How to use multiple logistic regression in retrospective database analyses

Research output: Contribution to journalArticle

8 Citations (Scopus)

Abstract

Accurately measuring the effectiveness of medical or pharmacological interventions is essential in economic evaluations. Many economic evaluations are performed retrospectively using medical and pharmacy claims databases. A challenge to using this approach is that variation in treatment patterns prevents simple comparisons between patient groups. Multiple logistic regression is a powerful technique that can overcome this challenge and is suited for evaluating dichotomous outcomes (eg, disease/no disease). An example is presented that applies multiple logistic regression to determine the impact of different drug therapies on hospitalization risk for heart failure among patient with congestive heart failure.

Original languageEnglish (US)
Pages (from-to)832-841
Number of pages10
JournalFormulary
Volume35
Issue number10
StatePublished - 2000

Fingerprint

Cost-Benefit Analysis
Heart Failure
Logistic Models
Databases
Hospitalization
Pharmacology
Drug Therapy
Therapeutics

ASJC Scopus subject areas

  • Pharmaceutical Science

Cite this

How to use multiple logistic regression in retrospective database analyses. / Abarca, J.; Armstrong, Edward P.

In: Formulary, Vol. 35, No. 10, 2000, p. 832-841.

Research output: Contribution to journalArticle

@article{e7b8eb4fa4ab43a2b8925dc2cbc8b692,
title = "How to use multiple logistic regression in retrospective database analyses",
abstract = "Accurately measuring the effectiveness of medical or pharmacological interventions is essential in economic evaluations. Many economic evaluations are performed retrospectively using medical and pharmacy claims databases. A challenge to using this approach is that variation in treatment patterns prevents simple comparisons between patient groups. Multiple logistic regression is a powerful technique that can overcome this challenge and is suited for evaluating dichotomous outcomes (eg, disease/no disease). An example is presented that applies multiple logistic regression to determine the impact of different drug therapies on hospitalization risk for heart failure among patient with congestive heart failure.",
author = "J. Abarca and Armstrong, {Edward P}",
year = "2000",
language = "English (US)",
volume = "35",
pages = "832--841",
journal = "Formulary",
issn = "1082-801X",
publisher = "Advanstar Communications",
number = "10",

}

TY - JOUR

T1 - How to use multiple logistic regression in retrospective database analyses

AU - Abarca, J.

AU - Armstrong, Edward P

PY - 2000

Y1 - 2000

N2 - Accurately measuring the effectiveness of medical or pharmacological interventions is essential in economic evaluations. Many economic evaluations are performed retrospectively using medical and pharmacy claims databases. A challenge to using this approach is that variation in treatment patterns prevents simple comparisons between patient groups. Multiple logistic regression is a powerful technique that can overcome this challenge and is suited for evaluating dichotomous outcomes (eg, disease/no disease). An example is presented that applies multiple logistic regression to determine the impact of different drug therapies on hospitalization risk for heart failure among patient with congestive heart failure.

AB - Accurately measuring the effectiveness of medical or pharmacological interventions is essential in economic evaluations. Many economic evaluations are performed retrospectively using medical and pharmacy claims databases. A challenge to using this approach is that variation in treatment patterns prevents simple comparisons between patient groups. Multiple logistic regression is a powerful technique that can overcome this challenge and is suited for evaluating dichotomous outcomes (eg, disease/no disease). An example is presented that applies multiple logistic regression to determine the impact of different drug therapies on hospitalization risk for heart failure among patient with congestive heart failure.

UR - http://www.scopus.com/inward/record.url?scp=0033782935&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=0033782935&partnerID=8YFLogxK

M3 - Article

VL - 35

SP - 832

EP - 841

JO - Formulary

JF - Formulary

SN - 1082-801X

IS - 10

ER -