Explaining accesses to electronic medical records using diagnosis information

被引:11
|
作者
Fabbri, Daniel [1 ]
LeFevre, Kristen [1 ]
机构
[1] Univ Michigan, Ann Arbor, MI 48109 USA
基金
美国国家科学基金会;
关键词
AUDIT TRAILS; HEALTH;
D O I
10.1136/amiajnl-2012-001018
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Objective Ensuring the security and appropriate use of patient health information contained within electronic medical records systems is challenging. Observing these difficulties, we present an addition to the explanation-based auditing system (EBAS) that attempts to determine the clinical or operational reason why accesses occur to medical records based on patient diagnosis information. Accesses that can be explained with a reason are filtered so that the compliance officer has fewer suspicious accesses to review manually. Methods Our hypothesis is that specific hospital employees are responsible for treating a given diagnosis. For example, Dr Carl accessed Alice's medical record because Hem/Onc employees are responsible for chemotherapy patients. We present metrics to determine which employees are responsible for a diagnosis and quantify their confidence. The auditing system attempts to use this responsibility information to determine the reason why an access occurred. We evaluate the auditing system's classification quality using data from the University of Michigan Health System. Results The EBAS correctly determines which departments are responsible for a given diagnosis. Adding this responsibility information to the EBAS increases the number of first accesses explained by a factor of two over previous work and explains over 94% of all accesses with high precision. Conclusions The EBAS serves as a complementary security tool for personal health information. It filters a majority of accesses such that it is more feasible for a compliance officer to review the remaining suspicious accesses manually.
引用
收藏
页码:52 / 60
页数:9
相关论文
共 50 条
  • [31] ELECTRONIC MEDICAL RECORDS
    Taft, Edwin G.
    [J]. SCIENTIFIC AMERICAN, 2014, 310 (03) : 6 - +
  • [32] Electronic medical records
    Viner, Gary
    Parush, Avi
    [J]. CANADIAN MEDICAL ASSOCIATION JOURNAL, 2008, 179 (01) : 54 - 54
  • [33] Electronic medical records
    Knebel, Patricia K.
    [J]. LABMEDICINE, 2007, 38 (07): : 393 - 393
  • [34] PREDICTING DEMENTIA DIAGNOSIS FROM COGNITIVE FOOTPRINTS IN ELECTRONIC MEDICAL RECORDS USING MACHINE LEARNING
    Zhou, Jiayi
    Luo, Hao
    Liu, Wenlong
    Zhou, Huiquan
    [J]. INNOVATION IN AGING, 2023, 7 : 391 - 391
  • [35] Identification of a potential fibromyalgia diagnosis using random forest modeling applied to electronic medical records
    Emir, Birol
    Masters, Elizabeth T.
    Mardekian, Jack
    Clair, Andrew
    Kuhn, Max
    Silverman, Stuart L.
    [J]. JOURNAL OF PAIN RESEARCH, 2015, 8 : 277 - 288
  • [36] Electronic medical records
    Nolfo, Emily A.
    [J]. CLEVELAND CLINIC JOURNAL OF MEDICINE, 2010, 77 (11) : 765 - 765
  • [37] USING ELECTRONIC COMPUTERS IN MEDICAL DIAGNOSIS
    LEDLEY, RS
    [J]. IRE TRANSACTIONS ON MEDICAL ELECTRONICS, 1960, 7 (04): : 274 - 280
  • [38] Securing electronic medical records using biometric authentication
    Krawczyk, S
    Jain, AK
    [J]. AUDIO AND VIDEO BASED BIOMETRIC PERSON AUTHENTICATION, PROCEEDINGS, 2005, 3546 : 1110 - 1119
  • [39] Learning and recommending treatments using electronic medical records
    Hoang, Khanh Hung
    Ho, Tu Bao
    [J]. KNOWLEDGE-BASED SYSTEMS, 2019, 181
  • [40] Which physicians and practices are using electronic medical records?
    Burt, CW
    Sisk, JE
    [J]. HEALTH AFFAIRS, 2005, 24 (05) : 1334 - 1343