| Literature DB >> 35433985 |
Jing Hao1, Yutao Huang2, Jianguo Su3, Zhaofeng Lu1.
Abstract
Background: The emergency rapid response system (RRS) can reduce the mortality of hospitalized patients, and its core is the activation criteria and the rapid response team (RRT). This study adopted a bibliometric method to analyze the research status of RRSs for hospitalized patients.Entities:
Keywords: Emergency; bibliometrics analysis; rapid response system (RRS)
Year: 2022 PMID: 35433985 PMCID: PMC9011274 DOI: 10.21037/atm-22-709
Source DB: PubMed Journal: Ann Transl Med ISSN: 2305-5839
Literature types
| Type | Records | Percentage (%) |
|---|---|---|
| Article | 1,096 | 83.03 |
| Review | 157 | 11.89 |
| Editorial | 51 | 3.86 |
| Proceedings | 47 | 3.56 |
| Online | 11 | 0.83 |
| Letter | 7 | 0.53 |
| Meeting abstract | 6 | 0.45 |
| Book | 3 | 0.23 |
| Re-publication | 2 | 0.15 |
| Note | 1 | 0.08 |
Figure 1Annual publications: the number of publications increased annually.
Figure 2The frequency of citations increased annually.
Figure 3Visualization map of countries.
Top 10 countries by number of publications
| Rank | Countries | Records |
|---|---|---|
| 1 | USA | 526 |
| 2 | Australia | 212 |
| 3 | China | 143 |
| 4 | England | 136 |
| 5 | Canada | 90 |
| 6 | Italy | 55 |
| 7 | Germany | 46 |
| 8 | South Korea | 43 |
| 9 | Netherlands | 42 |
| 10 | Switzerland | 32 |
Top 10 countries by centrality
| Rank | Countries | Centrality |
|---|---|---|
| 1 | USA | 0.29 |
| 2 | England | 0.24 |
| 3 | Argentina | 0.23 |
| 4 | Czech Republic | 0.14 |
| 5 | Switzerland | 0.12 |
| 6 | Canada | 0.08 |
| 7 | France | 0.08 |
| 8 | Chile | 0.07 |
| 9 | Australia | 0.05 |
| 10 | Bangladesh | 0.05 |
Figure 4Visualization map of institutions.
Top 10 institutions by number of publications
| Rank | Institutions | Records |
|---|---|---|
| 1 | Monash University | 46 |
| 2 | Austin Hospital | 32 |
| 3 | University of Washington | 32 |
| 4 | Deakin University | 28 |
| 5 | University of Pittsburgh | 28 |
| 6 | University of Melbourne | 27 |
| 7 | University of New South Wales | 24 |
| 8 | University of Pennsylvania | 21 |
| 9 | Harvard University | 17 |
| 10 | University of Adelaide | 16 |
Top 10 institutions by centrality
| Rank | Institutions | Centrality |
|---|---|---|
| 1 | Stanford University | 0.07 |
| 2 | Monash University | 0.05 |
| 3 | Austin Hospital | 0.05 |
| 4 | University of Pennsylvania | 0.05 |
| 5 | University of Washington | 0.04 |
| 6 | University of Pittsburgh | 0.04 |
| 7 | University of New South Wales | 0.04 |
| 8 | Harvard University | 0.04 |
| 9 | University of Toronto | 0.04 |
| 10 | University of Antwerp | 0.03 |
Top 10 authors by number of publications
| Rank | Authors | Records |
|---|---|---|
| 1 | Jones D | 28 |
| 2 | Bellomo R | 23 |
| 3 | Hillman K | 17 |
| 4 | Considine J | 16 |
| 5 | Flabouris A | 14 |
| 6 | Chen J | 12 |
| 7 | J Currey J | 12 |
| 8 | Devita MA | 11 |
| 9 | Welch J | 9 |
| 10 | Edelson DP | 8 |
Top 8 authors by centrality
| Rank | Authors | Centrality |
|---|---|---|
| 1 | Jones D | 0.02 |
| 2 | Bellomo R | 0.02 |
| 3 | Parr M | 0.02 |
| 4 | Nadkarni VM | 0.01 |
| 5 | Van Der Jagt EW | 0.01 |
| 6 | Hillman K | 0.01 |
| 7 | Chen J | 0.01 |
| 8 | Welch J | 0.01 |
Figure 5Co-author visualization map. Collaborations among authors were scattered and clustered.
