You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output.
Click here to find out more.
X Demographics
Mendeley readers
Attention Score in Context
| Title |
Reducing Time-dependent Bias in Estimates of the Attributable Cost of Health Care–associated Methicillin-resistant Staphylococcus aureus Infections
|
|---|---|
| Published in |
Medical care, September 2015
|
| DOI | 10.1097/mlr.0000000000000403 |
| Pubmed ID | |
| Authors |
Richard E. Nelson, Matthew H. Samore, Makoto Jones, Tom Greene, Vanessa W. Stevens, Chuan-Fen Liu, Nicholas Graves, Martin F. Evans, Michael A. Rubin |
| Abstract |
Previous estimates of the excess costs due to health care-associated infection (HAI) have scarcely addressed the issue of time-dependent bias. We examined time-dependent bias by estimating the health care costs attributable to an HAI due to methicillin-resistant Staphylococcus aureus (MRSA) using a unique dataset in the Department of Veterans Affairs (VA) that makes it possible to distinguish between costs that occurred before and after an HAI. In addition, we compare our results to those from 2 other estimation strategies. Using a historical cohort study design to estimate the excess predischarge costs attributable to MRSA HAIs, we conducted 3 analyses: (1) conventional, in which costs for the entire inpatient stay were compared between patients with and without MRSA HAIs; (2) post-HAI, which included only costs that occurred after an infection; and (3) matched, in which costs for the entire inpatient stay were compared between patients with an MRSA HAI and subset of patients without an MRSA HAI who were matched based on the time to infection. In our post-HAI analysis, estimates of the increase in inpatient costs due to MRSA HAI were $12,559 (P<0.0001) and $24,015 (P<0.0001) for variable and total costs, respectively. The excess variable and total cost estimates were 33.7% and 31.5% higher, respectively, when using the conventional methods and 14.6% and 11.8% higher, respectively, when using matched methods. This is the first study to account for time-dependent bias in the estimation of incremental per-patient health care costs attributable to HAI using a unique dataset in the VA. We found that failure to account for this bias can lead to overestimation of these costs. Matching on the timing of infection can reduce this bias substantially. |
X Demographics
The data shown below were collected from the profiles of 2 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 | 1 | 50% |
| Unknown | 1 | 50% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Practitioners (doctors, other healthcare professionals) | 1 | 50% |
| Members of the public | 1 | 50% |
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 % |
|---|---|---|
| Researcher | 5 | 23% |
| Student > Bachelor | 2 | 9% |
| Other | 2 | 9% |
| Student > Ph. D. Student | 2 | 9% |
| Professor > Associate Professor | 2 | 9% |
| Other | 4 | 18% |
| Unknown | 5 | 23% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 7 | 32% |
| Social Sciences | 2 | 9% |
| Mathematics | 1 | 5% |
| Business, Management and Accounting | 1 | 5% |
| Nursing and Health Professions | 1 | 5% |
| Other | 5 | 23% |
| Unknown | 5 | 23% |
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 26 August 2015.
All research outputs
#19,945,185
of 25,374,917 outputs
Outputs from Medical care
#3,379
of 4,204 outputs
Outputs of similar age
#189,783
of 276,789 outputs
Outputs of similar age from Medical care
#26
of 38 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 18th percentile – i.e., 18% of other outputs scored the same or lower than it.
So far Altmetric has tracked 4,204 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 12.1. This one is in the 16th percentile – i.e., 16% 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 276,789 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 26th percentile – i.e., 26% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 38 others from the same source and published within six weeks on either side of this one. This one is in the 28th percentile – i.e., 28% of its contemporaries scored the same or lower than it.