Rosen Tony, Bao Yuhua, Zhang Yiye, Clark Sunday, Wen Katherine, Elman Alyssa, Jeng Philip, Bloemen Elizabeth, Lindberg Daniel, Krugman Richard, Campbell Jacquelyn, Bachman Ronet, Fulmer Terry, Pillemer Karl, Lachs Mark
Department of Emergency Medicine, Weill Cornell Medicine/NewYork-Presbyterian Hospital, New York, New York, USA
Department of Health Policy & Research, Weill Cornell Medical College, New York, New York, USA.
BMJ Open. 2021 Feb 5;11(2):e044768. doi: 10.1136/bmjopen-2020-044768.
Physical elder abuse is common and has serious health consequences but is under-recognised and under-reported. As assessment by healthcare providers may represent the only contact outside family for many older adults, clinicians have a unique opportunity to identify suspected abuse and initiate intervention. Preliminary research suggests elder abuse victims may have different patterns of healthcare utilisation than other older adults, with increased rates of emergency department use, hospitalisation and nursing home placement. Little is known, however, about the patterns of this increased utilisation and associated costs. To help fill this gap, we describe here the protocol for a study exploring patterns of healthcare utilisation and associated costs for known physical elder abuse victims compared with non-victims.
We hypothesise that various aspects of healthcare utilisation are differentially affected by physical elder abuse victimisation, increasing ED/hospital utilisation and reducing outpatient/primary care utilisation. We will obtain Medicare claims data for a series of well-characterised, legally adjudicated cases of physical elder abuse to examine victims' healthcare utilisation before and after the date of abuse detection. We will also compare these physical elder abuse victims to a matched comparison group of non-victimised older adults using Medicare claims. We will use machine learning approaches to extend our ability to identify patterns suggestive of potential physical elder abuse exposure. Describing unique patterns and associated costs of healthcare utilisation among elder abuse victims may improve the ability of healthcare providers to identify and, ultimately, intervene and prevent victimisation.
This project has been reviewed and approved by the Weill Cornell Medicine Institutional Review Board, protocol #1807019417, with initial approval on 1 August 2018. We aim to disseminate our results in peer-reviewed journals at national and international conferences and among interested patient groups and the public.
身体虐待老年人的情况很常见，会造成严重的健康后果，但却未得到充分认识和报告。由于医疗保健提供者的评估可能是许多老年人与家庭以外的唯一接触，临床医生有独特的机会识别疑似虐待行为并启动干预措施。初步研究表明，受虐待的老年人可能与其他老年人有不同的医疗保健利用模式，急诊部门就诊、住院和养老院安置率有所增加。然而，对于这种利用率增加的模式和相关成本知之甚少。为了填补这一空白，我们在此描述一项研究方案，该研究将探索已知身体虐待老年人受害者与非受害者相比的医疗保健利用模式及相关成本。
我们假设身体虐待老年人会对医疗保健利用的各个方面产生不同影响，增加急诊/医院利用率，降低门诊/初级保健利用率。我们将获取一系列特征明确、经法律裁决的身体虐待老年人案件的医疗保险理赔数据，以检查受害者在虐待行为被发现之前和之后的医疗保健利用情况。我们还将使用医疗保险理赔数据，将这些身体虐待老年人受害者与一组匹配的未受虐待的老年人对照组进行比较。我们将使用机器学习方法来扩展我们识别潜在身体虐待暴露迹象模式的能力。描述受虐待老年人受害者独特的医疗保健利用模式及相关成本，可能会提高医疗保健提供者识别并最终干预和预防虐待行为的能力。
本项目已由威尔康奈尔医学院机构审查委员会审查并批准，方案编号为#1807019417，于2018年8月1日获得初步批准。我们旨在将研究结果发表在同行评审期刊上，并在国内和国际会议上以及向感兴趣的患者群体和公众进行传播。
