Robust primary care systems
Comis, Martin; Büsing, Christina Maria Katharina (Thesis advisor); Cleophas, Eva Catherine (Thesis advisor); Koster, Arie Marinus (Thesis advisor)
1. Auflage. - München : Verlag Dr. Hut (2021)
Book, Dissertation / PhD Thesis
Page(s)/Article-Nr.: xi, 235 Seiten : Illustrationen, Diagramme
Dissertation, RWTH Aachen University, 2021
Primary care systems are generally considered to be the backbone of universal health care. However, as the population ages and the number of primary care physicians declines, this foundation is starting to crumble. There result increasing access distances, waiting times, and workloads up to the point where the system's functioning can no longer be guaranteed. To counteract these developments, representatives from the government, insurances, and associations discuss an array of novel supply concepts and policy changes. This thesis aims to advance this discussion by providing suitable decision support tools, algorithms, and theoretic results. Special attention is thereby put on rural primary care systems, as these are particularly vulnerable due to their geographic-demographic facts. The resulting contributions can be categorized into three main groups and we summarize them hereinafter.The first part of this thesis addresses the fundamental question of how the quality of primary care systems can be quantified. Due to the inherent complexity and micro-level detail of primary care systems, this turns out to be a highly non-trivial problem and the predominant method of choice is therefore still an assessment of the physician-to-population ratio. To facilitate a more refined analysis, this thesis introduces the hybrid agent-based simulation model SiM-Care. SiM-Care models and tracks the micro-interactions of patients and primary care physicians on an individual level. The model thereby enables decision makers to access several performance indicators such as patient waiting times and physician utilization that can serve as a sound basis for the assessment and comparison of primary care systems. Furthermore, it becomes possible to evaluate changes in the infrastructure, patient behavior, and service design which is impossible with purely ratio-based assessments.The second part of this thesis examines mobile medical units (MMUs) for the supply of primary care services in rural environments. MMUs are customized vehicles fitted with medical equipment that are easy to relocate and therefore enable a demand-oriented and local provision of health services. Prior to their operation, MMUs necessitate a complex prelaunch strategy to ensure their effectiveness and sustainability. To devise such strategies, this thesis contributes an integrated multi-phased optimization framework. Novel to this framework is the consideration of two types of patient demands, namely patients who seek health services through a centralized appointment system as well as walk-ins who do not announce their visits. Moreover, the framework allows for the incorporation of uncertainties in both types of patient demands which was previously unconsidered.The third part of this thesis studies two matching problems that derive from the application of MMUs in primary care. It is shown that very restricted variants of these matching problems are already strongly NP-hard. Consequently, this thesis focuses on restricted graph classes and contributes a range of polynomial and pseudo-polynomial algorithms.