Figure 6Authors co-citation visualization map.
Top 10 authors by frequency of co-citation
| Rank | Authors | Frequency |
|---|---|---|
| 1 | Chan PS | 216 |
| 2 | Bellomo R | 187 |
| 3 | Winters BD | 178 |
| 4 | Jones DA | 176 |
| 5 | Buist MD | 169 |
| 6 | Chen J | 161 |
| 7 | Buist M | 114 |
| 8 | Hillman KM | 106 |
| 9 | Subbe CP | 93 |
| 10 | Maharaj R | 87 |
Top 10 authors by centrality of co-citation
| Rank | Authors | Centrality |
|---|---|---|
| 1 | Devita MA | 0.02 |
| 2 | Jones D | 0.02 |
| 3 | Subbe CP | 0.02 |
| 4 | Smith GB | 0.02 |
| 5 | Goldhill DB | 0.02 |
| 6 | Churpek MM | 0.02 |
| 7 | Eisenberg MS | 0.02 |
| 8 | Becker LB | 0.02 |
| 9 | Alberts MJ | 0.02 |
| 10 | Hillman K | 0.01 |
Top 10 journals by number of publications
| Rank | Journals | Records | Percentage (%) |
|---|---|---|---|
| 1 |
| 74 | 5.61 |
| 2 |
| 62 | 4.70 |
| 3 |
| 18 | 1.36 |
| 4 |
| 17 | 1.29 |
| 5 |
| 16 | 1.21 |
| 6 |
| 15 | 1.14 |
| 7 |
| 15 | 1.14 |
| 8 |
| 14 | 1.06 |
| 9 |
| 13 | 0.98 |
| 10 |
| 13 | 0.98 |
Top 10 journals by citations
| Rank | Journals | Frequency |
|---|---|---|
| 1 |
| 523 |
| 2 |
| 514 |
| 3 |
| 465 |
| 4 |
| 446 |
| 5 |
| 445 |
| 6 |
| 350 |
| 7 |
| 301 |
| 8 |
| 260 |
| 9 |
| 243 |
| 10 |
| 237 |
Top 10 journals by centrality
| Rank | Journals | Centrality |
|---|---|---|
| 1 |
| 0.16 |
| 2 |
| 0.10 |
| 3 |
| 0.10 |
| 4 |
| 0.09 |
| 5 |
| 0.09 |
| 6 |
| 0.09 |
| 7 |
| 0.09 |
| 8 |
| 0.09 |
| 9 |
| 0.08 |
| 10 |
| 0.08 |
Figure 7The keywords co-existence map. Each circle (dot) in the figure represents a keyword. The larger the number, the more times the keyword and other keywords appear in a document, which is consistent with the frequency in .
Top 10 keywords by frequency of use
| Rank | Keyword | Frequency |
|---|---|---|
| 1 | Medical emergency team | 347 |
| 2 | Mortality | 219 |
| 3 | System | 206 |
| 4 | Rapid response system | 194 |
| 5 | Cardiac arrest | 193 |
| 6 | Rapid response team | 138 |
| 7 | Care | 117 |
| 8 | Outcome | 107 |
| 9 | Impact | 105 |
| 10 | Intensive care | 91 |
Top 10 keywords by centrality
| Rank | Keyword | Centrality |
|---|---|---|
| 1 | Emergency | 0.15 |
| 2 | Critical illness | 0.12 |
| 3 | Cardiac arrest | 0.11 |
| 4 | Emergency medical service | 0.11 |
| 5 | Mortality | 0.09 |
| 6 | Adverse event | 0.09 |
| 7 | Survival | 0.08 |
| 8 | Hospital cardiac arrest | 0.07 |
| 9 | Automated external defibrillator | 0.07 |
| 10 | Admission | 0.05 |
Figure 8Top 25 keywords with the strongest citation bursts.