Abstract:
INTRODUCTION:Acute admissions to hospital are rising. As a part of a service evaluation we examined pathways of patients following hospital discharge depending on data available on admission to hospital. METHODS:We merged data available on admission to the Wrexham Maelor hospital from an existing data-base in the Acute Medical Unit with follow up data from local social services as part of a data sharing agreement. Patients requiring support by social services post-discharge were matched with patients not requiring social services from the same post-code. RESULTS:Stepwise logistic regression analysis identified candidate variables predicting likely support need. Decision tree analysis identified sub-groups of patients with higher likelihood to require support by social services after discharge from hospital. We found patients with normal physiology on admission as evidenced by a value of zero for the National Early Warning Score who were frail or older than 85years were most likely to require support after discharge. CONCLUSIONS:Information available on admission to hospital might inform long term care needs. Prospective testing is needed. The algorithms are prone to be dependent on availability of local services but our methodology is expected to be transferable to other organizations.
journal_name
Eur J Intern Medjournal_title
European journal of internal medicineauthors
Subbe CP,Goulden N,Mawdsley K,Smith Rdoi
10.1016/j.ejim.2017.09.029subject
Has Abstractpub_date
2017-11-01 00:00:00pages
74-77eissn
0953-6205issn
1879-0828pii
S0953-6205(17)30377-1journal_volume
45pub_type
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