Heterogeneity of Drug Allergies and Reaction Lists in Two US Health Care Systems' Electronic Health Records

被引:0
|
作者
Yerneni, Sharmitha [1 ]
Shah, Sonam N. [1 ,2 ]
Blackley, Suzanne V. [3 ]
Ortega, Carlos A. [1 ]
Blumenthal, Kimberly G. [4 ,5 ,6 ,7 ]
Goss, Foster [8 ,9 ]
Seger, Diane L. [3 ]
Wickner, Paige G. [4 ,10 ]
Mancini, Christian M. [4 ,5 ,6 ,7 ]
Bates, David W. [1 ,4 ]
Zhou, Li [1 ,4 ]
机构
[1] Brigham & Womens Hosp, Div Gen Internal Med & Primary Care, 75 Francis St, Boston, MA 02115 USA
[2] Massachusetts Coll Pharm & Hlth Sci, Boston, MA 02115 USA
[3] Mass Gen Brigham, Clin & Qual Anal, Somerville, NJ USA
[4] Harvard Med Sch, Boston, MA 02115 USA
[5] Massachusetts Gen Hosp, Dept Med, Div Rheumatol Allergy & Immunol, Boston, MA 02114 USA
[6] Massachusetts Gen Hosp, Mongan Inst, Boston, MA 02114 USA
[7] Massachusetts Gen Hosp, Edward P Lawrence Ctr Qual & Safety, Boston, MA 02114 USA
[8] Univ Colorado Hosp, Dept Emergency Med, Aurora, CO USA
[9] Univ Colorado, Sch Med, Aurora, CO USA
[10] Brigham & Womens Hosp, Dept Med, Div Allergy & Clin Immunol, 75 Francis St, Boston, MA 02115 USA
来源
APPLIED CLINICAL INFORMATICS | 2022年 / 13卷 / 03期
基金
美国医疗保健研究与质量局;
关键词
clinical documentation; quality of care; interoperability; electronic health records; EVENTS;
D O I
10.1055/a-1862-9425
中图分类号
R-058 [];
学科分类号
摘要
Background Health care institutions have their own "picklist" for clinicians to document adverse drug reactions (ADRs) into the electronic health record (EHR) allergy list. Whether the lack of a nationally standardized picklist impacts clinician data entries is unknown. Objectives The objective of this study was to assess the impact of defined reaction picklists on clinical documentation and, therefore, downstream analytics and clinical research using these data at two institutions. Methods ADR data were obtained from the EHRs of patients who visited the emergency department or outpatient clinics at Brigham and Women's Hospital (BWH) and University of Colorado Hospital (UCH) from 2013 to 2018. Reported drug class ADR prevalences were calculated. We investigated the reactions on each picklist and compared the top 40 reactions at each institution, as well as the top 10 reactions within each drug class. Results Of 2,160,116 patients, 640,444 (30%) had 928,973 active drug allergies. The most commonly reported drug class allergens were similar between BWH and UCH. BWH's picklist had 48 reactions, and UCH's had 160 reactions; 29 reactions were shared by both picklists. While the top four reactions overall (rash, GI upset/nausea/vomiting, hives, itching) were identical between sites, reactions by drug class exhibited greater documentation diversity. For example, while the summed prevalence of swelling-related reactions to angiotensin-converting-enzyme inhibitors was comparable across sites, swelling was represented by two terms ("swelling," "angioedema") at BWH but 11 terms at UCH (e.g., "swelling," "edema," by body locality). Conclusion The availability and granularity of reaction picklists impact ADR documentation in the EHR by health care providers; picklists may partially explain variations in reported ADRs across health care systems.
引用
收藏
页码:741 / 751
页数:11
相关论文
共 50 条
  • [21] Quality Gaps of Electronic Health Records in Diabetes Care
    Marani, Husayn
    Halperin, Ilana Jaye
    Jamieson, Trevor
    Mukerji, Geetha
    CANADIAN JOURNAL OF DIABETES, 2020, 44 (04) : 350 - 355
  • [22] Implementing Health Care Quality Measures in Electronic Health Records: A Conceptual Model
    Campbell, Claire M.
    Murphy, Daniel R.
    Taffet, George E.
    Major, Anita B.
    Ritchie, Christine S.
    Leff, Bruce
    Naik, Aanand D.
    JOURNAL OF THE AMERICAN GERIATRICS SOCIETY, 2021, 69 (04) : 1079 - 1085
  • [23] Markers of dementia-related health in primary care electronic health records
    Campbell, Paul
    Rathod-Mistry, Trishna
    Marshall, Michelle
    Bailey, James
    Chew-Graham, Carolyn A.
    Croft, Peter
    Frisher, Martin
    Hayward, Richard
    Negi, Rashi
    Singh, Swaran
    Tantalo-Baker, Shula
    Tarafdar, Suhail
    Babatunde, Opeyemi O.
    Robinson, Louise
    Sumathipala, Athula
    Thein, Nwe
    Walters, Kate
    Weich, Scott
    Jordan, Kelvin P.
    AGING & MENTAL HEALTH, 2021, 25 (08) : 1452 - 1462
  • [24] Applying institutional theory to the adoption of electronic health records in the US
    Sherer, Susan A.
    Meyerhoefer, Chad D.
    Peng, Lizhong
    INFORMATION & MANAGEMENT, 2016, 53 (05) : 570 - 580
  • [25] The Digitization of Patient Care: A Review of the Effects of Electronic Health Records on Health Care Quality and Utilization
    Atasoy, Hilal
    Greenwood, Brad N.
    McCullough, Jeffrey Scott
    ANNUAL REVIEW OF PUBLIC HEALTH, VOL 40, 2019, 40 : 487 - 500
  • [26] Electronic health records and health care quality over time in a federally qualified health center
    Kern, Lisa M.
    Edwards, Alison M.
    Pichardo, Michelle
    Kaushal, Rainu
    JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2015, 22 (02) : 453 - 458
  • [27] Electronic health records for integrated mental health care: protocol for a scoping review
    Kariotis, Timothy
    Prictor, Megan
    Gray, Kathleen
    Chang, Shanton
    ADVANCES IN MENTAL HEALTH, 2021, 19 (01) : 63 - 74
  • [28] CONFIDENTIALITY IN ELECTRONIC HEALTH RECORDS SYSTEMS: -A REVIEW-
    El Kettani, Assiya
    Housban, Samy
    Serhier, Zineb
    Othmani, Mohammed Bennani
    JOURNAL OF MEDICAL AND SURGICAL RESEARCH, 2018, 5 (02): : 551 - 554
  • [29] Involving Health Care Professionals in the Development of Electronic Health Records: Scoping Review
    Busse, Theresa Sophie
    Jux, Chantal
    Laser, Johannes
    Rasche, Peter
    Vollmar, Horst Christian
    Ehlers, Jan P.
    Kernebeck, Sven
    JMIR HUMAN FACTORS, 2023, 10
  • [30] Disrupting Electronic Health Records Systems: The Next Generation
    Celi, Leo Anthony
    Marshall, Jeffrey David
    Lai, Yuan
    Stone, David J.
    JMIR MEDICAL INFORMATICS, 2015, 3 (04)