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利用电子健康记录简化实施科学研究的提供者招募工作。

Using electronic health records to streamline provider recruitment for implementation science studies.

机构信息

From Geisel School of Medicine at Dartmouth College, Lebanon, NH, United States of America.

VA Salt Lake City Health Care System and University of Utah, Salt Lake City, UT, United States of America.

出版信息

PLoS One. 2022 May 13;17(5):e0267915. doi: 10.1371/journal.pone.0267915. eCollection 2022.

Abstract

BACKGROUND

Healthcare providers are often targeted as research participants, especially for implementation science studies evaluating provider- or system-level issues. Frequently, provider eligibility is based on both provider and patient factors. Manual chart review and self-report are common provider screening strategies but require substantial time, effort, and resources. The automated use of electronic health record (EHR) data may streamline provider identification for implementation science research. Here, we describe an approach to provider screening for a Veterans Health Administration (VHA)-funded study focused on implementing risk-aligned surveillance for bladder cancer patients.

METHODS

Our goal was to identify providers at 6 pre-specified facilities who performed ≥10 surveillance cystoscopy procedures among bladder cancer patients in the 12 months prior to recruitment start on January 16, 2020, and who were currently practicing at 1 of 6 pre-specified facilities. Using VHA EHR data (using CPT, ICD10 procedure, and ICD10 diagnosis codes), we identified cystoscopy procedures performed after an initial bladder cancer diagnosis (i.e., surveillance procedures). Procedures were linked to VHA staff data to determine the provider of record, the number of cystoscopies they performed, and their current location of practice. To validate this approach, we performed a chart review of 105 procedures performed by a random sample of identified providers. The proportion of correctly identified procedures was calculated (Positive Predictive Value (PPV)), along with binomial 95% confidence intervals (CI).

FINDINGS

We identified 1,917,856 cystoscopies performed on 703,324 patients from October 1, 1999-January 16, 2020, across the nationwide VHA. Of those procedures, 40% were done on patients who had a prior record of bladder cancer and were completed by 15,065 distinct providers. Of those, 61 performed ≥ 10 procedures and were currently practicing at 1 of the 6 facilities of interest in the 1 year prior to study recruitment. The random chart review of 7 providers found 101 of 105 procedures (PPV: 96%; 95% CI: 91% to 99%) were surveillance procedures and were performed by the selected provider on the recorded date.

IMPLICATIONS

These results show that EHR data can be used for accurate identification of healthcare providers as research participants when inclusion criteria consist of both patient- (temporal relationship between diagnosis and procedure) and provider-level (frequency of procedure and location of current practice) factors. As administrative codes and provider identifiers are collected in most, if not all, EHRs for billing purposes this approach can be translated from provider recruitment in VHA to other healthcare systems. Implementation studies should consider this method of screening providers.

摘要

背景

医疗保健提供者经常成为研究对象,特别是在评估提供者或系统层面问题的实施科学研究中。通常,提供者的资格是基于提供者和患者的因素。手动图表审查和自我报告是常见的提供者筛选策略,但需要大量的时间、精力和资源。电子健康记录(EHR)数据的自动使用可能会简化实施科学研究中提供者的识别。在这里,我们描述了一种针对退伍军人事务部(VA)资助的研究中提供者筛选的方法,该研究侧重于对膀胱癌患者实施风险一致的监测。

方法

我们的目标是确定 6 家指定设施中的提供者,这些提供者在 2020 年 1 月 16 日招募开始前的 12 个月内对膀胱癌患者进行了≥10 次监测膀胱镜检查,并在 6 家指定设施中的 1 家设施中进行当前的实践。使用 VA EHR 数据(使用 CPT、ICD10 程序和 ICD10 诊断代码),我们确定了在初始膀胱癌诊断后进行的膀胱镜检查程序(即监测程序)。程序与 VA 员工数据相关联,以确定记录提供者、他们进行的膀胱镜检查次数以及他们当前的实践地点。为了验证这种方法,我们对随机选择的提供者进行了 105 次程序的图表审查。计算了正确识别程序的比例(阳性预测值(PPV)),以及二项式 95%置信区间(CI)。

结果

我们在全国范围内的 VA 中确定了 1917856 例在 1999 年 10 月 1 日至 2020 年 1 月 16 日期间对 703324 名患者进行的膀胱镜检查。在这些程序中,40%是在有膀胱癌既往记录的患者身上进行的,由 15065 名不同的提供者完成。其中,61 人进行了≥10 次手术,且在研究招募前 1 年内,正在 6 家感兴趣的设施之一进行治疗。对 7 名提供者进行的随机图表审查发现,105 例中有 101 例(PPV:96%;95%CI:91%至 99%)是监测程序,是由选定的提供者在记录日期进行的。

结论

这些结果表明,当纳入标准包括患者层面(诊断和程序之间的时间关系)和提供者层面(程序的频率和当前实践地点)的因素时,EHR 数据可用于准确识别医疗保健提供者作为研究对象。由于大多数(如果不是全部)EHR 都为了计费目的而收集管理代码和提供者标识符,因此这种方法可以从 VA 中的提供者招募转化为其他医疗保健系统。实施研究应考虑这种筛选提供者的方法。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/a3ca/9106149/610f3d339d83/pone.0267915.g001.jpg

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