Recruitment

The PhD project studies the adoption of new technologies, e.g. AI, in long-term care markets with help of a survey. This survey can be linked to administrative data to evaluate how the adoption of new technologies is linked to the quality of care provision. Methods from industrial economics will be used to investigate how technology adoption will affect quality of care in the German long-term care market.

First Supervisor: Prof. Dr. Iris Kesternich

Driven by the digitalization in medicine and the health care sector, more and more unstructured data in the form of text and images are available. In this sub-project, it is planned to developed methods to estimate causal effects from such unstructured data based on Deep Learning and Foundation Models. The results will help to improve the quality of health care.

First Supervisor: Prof. Dr. Martin Spindler

An increasing number of patient-physician contacts takes place digitally / online. While this may allow faster and easier access to health care resources, it also has implications for the physician-patient relationship. For example, an online consultation offers less possibilities for using diagnostic procedures and is more restrictive with respect to the provision of preventive services during the contact. Yet, the lower barrier for access may also impact pharmaceutical prescribing and the likelihood for seeking or being prescribed sick leave. For the purpose of the research, administrative data from a statutory health insurer will be available.

First Supervisor: Prof. Dr. Tom Stargardt

We aim to analyze whether quality differences by health insurers have a measurable impact on health outcomes in a highly developed health care and insurance market such as Germany. We propose to investigate the above-mentioned research question based on the German Socio-Oeconomic-Panel (SOEP). It includes information on mortality, morbidity and standardized health outcome measures such as the SF-12 score as well as information on health care utilization.

First Supervisor: Prof. Dr. Petra Steinorth

People with chronic wounds often face significant physical and emotional impairment, resulting to a substantial need for ongoing care. In many cases, informal caregivers — typically family members — play a crucial role. Many caregivers are still working; others may have physical impairments themselves. While validated patient-reported outcomes measures exist to assess the treatment needs and quality of life of patients with chronic wounds, less is known about the needs of caregivers and their social and economic situation. The PhD student could develop a standardized questionnaire to assess the needs of informal caregivers and both benefits and burdens of their work which could then be used to identify consequences for the quality of care.

First Supervisor: Prof. Dr. Matthias Augustin

Different policy approaches are used to address the problem of provider-induced demand. With regard to hospitals, two approaches are of particular importance: Degressive pricing (introduced in 2017) and billing reviews (i.e, auditing conducted by health insures). Both approaches have received little attention in research. The aim of the research in this area is therefore to analyze the links between these policy approaches and the quality of care. In both cases, administrative data from a statutory health insurer will be available.

First Supervisor: Prof. Dr. Jonas Schreyögg

The PAIS is increasing in both children/adolescents and adults, including complex chronic diseases such as myalgic encephalomyelitis/chronic fatigue syndrome (ME/CFS) and Post-COVID syndrome. However, it is often challenging to procure the level of care needed (e.g., due to a lack of disease-related knowledge on the part of assessors, stigmatisation processes, and lack of physical capacity needed for the assessment process). Consequently, relatives assume a pivotal role in the provision of informal care for patients with PAIS. A PhD student could investigate the care-related needs and burdens of both caregivers and patients with PAIS using mixed-methods research designs.

First Supervisor: PD Dr. Christine Blome

This research project could use experimental methods to examine how reciprocity influences the behavior of physicians and patients and how it is affected by incentive mechanisms and payment systems. Building on previous experimental findings showing that physicians adjust their level of treatment effort based on patients’ decisions to purchase an out-of-pocket additional service, the study could further explore the underlying mechanisms of this interaction. The findings would have direct implications for the design of payment models and incentives for preventive care.

First Supervisor: Prof. Dr. Johanna Kokot

To increase the quality of care the government has made changes in the regulation of skilled labor quotas and personnel assessment limits. According to preliminary estimates, nursing homes will have to raise their employment levels by 36% on average. While this reform is likely to improve the quality of service provision for elderly who already have a place in a nursing home, it may also put a significant strain on the profitability of existing homes. In this project, the Ph.D. student investigate the effects of labor quotas with the use of German administrative data.

First Supervisor: Prof. Dr. Biliana Yontcheva

In healthcare, a key characteristic is that services are delivered by specialized professionals, and patients often lack the ability to assess whether they have received the appropriate quality of care. Such services are known as credence goods. Our analysis seeks to deepen the understanding of physicians' treatment decisions concerning patients' insurance status. This project is motivated by the German dual health insurance system, in which private health insurance generally provides more generous reimbursements to physicians. Our goal is to develop a credence good model tailored to this context that incorporates endogenous capacity constraints. The hypotheses derived from this model could serve as a foundation for a laboratory experiment.

First Supervisor: Prof. Dr. Mathias Kifmann

Quality indicators play an important role in the selection of family doctors. They can help patients make informed decisions by taking into account aspects such as practice organization, waiting times, patient satisfaction, and treatment outcomes. They can support healthcare systems in ensuring high-quality care and identifying areas for improvement. After systematically reviewing the current state of research, PhD students could, for example, develop a questionnaire to analyze the relevance of certain quality indicators for the choice of family doctors. Additionally, discrete choice experiments could be used for this purpose.

First Supervisor: Prof. Dr. André Hajek

The number of emergency medical services (EMS) calls in Germany is steadily increasing. A significant proportion of callers presents with low-acuity problems, for which a typical ambulance is an inefficient response; their reasons for calling EMS are not yet well understood. Identifying the factors that influence the decision to call EMS and the extent of their impact would allow the development of targeted interventions to guide potential callers to the primary care sector, enable them to self-manage, or provide more appropriate EMS resources. The factors will be elicited using interviews and their impact measured by using stated preference methods.

First Supervisor:  Prof. Dr. Hans-Helmut König