Incorporating Treatment Outcomes into Quality Measurement of Depression Care

将治疗结果纳入抑郁症护理的质量衡量

• 批准号: 9789661
• 负责人: Paul Nelson Pfeiffer
• 金额: --
• 依托单位: VETERANS HEALTH ADMINISTRATION
• 依托单位国家: 美国
• 财政年份: 2016
• 资助国家: 美国
• 起止时间: 2016-04-01 至 2020-09-30
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/9789661
• 关键词: Address; Affect; Antidepressive Agents; Caring; Case Mixes; Case-Mix Adjustments; Characteristics; Clinic; Clinical; Collection; Comorbidity; Computerized Medical Record; Data; Data Adjustments; Demographic Factors; Depressive disorder; Diagnosis; Elements; Enrollment; Evaluation; Goals; Health; Health system; Healthcare Systems; Individual; Institute of Medicine (U.S.); Longitudinal prospective study; Measurement; Measures; Mental Depression; Mental Health; Mental disorders; Methods; Modality; Modeling; Newly Diagnosed; Observational Study; Outcome; Patient Outcomes Assessments; Patient-Focused Outcomes; Patients; Performance; Pharmaceutical Preparations; Pharmacotherapy; Pharmacy facility; Primary Health Care; Process; Process Measure; Provider; Psychotherapy; Quality of Care; Questionnaires; Recommendation; Reporting; Residual state; Resources; Sampling; Severities; Social support; Structure; Suicide; Symptoms; System; Telephone; Testing; Travel; Treatment outcome; Veterans; Visit; Voice; base; clinical Diagnosis; depressive symptoms; disability; effective therapy; follow up assessment; health administration; improved; improved outcome; individual patient; meetings; member; multilevel analysis; patient population; prospective; response; severe mental illness; sociodemographics; suicidal morbidity; suicide mortality; treatment site; Address; Affect; Antidepressive Agents; Caring; Case Mixes; Case-Mix Adjustments; Characteristics; Clinic; Clinical; Collection; Comorbidity; Computerized Medical Record; Data; Data Adjustments; Demographic Factors; Depressive disorder; Diagnosis; Elements; Enrollment; Evaluation; Goals; Health; Health system; Healthcare Systems; Individual; Institute of Medicine (U.S.); Longitudinal prospective study; Measurement; Measures; Mental Depression; Mental Health; Mental disorders; Methods; Modality; Modeling; Newly Diagnosed; Observational Study; Outcome; Patient Outcomes Assessments; Patient-Focused Outcomes; Patients; Performance; Pharmaceutical Preparations; Pharmacotherapy; Pharmacy facility; Primary Health Care; Process; Process Measure; Provider; Psychotherapy; Quality of Care; Questionnaires; Recommendation; Reporting; Residual state; Resources; Sampling; Severities; Social support; Structure; Suicide; Symptoms; System; Telephone; Testing; Travel; Treatment outcome; Veterans; Visit; Voice; base; clinical Diagnosis; depressive symptoms; disability; effective therapy; follow up assessment; health administration; improved; improved outcome; individual patient; meetings; member; multilevel analysis; patient population; prospective; response; severe mental illness; sociodemographics; suicidal morbidity; suicide mortality; treatment site

