State-transition modeling: A report of the ISPOR-SMDM modeling good research practices task force-3

Uwe Siebert; Oguzhan Alagoz; Ahmed M. Bayoumi; Beate Jahn; Douglas K. Owens; David J. Cohen; Karen M. Kuntz

doi:10.1177/0272989X12455463

State-transition modeling: A report of the ISPOR-SMDM modeling good research practices task force-3

Uwe Siebert, Oguzhan Alagoz, Ahmed M. Bayoumi, Beate Jahn, Douglas K. Owens, David J. Cohen, Karen M. Kuntz

Health Policy and Management

Research output: Contribution to journal › Article › peer-review

201 Scopus citations

Abstract

State-transition modeling (STM) is an intuitive, flexible, and transparent approach of computer-based decision-analytic modeling, including both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) microsimulation. Conceptualizing a decision problem in terms of a set of (health) states and transitions among these states, STM is one of the most widespread modeling techniques in clinical decision analysis, health technology assessment, and health-economic evaluation. STMs have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs.

Original language	English (US)
Pages (from-to)	690-700
Number of pages	11
Journal	Medical Decision Making
Volume	32
Issue number	5
DOIs	https://doi.org/10.1177/0272989X12455463
State	Published - Sep 2012

Bibliographical note

Funding Information:
Source of financial support: This Task Force was supported by ISPOR. U.S. and B.J were supported in part by the Oncotyrol Center for Personalized Cancer Medicine (COMET center).

Keywords

Markov models
decision-analytic modeling
guidelines
state-transition modeling

Access

10.1177/0272989X12455463

OpenUrl availability

Full text

Cite this

@article{42d8516534894460a7319d71680f136e,

title = "State-transition modeling: A report of the ISPOR-SMDM modeling good research practices task force-3",

abstract = "State-transition modeling (STM) is an intuitive, flexible, and transparent approach of computer-based decision-analytic modeling, including both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) microsimulation. Conceptualizing a decision problem in terms of a set of (health) states and transitions among these states, STM is one of the most widespread modeling techniques in clinical decision analysis, health technology assessment, and health-economic evaluation. STMs have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs.",

keywords = "Markov models, decision-analytic modeling, guidelines, state-transition modeling",

author = "Uwe Siebert and Oguzhan Alagoz and Bayoumi, {Ahmed M.} and Beate Jahn and Owens, {Douglas K.} and Cohen, {David J.} and Kuntz, {Karen M.}",

note = "Funding Information: Source of financial support: This Task Force was supported by ISPOR. U.S. and B.J were supported in part by the Oncotyrol Center for Personalized Cancer Medicine (COMET center). ",

year = "2012",

month = sep,

doi = "10.1177/0272989X12455463",

language = "English (US)",

volume = "32",

pages = "690--700",

journal = "Medical Decision Making",

issn = "0272-989X",

publisher = "SAGE Publications Inc.",

number = "5",

}

TY - JOUR

T1 - State-transition modeling

T2 - A report of the ISPOR-SMDM modeling good research practices task force-3

AU - Siebert, Uwe

AU - Alagoz, Oguzhan

AU - Bayoumi, Ahmed M.

AU - Jahn, Beate

AU - Owens, Douglas K.

AU - Cohen, David J.

AU - Kuntz, Karen M.

N1 - Funding Information: Source of financial support: This Task Force was supported by ISPOR. U.S. and B.J were supported in part by the Oncotyrol Center for Personalized Cancer Medicine (COMET center).

PY - 2012/9

Y1 - 2012/9

N2 - State-transition modeling (STM) is an intuitive, flexible, and transparent approach of computer-based decision-analytic modeling, including both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) microsimulation. Conceptualizing a decision problem in terms of a set of (health) states and transitions among these states, STM is one of the most widespread modeling techniques in clinical decision analysis, health technology assessment, and health-economic evaluation. STMs have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs.

AB - State-transition modeling (STM) is an intuitive, flexible, and transparent approach of computer-based decision-analytic modeling, including both Markov model cohort simulation as well as individual-based (first-order Monte Carlo) microsimulation. Conceptualizing a decision problem in terms of a set of (health) states and transitions among these states, STM is one of the most widespread modeling techniques in clinical decision analysis, health technology assessment, and health-economic evaluation. STMs have been used in many different populations and diseases, and their applications range from personalized health care strategies to public health programs. Most frequently, state-transition models are used in the evaluation of risk factor interventions, screening, diagnostic procedures, treatment strategies, and disease management programs.

KW - Markov models

KW - decision-analytic modeling

KW - guidelines

KW - state-transition modeling

UR - http://www.scopus.com/inward/record.url?scp=84868153203&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=84868153203&partnerID=8YFLogxK

U2 - 10.1177/0272989X12455463

DO - 10.1177/0272989X12455463

M3 - Article

C2 - 22990084

AN - SCOPUS:84868153203

SN - 0272-989X

VL - 32

SP - 690

EP - 700

JO - Medical Decision Making

JF - Medical Decision Making

IS - 5

ER -

State-transition modeling: A report of the ISPOR-SMDM modeling good research practices task force-3

Abstract

Bibliographical note

Keywords

Access

OpenUrl availability

Other files and links

Fingerprint

Cite this