Development of a minimization instrument for allocation of a hospital-level performance improvement intervention to reduce waiting times in Ontario emergency departments

doi:10.1186/1748-5908-4-32

Implementation Science

Volume 4

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Leaver CA
Guttmann A
Zwarenstein M
Rowe BH
Anderson G
Stukel T
Golden B
Bell R
Morra D
Abrams H
Schull MJ

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Leaver CA
Guttmann A
Zwarenstein M
Rowe BH
Anderson G
Stukel T
Golden B
Bell R
Morra D
Abrams H
Schull MJ
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Research article

Development of a minimization instrument for allocation of a hospital-level performance improvement intervention to reduce waiting times in Ontario emergency departments

Chad Andrew Leaver¹ , Astrid Guttmann¹^,2^,3 , Merrick Zwarenstein¹^,3^,4 , Brian H Rowe⁵ , Geoff Anderson¹^,3 , Therese Stukel¹^,3 , Brian Golden³^,6 , Robert Bell⁷ , Dante Morra⁷^,8 , Howard Abrams⁸^,9 and Michael J Schull¹^,3^,4^,8^,10

¹Institute for Clinical Evaluative Sciences, 2075 Bayview Ave, Toronto, Canada

²Department of Paediatrics, University of Toronto, Toronto, Canada

³Department of Health Policy, Management and Evaluation, University of Toronto, Toronto, Canada

⁴Centre for Health Services Sciences, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, Toronto, Canada

⁵Department of Emergency Medicine and School of Public Health, University of Alberta, Edmonton, Canada

⁶Rotman School of Management, University of Toronto, Toronto, Canada

⁷University Health Network, 90 Elizabeth St, Toronto, Canada

⁸Department of Medicine, University of Toronto, Toronto, Canada

⁹Mount Sinai Hospital, 600 University Ave, Toronto, Canada

¹⁰Clinical Epidemiology Unit, Sunnybrook Health Sciences Centre, 2075 Bayview Ave, Toronto, Canada

author email corresponding author email

Implementation Science 2009, 4:32doi:10.1186/1748-5908-4-32


Published:	8 June 2009

Abstract

Background

Rigorous evaluation of an intervention requires that its allocation be unbiased with respect to confounders; this is especially difficult in complex, system-wide healthcare interventions. We developed a short survey instrument to identify factors for a minimization algorithm for the allocation of a hospital-level intervention to reduce emergency department (ED) waiting times in Ontario, Canada.

Methods

Potential confounders influencing the intervention's success were identified by literature review, and grouped by healthcare setting specific change stages. An international multi-disciplinary (clinical, administrative, decision maker, management) panel evaluated these factors in a two-stage modified-delphi and nominal group process based on four domains: change readiness, evidence base, face validity, and clarity of definition.

Results

An original set of 33 factors were identified from the literature. The panel reduced the list to 12 in the first round survey. In the second survey, experts scored each factor according to the four domains; summary scores and consensus discussion resulted in the final selection and measurement of four hospital-level factors to be used in the minimization algorithm: improved patient flow as a hospital's leadership priority; physicians' receptiveness to organizational change; efficiency of bed management; and physician incentives supporting the change goal.

Conclusion

We developed a simple tool designed to gather data from senior hospital administrators on factors likely to affect the success of a hospital patient flow improvement intervention. A minimization algorithm will ensure balanced allocation of the intervention with respect to these factors in study hospitals.