 DESCRIPTION (provided by applicant): Background: Depression affects an estimated one million Veterans Health Administration (VHA) patients each year and is a leading cause of disability and suicide death. There are several effective treatments for depression, including antidepressant medications and psychotherapy, yet the degree to which these treatments improve depression symptoms in clinical settings depends on the quality of care provided. Current VHA quality measures for depression mostly emphasize care processes, such as the number of days of medication dispensed or the number of psychotherapy sessions attended. However, comprehensive quality measurement should also include assessments of the clinic structures (e.g., staffing) that enable effective care processes and whether the ultimate goal of care-improved patient outcomes-is achieved. Incorporating patient-reported outcomes into quality improvement is a health system priority and has recently been recommended by the Institute of Medicine. Systematically collecting patient-reported outcomes in health care systems such as the VHA is challenging, particularly without burdening providers or introducing biases related to which patients receive follow-up assessments. This study will address these challenges by collecting depression symptom outcomes according to the Patient Health Questionnaire (PHQ-9) using an automated, telephone-based interactive voice response (IVR) system. PHQ-9 data collected across clinics in VISN 11 will be used to develop and test clinic-level outcome quality measures (OQMs). OQMs, after case-mix adjustment for differences in clinic patient populations, will allow determination of the structure and process measures (including a new measure of treatment intensification) associated with outcomes. Findings will enable leaders to identify under-performing clinics and the key aspects of care to address in order to achieve better depression outcomes for patients. Objectives: 1) Develop and assess outcome quality measures for depression from PHQ-9 and case-mix adjustment data collected by an automated IVR system, 2) assess the relationships between outcomes and care processes, including a new measure of treatment intensification, and 3) determine the association between facility characteristics (i.e., structures of care) and depression care processes and outcomes. Methods: This prospective longitudinal study will sample 2,500 VHA patients from 50 primary care and mental health clinics in VISN 11. Included patients will have a new clinical diagnosis of a depressive disorder and a PHQ-9 score ≥ 10. Patient characteristics (including duration of symptoms and socio-demographic factors) at baseline and PHQ-9 scores at 6 weeks, 12 weeks, 26 weeks and one year post-diagnosis will be collected via IVR. IVR data will be merged with health system electronic medical records of comorbid diagnoses, health system encounters, and pharmacy use. Threats to validity of IVR-based OQMs will be assessed by the percentage of enrolled patients who complete a 12-week PHQ-9 (i.e., response rate) and by predictors of call completion (i.e., response bias). Case-mix adjusted multilevel models will be used to determine reliability according to the intraclass correlation coefficient. OQMs will be defined as the clinic-level residuals in these models. Clinic-level residuals indicate an individua clinic's performance in comparison to the expected performance for the average clinic. The validity of current VHA depression care process measures (e.g., 84 days of antidepressant medication supply, 8 psychotherapy visits within 14 weeks) and a new measure of treatment intensification will be assessed by determining their association with depression outcomes at the individual and clinic-level. The association between care structures (e.g., mental health staff to-patient ratios, travel distance to clinic) and outcomes will similarly be examined, and separate models will examine the association between structures and care processes.

 描述（由申请人提供）： 背景：抑郁症每年影响约100万退伍军人卫生管理局（VHA）患者，是残疾和自杀死亡的主要原因。有几种有效的抑郁疗法，包括抗抑郁药和心理治疗，但是这些治疗方法在临床环境中改善抑郁症状的程度取决于所提供的护理质量。当前的VHA质量指标主要强调护理过程，例如分配药物的天数或参加的心理治疗疗法数量。但是，全面的质量测量还应包括对诊所结构（例如人员配备）的评估，这些评估能够实现有效的护理过程，以及是否实现了得到护理改良的患者结果的最终目标。将患者报告的结果纳入质量改进是卫生系统的优先事项，最近已由医学研究所推荐。 在诸如VHA之类的医疗保健系统中有系统地收集患者报告的结果受到挑战，尤其是没有燃烧提供者或引入与患者接受随访评估有关的偏见。这项研究将使用基于电话的，基于电话的交互式语音响应（IVR）系统根据患者健康问卷（PHQ-9）收集抑郁症的结果来解决这些挑战。 VISN 11中跨诊所收集的PHQ-9数据将用于开发和测试诊所级别质量质量指标（OQMS）。 OQM在调整临床患者人群差异的病例混合后，将允许确定与结果相关的结构和过程测量（包括对治疗强化的新测量）。调查结果将使领导者能够确定表现不佳的诊所和要解决的护理的关键方面，以便为患者带来更好的抑郁症状。 目的：1）从自动化IVR系统收集的PHQ-9和案例混合调整数据的抑郁症的结果质量度量，2）评估结果与护理过程之间的关系，包括治疗强化的新测量，以及3）确定设施特征之间的关联（即，护理的结构）和抑郁症护理过程和OUTCORES和OUTCOMES和OUTCOMES和OUTCOMES和OUTCOMES和OUTCOMES和OUTCOMES和OUTCOMES。 方法：这项前瞻性纵向研究将对VISN 11的50名初级保健和精神卫生诊所的2,500名VHA患者采样。包括患者将对抑郁症疾病的新临床诊断和PHQ-9分数≥10。患者特征（包括症状的持续时间和社会学因素和社会学因素的持续时间和社会学因素）在基线和9周，一年的时间为26周，在6周和26周中均为26周的SCORE。 IVR数据将与合并症诊断，卫生系统遭遇和药房使用的卫生系统电子病历合并。基于IVR OQM的有效性的威胁将通过完成为期12周的PHQ-9（即响应率）和呼叫完成的预测因素（即响应偏见）的入学患者百分比进行评估。案例混合调整后的多级模型将根据类内相关系数确定可靠性。 OQM将被定义为这些模型中的临床水平残差。与平均诊所的预期表现相比，诊所级残留物表明单个诊所的表现。当前VHA抑郁症护理过程测量的有效性（例如，抗抑郁药供应84天，在14周内进行8次心理治疗访问）和治疗强化的新测量方法将通过确定其与个人和临床水平的抑郁症结合的关联来评估。护理结构之间的关联（例如，心理健康人员 同样会检查患者比率，到诊所的旅行距离）和结果。 模型将检查结构和护理过程之间的关联。