title: The 'Big Five'. Hypothesis generation: a multidisciplinary intervention package reduces disease-specific hospitalisations from long-term care: a post hoc analysis of the ARCHUS cluster-randomised controlled trial.
abstract: long-term care (LTC) residents have higher hospitalisation rates than non-LTC residents. Rapid decline may follow hospitalisations, hence the importance of preventing unnecessary hospitalisations. Literature describes diagnosis-specific interventions (for cardiac failure, ischaemic heart disease, chronic obstructive pulmonary disease, stroke, pneumonia-termed 'big five' diagnoses), impacting on hospitalisations of older community-dwellers, but few RCTs show reductions in acute admissions from LTC.
  
  
  
  LTC facilities with higher than expected hospitalisations were recruited for a cluster-randomised controlled trial (RCT) of facility-based complex, non-disease-specific, 9-month intervention comprising gerontology nurse specialist (GNS)-led staff education, facility benchmarking, GNS resident review and multidisciplinary discussion of residents selected using standard criteria. In this post hoc exploratory analysis, the outcome was acute hospitalisations for 'big five' diagnoses. Re-randomisation analyses were used for end points during months 1-14. For end points during months 4-14, proportional hazards models are adjusted for within-facility clustering.
  
  
  
  we recruited 36 facilities with 1,998 residents (1,408 female; mean age 82.9 years); 1,924 were alive at 3 months. The intervention did not impact overall rates of acute hospitalisations or mortality (previously published), but resulted in fewer 'big five' admissions (RR = 0.73, 95% CI = 0.54-0.99; P = 0.043) with no significant difference in the rate of other acute admissions. When considering events occurring after 3 months (only), the intervention group were 34.7% (HR = 0.65; 95% CI = 0.49-0.88; P = 0.005) less likely to have a 'big five' acute admission than controls, with no differences in likelihood of acute admissions for other diagnoses (P = 0.96).
  
  
  
  this generic intervention may reduce admissions for common conditions which the literature shows are impacted by disease-specific admission reduction strategies.
authors.affiliation: Freemasons' Department of Geriatric Medicine, University of Auckland, Auckland, New Zealand Waitemata District Health Board, Auckland, New Zealand.
authors.forename: Martin J
authors.initials: MJ
authors.lastname: Connolly
authors.affiliation: Freemasons' Department of Geriatric Medicine, University of Auckland, Auckland, New Zealand.
authors.forename: Joanna B
authors.initials: JB
authors.lastname: Broad
authors.affiliation: Freemasons' Department of Geriatric Medicine, University of Auckland, Auckland, New Zealand Waitemata District Health Board, Auckland, New Zealand Department of Nursing, University of Auckland, Auckland, New Zealand.
authors.forename: Michal
authors.initials: M
authors.lastname: Boyd
authors.affiliation: Freemasons' Department of Geriatric Medicine, University of Auckland, Auckland, New Zealand.
authors.forename: Tony Xian
authors.initials: TX
authors.lastname: Zhang
authors.affiliation: School of Population Health, University of Auckland, Auckland, New Zealand.
authors.forename: Ngaire
authors.initials: N
authors.lastname: Kerse
authors.affiliation: Freemasons' Department of Geriatric Medicine, University of Auckland, Auckland, New Zealand Waitemata District Health Board, Auckland, New Zealand.
authors.forename: Susan
authors.initials: S
authors.lastname: Foster
authors.affiliation: Department of Statistics, University of Auckland, Auckland, New Zealand.
authors.forename: Thomas
authors.initials: T
authors.lastname: Lumley
authors.affiliation: Department of Nursing, University of Auckland, Auckland, New Zealand.
authors.forename: Noeline
authors.initials: N
authors.lastname: Whitehead
mesh_terms: D000368:Aged; D000369:Aged, 80 and over; D016000:Cluster Analysis; D016001:Confidence Intervals; D005260:Female; D015577:Geriatric Assessment; D006707:Homes for the Aged / Q000458:organization & administration*; D017052:Hospital Mortality / Q000639:trends; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D033183:Interdisciplinary Communication; D008134:Long-Term Care / Q000458:organization & administration*; D008297:Male; D009520:New Zealand; D009735:Nursing Homes / Q000458:organization & administration*; D010343:Patient Admission / Q000706:statistics & numerical data*; D010348:Patient Care Team / Q000458:organization & administration; D016016:Proportional Hazards Models; D018570:Risk Assessment; D016019:Survival Analysis
keywords: aged; hospitalisation; long-term care; older people