121 Patients with Prolonged Lengths of Stay. A Point Prevalence Study. (16th September 2019)

• Record Type: Journal Article
• Authors: Short, Eimear; D'Alton, Maeve; Dolan, Eamon; Dunne, Aoife; Hartigan, Denise; Jones, Claire; Morrison, Laura; O'Connor, Marie
• Is Part Of: Age and ageing. Volume 48(2019)Supplement 3
• Page Start: iii17
• Page End: iii65
• Publication Date: 2019-09-16
• Subjects: Aging -- Periodicals; Geriatrics -- Periodicals; 618.97
• DOI: 10.1093/ageing/afz103.69
• Languages: English
• ISSNs: 0002-0729

Abstract

Abstract: Background: A hospital's trolley count is often highlighted as a measure of its performance. However there is a more complex reality for each organisation in accessing suitable resources for often frail older patients to improve care and capacity. Coupled with this is the need for pathways that identify these patients early in their admission and access the appropriate specialist care. In 2018, 65% of this hospital's bed days were occupied by those whose hospital stay was greater than 14 days. Nationally this was 57%. We undertook to review processes locally around the care of older acute patients. Methods: On the 20th November 2018 we conducted a chart audit of 85 in-patients who had been in the acute setting for more than 14 days. A proforma was completed for each patient by a doctor and multi-disciplinary team member. Results: The length of stay ranged from 15 – 527 days with the median being 41 days. The average age was 76 years. A history of falls/dementia/"acopia" was recorded on admission in 57%. The mean time for referral to MDT was 5 days. Social history was only documented in 47% of cases. Ward transfers was a significant issue with 69% moving wards at least once and 9% moving three times or more. A care planning meeting had not been held in 49% of cases. Over 17% of charts audited were awaiting home care package hours whilst 20% were awaiting long term care. In 62% of cases there was no ongoing medical reason keeping them in hospital and 56% of this cohort could have been cared for elsewhere. Conclusion: Deficits in clear communication and appropriate timely planning for patients resulted in significant delays in discharge. The findings of our research informed a decision to conduct a root and branch analysis of discharge planning utilising the Lean Six Sigma model.