5N-5 INCORPORATION OF PATIENT COLONIZATION WITH VANCOMYCIN-RESISTANT ENTEROCOCCUS (VRE) AND METHICILLIN-RESISTANT STAPHYLOCOCCUS AUREUS (MRSA) AND PATIENT ACUITY INTO A DISCRETE EVENT SIMULATION MODEL OF INPATIENT BED ALLOCATION AND PATIENT FLOW

Wednesday, October 22, 2014: 11:00 AM

Erica Shenoy, MD, PhD, Hang Lee, PhD, Taige Hou, BS, Erin Ryan, MPH, Jessica Cotter, MPH, Winston Ware, MS, David Hooper, MD and Rochelle P. Walensky, MD, MPH, Massachusetts General Hospital, Boston, MA

Purpose:

   Our objective was to incorporate VRE/MRSA colonization and acuity into a discrete event simulation model of bed allocation and patient flow, which requires matching patients to beds on acuity and service. In semi-privates rooms, additional matching is required on gender and patient history of colonization with VRE/MRSA. Like-gender, like-colonized patients can be cohorted.

Methods:

   We developed a discrete event model, using input data from a repository of 104,725 admissions between 2010─2011, including clinical and demographic data. Probability distributions of hourly time-varying acuity states were created over the admission duration based on patient movement time-stamps. The data were reduced to populate the model with patients arriving hourly with characteristics drawn from a joint distribution of acuity, service, gender, and VRE/MRSA colonization status. At each 1h time step, the model drew samples from the distribution; if a change in colonization or acuity resulted in a patient-bed mismatch, the patient was re-allocated when an appropriate bed became available. We examined mean length of stay (LOS, d) and occupancy to ensure accurate capture of patient flow, colonization status, and relative proportions of acuity transitions.

Result:

   In a simulated hospital with 758 beds (67% semi-private), the model matched patients to beds based on observed characteristics: acuity (12% observation; 68% general; 12% step-down and 8% intensive care unit), service (53% medicine; 47% surgery) , gender (49% female) and colonization status (90.3% non-colonized, 4.1% VRE, 3.6% MRSA, 2.0% VRE/MRSA). Most patients remained in their current acuity, however, and the most common transition was to General Care Units (Figure). Mean LOS (± SD) in the repository was 4.7 ± 5.5d; the model-estimated LOS after five years and >240,000 admissions was 4.9 ± 5.1d. We achieved a model-estimated occupancy of 80.3 ± 4.3% compared to hospital-reported 82.9 ± 1.7%. The proportion of occupied beds, by observed colonization was: 89.8% non-colonized, 4.8% VRE, 3.2% MRSA and 2.2% VRE/MRSA.

Conclusion:

   Patient flow is influenced by arrivals and discharges of patients as well as within-hospital transfers, which are driven by observed VRE/MRSA colonization status and acuity. Incorporation of both in models of patient flow will increase their utility to clinicians and policy makers.

Figure. Relative proportions of acuity transitions from Observation, General Care, Step-Down and Intensive Care Units. The y-axes are the proportion transitioning.