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
收藏
页数:9
相关论文
共 50 条
  • [41] A study of user requests regarding the fully electronic health record system at Seoul National University Bundang Hospital: Challenges for future electronic health record systems
    Yoo, Sooyoung
    Kim, Seok
    Lee, Seungja
    Lee, Kee-Hyuck
    Baek, Rong-Min
    Hwang, Hee
    INTERNATIONAL JOURNAL OF MEDICAL INFORMATICS, 2013, 82 (05) : 387 - 397
  • [42] A Theory-Based Approach for Identifying Nurse and Team Member Contributions in the Electronic Health Record
    Will, Kristen K.
    Lamb, Gerri
    JOURNAL OF NURSING SCHOLARSHIP, 2021, 53 (06) : 781 - 789
  • [43] Enhancing nursing home quality through electronic health record implementation
    Pradhan, Rohit
    Dayama, Neeraj
    Morris, Michael
    Elliott, Kimberly
    Felix, Holly
    HEALTH INFORMATION MANAGEMENT JOURNAL, 2024,
  • [44] Screening for undiagnosed atrial fibrillation using an electronic health record-based clinical prediction model: clinical pilot implementation initiative
    Grout, Randall W.
    Ateya, Mohammad
    Direnzo, Baely
    Hart, Sara
    King, Chase
    Rajkumar, Joshua
    Sporrer, Susan
    Torabi, Asad
    Walroth, Todd A.
    Kovacs, Richard J.
    BMC MEDICAL INFORMATICS AND DECISION MAKING, 2024, 24 (01)
  • [45] Inverse Probability of Treatment Weighting and Confounder Missingness in Electronic Health Record-based Analyses: A Comparison of Approaches Using Plasmode Simulation
    Vader, Daniel T.
    Mamtani, Ronac
    Li, Yun
    Griffith, Sandra D.
    Calip, Gregory S.
    Hubbard, Rebecca A.
    EPIDEMIOLOGY, 2023, 34 (04) : 520 - 530
  • [46] A practical approach to identifying autistic adults within the electronic health record
    Malow, Beth A.
    Veatch, Olivia J.
    Niu, Xinnan
    Fitzpatrick, Kasey A.
    Hucks, Donald
    Maxwell-Horn, Angie
    Davis, Lea K.
    AUTISM RESEARCH, 2023, 16 (01) : 52 - 65
  • [47] Evaluation of electronic health record-integrated digital health tools to engage hospitalized patients in discharge preparation
    Dalal, Anuj K.
    Piniella, Nicholas
    Fuller, Theresa E.
    Pong, Denise
    Pardo, Michael
    Bessa, Nathaniel
    Yoon, Catherine
    Lipsitz, Stuart
    Schnipper, Jeffrey L.
    JOURNAL OF THE AMERICAN MEDICAL INFORMATICS ASSOCIATION, 2021, 28 (04) : 704 - 712
  • [48] Identifying Electronic Health Record Usability And Safety Challenges In Pediatric Settings
    Ratwani, Raj M.
    Savage, Erica
    Will, Amy
    Fong, Allan
    Karavite, Dean
    Muthu, Naveen
    Rivera, A. Joy
    Gibson, Cori
    Asmonga, Don
    Moscovitch, Ben
    Grundmeier, Robert
    Rising, Josh
    HEALTH AFFAIRS, 2018, 37 (11) : 1752 - 1759
  • [49] Evaluation of an Algorithm for Identifying Ocular Conditions in Electronic Health Record Data
    Stein, Joshua D.
    Rahman, Moshiur
    Andrews, Chris
    Ehrlich, Joshua R.
    Kamat, Shivani
    Shah, Manjool
    Boese, Erin A.
    Woodward, Maria A.
    Cowall, Jeff
    Trager, Edward H.
    Narayanaswamy, Prabha
    Hanauer, David A.
    JAMA OPHTHALMOLOGY, 2019, 137 (05) : 491 - 497
  • [50] Identifying Patients Experiencing Homelessness in an Electronic Health Record and Assessing Qualification for Medical Respite: A Five-Year Retrospective Review
    Biederman, Donna J.
    Modarai, Farhad
    Gamble, Julia
    Sloane, Richard
    Brown, Audrey
    Wilson, Sally
    Douglas, Christian
    JOURNAL OF HEALTH CARE FOR THE POOR AND UNDERSERVED, 2019, 30 (01) : 297 - 309