Making the Most of Your Data: Using an Alternative Statistical Methodology to Multilevel Modeling to Investigate Hospital Effects on Acute Hospital Length of Stay Following Stroke When Number of Hospitals Is Small

2020 ◽  
Author(s):  
Michelle Tørnes ◽  
Phyo Kyaw Myint ◽  
David McLernon
2018 ◽  
Vol 100 (7) ◽  
pp. 556-562 ◽  
Author(s):  
T Richards ◽  
A Glendenning ◽  
D Benson ◽  
S Alexander ◽  
S Thati

Introduction Management of hip fractures has evolved over recent years to drive better outcomes including length of hospital stay. We aimed to identify and quantify the effect that patient factors influence acute hospital and total health service length of stay. Methods A retrospective observational study based on National Hip Fracture Database data was conducted from 1 January 2014 to 31 December 2015. A multiple regression analysis of 330 patients was carried out to determine independent factors that affect acute hospital and total hospital length of stay. Results American Society of Anesthesiologists (ASA) grade 3 or above, Abbreviated Mental Test Score (AMTS) less than 8 and poor mobility status were independent factors, significantly increasing length of hospital stay in our population. Acute hospital length of stay can be predicted as 8.9 days longer when AMTS less than 8, 4.2 days longer when ASA grade was 3 or above and 20.4 days longer when unable to mobilise unaided (compared with independently mobile individuals). Other factors including total hip replacement compared with hemiarthroplasty did not independently affect length of stay. Conclusions Our analysis in a representative and generalisable population illustrates the importance of identifying these three patient characteristics in hip fracture patients. When recognised and targeted with orthogeriatric support, the length of hospital stay for these patients can be reduced and overall hip fracture care improved. Screening on admission for ASA grade, AMTS and mobility status allows prediction of length of stay and tailoring of care to match needs.


QJM ◽  
2011 ◽  
Vol 104 (8) ◽  
pp. 671-679 ◽  
Author(s):  
Y. Pai ◽  
C. Butchart ◽  
C. J. Lunt ◽  
P. Musonda ◽  
N. Gautham ◽  
...  

BMJ Open ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. e024506 ◽  
Author(s):  
Michelle Tørnes ◽  
David McLernon ◽  
Max Bachmann ◽  
Stanley Musgrave ◽  
Elizabeth A Warburton ◽  
...  

ObjectivesTo determine whether stroke patients’ acute hospital length of stay (AHLOS) varies between hospitals, over and above case mix differences and to investigate the hospital-level explanatory factors.DesignA multicentre prospective cohort study.SettingEight National Health Service acute hospital trusts within the Anglia Stroke & Heart Clinical Network in the East of England, UK.ParticipantsThe study sample was systematically selected to include all consecutive patients admitted within a month to any of the eight hospitals, diagnosed with stroke by an accredited stroke physician every third month between October 2009 and September 2011.Primary and secondary outcome measuresAHLOS was defined as the number of days between date of hospital admission and discharge or death, whichever came first. We used a multiple linear regression model to investigate the association between hospital (as a fixed-effect) and AHLOS, adjusting for several important patient covariates, such as age, sex, stroke type, modified Rankin Scale score (mRS), comorbidities and inpatient complications. Exploratory data analysis was used to examine the hospital-level characteristics which may contribute to variance between hospitals. These included hospital type, stroke monthly case volume, service provisions (ie, onsite rehabilitation) and staffing levels.ResultsA total of 2233 stroke admissions (52% female, median age (IQR) 79 (70 to 86) years, 83% ischaemic stroke) were included. The overall median AHLOS (IQR) was 9 (4 to 21) days. After adjusting for patient covariates, AHLOS still differed significantly between hospitals (p<0.001). Furthermore, hospitals with the longest adjusted AHLOS’s had predominantly smaller stroke volumes.ConclusionsWe have clearly demonstrated that AHLOS varies between different hospitals, and that the most important patient-level explanatory variables are discharge mRS, dementia and inpatient complications. We highlight the potential importance of stroke volume in influencing these differences but cannot discount the potential effect of unmeasured confounders.


2021 ◽  
Vol 16 (1) ◽  
Author(s):  
Sim H. S. Craigven ◽  
Sultana Rehena ◽  
Tay X. K. Kenny ◽  
C. Y. Howe ◽  
T. S. Howe ◽  
...  

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