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Accurate identification of hospital admissions from care homes; development and validation of an automated algorithm
Gemma Housley1, Sarah Lewis2, Adeela Usman3
1East Midlands Academic Health Science Network, Clinical Sciences Building, Nottingham City Hospital Campus, Hucknall Road, Nottingham, UK.
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.
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