Research paperTrajectory of cost overtime after psychotherapy for depression in older Veterans via telemedicine
Introduction
Depression is the leading cause of disability worldwide, and is associated with an increased risk of mortality and morbidity (Kessler, 2012, Kessler and Bromet, 2013, Global Burden of Disease Study 2013 Collaborators, 2013). In addition to an increased risk from suicide, depression is associated with onset and severity of multiple chronic physical disorders including arthritis, cardiovascular disease, diabetes, hypertension and chronic pain (Kessler, 2012, Kessler and Bromet, 2013, Blazer et al., 1987). Financial costs of depression are significant, with US costs alone estimated at $210.5 billion annually (Greenberg et al., 2015). While more prevalent in younger age groups, the existing medical illnesses and disability of the elderly make the diagnosis detrimental to cognitive and role functioning (Blazer et al., 1987, Alexopoulos, 2005, Fiske et al., 2009). Suicide in the elderly is nearly twice that of younger age groups, in addition to depression being the most frequent cause of emotional distress in the elderly (Alexopoulos, 2005, Bottino et al., 2012, National Alliance on Mental Illness (NAMI), 2015).
Treatment has been shown to reduce depression, decrease pain, and increase quality of life, but the rate of treatment for individuals with depression has been historically low, and in a recent report noted it remains at 56% of those diagnosed (Greenberg et al., 2015, Snowden et al., 2003). Reasons for low levels of treatment include mobility issues, geographic isolation, and negative attitudes or stigma toward depression, which may lead people to deny symptoms or delay treatment (Alexopoulos, 2005, Centers for Disease Control and Prevention (CDC), 2010, Weiss, 1994, Egede et al., 2015). Telemedicine may offer an important option to increase access by addressing patient costs resulting from transportation and missed work, the need for increased coverage by providers to geographically remote areas, and a desire for confidentiality for those concerned with stigma (Gros et al., 2013, Stronge et al., 2007, Fortney et al., 2013, Frueh et al., 2000, Frueh et al., 2007, Richardson et al., 2009). A recent trial of psychotherapy for elderly patients with depression found telemedicine was not inferior to same-room care based on clinical outcomes of treatment response (50% reduction in symptoms from baseline to 12-months, and no longer diagnosed with major depressive disorder at 12-months) (Egede et al., 2015). The results of this trial added significantly to the evidence base in support of telepsychiatry as a way to provide effective care for depression (Egede et al., 2015).
Though theoretically cheaper, many claims regarding the cost savings of telehealth are based on logic, with few studies actually investigating the cost-effectiveness of interventions (Whitten et al., 2002, Hailey et al., 2002, Bergmo, 2009). A cross-sectional analysis found lower utilization and cost for patients in treatment for depression at a community practice (Simon et al., 2006), however, most interventional studies have shown an increase in healthcare costs after treatment as a result of increased care-seeking (Pyne et al., 2010, Fortney et al., 2011, Simon et al., 2009). In addition, most analyzes investigated cost only during the intervention, with little follow-up or attention to changes over time (Whitten et al., 2002, Hailey et al., 2002). Economic analyzes conducted on collaborative care interventions for depression found them to be effective but expensive, with increased expenditures for patients in the intervention group rather than usual care (Pyne et al., 2010). In addition, both programs in a study of telephone based care management versus additional telephone based psychotherapy led to higher outpatient costs, with the more intensive program approximately $150 higher (Simon et al., 2009).
Little strong evidence exists regarding the costs of telemedicine, and specifically telepsychiatry (Whitten et al., 2002, Hailey et al., 2002). The aim of this analysis was to analyze the trajectory of cost over time for a trial investigating the impact of telepsychology and same-room delivery of behavioral activation to elderly Veterans with depression. Analyzes focused on understanding the trajectory of cost for both treatment groups over time, and understanding the effect of treatment on cost overtime, by targeting the impact on healthcare costs before, during, and after a behavioral activation intervention.
Section snippets
Study design and participants
This randomized, controlled, non-inferiority trial is registered with ClinicaTrials.gov, number NCT00324701 (Egede et al., 2009). Participants were recruited from the Ralph H. Johnson Veterans Affairs Medical Center (VAMC) in Charleston, SC, USA and four VA community outpatient based clinics (Goose Creek, Beaufort, and Myrtle Beach, SC and Savannah, GA, USA). Eligibility was initially Veterans aged 60 years or older, however, was decreased to ages 58 or older following requests to lower the age
Results
Table 1 shows the characteristics of the study population by group assignment. The majority of patients were male (97.5%), white (60.3%), married (69%) with a mean age of 64 years old. There were no significant differences between the two groups, with the exception of health status compared to the previous year (p=0.02). 80% of participants completed all 8 sessions, and therapists achieved more than 90% protocol fidelity. See Egede et al. (2015) for detailed information on the behavioral
Discussion
Based on a randomized controlled design trial investigating evidence-based psychotherapy via telemedicine and in-person delivery, we found that while costs of care are increasing over time, increased expenditures are not due to the intervention itself. Cost trajectories between the telemedicine and in-person delivery were the same, and delivery of care via telemedicine did not change the pattern of cost in elderly patients with depression. Finally, we found that outpatient costs drove increases
Conflict of interest
The authors report no potential conflicts of interest relevant to this article.
Funding source
This study was supported by Grant #IIR 04-421 funded by the Veterans Affairs Health Services Research and Development (VA HSR&D) program (PI: Leonard Egede).
Author contributions
LEE obtained funding for the study. LEE and MG designed the study and developed the analysis. LEE, MG, EH, RJW acquired and analyzed the data. LEE, MG, EH, RJW, RA, BCF contributed to interpretation and critically revised the manuscript for important intellectual content. All authors approved the final manuscript.
Disclaimer
This article represents the views of the authors and not those of NIH, VHA or HSR&D.
Acknowledgments
We deeply appreciate the Veterans and Veterans Affairs primary care and mental health providers who contributed to this research effort.
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