| Title |
What have we learned in minimally invasive colorectal surgery from NSQIP and NIS large databases? A systematic review
|
|---|---|
| Published in |
International Journal of Colorectal Disease, April 2018
|
| DOI | 10.1007/s00384-018-3036-4 |
| Pubmed ID | |
| Authors |
Gabriela Batista Rodríguez, Andrea Balla, Santiago Corradetti, Carmen Martinez, Pilar Hernández, Jesús Bollo, Eduard M. Targarona |
| Abstract |
"Big data" refers to large amount of dataset. Those large databases are useful in many areas, including healthcare. The American College of Surgeons National Surgical Quality Improvement Program (ACS-NSQIP) and the National Inpatient Sample (NIS) are big databases that were developed in the USA in order to record surgical outcomes. The aim of the present systematic review is to evaluate the type and clinical impact of the information retrieved through NISQP and NIS big database articles focused on laparoscopic colorectal surgery. A systematic review was conducted using The Meta-Analysis Of Observational Studies in Epidemiology (MOOSE) guidelines. The research was carried out on PubMed database and revealed 350 published papers. Outcomes of articles in which laparoscopic colorectal surgery was the primary aim were analyzed. Fifty-five studies, published between 2007 and February 2017, were included. Articles included were categorized in groups according to the main topic as: outcomes related to surgical technique comparisons, morbidity and perioperatory results, specific disease-related outcomes, sociodemographic disparities, and academic training impact. NSQIP and NIS databases are just the tip of the iceberg for the potential application of Big Data technology and analysis in MIS. Information obtained through big data is useful and could be considered as external validation in those situations where a significant evidence-based medicine exists; also, those databases establish benchmarks to measure the quality of patient care. Data retrieved helps to inform decision-making and improve healthcare delivery. |
X Demographics
The data shown below were collected from the profile of 1 X user who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 1 | 100% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 1 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 77 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 77 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Bachelor | 10 | 13% |
| Student > Master | 9 | 12% |
| Researcher | 6 | 8% |
| Student > Postgraduate | 5 | 6% |
| Other | 4 | 5% |
| Other | 16 | 21% |
| Unknown | 27 | 35% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 27 | 35% |
| Engineering | 4 | 5% |
| Nursing and Health Professions | 3 | 4% |
| Psychology | 3 | 4% |
| Computer Science | 2 | 3% |
| Other | 4 | 5% |
| Unknown | 34 | 44% |
Attention Score in Context
This research output has an Altmetric Attention Score of 1. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 31 May 2018.
All research outputs
#20,516,195
of 23,083,773 outputs
Outputs from International Journal of Colorectal Disease
#1,441
of 1,845 outputs
Outputs of similar age
#291,028
of 329,661 outputs
Outputs of similar age from International Journal of Colorectal Disease
#44
of 48 outputs
Altmetric has tracked 23,083,773 research outputs across all sources so far. This one is in the 1st percentile – i.e., 1% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,845 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 1st percentile – i.e., 1% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 329,661 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 48 others from the same source and published within six weeks on either side of this one. This one is in the 1st percentile – i.e., 1% of its contemporaries scored the same or lower than it.