A step therapy algorithm for the treatment and management of chronic depression
Depression is a chronic and progressive condition that, when not treated adequately, can lead to severe morbidity and mortality in patients and increased costs for health plans. Despite the significance of this disease state, the majority of patients are not treated adequately to the widely accepted...
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Veröffentlicht in: | The American journal of managed care 2006-10, Vol.12 (12 Suppl), p.S335-S343 |
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container_title | The American journal of managed care |
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creator | Dunn, Jeffrey D Tierneey, John G |
description | Depression is a chronic and progressive condition that, when not treated adequately, can lead to severe morbidity and mortality in patients and increased costs for health plans. Despite the significance of this disease state, the majority of patients are not treated adequately to the widely accepted goal of remission. Patients who do not achieve remission are at greater risk of relapse and recurrence, more chronic depressive episodes, and a shorter duration between depressive episodes. Modeled partially after the Sequenced Treatment Algorithm to Relieve Depression (STAR*D) trial and based on trial data and the consensus statements of a panel of clinical professionals, a step therapy algorithm is proposed in this supplement, including considerations for screening and intervention. The primary concepts in the development of this algorithm were the use of the same clinical tool for both screening and diagnosis and the incorporation of frequent follow-up visits or calls to continuously monitor progress in patients being treated. Also discussed are considerations for drug therapy choices when switching is deemed necessary. Switching to a drug from a different class of agents than the failed trial drug is recommended based on the differential mechanism of action between classes. |
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Despite the significance of this disease state, the majority of patients are not treated adequately to the widely accepted goal of remission. Patients who do not achieve remission are at greater risk of relapse and recurrence, more chronic depressive episodes, and a shorter duration between depressive episodes. Modeled partially after the Sequenced Treatment Algorithm to Relieve Depression (STAR*D) trial and based on trial data and the consensus statements of a panel of clinical professionals, a step therapy algorithm is proposed in this supplement, including considerations for screening and intervention. The primary concepts in the development of this algorithm were the use of the same clinical tool for both screening and diagnosis and the incorporation of frequent follow-up visits or calls to continuously monitor progress in patients being treated. Also discussed are considerations for drug therapy choices when switching is deemed necessary. 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Despite the significance of this disease state, the majority of patients are not treated adequately to the widely accepted goal of remission. Patients who do not achieve remission are at greater risk of relapse and recurrence, more chronic depressive episodes, and a shorter duration between depressive episodes. Modeled partially after the Sequenced Treatment Algorithm to Relieve Depression (STAR*D) trial and based on trial data and the consensus statements of a panel of clinical professionals, a step therapy algorithm is proposed in this supplement, including considerations for screening and intervention. The primary concepts in the development of this algorithm were the use of the same clinical tool for both screening and diagnosis and the incorporation of frequent follow-up visits or calls to continuously monitor progress in patients being treated. Also discussed are considerations for drug therapy choices when switching is deemed necessary. 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Despite the significance of this disease state, the majority of patients are not treated adequately to the widely accepted goal of remission. Patients who do not achieve remission are at greater risk of relapse and recurrence, more chronic depressive episodes, and a shorter duration between depressive episodes. Modeled partially after the Sequenced Treatment Algorithm to Relieve Depression (STAR*D) trial and based on trial data and the consensus statements of a panel of clinical professionals, a step therapy algorithm is proposed in this supplement, including considerations for screening and intervention. The primary concepts in the development of this algorithm were the use of the same clinical tool for both screening and diagnosis and the incorporation of frequent follow-up visits or calls to continuously monitor progress in patients being treated. Also discussed are considerations for drug therapy choices when switching is deemed necessary. 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source | MEDLINE; Elektronische Zeitschriftenbibliothek - Frei zugängliche E-Journals |
subjects | Algorithms Chronic Disease Consensus Depressive Disorder - complications Depressive Disorder - therapy Disease Management Episode of Care Health administration Humans Managed Care Programs Recurrence United States |
title | A step therapy algorithm for the treatment and management of chronic depression |
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