title: Variation in Acute Medicine Units: Measuring it, understanding it, and reducing it.
abstract: Although there are national recommendations on the function of Acute Medicine Units (AMUs), there is no single agreed best model of care. Additionally, robust data is not always available to determine whether system changes have resulted in improvement. We designed an Excel file to interface with the hospital patient management system to provide real-time data on a number of metrics including AMU length of stay (AMULOS), mortality and readmissions. This demonstrated that improving consultant continuity of care was associated with a reduction in AMULOS and reduced variation in AMULOS. Additionally, the Excel file provides timely access to consultant and individual patient-level data. These data are clinically owned, and critical for both unit governance and quality improvement work. We would encourage all AMUs to develop a similar dataset to allow standardised comparisons between units, and better understanding of the association between models of care and patient outcomes.
authors.affiliation: Consultant in Acute Medicine, NHS Forth Valley and National Clinical Lead, Whole Systems Patient Flow Programme, Scottish Government.
authors.forename: Daniel J
authors.initials: DJ
authors.lastname: Beckett
authors.affiliation: Senior Data Analyst, NHS Forth Valley, Larbert, FK5 4WR.
authors.forename: Elaine
authors.initials: E
authors.lastname: Thomson
authors.affiliation: Speciality Trainee 5 in Acute Medicine and Clinical Research Fellow, Royal College of Physicians of Edinburgh.
authors.forename: Lindsay Em
authors.initials: LE
authors.lastname: Reid
authors.affiliation: Vice President, Institute for Healthcare Improvement, Boston, USA.
authors.forename: Robert C
authors.initials: RC
authors.lastname: Lloyd
mesh_terms: D019468:Disease Management; D004636:Emergency Service, Hospital / Q000458:organization & administration*; D005260:Female; D005544:Forecasting; D006801:Humans; D007902:Length of Stay / Q000706:statistics & numerical data*; D008297:Male; D016347:Medical Records Systems, Computerized / Q000458:organization & administration*; D017146:Models, Organizational; D009936:Organizational Innovation; D017063:Outcome Assessment, Health Care; D014481:United States