Identifying Accessibility Requests for Patients With Disabilities Through an Electronic Health Record-Based Questionnaire

被引:1
|
作者
Varadaraj, Varshini [2 ,3 ]
Guo, Xinxing [2 ]
Reed, Nicholas S. [3 ,4 ]
Smith, Kerry [2 ]
Boland, Michael, V [5 ]
Nanayakkara, A. J. [6 ,7 ]
Swenor, Bonnielin K. [1 ,2 ,3 ]
机构
[1] Johns Hopkins Univ, Sch Nursing, 525 N Wolfe St,Room 530P, Baltimore, MD 21287 USA
[2] Johns Hopkins Univ, Wilmer Eye Inst, Sch Med, Baltimore, MD 21287 USA
[3] Johns Hopkins Disabil Hlth Res Ctr, Baltimore, MD USA
[4] Johns Hopkins Univ, Dept Otolaryngol, Sch Med, Baltimore, MD 21287 USA
[5] Facebook, Global Accessibil Compliance, Washington, DC USA
[6] Massachusetts Eye & Ear, Boston, MA USA
[7] Harvard Med Sch, Boston, MA 02115 USA
关键词
CARE; ADA; DIAGNOSIS; ACCESS; ADULTS; PEOPLE;
D O I
10.1001/jamanetworkopen.2022.6555
中图分类号
R5 [内科学];
学科分类号
1002 ; 100201 ;
摘要
IMPORTANCE People with disabilities experience disparities in health care access and outcomes, and inaccessible health care facilities are major barriers to health care access. Methods to collect accessibility request information are needed to improve health care outcomes for patients with disabilities. OBJECTIVE To evaluate an electronic health record (EHR)-based questionnaire designed to identify accessibility requests for patients with disabilities at an eye clinic. DESIGN, SETTING, AND PARTICIPANTS This cross-sectional pilot study implemented an EHR questionnaire and prospectively collected data on accessibility requests at a university-based eye clinic. The study included 55 722 patients making appointments at the Johns Hopkins Wilmer Eye Institute from April 1, 2019, to March 31, 2020. MAIN OUTCOMES AND MEASURES The Wilmer Eye Institute staff were trained to assess accessibility requests of patients making appointments in-person or via telephone using a standardized script and entering patient responses into the EHR. Data were later extracted for analysis and used to determine the proportion of patients making eye appointments who reported a disability accessibility request (physical, sensory, or intellectual) during their clinic visit. RESULTS Accessibility request data were collected from 250 932 patient encounters. Patients had a mean (SD) age of 61.9 (20.6) years; most were women (146 846 [58.5%]) and were White individuals (162 720 (64.9%]). Of these, 23 510 (9.4%) encounters were associated with an accessibility request. The most reported accessibility request was mobility related (18 857 [7.5%]) (needing a cane, crutches, motorized scooter, walker, wheelchair, stretcher, assistance standing, or transport services), followed by sensory-related (2988 [1.2%]) (visual, hearing, or speech impairment), intellectual (353 [0.1%]), and other (1312 [0.5%]) (assistance with filling forms or service animal) requests. Patients with an accessibility request compared with those without, were older (72.6 vs 60.8 years), less likely to be White individuals (59.7% vs 65.4%), and more likely to be women (62.6% vs 58.1%), receiving Medicare (69.6% vs 41.5%), and have vision impairment (41.3% vs 13.6%) (P < .001 for all). CONCLUSIONS AND RELEVANCE In this cross-sectional study, a substantial proportion of patients making eye appointments reported having accessibility requests as captured using a new EHR-based questionnaire. Such standardization of data collection for disability-related accessibility requests in EHR is scalable, could be expanded to other clinical settings, and has the potential to improve accessibility of health care interactions for patients with disabilities.
引用
下载
收藏
页数:9
相关论文
共 50 条
  • [21] Electronic health record-based surveillance of diagnostic errors in primary care
    Singh, Hardeep
    Giardina, Traber Davis
    Forjuoh, Samuel N.
    Reis, Michael D.
    Kosmach, Steven
    Khan, Myrna M.
    Thomas, Eric J.
    BMJ QUALITY & SAFETY, 2012, 21 (02) : 93 - 100
  • [22] Electronic health record-based patient tracking by emergency medicine physicians
    Villalba, Constanza
    Burke, Ryan C.
    Gurley, Kiersten
    Dhaliwal, Gurpreet
    Grossman, Shamai
    AEM EDUCATION AND TRAINING, 2022, 6 (02)
  • [23] Pharmacist Hypertension Management Using an Electronic Health Record-Based Approach
    Soreide, Kristin K.
    Solomon, Octavia
    Farhat, Nada M.
    Kolander, Sarah
    Gottschall, Terry
    George, Diane L.
    Szandzik, Edward G.
    Kalus, James S.
    Thomas, Emily
    AMERICAN JOURNAL OF MANAGED CARE, 2022, 28 (04): : E121 - E125
  • [24] A narrative review on the validity of electronic health record-based research in epidemiology
    Gianfrancesco, Milena A.
    Goldstein, Neal D.
    BMC MEDICAL RESEARCH METHODOLOGY, 2021, 21 (01)
  • [25] The Evolution of Electronic Health Record-Based Drug Information Systems in Canada
    Bishop, Kurtis
    CANADIAN JOURNAL OF HOSPITAL PHARMACY, 2005, 58 : 18 - 18
  • [26] Bias in electronic health record-based studies: Seeing the forest for the trees
    Arterburn, David
    Aminian, Ali
    Nissen, Steve
    Schauer, Phil
    Haneuse, Sebastien
    DIABETES OBESITY & METABOLISM, 2021, 23 (07): : 1692 - 1693
  • [27] Test collections for electronic health record-based clinical information retrieval
    Wang, Yanshan
    Wen, Andrew
    Liu, Sijia
    Hersh, William
    Bedrick, Steven
    Liu, Hongfang
    JAMIA OPEN, 2019, 2 (03) : 360 - 368
  • [28] Development of an Electronic Health Record-Based Clinical Decision Support Tool for Patients With Lynch Syndrome
    Lau-Min, Kelsey S.
    Bleznuck, Joseph
    Wollack, Colin
    McKenna, Danielle B.
    Long, Jessica M.
    Hubert, Anna P.
    Johnson, Mariah
    Rochester, Shavon E.
    Constantino, Gillain
    Dudzik, Christina
    Doucette, Abigail
    Wangensteen, Kirk
    Domchek, Susan M.
    Landgraf, Jeffrey
    Chen, Jessica
    Nathanson, Katherine L.
    Katona, Bryson W.
    JCO CLINICAL CANCER INFORMATICS, 2023, 7 : e2300024
  • [29] Challenges in and Opportunities for Electronic Health Record-Based Data Analysis and Interpretation
    Kim, Michelle Kang
    Rouphael, Carol
    Mcmichael, John
    Welch, Nicole
    Dasarathy, Srinivasan
    GUT AND LIVER, 2024, 18 (02) : 201 - 208
  • [30] Development and validation of an electronic health record-based algorithm for identifying TBI in the VA: A VA Million Veteran Program study
    Merritt, Victoria C.
    Chen, Alicia W.
    Bonzel, Clara-Lea
    Hong, Chuan
    Sangar, Rahul
    Morini Sweet, Sara
    Sorg, Scott F.
    Chanfreau-Coffinier, Catherine
    BRAIN INJURY, 2024,