Mees Mosseveld

2.7k total citations
30 papers, 1.5k citations indexed

About

Mees Mosseveld is a scholar working on Health Information Management, Public Health, Environmental and Occupational Health and General Health Professions. According to data from OpenAlex, Mees Mosseveld has authored 30 papers receiving a total of 1.5k indexed citations (citations by other indexed papers that have themselves been cited), including 9 papers in Health Information Management, 6 papers in Public Health, Environmental and Occupational Health and 5 papers in General Health Professions. Recurrent topics in Mees Mosseveld's work include Electronic Health Records Systems (8 papers), Clinical practice guidelines implementation (5 papers) and Biomedical Text Mining and Ontologies (4 papers). Mees Mosseveld is often cited by papers focused on Electronic Health Records Systems (8 papers), Clinical practice guidelines implementation (5 papers) and Biomedical Text Mining and Ontologies (4 papers). Mees Mosseveld collaborates with scholars based in Netherlands, United Kingdom and United States. Mees Mosseveld's co-authors include Johan van der Lei, Miriam Sturkenboom, Peter R. Rijnbeek, Jan H. van Bemmel, Daniel Prieto‐Alhambra, Talita Duarte‐Salles, Marc A. M. van Wijk, Francesco Lapi, David Ansell and M Alexander and has published in prestigious journals such as Circulation, Annals of Internal Medicine and Gastroenterology.

In The Last Decade

Mees Mosseveld

29 papers receiving 1.4k citations

Peers — A (Enhanced Table)

Peers by citation overlap · career bar shows stage (early→late) cites · hero ref

Name h Career Trend Papers Cites
Mees Mosseveld Netherlands 15 657 281 280 193 186 30 1.5k
Anil Jain United States 29 534 0.8× 261 0.9× 139 0.5× 162 0.8× 275 1.5× 71 2.4k
Sameer D. Saini United States 30 763 1.2× 131 0.5× 340 1.2× 66 0.3× 1.0k 5.5× 179 3.5k
Henri Leleu France 15 945 1.4× 180 0.6× 611 2.2× 26 0.1× 191 1.0× 42 1.7k
Sven Van Poucke Belgium 18 546 0.8× 184 0.7× 233 0.8× 51 0.3× 218 1.2× 49 1.3k
Melissa A. Robb United States 10 235 0.4× 139 0.5× 35 0.1× 103 0.5× 179 1.0× 12 2.2k
Changping Li China 16 291 0.4× 354 1.3× 40 0.1× 61 0.3× 299 1.6× 44 1.8k
Ryan Colvin United States 13 822 1.3× 595 2.1× 161 0.6× 27 0.1× 150 0.8× 31 1.4k
Yong Han China 24 726 1.1× 302 1.1× 34 0.1× 638 3.3× 546 2.9× 92 2.8k
Lauren A. Beste United States 26 1.7k 2.6× 98 0.3× 1.6k 5.7× 66 0.3× 203 1.1× 89 2.4k
Claire Beguin Belgium 23 328 0.5× 139 0.5× 126 0.5× 16 0.1× 370 2.0× 66 1.7k

Countries citing papers authored by Mees Mosseveld

Since Specialization
Citations

This map shows the geographic impact of Mees Mosseveld's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Mees Mosseveld with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Mees Mosseveld more than expected).

Fields of papers citing papers by Mees Mosseveld

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Mees Mosseveld. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Mees Mosseveld. The network helps show where Mees Mosseveld may publish in the future.

Co-authorship network of co-authors of Mees Mosseveld

This figure shows the co-authorship network connecting the top 25 collaborators of Mees Mosseveld. A scholar is included among the top collaborators of Mees Mosseveld based on the total number of citations received by their joint publications. Widths of edges represent the number of papers authors have co-authored together. Node borders signify the number of papers an author published with Mees Mosseveld. Mees Mosseveld is excluded from the visualization to improve readability, since they are connected to all nodes in the network.

