Accurate identification of hospital admissions from care homes: development and validation of an automated algorithm
Housley, Gemma; Lewis, Sarah; Usman, Adeela; Gordon, Adam L.; Shaw, Dominick E.
Professor SARAH LEWIS firstname.lastname@example.org
Professor of Medical Statistics
ADEELA USMAN MOHAMMED USMAN Adeela.UsmanMohammedusman@nottingham.ac.uk
ADAM GORDON Adam.Gordon@nottingham.ac.uk
Professor of The Care of Older People
Professor DOMINICK SHAW email@example.com
Professor of Respiratory Medicine
Background: measuring the complex needs of care home residents is crucial for resource allocation. Hospital patient administration systems (PAS) may not accurately identify admissions from care homes.
Objective: to develop and validate an accurate, practical method of identifying care home resident hospital admission using routinely collected PAS data.
Method: admissions data between 2011 and 2012 (n = 103,105) to an acute Trust were modelled to develop an automated tool which compared the hospital PAS address details with the Care Quality Commission’s (CQC) database, producing a likelihood of care home residency. This tool and the Nuffield method (CQC postcode match only) were validated against a manual check of a random sample of admissions (n = 2,000). A dataset from a separate Trust was analysed to assess generalisability.
Results:the hospital PAS was inaccurate; none of the admissions from a care home identified on manual check had a care home source of admission recorded on the PAS. Both methods performed well; the automated tool had a higher positive predictive value than the Nuffield method (100% 95% confidence interval (CI) 98.23–100% versus 87.10% 95%CI 82.28–91.00%), meaning those coded as care home residents were more likely to actually be from a care home. Our automated tool had a high level of agreement 99.2% with the second Trust’s data (Kappa 0.86 P < 0.001).
Conclusions: care home status is not routinely or accurately captured. Automated matching offers an accurate, repeatable, scalable method to identify care home residency and could be used as a tool to benchmark how care home residents use acute hospital resources across the National Health Service.
Housley, G., Lewis, S., Usman, A., Gordon, A. L., & Shaw, D. E. (2018). Accurate identification of hospital admissions from care homes: development and validation of an automated algorithm. Age and Ageing, 47(3), 387-391. https://doi.org/10.1093/ageing/afx182
|Journal Article Type||Article|
|Acceptance Date||Nov 20, 2017|
|Online Publication Date||Dec 18, 2017|
|Publication Date||May 1, 2018|
|Deposit Date||Jan 3, 2018|
|Publicly Available Date||Jan 3, 2018|
|Journal||Age and Ageing|
|Publisher||Oxford University Press|
|Peer Reviewed||Peer Reviewed|
|Keywords||care homes, algorithm, secondary care, informatics, patient admission, older people|
|Copyright Statement||Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0|
Housley 2017 Age and Ageing.pdf
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Copyright information regarding this work can be found at the following address: http://creativecommons.org/licenses/by-nc-nd/4.0