统计方法在神经外科护理质量评估中的应用。
Statistical Approaches for Quantifying the Quality of Neurosurgical Care.
机构信息
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA; Department of Biostatistics, Harvard Chan School of Public Health, Boston, Massachusetts, USA.
Department of Health Care Policy, Harvard Medical School, Boston, Massachusetts, USA.
出版信息
World Neurosurg. 2022 May;161:331-342.e1. doi: 10.1016/j.wneu.2022.01.047.
BACKGROUND
Quantifying quality of health care can provide valuable information to patients, providers, and policy makers. However, the observational nature of measuring quality complicates assessments.
METHODS
We describe a conceptual model for defining quality and its implications about the data collected, how to make inferences about quality, and the assumptions required to provide statistically valid estimates. Twenty-one binary or polytomous quality measures collected from 101,051 adult Medicaid beneficiaries aged 18-64 years with schizophrenia from 5 U.S. states show methodology. A categorical principal components analysis establishes dimensionality of quality, and item response theory models characterize the relationship between each quality measure and a unidimensional quality construct. Latent regression models estimate racial/ethnic and geographic quality disparities.
RESULTS
More than 90% of beneficiaries filled at least 1 antipsychotic prescription and 19% were hospitalized for schizophrenia during a 12-month observational period in our multistate cohort with approximately 2/3 nonwhite beneficiaries. Four quality constructs emerged: inpatient, emergency room, pharmacologic/ambulatory, and ambulatory only. Using a 2-parameter logistic model, pharmacologic/ambulatory care quality varied from -2.35 to 1.26 (higher = better quality). Black and Latinx beneficiaries had lower pharmacologic/ambulatory quality compared with whites. Race/ethnicity modified the association of state and pharmacologic/ambulatory care quality in latent regression modeling. Average quality ranged from -0.28 (95% confidence interval, -2.15 to 1.04) for blacks in New Jersey to 0.46 [95% confidence interval, -0.89 to 1.40] for whites in Michigan.
CONCLUSIONS
By combining multiple quality measures using item response theory models, a composite measure can be estimated that has more statistical power to detect differences among subjects than the observed mean per subject.
背景
量化医疗保健质量可以为患者、提供者和政策制定者提供有价值的信息。然而，衡量质量的观察性质使评估变得复杂。
方法
我们描述了一个定义质量的概念模型，以及它对所收集数据的影响、如何对质量进行推断，以及提供统计有效估计所需的假设。来自美国 5 个州的 21 个二项或多项质量测量指标，涉及 101051 名年龄在 18-64 岁的成年医疗补助受益人的精神分裂症，展示了方法学。分类主成分分析确定质量的维度，项目反应理论模型描述每个质量测量指标与单一质量结构之间的关系。潜在回归模型估计种族/族裔和地理质量差距。
结果
在我们的多州队列中，超过 90%的受益人在 12 个月的观察期内至少开了 1 种抗精神病药物处方，19%的受益人因精神分裂症住院。有大约 2/3 的非白人受益人。出现了 4 个质量结构：住院、急诊、药物/门诊和仅门诊。使用双参数逻辑模型，药物/门诊护理质量从-2.35 到 1.26（越高越好）。与白人相比，黑人受益人和拉丁裔受益人的药物/门诊护理质量较低。种族/族裔在潜在回归模型中改变了州和药物/门诊护理质量的关联。平均质量从新泽西州黑人的-0.28（95%置信区间，-2.15 至 1.04）到密歇根州白人的 0.46（95%置信区间，-0.89 至 1.40）不等。
结论
通过使用项目反应理论模型结合多个质量测量指标，可以估计一个综合指标，该指标在检测受试者之间的差异方面比观察到的每个受试者的平均值具有更高的统计能力。
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