Geiger, Isabel Desirée (2023): Assessing a population’s need for healthcare: the role of multimorbidity. Dissertation, LMU München: Faculty of Medicine |
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Abstract
The need for healthcare corresponds to the level of treatable morbidity in a population and is a vital component in healthcare planning to estimate the required number of physicians. As such, the need for healthcare is a complex construct that is ought to be approximated through a robust theoretical concept, considering central indicators. However, a systematic assessment of current methodologies to estimate needs-based supply of physicians using central requirements is missing. In Germany, physician planning follows a supply-based approach using physician-to-population ratios, which are adapted with a demographic factor. In recent years, it was found that multimorbidity (the occurrence of multiple conditions in one individual) is correlated with healthcare utilisation and it has seen a steady increase in prevalence. Thus, multimorbidity as a central driver of need was declared a major challenge for health systems – including Germany – as health systems are centred on single-disease treatment approaches and fragmented in the provision of healthcare. Yet information on the distribution of multimorbid individuals is ambiguous. This thesis aims to enhance knowledge in both areas: (1) needs-based planning of physicians and (2) necessity to integrate regional multimorbidity in office-based physician planning. First, a methodological review was conducted to assess current approaches that estimate needs-based supply of physicians through a set of quality criteria while determining the role of multimorbidity. The review highlighted differences in the conceptual frameworks, data bases, modelling approaches and integration of future trends. It was also found that approaches estimating needs-based supply of physicians against quality criteria revealed several weaknesses and methodological gaps, with none of the studies meeting all quality criteria. Importantly, no incorporation of multimorbidity measures in needs-based physician planning was found. Second, a cross-sectional study was conducted to analyse regional variations of multimorbidity levels in four physician disciplines in Germany: General practitioners (GPs), neurologists, ophthalmologists, and orthopaedic specialists. Bernoulli cluster analysis was applied to detect high-rate and low-rate clusters of multimorbid patients per discipline, with the results tested for robustness through spatial autocorrelation mapping. Additionally, high-rate clusters were compared with the available supply of physicians. The study identified significant variations in the regional distribution of multimorbidity levels. High-rate clusters with varying size and location were predominantly found in central and eastern Germany for all physician groups. The comparison of high-rate clusters with supply demonstrated that almost all high-rate clusters of specialised physicians were met by average supply that exceeded the targeted coverage, but high-rate clusters of GPs were met with average supply below targeted coverage in 5 out of 11 clusters. To conclude, the methodological weaknesses identified in the systematic review can now be tackled by policymakers and scholars alike to improve future needs-based planning of physicians. Moreover, the variations in regional distribution of multimorbidity clusters highlight the importance of integrating multimorbidity measures when estimating the need for office-based physicians. These findings can be used as an additional resource to reform German physician planning as it will help to direct the planning focus on areas of increased need for healthcare services and care coordination. Given the situation in general practice, improvements in GP care should be targeted most urgently.
Item Type: | Theses (Dissertation, LMU Munich) |
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Subjects: | 600 Technology, Medicine 600 Technology, Medicine > 610 Medical sciences and medicine |
Faculties: | Faculty of Medicine |
Language: | English |
Date of oral examination: | 24. October 2023 |
1. Referee: | Sundmacher, Leonie |
MD5 Checksum of the PDF-file: | 19e63cc457c6e17beb972fdd1ae495f4 |
Signature of the printed copy: | 0700/UMD 21423 |
ID Code: | 32663 |
Deposited On: | 22. Nov 2023 11:32 |
Last Modified: | 22. Nov 2023 11:32 |