Provider and patient characteristics associated with antidepressant nonadherence: the impact of provider specialty.
ABSTRACT Given the widespread use of anti-depressants in primary care and specialty populations, we sought to examine whether provider specialty and patient demographic and clinical characteristics were associated with nonadherence to antidepressant therapy.
We conducted an observational cohort study of 11,878 patients enrolled in Harvard Pilgrim Health Care who were newly treated with antidepressants between May 2002 and May 2004. Using generalized estimating equations, we examined predictors of 2 types of anti-depressant nonadherence: (1) immediate non-adherence: never refilling an antidepressant prescription; and (2) 6-month nonadherence: refilling an antidepressant prescription at least once, but not satisfactorily completing a 6-month treatment episode.
Compared with patients treated by primary care physicians (PCP), being treated by a psychiatrist was associated with significantly lower odds of immediate nonadherence (PCP 18% vs. psychiatrist 13%). Being treated by another type of specialist was associated with significantly higher odds of both immediate (other specialist 23%) and 6-month nonadherence (PCP 53%, psychiatrist 49%, other specialist 62%). Treatment by multiple providers was associated with lower odds of nonadherence than being treated by only 1 provider. Younger patient age and use of pain medication were associated with greater nonadherence.
Rates of both immediate and 6-month nonadherence are high, and clinicians should emphasize the importance of continuing antidepressant treatment for a sufficient duration. Patients whose depression treatment is initiated by nonpsychiatric specialists may benefit from collaborative care models. These strategies may enable providers to better manage the long-term disability associated with their patients' depression.
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ABSTRACT: Energy detection is popularly used in the detection of idle spectrum because of its simple implement and low complexity. But, the detection performance can be observably affected due to noise uncertainty. Papers have proposed some solutions to resist the effects of noise uncertainty. However, most of these papers are assumed that the noise uncertainty interval is known to the detector, designing algorithms to detect the primary user signal. Few algorithms are designed to estimate the range of the noise uncertainty. This paper presents an algorithm for energy detection based on noise variance estimation that can be relatively accurate estimated the noise uncertainty interval. The simulation results show that in the case of the noise uncertainty interval is unknown to the detector, our proposed algorithm can detect well, which is similar to the theoretical detection, and its complexity is also very low.Communication Technology (ICCT), 2012 IEEE 14th International Conference on; 01/2012
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ABSTRACT: To know the adherence to treatment in patients who initiate antidepressant drugs and to analyze the determinant factors of non-compliance, so much clinical as sociodemographic. Prospective longitudinal observational study. Primary Health Care and Mental Health Surgeries of three Castilla-La Mancha Areas. 185 adults patients who were started in antidepressant treatment were evaluated. Treatment adherence (test Haynes-Sackett, test Morisky-Green, count of tablets and MEMS), adverse effects, intensity of depressive symptoms, sociodemographic characteristics and other characteristics related to antidepressants or participants. After 6months of beginning antidepressing treatment, 46.9% (95%IC: 36.5-57.3) showed an inadequate fulfilment by pill count method and 28.6% (95%IC: 19.1-38.0) with Morisky-Green's questionnaire. To 15days the lack of adherence was 48.5% (95%IC: 40.6-56.4) and of 33.5% (95%IC: 26.1-41.0). The 38.4% (95%IC: 31.1-45.7) demonstrated some side effect during the follow-up. Using proportional risk model of Cox the variables related to compliance were: younger age, level of instruction lower than secondary studies, free medicines for pensioner, no psychotherapeutic treatment, consume a fewer antidepressants drugs and a frequency ≤3 visits to the family doctor 3months previous to the study. The non-compliance of antidepressant treatment in primary care is high from the first weeks after initiating it. The conditioning factors are related to sociodemographic characteristics and other patient characteristics as type of financing of pharmaceutical benefit and frequentness at primary care.Atención Primaria 04/2014; DOI:10.1016/j.aprim.2013.11.003 · 0.89 Impact Factor
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ABSTRACT: Background and Aims: Schizophrenia leads to significant personal costs matched by high economic costs. Cognitive function is a strong predictor of disabilities in schizophrenia, which underpin these costs. This study of cognitive remediation therapy (CRT), which has been shown to improve cognition and reduce disability in schizophrenia, aims to investigate associations between improvements in cognition and cost changes. Methods: Eighty-five participants with schizophrenia were randomized to receive CRT or treatment as usual and were assessed at baseline, posttherapy, and 6 month follow-up. Four structural equation models investigated associations between changes in cognitive function and costs of care. Results: All 4 models provided a good fit. Improvement in 3 individual cognitive variables did not predict total cost changes (model 1). But improvement in a single latent cognition factor was associated with a reduction in depression, which in turn was associated with reduced subsequent total costs (model 2). No significant associations with constituent daycare and special accommodation cost changes were apparent with 3 individual cognitive change variables (model 3). But improvement in a single latent cognitive change variable was associated with subsequent reductions in both daycare and special accommodation costs (model 4). Conclusion: This study exemplifies a method of using cost changes to investigate the effects and mechanisms of CRT and suggests that executive function change may be an important target if we are to reduce disability and resultant health and social care costs.Schizophrenia Bulletin 03/2014; 40(6). DOI:10.1093/schbul/sbu046 · 8.61 Impact Factor