Leveraging unstructured data to identify hereditary angioedema patients in electronic medical records

被引:2
作者
Brouwer, Emily S. [1 ]
Bratton, Emily W. [2 ]
Near, Aimee M. [2 ]
Sanders, Lynn [1 ]
Mack, Christina D. [2 ]
机构
[1] Takeda Pharmaceut Co Ltd, 300 Shire Way, Lexington, MA 02421 USA
[2] IQVIA, Durham, NC USA
关键词
Electronic medical records; Epidemiology; Feasibility study; Hereditary angioedema; Real-world data; Unstructured data;
D O I
10.1186/s13223-021-00541-6
中图分类号
R392 [医学免疫学];
学科分类号
100102 ;
摘要
Background The epidemiologic impact of hereditary angioedema (HAE) is difficult to quantify, due to misclassification in retrospective studies resulting from non-specific diagnostic coding. The aim of this study was to identify cohorts of patients with HAE-1/2 by evaluating structured and unstructured data in a US ambulatory electronic medical record (EMR) database. Methods A retrospective feasibility study was performed using the GE Centricity EMR Database (2006-2017). Patients with >= 1 diagnosis code for HAE-1/2 (International Classification of Diseases, Ninth Revision, Clinical Modification 277.6 or International Classification of Diseases, Tenth Revision, Clinical Modification D84.1) and/or >= 1 physician note regarding HAE-1/2 and >= 6 months' data before and after the earliest code or note (index date) were included. Two mutually exclusive cohorts were created: probable HAE (>= 2 codes or >= 2 notes on separate days) and suspected HAE (only 1 code or note). The impact of manually reviewing physician notes on cohort formation was assessed, and demographic and clinical characteristics of the 2 final cohorts were described. Results Initially, 1691 patients were identified: 190 and 1501 in the probable and suspected HAE cohorts, respectively. After physician note review, the confirmed HAE cohort comprised 254 patients and the suspected HAE cohort decreased to 1299 patients; 138 patients were determined not to have HAE and were excluded. The overall false-positive rate for the initial algorithms was 8.2%. Across final cohorts, the median age was 50 years and > 60% of patients were female. HAE-specific prescriptions were identified for 31% and 2% of the confirmed and suspected HAE cohorts, respectively. Conclusions Unstructured EMR data can provide valuable information for identifying patients with HAE-1/2. Further research is needed to develop algorithms for more representative HAE cohorts in retrospective studies.
引用
收藏
页数:10
相关论文
共 39 条
  • [1] Improving Case Definition of Crohn's Disease and Ulcerative Colitis in Electronic Medical Records Using Natural Language Processing: A Novel Informatics Approach
    Ananthakrishnan, Ashwin N.
    Cai, Tianxi
    Savova, Guergana
    Cheng, Su-Chun
    Chen, Pei
    Perez, Raul Guzman
    Gainer, Vivian S.
    Murphy, Shawn N.
    Szolovits, Peter
    Xia, Zongqi
    Shaw, Stanley
    Churchill, Susanne
    Karlson, Elizabeth W.
    Kohane, Isaac
    Plenge, Robert M.
    Liao, Katherine P.
    [J]. INFLAMMATORY BOWEL DISEASES, 2013, 19 (07) : 1411 - 1420
  • [2] Epidemiology of Bradykinin-mediated angioedema: a systematic investigation of epidemiological studies
    Aygoeren-Puersuen, Emel
    Magerl, Markus
    Maetzel, Andreas
    Maurer, Marcus
    [J]. ORPHANET JOURNAL OF RARE DISEASES, 2018, 13
  • [3] Hereditary angioedema from the patient's perspective: A follow-up patient survey
    Banerji, Aleena
    Li, Yu
    Busse, Paula
    Riedl, Marc A.
    Holtzman, Nicole S.
    Li, Huamin Henry
    Davis-Lorton, Mark
    Bernstein, Jonathan A.
    Frank, Michael
    Castaldo, Anthony J.
    Long, Janet
    Zuraw, Bruce
    Lumry, William
    Christiansen, Sandra
    [J]. ALLERGY AND ASTHMA PROCEEDINGS, 2018, 39 (03) : 212 - 223
  • [4] Research use of electronic health records: patients' perspectives on contact by researchers
    Brelsford, Kathleen M.
    Spratt, Susan E.
    Beskow, Laura M.
    [J]. JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2018, 25 (09) : 1122 - 1129
  • [5] Contribution of Electronic Medical Records to the Management of Rare Diseases
    Bremond-Gignac, Dominique
    Lewandowski, Elisabeth
    Copin, Henri
    [J]. BIOMED RESEARCH INTERNATIONAL, 2015, 2015
  • [6] Disease Severity, Activity, Impact, and Control and How to Assess Them in Patients with Hereditary Angioedema.
    Bygum, Anette
    Busse, Paula
    Caballero, Teresa
    Maurer, Marcus
    [J]. FRONTIERS IN MEDICINE, 2017, 4
  • [7] Intelligent use and clinical benefits of electronic health records in rheumatoid arthritis
    Carroll, Robert J.
    Eyler, Anne E.
    Denny, Joshua C.
    [J]. EXPERT REVIEW OF CLINICAL IMMUNOLOGY, 2015, 11 (03) : 329 - 337
  • [8] Development of a validated algorithm for the diagnosis of paediatric asthma in electronic medical records
    Cave, Andrew J.
    Davey, Christina
    Ahmadi, Elaheh
    Drummond, Neil
    Fuentes, Sonia
    Kazemi-Bajestani, Seyyed Mohammad Reza
    Sharpe, Heather
    Taylor, Matt
    [J]. NPJ PRIMARY CARE RESPIRATORY MEDICINE, 2016, 26
  • [9] Early recognition of multiple sclerosis using natural language processing of the electronic health record
    Chase, Herbert S.
    Mitrani, Lindsey R.
    Lu, Gabriel G.
    Fulgieri, Dominick J.
    [J]. BMC MEDICAL INFORMATICS AND DECISION MAKING, 2017, 17 : 24
  • [10] Clarke Christina L, 2016, EGEMS (Wash DC), V4, P1209, DOI 10.13063/2327-9214.1209