All Works

20 of 20 papers shown
1.
Reyes, Carlen, Danielle Newby, Berta Raventós, et al.. (2024). Trends of use and characterisation of anti-dementia drugs users: a large multinational-network population-based study. Age and Ageing. 53(5). 1 indexed citations
2.
Jödicke, Annika M., Edward Burn, Maria de Ridder, et al.. (2024). Calculating daily dose in the Observational Medical Outcomes Partnership Common Data Model. Pharmacoepidemiology and Drug Safety. 33(6). e5809–e5809.
3.
Tan, Eng Hooi, Annika M. Jödicke, Mees Mosseveld, et al.. (2021). The impact of COVID-19 on population-level drug utilization of alendronate. Osteoporosis International. 1 indexed citations
4.
Hek, Karin, Linda E. Flinterman, Ron M. C. Herings, et al.. (2020). Prevalence and incidence rate of hospital admissions related to medication between 2008 and 2013 in The Netherlands. Pharmacoepidemiology and Drug Safety. 29(12). 1659–1668. 9 indexed citations
5.
Newby, Danielle, Daniel Prieto‐Alhambra, Talita Duarte‐Salles, et al.. (2020). Methotrexate and relative risk of dementia amongst patients with rheumatoid arthritis: a multi-national multi-database case-control study. Alzheimer s Research & Therapy. 12(1). 38–38. 23 indexed citations
6.
Alexander, M, A. Katrina Loomis, Johan van der Lei, et al.. (2019). Non-alcoholic fatty liver disease and risk of incident acute myocardial infarction and stroke: findings from matched cohort study of 18 million European adults. BMJ. 367. l5367–l5367. 183 indexed citations
7.
Alexander, M, A. Katrina Loomis, Johan van der Lei, et al.. (2019). Risks and clinical predictors of cirrhosis and hepatocellular carcinoma diagnoses in adults with diagnosed NAFLD: real-world study of 18 million patients in four European cohorts. BMC Medicine. 17(1). 95–95. 219 indexed citations
8.
Alexander, M, A. Katrina Loomis, Johan van der Lei, et al.. (2018). Real-world data reveal a diagnostic gap in non-alcoholic fatty liver disease. BMC Medicine. 16(1). 130–130. 174 indexed citations
9.
Coloma, Preciosa M., Maria de Ridder, Irene D. Bezemer, et al.. (2015). Risk of cardiac valvulopathy with use of bisphosphonates: a population-based, multi-country case-control study. Osteoporosis International. 27(5). 1857–1867. 22 indexed citations
10.
Bezemer, Irene D., Katia Verhamme, Rosa Gini, et al.. (2015). Use of oral contraceptives in three European countries: a population-based multi-database study. The European Journal of Contraception & Reproductive Health Care. 21(1). 81–87. 11 indexed citations
11.
Trifirò, Gianluca, Preciosa M. Coloma, Peter R. Rijnbeek, et al.. (2014). Combining multiple healthcare databases for postmarketing drug and vaccine safety surveillance: why and how?. Journal of Internal Medicine. 275(6). 551–561. 87 indexed citations
12.
Valkhoff, Vera E., Preciosa M. Coloma, Gwen Masclee, et al.. (2014). Validation study in four health-care databases: upper gastrointestinal bleeding misclassification affects precision but not magnitude of drug-related upper gastrointestinal bleeding risk. Journal of Clinical Epidemiology. 67(8). 921–931. 47 indexed citations
13.
Coloma, Preciosa M., Vera E. Valkhoff, Giampiero Mazzaglia, et al.. (2013). Identification of acute myocardial infarction from electronic healthcare records using different disease coding systems: a validation study in three European countries. BMJ Open. 3(6). e002862–e002862. 106 indexed citations
14.
Mosseveld, Mees, et al.. (2010). Is population-oriented IT supported preventive care in general practice feasible? A database study.. PubMed. 160(Pt 1). 462–5. 2 indexed citations
15.
16.
Mosseveld, Mees, et al.. (2005). A Technical Infrastructure to Conduct Randomized Database Studies Facilitated by a General Practice Research Database: Figure 1. Journal of the American Medical Informatics Association. 12(6). 602–607. 9 indexed citations
17.
Wijk, Marc A. M. van, et al.. (2003). AsthmaCritic: Issues in Designing a Noninquisitive Critiquing System for Daily Practice. Journal of the American Medical Informatics Association. 10(5). 419–424. 12 indexed citations
18.
Wijk, Marc A. M. van, Johan van der Lei, Mees Mosseveld, Arthur M. Bohnen, & Jan H. van Bemmel. (2001). Assessment of Decision Support for Blood Test Ordering in Primary Care. Annals of Internal Medicine. 134(4). 274–281. 78 indexed citations
19.
Mosseveld, Mees, et al.. (1999). Design of a Decision Support System for Test Ordering in General Practice: Choices and Decisions to Make. Methods of Information in Medicine. 38(04/05). 355–361. 13 indexed citations
20.
Teije, Annette ten, et al.. (1999). A study of PROforma, a development methodology for clinical procedures. Artificial Intelligence in Medicine. 17(2). 195–221. 11 indexed citations

Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.

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