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Calculating hospital length of stay using the Hospital Episode Statistics; a comparison of methodologies

Overview of attention for article published in BMC Health Services Research, May 2017
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Title
Calculating hospital length of stay using the Hospital Episode Statistics; a comparison of methodologies
Published in
BMC Health Services Research, May 2017
DOI 10.1186/s12913-017-2295-z
Pubmed ID
Authors

John Busby, Sarah Purdy, William Hollingworth

Abstract

Accurate calculation of hospital length of stay (LOS) from the English Hospital Episode Statistics (HES) is important for a wide range of audit and research purposes. The two methodologies which are commonly used to achieve this differ in their accuracy and complexity. We compare these methods and make recommendations on when each is most appropriate. We calculated LOS using continuous inpatient spells (CIPS), which link care spanning across multiple hospitals, and spells, which do not, for six conditions with short (dyspepsia or other stomach function, ENT infection), medium (dehydration and gastroenteritis, perforated or bleeding ulcer), and long (stroke, fractured proximal femur) average LOS. We examined how inter-area comparisons (i.e. benchmarking) and temporal trends differed. We defined a classification system for spells and explored the causes of differences. Stroke LOS was 16.5 days using CIPS but 24% (95% CI: 23, 24) lower, at 12.6 days, using spells. Smaller differences existed for shorter-LOS conditions including dehydration and gastroenteritis (4.5 vs. 4.2 days) and ENT infection (0.9 vs. 0.8 days). Typical patient pathways differed markedly between areas and have evolved over time. One area had the third shortest stroke LOS (out of 151) using spells but the fourth longest using CIPS. These issues were most profound for stroke and fractured proximal femur, as patients were frequently transferred to a separate hospital for rehabilitation, however important disparities also existed for conditions with simpler secondary care pathways (e.g. ENT infections, dehydration and gastroenteritis). Spell-based LOS is widely used by researchers and national reporting organisations, including the Health and Social Care Information Centre, however it can substantially underestimate the time patients spend in hospital. A widespread shift to a CIPS methodology is required to improve the quality of LOS estimates and the robustness of research and benchmarking findings. This is vital when investigating clinical areas with typically long, complex patient pathways. Researchers should ensure that their LOS calculation methodology is fully described and explicitly acknowledge weaknesses when appropriate.

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The data shown below were collected from the profile of 1 tweeter who shared this research output. Click here to find out more about how the information was compiled.

Mendeley readers

The data shown below were compiled from readership statistics for 49 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 49 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 10 20%
Student > Ph. D. Student 8 16%
Student > Master 5 10%
Student > Bachelor 5 10%
Student > Doctoral Student 3 6%
Other 7 14%
Unknown 11 22%
Readers by discipline Count As %
Medicine and Dentistry 8 16%
Engineering 4 8%
Nursing and Health Professions 4 8%
Psychology 4 8%
Economics, Econometrics and Finance 3 6%
Other 11 22%
Unknown 15 31%

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 16 May 2017.
All research outputs
#5,997,233
of 10,263,476 outputs
Outputs from BMC Health Services Research
#2,440
of 3,545 outputs
Outputs of similar age
#146,894
of 262,771 outputs
Outputs of similar age from BMC Health Services Research
#79
of 110 outputs
Altmetric has tracked 10,263,476 research outputs across all sources so far. This one is in the 25th percentile – i.e., 25% of other outputs scored the same or lower than it.
So far Altmetric has tracked 3,545 research outputs from this source. They typically receive a little more attention than average, with a mean Attention Score of 5.7. This one is in the 20th percentile – i.e., 20% of its peers scored the same or lower than it.
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