Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm
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...
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| Format: | Article |
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Oxford University Press
2017
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| Online Access: | https://eprints.nottingham.ac.uk/48905/ |
| _version_ | 1848797875356565504 |
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| author | Housley, Gemma Lewis, Sarah Usman, Adeela Gordon, Adam L. Shaw, Dominick E. |
| author_facet | Housley, Gemma Lewis, Sarah Usman, Adeela Gordon, Adam L. Shaw, Dominick E. |
| author_sort | Housley, Gemma |
| building | Nottingham Research Data Repository |
| collection | Online Access |
| description | 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. |
| first_indexed | 2025-11-14T20:10:49Z |
| format | Article |
| id | nottingham-48905 |
| institution | University of Nottingham Malaysia Campus |
| institution_category | Local University |
| last_indexed | 2025-11-14T20:10:49Z |
| publishDate | 2017 |
| publisher | Oxford University Press |
| recordtype | eprints |
| repository_type | Digital Repository |
| spelling | nottingham-489052020-05-04T19:22:59Z https://eprints.nottingham.ac.uk/48905/ 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. 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. Oxford University Press 2017-12-18 Article PeerReviewed Housley, Gemma, Lewis, Sarah, Usman, Adeela, Gordon, Adam L. and Shaw, Dominick E. (2017) Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm. Age and Ageing . ISSN 0002-0729 care homes algorithm secondary care informatics patient admission older people https://academic.oup.com/ageing/advance-article/doi/10.1093/ageing/afx182/4757114 doi:10.1093/ageing/afx182 doi:10.1093/ageing/afx182 |
| spellingShingle | care homes algorithm secondary care informatics patient admission older people Housley, Gemma Lewis, Sarah Usman, Adeela Gordon, Adam L. Shaw, Dominick E. Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm |
| title | Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm |
| title_full | Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm |
| title_fullStr | Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm |
| title_full_unstemmed | Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm |
| title_short | Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm |
| title_sort | accurate identification of hospital admissions from care homes; development and validation of an automated algorithm |
| topic | care homes algorithm secondary care informatics patient admission older people |
| url | https://eprints.nottingham.ac.uk/48905/ https://eprints.nottingham.ac.uk/48905/ https://eprints.nottingham.ac.uk/48905/ |