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Measuring adherence with antidepressant medication: Comparison of hedis and PDC methodologies.

机译:用抗抑郁药测量依从性:hedis和PDC方法论的比较。

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摘要

Depression is a significant problem for the managed care system. Antidepressant medication helps ameliorate the symptoms of depression yet adherence to medication is known to be poor. The current approach to adherence measurement (i.e HEDIS) is limited or lacking. Other methods are used ( e.g Proportion of Days Covered --PDC) in other chronic diseases to measure adherence. Medication adherence is a growing concern for clinicians and other health care stakeholders (e.g payer) because of the increasing evidence that non-adherence is prevalent and places patients at an increased risk for adverse health outcomes and higher cost of care.;We conducted a retrospective cohort study of patients enrolled in a Medicaid plan. For the inclusion in the study population patients had to meet HEDIS inclusion criteria and PDC respectively. Patients included in the HEDIS study's cohort were adults at least 18 years of age with a new diagnosis of depression confirmed by outpatient medication use and an ICD-9 diagnostic code. The upper limit age was set at 75 years old in order to maintain the hidden information about the patients. Patients had to meet certain enrollment eligibility criteria as well. For the PDC study population patients met the same age requirement as for the HEDIS measurement inclusion criteria. Patients included in the study for the PDC cohort were not required to have a new diagnosis of depression certified by a diagnostic code; they only had to be antidepressant medication users during the study period. We evaluated antidepressant medication adherence by applying the HEDIS measures and PDC measures. The measure of effect was the odds ratio in separate models. We also applied HEDIS measures to the PDS cohort to be provide a head-to-head comparison of the rates of adherence. Adherence was assessed with seven medication classes as recommended by HEDIS: Miscellaneous Antidepressants Monoamine Oxidase Inhibitors (MAOIs) Phenylpiperazine Antidepressants Selective Serotonin-Norepinephrine Reuptake Inhibitors Antidepressants (SSNRIs) Selective Serotonin Reuptake Inhibitors Antidepressants (SSRIs) Tetracyclic Antidepressants (TeCAs) Tricyclic Antidepressants (TCAs). Differences in baseline characteristics and the odds of adherence were assessed between the groups for each methodology separately as well as patient demographic and health related variables. We constructed multivariate logistic regression models to measure the odds of adherence with antidepressant medication for each methodology while controlling for potential confounders and assessing for interaction terms. The level of significance and the corresponding 95% confidence intervals of the odds were presented as well.;A total of 626 eligible antidepressant users were identified according to the HEDIS criteria and 22,351 eligible antidepressant users were identified according to PDC criteria and were evaluated for adherence with antidepressant medication. In both study samples patients 50 years and older were significantly more likely to be adherent with antidepressant medication than the younger group (<35 years ) patients . In both groups patients that had respiratory disease had an increased odds of adherence with antidepressant medication relative to patients that were not classified having a respiratory disease . Patients that had other mental health diagnosis in addition to depression had a statistically increased odds of adherence with antidepressant medication relative to patients that did not have such diagnoses. The beta coefficient representing the relationship between the antidepressant medication adherence and the therapy regimen was positive and statistically significant for both samples. Patients that were using more than one drug were significantly more likely to be adherent to antidepressant medication regimen than patients that were using only one type of antidepressant drugs.;Our results implicate older age and comorbid diseases such as respiratory and other mental health diseases and polymedication as risk factors associated with better adherence with antidepressant medication therapy in Medicaid insured people. Interventions that strive to improve adherence with antidepressant medication therapy should continue to be implemented and evaluated.
机译:抑郁症是管理式护理系统的重要问题。抗抑郁药有助于缓解抑郁症状,但对药物的依从性较差。当前的依从性衡量方法(即HEDIS)有限或缺乏。在其他慢性疾病中使用其他方法(例如,所覆盖天数的比例-PDC)来衡量依从性。越来越多的证据表明,不依从现象很普遍,使患者面临不利健康结果和更高医疗费用的风险增加,因此药物依从性成为临床医生和其他医疗保健利益相关者(例如付款人)日益关注的问题。参加医疗补助计划的患者的队列研究。为了纳入研究人群,患者必须分别满足HEDIS纳入标准和PDC。 HEDIS研究队列中的患者是年龄至少18岁的成年人,通过门诊用药和ICD-9诊断代码证实患有抑郁症。上限年龄设置为75岁,以维护有关患者的隐藏信息。患者还必须满足某些入组资格标准。对于PDC研究人群,患者达到了与HEDIS测量纳入标准相同的年龄要求。参加PDC队列研究的患者不需要通过诊断代码对新发现的抑郁症进行诊断;在研究期间,他们只需要是抗抑郁药的使用者。我们通过应用HEDIS措施和PDC措施评估了抗抑郁药物的依从性。效果的量度是不同模型中的优势比。我们还对PDS队列应用了HEDIS措施,以便对依从率进行正面对比。按照HEDIS推荐的七种药物类别评估粘附性:杂类抗抑郁药单胺氧化酶抑制剂(MAOIs)苯哌嗪抗抑郁药选择性5-羟色胺-去甲肾上腺素再摄取抑制剂抗抑郁药(SSNRIs)选择性5-羟色胺再摄取抑制剂抗抑郁药(环)(抗抑郁药) 。分别评估了每种方法在各组之间基线特征和依从性的差异以及患者的人口统计学和健康相关变量。我们构建了多元逻辑回归模型,以测量每种方法对抗抑郁药物依从性的可能性,同时控制潜在的混杂因素并评估相互作用项。还给出了显着性水平和相应的赔率的95%置信区间。;根据HEDIS标准,确定了626位合格的抗抑郁药使用者;根据PDC标准,确定了22,351名合格的抗抑郁药使用者,并评估其依从性服用抗抑郁药。在这两个研究样本中,与年轻组(<35岁)患者相比,年龄在50岁及50岁以上的患者更有可能坚持使用抗抑郁药。在两组中,与未分类为呼吸系统疾病的患者相比,患有呼吸系统疾病的患者坚持抗抑郁药物的几率增加。与没有抑郁症诊断的患者相比,除了抑郁症以外还有其他精神健康诊断的患者在统计学上增加了抗抑郁药依从性的可能性。代表抗抑郁药物依从性和治疗方案之间关系的β系数对于两个样品都是阳性的,并且在统计学上具有统计学意义。与仅使用一种抗抑郁药的患者相比,使用一种以上药物的患者坚持抗抑郁药物治疗的可能性要高得多。我们的研究结果表明年龄较大且合并症包括呼吸系统疾病和其他精神疾病以及多药治疗作为医疗补助对象中与抗抑郁药物治疗依从性更好相关的危险因素。努力提高抗抑郁药物治疗依从性的干预措施应继续实施和评估。

著录项

  • 作者

    Telinoiu, Carmen Monica.;

  • 作者单位

    University of Rhode Island.;

  • 授予单位 University of Rhode Island.;
  • 学科 Health sciences.;Health care management.
  • 学位 M.S.
  • 年度 2016
  • 页码 52 p.
  • 总页数 52
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

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