Literature DB >> 24327482

Economic analysis of an internet-based depression prevention intervention.

Alexander Ruby1, Monika Marko-Holguin, Joshua Fogel, Benjamin W Van Voorhees.   

Abstract

BACKGROUND: The transition through adolescence places adolescents at increased risk of depression, yet care-seeking in this population is low, and treatment is often ineffective. In response, we developed an Internet-based depression prevention intervention (CATCH-IT) targeting at-risk adolescents. AIMS OF THE STUDY: We explore CATCH-IT program costs, especially safety costs, in the context of an Accountable Care Organization as well as the perceived value of the Internet program.
METHODS: Total and per-patient costs of development were calculated using an assumed cohort of a 5,000-patient Accountable Care Organization. Total and per-patient costs of implementation were calculated from grant data and the Medicare Resource-Based Relative Value Scale (RBRVS) and were compared to the willingness-to-pay for CATCH-IT and to the cost of current treatment options. The cost effectiveness of the safety protocol was assessed using the number of safety calls placed and the percentage of patients receiving at least one safety call. The willingness-to-pay for CATCH-IT, a measure of its perceived value, was assessed using post-study questionnaires and was compared to the development cost for a break-even point.
RESULTS: We found the total cost of developing the intervention to be USD 138,683.03. Of the total, 54% was devoted to content development with per patient cost of USD 27.74. The total cost of implementation was found to be USD 49,592.25, with per patient cost of USD 597.50. Safety costs accounted for 35% of the total cost of implementation. For comparison, the cost of a 15-session group cognitive behavioral therapy (CBT) intervention aimed at at-risk adolescents was USD 1,632 per patient. Safety calls were successfully placed to 96.4% of the study participants. The cost per call was USD 40.51 with a cost per participant of USD 197.99. The willingness-to-pay for the Internet portion of CATCH-IT had a median of USD 40. The break-even point to offset the cost of development was 3,468 individuals. DISCUSSION AND LIMITATIONS: Developing Internet-based interventions like CATCH-IT appears economically viable in the context of an Accountable Care Organization. Furthermore, while the cost of implementing an effective safety protocol is proportionally high for this intervention, CATCH-IT is still significantly cheaper to implement than current treatment options. Limitations of this research included diminished participation in follow-up surveys assessing willingness-to-pay. IMPLICATIONS FOR HEALTH CARE PROVISION AND USE AND HEALTH POLICIES: This research emphasizes that preventive interventions have the potential to be cheaper to implement than treatment protocols, even before taking into account lost productivity due to illness. Research such as this business application analysis of the CATCH-IT program highlights the importance of supporting preventive medical interventions as the healthcare system already does for treatment interventions. IMPLICATIONS FOR FURTHER RESEARCH: This research is the first to analyze the economic costs of an Internet-based intervention. Further research into the costs and outcomes of such interventions is certainly warranted before they are widely adopted. Furthermore, more research regarding the safety of Internet-based programs will likely need to be conducted before they are broadly accepted.

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Mesh:

Year:  2013        PMID: 24327482      PMCID: PMC6205755     

Source DB:  PubMed          Journal:  J Ment Health Policy Econ        ISSN: 1099-176X


  18 in total

Review 1.  Theory versus practice: a review of 'willingness-to-pay' in health and health care.

Authors:  J A Olsen; R D Smith
Journal:  Health Econ       Date:  2001-01       Impact factor: 3.046

2.  Cost-effectiveness of an intervention to prevent depression in at-risk teens.

Authors:  Frances L Lynch; Mark Hornbrook; Gregory N Clarke; Nancy Perrin; Michael R Polen; Elizabeth O'Connor; John Dickerson
Journal:  Arch Gen Psychiatry       Date:  2005-11

3.  The prevention of depressive symptoms in children and adolescents: A meta-analytic review.

Authors:  Jason L Horowitz; Judy Garber
Journal:  J Consult Clin Psychol       Date:  2006-06

Review 4.  Adolescent depression: description, causes, and interventions.

Authors:  Benjamin L Hankin
Journal:  Epilepsy Behav       Date:  2005-12-13       Impact factor: 2.937

5.  Internet-based depression prevention over the life course: a call for behavioral vaccines.

Authors:  Benjamin W Van Voorhees; Nicholas Mahoney; Rina Mazo; Alinne Z Barrera; Christopher P Siemer; Tracy R G Gladstone; Ricardo F Muñoz
Journal:  Psychiatr Clin North Am       Date:  2011-03

Review 6.  Major depressive disorder in older adolescents: prevalence, risk factors, and clinical implications.

Authors:  P M Lewinsohn; P Rohde; J R Seeley
Journal:  Clin Psychol Rev       Date:  1998-11

7.  Cost-effectiveness of targeted and tailored interventions on colorectal cancer screening use.

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8.  Cost-effectiveness of treatments for adolescent depression: results from TADS.

