are the gold standard method for inferring causality. In health services research it is often neither practical nor ethically acceptable to conduct randomized trials. However, it may be possible to infer causal effects from observational data by making use of so-called natural experiments, exploiting random variations in exposures of interest. This is the backdrop of this project, which comprise four work packages.
The first package will study the effects of practice variation, such as differences in referral practices between general practitioners, and differences in the availability of specialized primary health services between geographical areas. To date, we have published studies on the effects of general practitioner discontinuity, practice variation between physicians working in an out-of-hours setting and the consequences of a varying tendency to admit to hospital, and the effects of capacity pressure on surgery for hip fracture patients. Currently, a paper on effects of a discontinuity in the general practitioner-patient relationship on health services use is also being finalised. Under the auspices of the project, a national seminar for research into the primary healthcare service was organized in the autumn of 2022, which generated great interest. Next year, the project’s partners in Bergen will organize a continuation of this seminar.
In package two, we look at the effects of centralizing hospital services. To date, two articles have been published which concern busy hospitals and busy wards, and the effects this can have on elderly and frail patients. We are now finalizing work that looks at the importance of volume and travel time on patient safety at maternity wards in Norway. This work has been presented in preliminary form to decision makers and in professional forums. Another work that is being completed deals with quality in ambulance services, concurrency conflicts and delayed response.
The third package aims to increase our knowledge of vulnerable groups' needs for health services by studying the causal effects of mental health problems and socio-economic status on the use of health services. Here, genetic markers are mainly used as a source of exogenous variation in exposure. For example, we have published several studies on the consequences of body mass index, such as the effect on personal income, health service use and work participation.
The last package ensures user participation through collaboration with health personnel in hospitals, GPs, administrative managers in the health sector and patient organisations. We have organized seminars for skills development, as well as participated in several contexts with lectures and presentations. The project has also invested in dissemination to a wider audience. Among other things, we have published features in national and local newspapers that deal with issues surrounding research and registration of health data, and about obesity and costs in the health services. Popular science dissemination to young people has also been organized through a stand at the Forskarnatt event organised at NTNU
Questions regarding the health care system often revolve around cause and effect: Are births safer at larger hospitals than smaller? Are differences between physicians important for patient safety? Contrary to the introduction of new medications and treatment methods, organizational aspects of changes in health care services are rarely justified by randomized controlled trials, which is the primary method for assessing causal effects. Assessment of composite exposures, often involving patients with complex problems, is difficult to conduct within the rigorous frames required in such trials. Randomization is also difficult due to ethical or practical reasons associated with system level interventions. Because of this, health services research is essentially based on observational data.
We apply for funding to establish a research environment to improve causal inference in health and welfare services. The project group aims to establish a better foundation for knowledge-based decision for clinical management and policy evaluation. Utilizing state-of-the art research methodology for causal inference with observational data achieves this.
The research environment will be organized within the frame of four work packages: Work package (WP) 1: Practice variation between physicians and municipalities, WP2 centralization vs decentralization of the provision of specialized health services, WP 3 differences in health care needs for vulnerable groups and WP4 user involvment.
In this proposal, we present research designs which are receiving increased attention in health services research and epidemiology internationally. We aim to connect with other Norwegian groups with the aim of strengthening the national competence on causal inference with observational data. A strong environment for causal inference in health and welfare research at NTNU and nationally will ensure high quality evidence for decision-making and makes it possible to study a broad field of issues.