Browsing by Subject "Depressive Disorder"

Now showing 1 - 4 of 4
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    Cost effectiveness of telecare management for pain and depression in patients with cancer: results from a randomized trial
    (Elsevier, 2014-11) Choi Yoo, Sung J.; Nyman, John A.; Cheville, Andrea L.; Kroenke, Kurt; Department of Medicine, IU School of Medicine
    OBJECTIVE: Pain and depression are prevalent and treatable symptoms among patients with cancer, yet they are often undetected and undertreated. The Indiana Cancer Pain and Depression (INCPAD) trial demonstrated that telecare management can improve pain and depression outcomes. This article investigates the incremental cost effectiveness of the INCPAD intervention. METHODS: The INCPAD trial was conducted in 16 community-based urban and rural oncology practices in Indiana. Of the 405 participants, 202 were randomized to the intervention group and 203 to the usual-care group. Intervention costs were determined, and effectiveness outcomes were depression-free days and quality-adjusted life years. RESULTS: The intervention group was associated with a yearly increase of 60.3 depression-free days (S.E. = 15.4; P < 0.01) and an increase of between 0.033 and 0.066 quality-adjusted life years compared to the usual care group. Total cost of the intervention per patient was US$1189, which included physician, nurse care manager and automated monitoring set-up and maintenance costs. Incremental cost per depression-free day was US$19.72, which yields a range of US$18,018 to US$36,035 per quality-adjusted life year when converted to that metric. When measured directly, the incremental cost per quality-adjusted life year ranged from US$10,826 based on the modified EQ-5D to US$73,286.92 based on the SF-12. CONCLUSION: Centralized telecare management, coupled with automated symptom monitoring, appears to be a cost effective intervention for managing pain and depression in cancer patients.
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    Measurement invariance of the patient health questionnaire-9 (PHQ-9) depression screener in U.S. adults across sex, race/ethnicity, and education level: NHANES 2005–2016
    (Wiley, 2019-07-29) Patel, Jay S.; Oh, Youngha; Rand, Kevin L.; Wu, Wei; Cyders, Melissa A.; Kroenke, Kurt; Stewart, Jesse C.; Psychology, School of Science
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    Minimally Important Differences and Severity Thresholds are Estimated for the PROMIS Depression Scales from Three Randomized Clinical Trials
    (Elsevier, 2020-04-01) Kroenke, Kurt; Stump, Timothy E.; Chen, Chen X.; Kean, Jacob; Bair, Matthew J.; Damush, Teresa M.; Krebs, Erin E.; Monahan, Patrick O.
    BACKGROUND: Patient Reported Outcomes Measurement Information Systems (PROMIS) scales are increasingly being used to measure symptoms in research and practice. The purpose of this study was to determine the minimally important difference (MID) and severity thresholds (cut-points) for the four fixed-length PROMIS depression scales. METHODS: The study sample was adult participants in three randomized clinical trials (N=651). MID was estimated using multiple distribution- and anchor-based approaches including assessing correspondence between Patient Health Questionnaire (PHQ-9) and PROMIS depression scores. RESULTS: The best MID estimate was a PROMIS depression T-score of 3.5 points with most methods producing an MID in the 3 to 4 point range across all three samples. MID estimates were similar for all four PROMIS scales. A PHQ-9 1-point change equated to a PROMIS 1.25-point T-score change. PROMIS T-scores of 55, 60, 65, and 70 appeared to be reasonable thresholds for mild, moderate, moderately severe, and severe depression, respectively. LIMITATIONS: The study sample was predominantly male veterans with either chronic pain (2 trials) or previous stroke (1 trial). The severity of depression was mild to moderate. CONCLUSION: A T-score of 3 to 4 points is a reasonable MID for PROMIS depression scales and can be used to assess treatment effects in both practice and research as well to calculate sample sizes for clinical trials. Severity cut-points can help interpret the meaning of scores and action thresholds for treatment decisions.
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