Implicit gender bias in the diagnosis and treatment of type 2 diabetes: A randomized online study.

AIMS: Implicit gender biases (IGBs) are unconscious evaluations about a person based on gender. IGBs of healthcare providers may affect medical decision making. This study investigated whether IGBs and genders of patients and general practitioners (GPs) influence diagnostics and treatment decisions in the context of diabetes type 2. METHODS: Ninety-nine GPs participated in this randomized online study. Implicit Associations Tasks were used to measure two IGBs, related to lifestyle (women have a healthier lifestyle than men) and communication (men are less communicative than women). Clinical decisions regarding type 2 diabetes were measured with vignettes that included a fictional male or female patient case. RESULTS: Female GPs exhibited a significant lifestyle IGB (p < 0.001). GPs of both genders exhibited a significant communication IGB (p < 0.001). Several associations between IGBs and clinical decisions were found. The gender of the vignette character affected several outcomes, for example GPs were less certain in the diabetes diagnosis when the character was a woman (p < 0.001). CONCLUSION: We demonstrated that GPs have IGBs and these biases as well as patient's gender affect decisions of GP's when they are solving a diabetes vignette case. Future research is needed to understand the most important consequences of IGBs in the context of type 2 diabetes.

The impact of the covid-19 pandemic on diabetes care: the perspective of healthcare providers across Europe.

AIMS: Covid-19 caused changes on the delivery of diabetes care. This study aimed to explore perceptions of healthcare providers across Europe concerning 1) the impact of covid-19 on delivery of diabetes care; 2) impact of changes in diabetes care on experienced workload; 3) experiences with video consultation in diabetes care. METHODS: Cross-sectional survey among healthcare providers in the Netherlands, United Kingdom, Turkey, Ukraine and Sweden, with a focus on primary care. RESULTS: The survey was completed by 180 healthcare providers. During the COVID-19 pandemic 57.1% of respondents provided less diabetes care and 72.8% observed a negative impact on people with diabetes. More than half of respondents (61.9%) expressed worries to some extent about getting overloaded by work. Although the vast majority considered their work meaningful (85.6%). Almost half of healthcare providers (49.4%) thought that after the pandemic video-consultation could be blended with face-to-face contact. CONCLUSIONS: Less diabetes care was delivered and a negative impact on people with diabetes was observed by healthcare providers. Despite healthcare providers' feeling overloaded, mental wellbeing seemed unaffected. Video consultations were seen as having potential. Given the remaining covid-19 risks and from the interest of proactive management of people with diabetes, these findings urge for further exploration of incorporating video consultation in diabetes care.

The introduction of a data-driven population health management approach in the Netherlands since 2019: The Extramural LUMC Academic Network data infrastructure.

Improving population health and reducing inequalities through better integrated health and social care services is high up on the agenda of policymakers internationally. In recent years, regional cross-domain partnerships have emerged in several countries, which aim to achieve better population health, quality of care and a reduction in the per capita costs. These cross-domain partnerships aim to have a strong data foundation and are committed to continuous learning in which data plays an essential role. This paper describes our approach towards the development of the regional integrative population-based data infrastructure Extramural LUMC (Leiden University Medical Center) Academic Network (ELAN), in which we linked routinely collected medical, social and public health data at the patient level from the greater The Hague and Leiden area. Furthermore, we discuss the methodological issues of routine care data and the lessons learned about privacy, legislation and reciprocities. The initiative presented in this paper is relevant for international researchers and policy-makers because a unique data infrastructure has been set up that contains data across different domains, providing insights into societal issues and scientific questions that are important for data driven population health management approaches.