Evidence map›Paper›PMID 28662601›Full record

ArticleMedical decision making : an international journal of the Society for Medical Decision Making2018

A Discrete Event Simulation Model of Patient Flow in a General Hospital Incorporating Infection Control Policy for Methicillin-Resistant Staphylococcus Aureus (MRSA) and Vancomycin-Resistant Enterococcus (VRE).

Erica S Shenoy, Hang Lee, Erin E Ryan, Taige Hou, Rochelle P Walensky, Winston Ware, David C Hooper

Abstract read
In one paragraph

Article in Medical decision making : an international journal of the Society for Medical Decision Making, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
2citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

2 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors.

Erica S ShenoyInfection Control Unit, Massachusetts General Hospital, Boston, MA, USA (ESS, DCH).
Hang LeeMassachusetts General Hospital Biostatistics Center, Boston, MA, USA (HL).
Erin E RyanMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA (ESS, ER, TH, RPW).
Taige HouMedical Practice Evaluation Center, Massachusetts General Hospital, Boston, MA, USA (ESS, ER, TH, RPW).
Rochelle P WalenskyDivision of Infectious Diseases, Department of Medicine, Massachusetts General Hospital, Boston, MA, USA (ESS, RPW, DCH).
Winston WareClinical Care Management Unit, Massachusetts General Hospital, Boston, MA, USA (WW).
David C HooperInfection Control Unit, Massachusetts General Hospital, Boston, MA, USA (ESS, DCH).

Funding

Harvard Clinical and Translational Science CenterUL1TR001102 · NCATS · HARVARD MEDICAL SCHOOL · PI NADLER, LEE MARSHALL · 2013 to 2017
$106.2M
Improving clinical, operational and economic outcomes related to MRSAK01AI110524 · NIAID · MASSACHUSETTS GENERAL HOSPITAL · PI SHENOY, ERICA SEIGUER · 2014 to 2016
$411k
NCATS NIH HHS UL1 TR001102NIAID NIH HHS K01 AI110524
6 · The paper itself

Abstract

backgroundHospitalized patients are assigned to available staffed beds based on patient acuity and services required. In hospitals with double-occupancy rooms, patients must be additionally matched by gender. Patients with methicillin-resistant Staphylococcus aureus (MRSA) or vancomycin-resistant Enterococcus (VRE) must be bedded in single-occupancy rooms or cohorted with other patients with similar MRSA/VRE flags.

methodsWe developed a discrete event simulation (DES) model of patient flow through an acute care hospital. Patients are matched to beds based on acuity, service, gender, and known MRSA/VRE colonization. Outcomes included time to bed arrival, length of stay, patient-bed acuity mismatches, occupancy, idle beds, acuity-related transfers, rooms with discordant MRSA/VRE colonization, and transmission due to discordant colonization.

resultsObserved outcomes were well-approximated by model-generated outcomes for time-to-bed arrival (6.7 v. 6.2 to 6.5 h) and length of stay (3.3 v. 2.9 to 3.0 days), with overlapping 90% coverage intervals. Patient-bed acuity mismatches, where patient acuity exceeded bed acuity and where patient acuity was lower than bed acuity, ranged from 0.6 to 0.9 and 8.6 to 11.1 mismatches per h, respectively. Values for observed occupancy, total idle beds, and acuity-related transfers compared favorably to model-predicted values (91% v. 86% to 87% occupancy, 15.1 v. 14.3 to 15.7 total idle beds, and 27.2 v. 22.6 to 23.7 transfers). Rooms with discordant colonization status and transmission due to discordance were modeled without an observed value for comparison. One-way and multi-way sensitivity analyses were performed for idle beds and rooms with discordant colonization.

conclusionsWe developed and validated a DES model of patient flow incorporating MRSA/VRE flags. The model allowed for quantification of the substantial impact of MRSA/VRE flags on hospital efficiency and potentially avoidable nosocomial transmission.

Indexed as

Hospitals, GeneralInfection ControlMethicillin-Resistant Staphylococcus aureusModels, TheoreticalOrganizational PolicyPatient TransferAnti-Bacterial AgentsCross InfectionEnterococcusFemaleHumansMaleMethicillinVancomycinAnti-Bacterial AgentsMethicillinVancomycindiscrete event simulationinfection controlMRSApatient flowVRE

Identifiers

PMID28662601
PMCPMC5711633

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.