Department of Medicine, Johns Hopkins School of Medicine, Baltimore, Maryland.
Biostatistics, Epidemiology, and Data Management (BEAD) Core, Johns Hopkins School of Medicine, Baltimore, Maryland.
J Hosp Med. 2021 Feb;16(2):77-83. doi: 10.12788/jhm.3547.
We developed a diagnostic overuse index that identifies hospitals with high levels of diagnostic intensity by comparing negative diagnostic testing rates for common diagnoses.
We prospectively identified candidate overuse metrics, each defined by the percentage of patients with a particular diagnosis who underwent a potentially unnecessary diagnostic test. We used data from seven states participating in the State Inpatient Databases. Candidate metrics were tested for temporal stability and internal consistency. Using mixed-effects ordinal regression and adjusting for regional and hospital characteristics, we compared results of our index with three Dartmouth health service area-level utilization metrics and three Medicare county-level cost metrics.
The index was comprised of five metrics with good temporal stability and internal consistency. It correlated with five of the six prespecified overuse measures. Among the Dartmouth metrics, our index correlated most closely with physician reimbursement, with an odds ratio of 2.02 (95% CI, 1.11-3.66) of being in a higher tertile of the overuse index when comparing tertiles 3 and 1 of this Dartmouth metric. Among the Medicare county-level metrics, our index correlated most closely with standardized costs of procedures per capita, with an odds ratio of 2.03 (95% CI, 1.21-3.39) of being in a higher overuse index tertile when comparing tertiles 3 and 1 of this metric.
We developed a novel overuse index that is preliminary in nature. This index is derived from readily available administrative data and shows some promise for measuring overuse of diagnostic testing at the hospital level.
通过比较常见诊断的阴性诊断检测率,我们开发了一种诊断过度使用指数,通过比较常见诊断的阴性诊断检测率,来确定诊断强度较高的医院。
我们前瞻性地确定了候选过度使用指标,每个指标都由接受特定诊断的患者中进行潜在不必要的诊断测试的百分比定义。我们使用来自参与州住院患者数据库的七个州的数据。候选指标经过时间稳定性和内部一致性测试。使用混合效应有序回归并调整区域和医院特征,我们将我们的指数与三个达特茅斯健康服务区水平利用指标和三个医疗保险县水平成本指标的结果进行了比较。
该指数由五个具有良好时间稳定性和内部一致性的指标组成。它与五个指定的过度使用指标中的五个相关。在达特茅斯指标中,我们的指数与医生报酬最相关,在比较这一达特茅斯指标的第 3 tertile 和第 1 tertile 时,其比值比为 2.02(95%CI,1.11-3.66)。在医疗保险县水平成本指标中,我们的指数与人均程序标准化成本最相关,在比较这一指标的第 3 tertile 和第 1 tertile 时,其比值比为 2.03(95%CI,1.21-3.39)。
我们开发了一种新颖的过度使用指数,具有初步性质。该指数源自现成的行政数据,在衡量医院层面诊断检测过度使用方面显示出一定的前景。