| Title |
Optimizing Travel Time to Outpatient Interventional Radiology Procedures in a Multi-Site Hospital System Using a Google Maps Application
|
|---|---|
| Published in |
Journal of Digital Imaging, February 2018
|
| DOI | 10.1007/s10278-018-0054-2 |
| Pubmed ID | |
| Authors |
Jacob E. Mandel, Louis Morel-Ovalle, Franz E. Boas, Etay Ziv, Hooman Yarmohammadi, Amy Deipolyi, Heeralall R. Mohabir, Joseph P. Erinjeri |
| Abstract |
The purpose of this study is to determine whether a custom Google Maps application can optimize site selection when scheduling outpatient interventional radiology (IR) procedures within a multi-site hospital system. The Google Maps for Business Application Programming Interface (API) was used to develop an internal web application that uses real-time traffic data to determine estimated travel time (ETT; minutes) and estimated travel distance (ETD; miles) from a patient's home to each a nearby IR facility in our hospital system. Hypothetical patient home addresses based on the 33 cities comprising our institution's catchment area were used to determine the optimal IR site for hypothetical patients traveling from each city based on real-time traffic conditions. For 10/33 (30%) cities, there was discordance between the optimal IR site based on ETT and the optimal IR site based on ETD at non-rush hour time or rush hour time. By choosing to travel to an IR site based on ETT rather than ETD, patients from discordant cities were predicted to save an average of 7.29 min during non-rush hour (p = 0.03), and 28.80 min during rush hour (p < 0.001). Using a custom Google Maps application to schedule outpatients for IR procedures can effectively reduce patient travel time when more than one location providing IR procedures is available within the same hospital system. |
X Demographics
The data shown below were collected from the profiles of 8 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 2 | 25% |
| United Kingdom | 1 | 13% |
| Unknown | 5 | 63% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 4 | 50% |
| Practitioners (doctors, other healthcare professionals) | 2 | 25% |
| Science communicators (journalists, bloggers, editors) | 1 | 13% |
| Scientists | 1 | 13% |
Mendeley readers
The data shown below were compiled from readership statistics for 22 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 22 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Professor > Associate Professor | 4 | 18% |
| Student > Bachelor | 3 | 14% |
| Other | 2 | 9% |
| Researcher | 2 | 9% |
| Lecturer | 1 | 5% |
| Other | 0 | 0% |
| Unknown | 10 | 45% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 4 | 18% |
| Business, Management and Accounting | 2 | 9% |
| Nursing and Health Professions | 2 | 9% |
| Engineering | 2 | 9% |
| Energy | 1 | 5% |
| Other | 1 | 5% |
| Unknown | 10 | 45% |
Attention Score in Context
This research output has an Altmetric Attention Score of 15. 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 10 November 2019.
All research outputs
#2,117,785
of 23,025,074 outputs
Outputs from Journal of Digital Imaging
#51
of 1,063 outputs
Outputs of similar age
#48,069
of 331,055 outputs
Outputs of similar age from Journal of Digital Imaging
#2
of 18 outputs
Altmetric has tracked 23,025,074 research outputs across all sources so far. Compared to these this one has done particularly well and is in the 90th percentile: it's in the top 10% of all research outputs ever tracked by Altmetric.
So far Altmetric has tracked 1,063 research outputs from this source. They receive a mean Attention Score of 4.6. This one has done particularly well, scoring higher than 95% of its peers.
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 331,055 tracked outputs that were published within six weeks on either side of this one in any source. This one has done well, scoring higher than 85% of its contemporaries.
We're also able to compare this research output to 18 others from the same source and published within six weeks on either side of this one. This one has done well, scoring higher than 88% of its contemporaries.