David Ting

16 papers receiving 277 citations

Peers

David Ting
Comparison fields: 5 of 70
  • Health Informatics 19
  • Health Information Management 63
  • General Health Professions 169
  • Family Practice 14
  • Gender Studies 43
Replace Frances E. Biagioli with:
Frances E. Biagioli United States
Nancy Morioka-Douglas United States
Patrick Kneeland United States
J. C. Puffer United States
Ryan Palmer United States
Jeffrey Chi United States
Thomas R. O’Neill United States
Timothy Zhang Canada
Jessica Kemp Canada
Macda Gerard United States
David Ting relative to Frances E. Biagioli United States Frances E. Biagioli's profile →
Citations per field
00.5×5.3×
Frances E. Biagioli · 1×
Citations per year

Countries citing papers authored by David Ting

Since Specialization
Citations

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

Fields of papers citing papers by David Ting

Since Specialization
Physical SciencesHealth SciencesLife SciencesSocial Sciences

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

Co-authors

The 25 scholars most cited alongside David Ting, 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 David Ting Line = papers co-authored together David Ting links everyone, so they are left out of the graph.

All Works

17 of 17 papers shown
#Work
1 2019122
2 202230
3 202424
4 201423
5 201622
6 201716
7 201511
8 202010
9 20099
10 20116
11 20233
12 20063
13 20052
14 20112
15 20251
16 20071
17 20250

About David Ting

David Ting is a scholar working on Health Information Management, General Health Professions, Public Health, Environmental and Occupational Health, Organizational Behavior and Human Resource Management and Economics and Econometrics, having authored 17 papers that have together received 285 indexed citations. Recurring topics across this work include Electronic Health Records Systems (8 papers), Healthcare Systems and Technology (5 papers), Primary Care and Health Outcomes (3 papers), Telemedicine and Telehealth Implementation (2 papers), Healthcare Policy and Management (2 papers), Innovations in Medical Education (1 paper), Mobile Health and mHealth Applications (1 paper) and Patient Satisfaction in Healthcare (1 paper). The work is most often cited by research in Health Informatics (19 citations), Health Information Management (63 citations), General Health Professions (169 citations), Family Practice (14 citations) and Gender Studies (43 citations). David Ting has collaborated with scholars based in United States and Brazil. Frequent co-authors include Stuart R. Lipsitz, John B. Herman, Timothy G. Ferris, Marcela G. del Carmen, Sara R. Lehrhoff, Sandhya K. Rao, Michael K. Hidrue, Srinivas Emani, David W. Bates and Lisa S. Rotenstein. Their work appears in journals such as JAMA Network Open, Applied Clinical Informatics, Journal of General Internal Medicine, Patient Education and Counseling and npj Digital Medicine.

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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