Literature DB >> 31943019

Interfaces for collecting data from patients: 10 golden rules.

Andrew J Vickers1, Ling Y Chen1, Peter D Stetson2.   

Abstract

Memorial Sloan Kettering Cancer Center has more than a decade's experience creating online interfaces for obtaining data from patients as part of routine clinical care. We have developed a set of "golden rules" for design of these interfaces. Many relate to the knowledge imbalance between professional staff (whether medical or informatics) and patients, who are often old and sick and have limited knowledge of technology. Others relate to the clinical nature of the encounter: data cannot be taken from patients as part of clinical care unless there is a plan to act on whatever information is prepared. We also note that the plethora of marketing questionnaires makes patients suspicious of surveys: patient trust is hard to gain and easy to lose. Addition of these golden rules to standard approaches to interface design will maximize our ability to obtain data from patients and thus improve communication between patients and clinicians.
© The Author(s) 2020. Published by Oxford University Press on behalf of the American Medical Informatics Association. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Entities:  

Keywords:  interfaces; patient data

Mesh:

Year:  2020        PMID: 31943019      PMCID: PMC7025343          DOI: 10.1093/jamia/ocz215

Source DB:  PubMed          Journal:  J Am Med Inform Assoc        ISSN: 1067-5027            Impact factor:   4.497


  2 in total

1.  Lack of comprehension of common prostate cancer terms in an underserved population.

Authors:  Kerry L Kilbridge; Gertrude Fraser; Murray Krahn; Elizabeth M Nelson; Mark Conaway; Randall Bashore; Andrew Wolf; Michael J Barry; Debra A Gong; Robert F Nease; Alfred F Connors
Journal:  J Clin Oncol       Date:  2009-03-23       Impact factor: 44.544

2.  Manifesto: towards a clinically-oriented psychometrics.

Authors:  Andrew J Vickers; Ling Y Chen
Journal:  Health Qual Life Outcomes       Date:  2017-04-26       Impact factor: 3.186

  2 in total
  1 in total

Review 1.  Early Detection of Pancreatic Cancer: Applying Artificial Intelligence to Electronic Health Records.

Authors:  Barbara J Kenner; Natalie D Abrams; Suresh T Chari; Bruce F Field; Ann E Goldberg; William A Hoos; David S Klimstra; Laura J Rothschild; Sudhir Srivastava; Matthew R Young; Vay Liang W Go
Journal:  Pancreas       Date:  2021-08-01       Impact factor: 3.243

  1 in total

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