title: Use of an administrative data set to determine optimal scheduling of an alcohol intervention worker.
abstract: BACKGROUND
  Brief alcohol interventions are efficacious in reducing alcohol-related consequences among emergency department (ED) patients. Use of non-clinical staff may increase alcohol screening and intervention; however, optimal scheduling of an alcohol intervention worker (AIW) is unknown.
  
  
  OBJECTIVE
  Determine optimal scheduling of an AIW based on peak discharge time of alcohol-related ED visits.
  
  
  METHODS
  Discharge times for consecutive patients with an alcohol-related diagnosis were abstracted from an urban ED's administrative data set from September 2005 through August 2007. Queuing theory was used to identify optimal scheduling. Data for weekends and weekdays were analyzed separately. Stationary independent period-by-period analysis was performed for hourly periods. An M/M/s queuing model, for Markovian inter-arrival time/Markovian service time/and potentially more than one server, was developed for each hour assuming: 1) a single unlimited queue; 2) 75% of patients waited no longer than 30 min for intervention; 3) AIW spent an average 20 min/patient. Estimated average utilization/hour was calculated; if utilization/hour exceeded 25%, AIW staff was considered necessary.
  
  
  RESULTS
  There were 2282 patient visits (mean age 38 years, range 11-84 years). Weekdays accounted for 45% of visits; weekends 55%. On weekdays, one AIW from 6:00 a.m.-9:00 a.m. (max utilization 42%/hour) would accommodate 28% of weekday alcohol-related patients. On weekends, 5:00 a.m.-11:00 a.m. (max utilization 50%), one AIW would cover 54% of all weekend alcohol-related visits. During other hours the utilization rate falls below 25%/hour.
  
  
  CONCLUSIONS
  Evaluating 2 years of discharge data revealed that 30 h of dedicated AIW time--18 weekend hours (5:00 a.m.-11:00 a.m.), 12 weekday hours (6:00 a.m.-9:00 a.m.)--would allow maximal patient alcohol screening and intervention with minimal additional burden to clinical staff.
authors.affiliation: Department of Emergency Medicine, University of Michigan, Ann Arbor, Michigan 48109-5303, USA.
authors.forename: Timothy A
authors.initials: TA
authors.lastname: Peterson
authors.forename: Jeffrey S
authors.initials: JS
authors.lastname: Desmond
authors.forename: Rebecca
authors.initials: R
authors.lastname: Cunningham
mesh_terms: D000293:Adolescent; D000328:Adult; D000368:Aged; D000369:Aged, 80 and over; D019973:Alcohol-Related Disorders / Q000517:prevention & control*; D001071:Appointments and Schedules; D002648:Child; D004636:Emergency Service, Hospital / Q000458:organization & administration* / Q000706:statistics & numerical data; D005260:Female; D006739:Hospital Administration; D006786:Hospitals, Urban; D006801:Humans; D008297:Male; D008875:Middle Aged; D010351:Patient Discharge; D012189:Retrospective Studies; D014850:Waiting Lists; D000078329:Workforce; D055815:Young Adult