Alison Bourke

15 papers receiving 1.2k citations

Alison Bourke's Hit Papers

Generalisability of The Health Improvement Network (THIN) database: demographics, chronic disease prevalence and mortality rates 2011 · 587 citations
5870+5+10Years since publication100200300400500

Peers

Alison Bourke
Comparison fields: 5 of 111
  • Toxicology 59
  • Applied Microbiology and Biotechnology 18
  • Statistics and Probability 64
  • Endocrinology, Diabetes and Metabolism 78
  • Health Informatics 7
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Joyce Lii United States
Gregory W. Daniel United States
Jonathan Hirohiko Watanabe United States
Stephen E. Kimmel United States
Cécile Droz‐Perroteau France
Lily Gui Bessette United States
Shinya H. Kimura Japan
Gregory E. Brill United States
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Countries citing papers authored by Alison Bourke

Since Specialization
Citations

This map shows the geographic impact of Alison Bourke'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 Alison Bourke with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Alison Bourke more than expected).

Fields of papers citing papers by Alison Bourke

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

This network shows the impact of papers produced by Alison Bourke. 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 Alison Bourke. The network helps show where Alison Bourke may publish in the future.

Co-authors

The 25 scholars most cited alongside Alison Bourke, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.

Border = papers with Alison Bourke Line = papers co-authored together Alison Bourke links everyone, so they are left out of the graph.

All Works

15 of 15 papers shown
#Work
1
Generalisability of The Health Improvement Network (THIN) database: demographics, chronic disease prevalence and mortality rates
Hit paper breakdown →
2011587
2 2004260
3 2011158
4 202268
5 201134
6 201526
7 202122
8 202022
9 201615
10 202015
11 201511
12 20198
13 20125
14 20165
15 20192

About Alison Bourke

Alison Bourke is a scholar working on Statistics, Probability and Uncertainty, Pharmacology, Geriatrics and Gerontology, Public Health, Environmental and Occupational Health and Statistics and Probability, having authored 15 papers that have together received 1.2k indexed citations. Recurring topics across this work include Pregnancy and Medication Impact (4 papers), Meta-analysis and systematic reviews (3 papers), Pharmacogenetics and Drug Metabolism (3 papers), Statistical Methods in Clinical Trials (2 papers), Pharmaceutical Practices and Patient Outcomes (2 papers), Health Systems, Economic Evaluations, Quality of Life (2 papers), COVID-19 Clinical Research Studies (1 paper) and Electronic Health Records Systems (1 paper). The work is most often cited by research in Toxicology (59 citations), Applied Microbiology and Biotechnology (18 citations), Statistics and Probability (64 citations), Endocrinology, Diabetes and Metabolism (78 citations) and Health Informatics (7 citations). Alison Bourke has collaborated with scholars based in United Kingdom, United States and Poland. Frequent co-authors include Betina T. Blak, Mary Ann Thompson, Michael A. Robinson, Matthew W. Reynolds, Jeffrey Scott Brown, Brian C. Sauer, Nancy A Dreyer, Orla Doyle, Richard Hubbard and Laila Jal Tata. Their work appears in journals such as Pharmacoepidemiology and Drug Safety, Journal of Innovation in Health Informatics, JMIR Public Health and Surveillance, BMC Public Health and Nature Communications.

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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