Trends in delirium coding rates in older hospital inpatients in England and Scotland: full population data comprising 7.7M patients per year show substantial increases between 2012 and 2020

Background: Little information is available on change in delirium coding rates over time in major healthcare systems. We examined trends in delirium discharge coding rates in older patients in hospital admissions to the National Health Service (NHS) in England and Scotland between 2012 and 2020. / Methods: Hospital administrative coding data were sourced from NHS Digital England and Public Health Scotland. We examined rates of delirium (F05 from ICD-10) in patients aged ≥70 years in 5 year and ≥90 age bands. / Results: There were approximately 7,000,000 discharges/year in England and 700,000/year in Scotland. Substantially increased delirium coding was observed for all age bands between 2012/2013 and 2019/2020 (p<0.001, Mann Kendall’s tau). In the ≥90 age band, there was a 4-fold increase between 2012 and 2020. / Conclusion: Delirium coding rates have shown large increases in the NHS in England and Scotland, likely reflecting several factors including policy initiatives, detection tool implementation and education

Trends in delirium coding rates in older hospital inpatients in England and Scotland:full population data comprising 7.7M patients per year show substantial increases between 2012 and 2020

BackgroundLittle information is available on change in delirium coding rates over time in major healthcare systems. We examined trends in delirium discharge coding rates in older patients in hospital admissions to the National Health Service (NHS) in England and Scotland between 2012 and 2020.MethodsHospital administrative coding data were sourced from NHS Digital England and Public Health Scotland. We examined rates of delirium (F05 from ICD-10) in patients aged ≥70 years in 5 year and ≥90 age bands.ResultsThere were approximately 7,000,000 discharges/year in England and 700,000/year in Scotland. Substantially increased delirium coding was observed for all age bands between 2012/2013 and 2019/2020 (p&lt;0.001, Mann Kendall’s tau). In the ≥90 age band, there was a 4-fold increase between 2012 and 2020.ConclusionDelirium coding rates have shown large increases in the NHS in England and Scotland, likely reflecting several factors including policy initiatives, detection tool implementation and education

Positive Scores on the 4AT Delirium Assessment Tool at Hospital Admission are Linked to Mortality, Length of Stay, and Home Time:Two-Centre Study of 82,770 Emergency Admissions

BACKGROUND: Studies investigating outcomes of delirium using large-scale routine data are rare. We performed a two-centre study using the 4 ‘A’s Test (4AT) delirium detection tool to analyse relationships between delirium and 30-day mortality, length of stay and home time (days at home in the year following admission). METHODS: The 4AT was performed as part of usual care. Data from emergency admissions in patients ≥65 years in Lothian, UK (n = 43,946) and Salford, UK (n = 38,824) over a period of [Formula: see text] 3 years were analysed using logistic regression models adjusted for age and sex. RESULTS: 4AT completion rates were 77% in Lothian and 49% in Salford. 4AT scores indicating delirium (≥4/12) were present in 18% of patients in Lothian, and 25% of patients in Salford. Thirty-day mortality with 4AT ≥4 was 5.5-fold greater than the 4AT 0/12 group in Lothian (adjusted odds ratio (aOR) 5.53, 95% confidence interval [CI] 4.99–6.13) and 3.4-fold greater in Salford (aOR 3.39, 95% CI 2.98–3.87). Length of stay was more than double in patients with 4AT scores of 1–3/12 (indicating cognitive impairment) or ≥ 4/12 compared with 4AT 0/12. Median home time at 1 year was reduced by 112 days (Lothian) and 61 days (Salford) in the 4AT ≥4 group (P < 0.001). CONCLUSIONS: Scores on the 4AT used at scale in practice are strongly linked with 30-day mortality, length of hospital stay and home time. The findings highlight the need for better understanding of why delirium is linked with poor outcomes and also the need to improve delirium detection and treatment

Delirium detection tools show varying tool completion rates and positive score proportions when used at scale in routine care: a systematic review.

Background: Multiple short delirium detection tools have been validated in research studies and implemented in routine care, but there has been little study of these tools in real-world conditions. This systematic review synthesized literature reporting completion rates and/or delirium positive score rates of detection tools in large clinical populations in general hospital settings.Methods: PROSPERO (CRD42022385166).Medline, Embase, PsycINFO, CINAHL, and gray literature were searched from1980 to December 31, 2022. Included studies or audit reports used a validateddelirium detection tool performed directly with the patient as part of routinecare in large clinical populations (n ≥ 1000) within a general acute hospitalsetting. Narrative synthesis was performed.Results: Twenty-two research studies and four audit reports were included.Tools used alone or in combination were the Confusion Assessment Method(CAM), 4 ‘A's Test (4AT), Delirium Observation Screening Scale (DOSS), BriefCAM (bCAM), Nursing Delirium Screening Scale (NuDESC), and IntensiveCare Delirium Screening Checklist (ICDSC). Populations and settings variedand tools were used at different stages and frequencies in the patient journey,including on admission only; inpatient, daily or more frequently; on admissionand as inpatient; inpatient post-operatively. Tool completion rates ranged from19% to 100%. Admission positive score rates ranged from: CAM 8%–51%; 4AT13%–20%. Inpatient positive score rates ranged from: CAM 2%–20%, DOSS 6%–42%, and NuDESC 5–13%. Postoperative positive score rates were 21% and28% (4AT). All but two studies had moderate–high risk of bias.Conclusions: This systematic review of delirium detection tool implementation in large acute patient populations found clinically important variability intool completion rates, and in delirium positive score rates relative to expecteddelirium prevalence. This study highlights a need for greater reporting andanalysis of relevant healthcare systems data. This is vital to advance understanding of effective delirium detection in routine car