dc.contributor.author |
McAnany, Steven J |
|
dc.contributor.author |
Anwar, Muhammad AF |
|
dc.contributor.author |
Qureshi, Sheeraz A |
|
dc.date.accessioned |
2022-12-01T14:34:13Z |
|
dc.date.available |
2022-12-01T14:34:13Z |
|
dc.date.issued |
2015-10 |
|
dc.identifier |
S1529-9430(15)00632-4 |
|
dc.identifier.issn |
1529-9430 |
|
dc.identifier.issn |
1878-1632 |
|
dc.identifier.uri |
https://hdl.handle.net/10161/26254 |
|
dc.description.abstract |
<h4>Background context</h4>In recent years, there has been an increase in the number
of decision analysis studies in the spine literature. Although there are several published
reviews on the different types of decision analysis (cost-effectiveness, cost-benefit,
cost-utility), there is limited information in the spine literature regarding the
mathematical models used in these studies (decision tree, Markov modeling, Monte Carlo
simulation).<h4>Purpose</h4>The purpose of this review was to provide an overview
of the types of decision analytic models used in spine surgery. A secondary aim was
to provide a systematic overview of the most cited studies in the spine literature.<h4>Study
design/setting</h4>This is a systematic review of the available information from all
sources regarding decision analytics and economic modeling in spine surgery.<h4>Methods</h4>A
systematic search of PubMed, Embase, and Cochrane review was performed to identify
the most relevant peer-reviewed literature of decision analysis/cost-effectiveness
analysis (CEA) models including decisions trees, Markov models, and Monte Carlo simulations.
Additionally, CEA models based on investigational drug exemption studies were reviewed
in particular detail, as these studies are prime candidates for economic modeling.<h4>Results</h4>The
initial review of the literature resulted in 712 abstracts. After two reviewer-assessment
of abstract relevance and methodologic quality, 19 studies were selected: 12 with
decision tree constructs and 7 with Markov models. Each study was assessed for methodologic
quality and a review of the overall results of the model. A generalized overview of
the mathematical construction and methodology of each type of model was also performed.
Limitations, strengths, and potential applications to spine research were further
explored.<h4>Conclusions</h4>Decision analytic modeling represents a powerful tool
both in the assessment of competing treatment options and potentially in the formulation
of policy and reimbursement. Our review provides a generalized overview and a conceptual
framework to help spine physicians with the construction of these models.
|
|
dc.language |
eng |
|
dc.publisher |
Elsevier BV |
|
dc.relation.ispartof |
The spine journal : official journal of the North American Spine Society |
|
dc.relation.isversionof |
10.1016/j.spinee.2015.06.045 |
|
dc.subject |
Spine |
|
dc.subject |
Humans |
|
dc.subject |
Neurosurgical Procedures |
|
dc.subject |
Decision Support Techniques |
|
dc.title |
Decision analytic modeling in spinal surgery: a methodologic overview with review
of current published literature.
|
|
dc.type |
Journal article |
|
duke.contributor.id |
Anwar, Muhammad AF|1114623 |
|
dc.date.updated |
2022-12-01T14:34:13Z |
|
pubs.begin-page |
2254 |
|
pubs.end-page |
2270 |
|
pubs.issue |
10 |
|
pubs.organisational-group |
Duke |
|
pubs.organisational-group |
School of Medicine |
|
pubs.organisational-group |
Clinical Science Departments |
|
pubs.organisational-group |
Anesthesiology |
|
pubs.organisational-group |
Anesthesiology, Pain Management |
|
pubs.publication-status |
Published |
|
pubs.volume |
15 |
|
duke.contributor.orcid |
Anwar, Muhammad AF|0000-0002-0723-4710 |
|