Multi-objective optimization models for patient allocation during a pandemic influenza outbreak

Sun, Li; DePuy, Gail W.; Evans, Gerald W.

doi:10.1016/j.cor.2013.12.001

Cited by 98 publications

(70 citation statements)

References 46 publications

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“…Following abstract and article review for relevance, a total of 313 articles addressing surge and surge capacity remained. Following detailed text review, 50 quantitative and 11 concept papers (consensus conference recommendations) met all inclusion criteria (Tables A–E and Data Supplement S1, available as supporting information in the online version of this paper). Of the quantitative articles judged relevant, 31 articles focused on criteria and methods for decision‐making for scarce resource allocation, 16 were related to effective triage protocols, nine concerned key decision makers for surge‐capacity planning and evaluating response efficacy, seven addressed meeting workforce needs, and seven were related to developing communication and information‐sharing strategies.…”

Section: Resultsmentioning

confidence: 99%

Developments in Surge Research Priorities: A Systematic Review of the Literature Following the Academic Emergency Medicine Consensus Conference, 2007–2015

Morton

DeAugustinis

Velasquez

et al. 2015

Academic Emergency Medicine

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Objectives: In 2006, Academic Emergency Medicine (AEM) published a special issue summarizing the proceedings of the AEM consensus conference on the "Science of Surge." One major goal of the conference was to establish research priorities in the field of "disasters" surge. For this review, we wished to determine the progress toward the conference's identified research priorities: 1) defining criteria and methods for allocation of scarce resources, 2) identifying effective triage protocols, 3) determining decision-makers and means to evaluate response efficacy, 4) developing communication and information sharing strategies, and 5) identifying methods for evaluating workforce needs.Methods: Specific criteria were developed in conjunction with library search experts. PubMed, Embase, Web of Science, Scopus, and the Cochrane Library databases were queried for peer-reviewed articles from 2007 to 2015 addressing scientific advances related to the above five research priorities identified by AEM consensus conference. Abstracts and foreign language articles were excluded. Only articles with quantitative data on predefined outcomes were included; consensus panel recommendations on the above priorities were also included for the purposes of this review. Included study designs were randomized controlled trials, prospective, retrospective, qualitative (consensus panel), observational, cohort, case-control, or controlled before-and-after studies. Quality assessment was performed using a standardized tool for quantitative studies.Results: Of the 2,484 unique articles identified by the search strategy, 313 articles appeared to be related to disaster surge. Following detailed text review, 50 articles with quantitative data and 11 concept papers (consensus conference recommendations) addressed at least one AEM consensus conference surge research priority. Outcomes included validation of the benchmark of 500 beds/million of population for disaster surge capacity, effectiveness of simulation-and Internet-based tools for forecasting of hospital and regional demand during disasters, effectiveness of reverse triage approaches, development of new disaster surge metrics, validation of mass critical care approaches (altered standards of care), use of telemedicine, and predictions of optimal hospital staffing levels for disaster surge events. Simulation tools appeared to provide some of the highest quality research.

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Section: Resultsmentioning

confidence: 99%

Developments in Surge Research Priorities: A Systematic Review of the Literature Following the Academic Emergency Medicine Consensus Conference, 2007–2015

Morton

DeAugustinis

Velasquez

et al. 2015

Academic Emergency Medicine

View full text Add to dashboard Cite

show abstract

“…Nevertheless, although it is known that different definitions of equity may conflict with each other (Oliveira, 2003), most studies do not consider the joint effect of multiple equity concepts. In addition to equity, minimization of total costs has also been considered in some studies (Bretthauer Coté, 1998;Rowse, Harper, Williams & Smithies, 2013;Stummer, Doerner, Focke & Heidenberger, 2004;Sun, DePuy & Evans, 2014).…”

Section: Location Selection and Capacity Planning In The Health Sectormentioning

confidence: 98%

An integrated approach for planning a long-term care network with uncertainty, strategic policy and equity considerations

Cardoso

Oliveira

Barbosa‐Póvoa

et al. 2015

European Journal of Operational Research

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“…Accuracy of estimates of disease parameters, R 0 among them, was shown to be of paramount importance. Sun et al (2014) optimized the allocation of patients and resources to an existing network of hospitals during an influenza outbreak. A medium-term planning horizon was adopted, where surge capacity could be made available to hospitals.…”

Section: Resource Allocation For Infectious Diseasesmentioning

confidence: 99%

Spatial Resource Allocation for Emerging Epidemics: A Comparison of Greedy, Myopic, and Dynamic Policies

Long

Nohdurft

Spinler

2018

M&SOM

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Rapidly evolving infectious disease epidemics, such as the 2014 West African Ebola outbreak, pose significant health threats and present challenges to the global health community because of their heterogeneous geographic spread. Policy makers must allocate limited intervention resources quickly, in anticipation of where the outbreak is moving next. We develop a two-stage model for optimizing when and where to assign Ebola treatment units across geographic regions during the outbreak's early phases. The first stage employs a novel dynamic transmission model to forecast the occurrence of new cases at the region level, capturing connectivity among regions. We introduce an empirically estimated coefficient for behavioral adaptation to changing epidemic conditions. The second stage compares four approaches to allocate units across affected regions: (i) a heuristic based on observed cases, (ii) a greedy policy that prioritizes regions based on the reproductive number, (iii) a myopic linear program that allocates resources in the next period based on an iterative estimation-optimization approach coupled with the underlying epidemic model, and (iv) an approximate dynamic programming algorithm that optimizes over all future periods. After testing the allocation schemes under different budgets and time periods, we find that the myopic policy performs best, even when limited data are available. Our methodology could be generalized to other disease outbreaks, including the Zika virus, and other interventions.

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Multi-objective optimization models for patient allocation during a pandemic influenza outbreak

Cited by 98 publications

References 46 publications

Developments in Surge Research Priorities: A Systematic Review of the Literature Following the Academic Emergency Medicine Consensus Conference, 2007–2015

Developments in Surge Research Priorities: A Systematic Review of the Literature Following the Academic Emergency Medicine Consensus Conference, 2007–2015

An integrated approach for planning a long-term care network with uncertainty, strategic policy and equity considerations

Spatial Resource Allocation for Emerging Epidemics: A Comparison of Greedy, Myopic, and Dynamic Policies

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