The changing nature of patient attributes available for matching.

IF 1.6 Q3 HEALTH CARE SCIENCES & SERVICES International Journal of Population Data Science Pub Date : 2022-08-25 DOI:10.23889/ijpds.v7i3.2079
Yu Deng, Lacey P. Gleason, Adam Culbertson, Don Asmonga, S. Grannis, A. Kho
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Abstract

ObjectivesPatient matching rates between organizations can be as low as fifty percent. Challenges to matching include the variation in quality and availability of patient attributes. Here we describe the changing nature of patient attributes available over the past 11-years across a diversity of care settings in the United States. ApproachOur expert panel identified 64 patient attributes that are currently used or could potentially be candidates for patient matching. We identified a national sample of 14 health care sites who sent us aggregated information on the 64 patient attributes from 2010 to 2020 (inclusive). The information included overall counts and percent availability, overall counts and percent availability by race, and counts and availability by year. Only patients having at least one visit to the site since 2010 and who were between 18 and 89 years of age at time of extraction were included. ResultsThe aggregated results revealed that first name, last name, gender, postal codes, and date of birth are highly available (>90%) across healthcare organizations and time.  Patient reported social security number, work phone number, and emergency contact declined markedly, potentially reflecting privacy concerns.  Email addresses (from 18.0% to 63.7%) and phone numbers (from 14.7% to 69.4%) increased greatly over the past 11 years. Novel patient matching attributes such as blood type, facial image, thumb print, or eye color are rarely collected across sites for all years. We observed emerging attributes including sexuality, occupation, and nickname with a small number of sites collecting these over 70%, reflecting the feasibility of wider adoption in the future. ConclusionIn this study, we examined the availability of 64 patient attributes across 14 sites from 2010 and 2020. Our findings could inform policy makers and readers about patient attributes that are used for current patient matching and emerging data attributes that could be considered for incorporation into future matching algorithms.
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可用于匹配的患者属性的变化性质。
目标组织间的患者匹配率可以低至50%。匹配的挑战包括患者属性的质量和可用性的差异。在这里,我们描述了过去11年来美国各种护理环境中患者特征的变化。方法我们的专家小组确定了64个患者属性,这些属性目前正在使用或可能是患者匹配的候选者。我们确定了14个医疗机构的全国样本,这些医疗机构向我们发送了2010年至2020年(包括2020年)64名患者特征的汇总信息。这些信息包括总体计数和可用性百分比、按种族划分的总体计数和可利用性百分比,以及按年份划分的计数和可用率。只有自2010年以来至少访问过一次该部位的患者,以及在提取时年龄在18至89岁之间的患者才被包括在内。结果汇总结果显示,不同医疗机构和时间的名字、姓氏、性别、邮政编码和出生日期的可用性很高(>90%)。患者报告的社会安全号码、工作电话号码和紧急联系明显减少,这可能反映了隐私问题。电子邮件地址(从18.0%增加到63.7%)和电话号码(从14.7%增加到69.4%)在过去11年中大幅增加。多年来,很少在不同地点收集新的患者匹配属性,如血型、面部图像、拇指指纹或眼睛颜色。我们观察到了包括性、职业和昵称在内的新兴属性,少数网站收集了超过70%的这些属性,反映了未来更广泛采用的可行性。结论在这项研究中,我们检查了2010年至2020年14个地点64个患者属性的可用性。我们的研究结果可以让政策制定者和读者了解用于当前患者匹配的患者属性,以及可以考虑纳入未来匹配算法的新兴数据属性。
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来源期刊
CiteScore
2.50
自引率
0.00%
发文量
386
审稿时长
20 weeks
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