Hendryx M S, Dyck D G, Srebnik D
Washington Institute for Mental Illness Research and Training, Washington State University, Spokane 99201, USA.
Health Serv Res. 1999 Apr;34(1 Pt 1):171-95.
To develop and test risk-adjustment outcome models in publicly funded mental health outpatient settings. We developed prospective risk models that used demographic and diagnostic variables; client-reported functioning, satisfaction, and quality of life; and case manager clinical ratings to predict subsequent client functional status, health-related quality of life, and satisfaction with services.
DATA SOURCES/STUDY SETTING: Data collected from 289 adult clients at five- and ten-month intervals, from six community mental health agencies in Washington state located primarily in suburban and rural areas. Data sources included client self-report, case manager ratings, and management information system data.
Model specifications were tested using prospective linear regression analyses. Models were validated in a separate sample and comparative agency performance examined.
Presence of severe diagnoses, substance abuse, client age, and baseline functional status and quality of life were predictive of mental health outcomes. Unadjusted versus risk-adjusted scores resulted in differently ranked agency performance.
Risk-adjusted functional status and patient satisfaction outcome models can be developed for public mental health outpatient programs. Research is needed to improve the predictive accuracy of the outcome models developed in this study, and to develop techniques for use in applied settings. The finding that risk adjustment changes comparative agency performance has important consequences for quality monitoring and improvement. Issues in public mental health risk adjustment are discussed, including static versus dynamic risk models, utilization versus outcome models, choice and timing of measures, and access and quality improvement incentives.
在公共资助的心理健康门诊环境中开发并测试风险调整结果模型。我们开发了前瞻性风险模型，该模型使用人口统计学和诊断变量、服务对象报告的功能状况、满意度和生活质量，以及个案管理员的临床评分来预测服务对象随后的功能状态、健康相关生活质量和对服务的满意度。
数据来源/研究背景：从华盛顿州六个主要位于郊区和农村地区的社区心理健康机构的289名成年服务对象那里，每隔五个月和十个月收集一次数据。数据来源包括服务对象的自我报告、个案管理员评分以及管理信息系统数据。
使用前瞻性线性回归分析对模型规格进行测试。在一个单独的样本中对模型进行验证，并对各机构的绩效进行比较分析。
严重诊断的存在、药物滥用、服务对象年龄、基线功能状态和生活质量可预测心理健康结果。未经调整的分数与风险调整后的分数导致各机构绩效排名不同。
可为公共心理健康门诊项目开发风险调整后的功能状态和患者满意度结果模型。需要开展研究以提高本研究中开发的结果模型的预测准确性，并开发适用于实际应用场景的技术。风险调整会改变各机构绩效比较这一发现，对质量监测和改进具有重要意义。本文讨论了公共心理健康风险调整中的问题，包括静态与动态风险模型、利用率与结果模型、测量的选择和时机，以及获得服务的机会和质量改进激励措施。
