Lausberg, (Christine) MA BN, Wit de, (Mariska) PhD, Syurina, (Elena) PhD, Kam de, (Daniël) PhD, Boer de, (Angela) MD, PhD, Anema, (Han) MD, PhD
My name is Christine Lausberg. In December 2024, I started my PhD research at the KCVG, Amsterdam UMC/ VU location. Besides my work as a PhD candidate at the KCVG, I work as a social medical nurse at UWV in Eindhoven.
Currently, administrative burdens have a significant impact on the workload and job satisfaction of medical professionals working within insurance medicine. These burdens are increasing due to rising staff shortages and a growing demand for social medical assessments. For clients, it is crucial to receive a high-quality and accurate assessment, as well as timely clarity regarding their income and potential reintegration. The use of Artificial Intelligence (AI) can play a supportive role in addressing these challenges. Specifically, Natural Language Processing (NLP) and NLP-based support could be used to reduce the administrative burden on healthcare professionals. NLP employs various techniques to analyze spoken or written text and generate summaries, transcripts, or reports. This technology can be applied in multiple ways and has already been successfully implemented in various sectors.
The aim of this study is to explore how NLP can be used for administrative support within insurance medical practice, as well as to identify the conditions necessary for its acceptance and implementation in daily practice. We anticipate that NLP-based administrative support will enhance the overall quality and effectiveness of the social medical assessment. For example, NLP can reduce practice variation among professionals in reporting. Additionally, we expect that this technology can improve efficiency by lowering the administrative burden for insurance physicians, potentially reducing waiting times for clients through faster processing of applications.
The research consists of different sub-projects. First, an inventory will be conducted to identify existing NLP systems designed for administrative support within the curative sector, occupational health, and private insurance medicine. (Medical) professionals from these sectors will be interviewed to gain insight into their experiences with NLP systems, as well as the barriers and facilitators influencing the acceptance and implementation of such tools.
Subsequently, a systematic review will be conducted to examine the use of NLP for administrative support in healthcare at both national and international levels. In a later phase, a validation study will assess the extent to which NLP systems can be used to summarize data and reports in insurance medical practice, and whether the output is of sufficient quality, accuracy, and free from bias. Finally, the effects and cost-effectiveness of NLP-based administrative support for insurance physicians in practice will be evaluated.
By gaining insight into existing tools and the factors that influence their acceptance, as well as by focusing on thorough implementation, we hope that in the future NLP-based support can help insurance physicians to:
The qualitative study on user experiences regarding the use of Natural Language Processing (NLP) as administrative support has been completed (Sub study 1). For this, (medical) professionals from various sectors were interviewed, and their experiences with software containing an NLP component were mapped. The results have been compiled into a draft article, with the aim of submitting the final version to an international peer-reviewed journal in Q1 2026.
In Q2 2026, the second sub study will commence, namely a systematic review on the use of NLP as administrative support in healthcare at a (inter)national level. This study will examine how NLP-based systems are described in the scientific literature, with a focus on their applications, characteristics, and impact within healthcare.
Email: c.lausberg@amsterdamumc.nl
Update: 27-02-2026
