| Title |
Explaining length of stay variation of episodes of care in the Netherlands
|
|---|---|
| Published in |
HEPAC Health Economics in Prevention and Care, October 2012
|
| DOI | 10.1007/s10198-012-0436-1 |
| Pubmed ID | |
| Authors |
Siok Swan Tan, Leona Hakkaart-van Roijen, B. Martin van Ineveld, W. Ken Redekop |
| Abstract |
Diagnosis Related Group (DRG) systems aim to classify patients into mutually exclusive groups of patients, with the patients in each group having the same expected length of stay (LOS). We examined the ability of current classification variables to explain LOS variation between DRG-like Diagnosis Treatment Combination (DBC)s for ten episodes of care in the Netherlands, including breast cancer, stroke and inguinal hernia repair. Additionally, we assessed the predictive ability of some other classification variables. |
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 31 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| Unknown | 31 | 100% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Student > Ph. D. Student | 6 | 19% |
| Student > Master | 5 | 16% |
| Student > Doctoral Student | 3 | 10% |
| Researcher | 3 | 10% |
| Professor | 2 | 6% |
| Other | 3 | 10% |
| Unknown | 9 | 29% |
| Readers by discipline | Count | As % |
|---|---|---|
| Medicine and Dentistry | 8 | 26% |
| Engineering | 2 | 6% |
| Agricultural and Biological Sciences | 1 | 3% |
| Computer Science | 1 | 3% |
| Physics and Astronomy | 1 | 3% |
| Other | 5 | 16% |
| Unknown | 13 | 42% |
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 25 October 2013.
All research outputs
#22,759,802
of 25,374,917 outputs
Outputs from HEPAC Health Economics in Prevention and Care
#1,211
of 1,303 outputs
Outputs of similar age
#173,794
of 194,155 outputs
Outputs of similar age from HEPAC Health Economics in Prevention and Care
#15
of 21 outputs
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