Authors:  Marisa Elena Domino; Barbara J Burns; Susan G Silva; Christopher J Kratochvil; Benedetto Vitiello; Mark A Reinecke; Jeremy Mario; John S March
Journal:  Am J Psychiatry       Date:  2008-04-15       Impact factor: 18.112

9.  The epidemiology of major depressive disorder: results from the National Comorbidity Survey Replication (NCS-R).

Authors:  Ronald C Kessler; Patricia Berglund; Olga Demler; Robert Jin; Doreen Koretz; Kathleen R Merikangas; A John Rush; Ellen E Walters; Philip S Wang
Journal:  JAMA       Date:  2003-06-18       Impact factor: 56.272

10.  Randomized clinical trial of an Internet-based depression prevention program for adolescents (Project CATCH-IT) in primary care: 12-week outcomes.

Authors:  Benjamin W Van Voorhees; Joshua Fogel; Mark A Reinecke; Tracy Gladstone; Scott Stuart; Jackie Gollan; Nathan Bradford; Rocco Domanico; Blake Fagan; Ruth Ross; Jon Larson; Natalie Watson; Dave Paunesku; Stephanie Melkonian; Sachiko Kuwabara; Tim Holper; Nicholas Shank; Donald Saner; Amy Butler; Amy Chandler; Tina Louie; Cynthia Weinstein; Shannon Collins; Melinda Baldwin; Abigail Wassel; Karin Vanderplough-Booth; Jennifer Humensky; Carl Bell
Journal:  J Dev Behav Pediatr       Date:  2009-02       Impact factor: 2.225

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  12 in total

1.  More than just tracking time: Complex measures of user engagement with an internet-based health promotion intervention.

Authors:  Nina B Baltierra; Kathryn E Muessig; Emily C Pike; Sara LeGrand; Sheana S Bull; Lisa B Hightow-Weidman
Journal:  J Biomed Inform       Date:  2015-12-28       Impact factor: 6.317

2.  Understanding adolescent response to a technology-based depression prevention program.

Authors:  Tracy Gladstone; Monika Marko-Holguin; Jordan Henry; Joshua Fogel; Anne Diehl; Benjamin W Van Voorhees
Journal:  J Clin Child Adolesc Psychol       Date:  2013-11-18

3.  Effectiveness and Cost-effectiveness of School-based Dissemination Strategies of an Internet-based Program for the Prevention and Early Intervention in Eating Disorders: A Randomized Trial.

Authors:  Markus Moessner; Carla Minarik; Fikret Ozer; Stephanie Bauer
Journal:  Prev Sci       Date:  2016-04

4.  Impact of an online depression prevention intervention on suicide risk factors for adolescents and young adults.

Authors:  Benjamin Dickter; Eduardo L Bunge; Lisa M Brown; Yan Leykin; Erin E Soares; Benjamin Van Voorhees; Monika Marko-Holguin; Tracy R G Gladstone
Journal:  Mhealth       Date:  2019-05-07

Review 5.  Economic Evaluations of Internet-Based Psychological Interventions for Anxiety Disorders and Depression: A Systematic Review.

Authors:  Lauren M Mitchell; Udita Joshi; Vikram Patel; Chunling Lu; John A Naslund
Journal:  J Affect Disord       Date:  2021-02-05       Impact factor: 4.839

6.  Assessing costs of developing a digital program for training community health workers to deliver treatment for depression: A case study in rural India.

Authors:  Udita Joshi; John A Naslund; Aditya Anand; Deepak Tugnawat; Ram Vishwakarma; Anant Bhan; Vikram Patel; Chunling Lu
Journal:  Psychiatry Res       Date:  2021-11-25       Impact factor: 3.222

7.  Music Streaming Services as Adjunct Therapies for Depression, Anxiety, and Bipolar Symptoms: Convergence of Digital Technologies, Mobile Apps, Emotions, and Global Mental Health.

Authors:  Karl Schriewer; Grzegorz Bulaj
Journal:  Front Public Health       Date:  2016-09-30

Review 8.  eMental Healthcare Technologies for Anxiety and Depression in Childhood and Adolescence: Systematic Review of Studies Reporting Implementation Outcomes.

Authors:  Lori Wozney; Patrick J McGrath; Kathryn Bennett; Anna Huguet; Lisa Hartling; Michele P Dyson; Nicole D Gehring; Amir Soleimani; Amanda S Newton
Journal:  JMIR Ment Health       Date:  2018-06-26

9.  Prevention of Adolescent Depression in Primary Care: Barriers and Relational Work Solutions.

Authors:  Nicholas Mahoney; Tracy Gladstone; Daniela DeFrino; Allison Stinson; Jennifer Nidetz; Jason Canel; Eumene Ching; Anita Berry; James Cantorna; Joshua Fogel; Milton Eder; Megan Bolotin; Benjamin W Van Voorhees
Journal:  Calif J Health Promot       Date:  2017-08

Review 10.  Support from the Internet for Individuals with Mental Disorders: Advantages and Disadvantages of e-Mental Health Service Delivery.

Authors:  Jörn Moock
Journal:  Front Public Health       Date:  2014-06-11
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