Kristen Miller1, Danielle Mosby1, Muge Capan2, Rebecca Kowalski1,2, Raj Ratwani1, Yaman Noaiseh3, Rachel Kraft2, Sanford Schwartz4, William S Weintraub5, Ryan Arnold2,6. 1. National Center for Human Factors in Healthcare, MedStar Health, Washington, DC, USA. 2. Value Institute, Christiana Care Health System, Newark, DE, USA. 3. College of Computing and Informatics, Drexel University, Philadelphia, PA, USA. 4. Health Care Management, University of Pennsylvania, Wharton, Philadelphia, PA, USA. 5. MedStar Washington Hospital Center, MedStar Health, Washington, DC, USA. 6. Christiana Care Health System, Newark, DE, USA.
Abstract
Objective: Provider acceptance and associated patient outcomes are widely discussed in the evaluation of clinical decision support systems (CDSSs), but critical design criteria for tools have generally been overlooked. The objective of this work is to inform electronic health record alert optimization and clinical practice workflow by identifying, compiling, and reporting design recommendations for CDSS to support the efficient, effective, and timely delivery of high-quality care. Material and Methods: A narrative review was conducted from 2000 to 2016 in PubMed and The Journal of Human Factors and Ergonomics Society to identify papers that discussed/recommended design features of CDSSs that are associated with the success of these systems. Results: Fourteen papers were included as meeting the criteria and were found to have a total of 42 unique recommendations; 11 were classified as interface features, 10 as information features, and 21 as interaction features. Discussion: Features are defined and described, providing actionable guidance that can be applied to CDSS development and policy. To our knowledge, no reviews have been completed that discuss/recommend design features of CDSS at this scale, and thus we found that this was important for the body of literature. The recommendations identified in this narrative review will help to optimize design, organization, management, presentation, and utilization of information through presentation, content, and function. The designation of 3 categories (interface, information, and interaction) should be further evaluated to determine the critical importance of the categories. Future work will determine how to prioritize them with limited resources for designers and developers in order to maximize the clinical utility of CDSS. Conclusion: This review will expand the field of knowledge and provide a novel organization structure to identify key recommendations for CDSS.
Objective: Provider acceptance and associated patient outcomes are widely discussed in the evaluation of clinical decision support systems (CDSSs), but critical design criteria for tools have generally been overlooked. The objective of this work is to inform electronic health record alert optimization and clinical practice workflow by identifying, compiling, and reporting design recommendations for CDSS to support the efficient, effective, and timely delivery of high-quality care. Material and Methods: A narrative review was conducted from 2000 to 2016 in PubMed and The Journal of Human Factors and Ergonomics Society to identify papers that discussed/recommended design features of CDSSs that are associated with the success of these systems. Results: Fourteen papers were included as meeting the criteria and were found to have a total of 42 unique recommendations; 11 were classified as interface features, 10 as information features, and 21 as interaction features. Discussion: Features are defined and described, providing actionable guidance that can be applied to CDSS development and policy. To our knowledge, no reviews have been completed that discuss/recommend design features of CDSS at this scale, and thus we found that this was important for the body of literature. The recommendations identified in this narrative review will help to optimize design, organization, management, presentation, and utilization of information through presentation, content, and function. The designation of 3 categories (interface, information, and interaction) should be further evaluated to determine the critical importance of the categories. Future work will determine how to prioritize them with limited resources for designers and developers in order to maximize the clinical utility of CDSS. Conclusion: This review will expand the field of knowledge and provide a novel organization structure to identify key recommendations for CDSS.
Authors: Eren Gultepe; Jeffrey P Green; Hien Nguyen; Jason Adams; Timothy Albertson; Ilias Tagkopoulos Journal: J Am Med Inform Assoc Date: 2013-08-19 Impact factor: 4.497
Authors: Saverio M Maviglia; Rita D Zielstorff; Marilyn Paterno; Jonathan M Teich; David W Bates; Gilad J Kuperman Journal: J Am Med Inform Assoc Date: 2003 Mar-Apr Impact factor: 4.497
Authors: Blackford Middleton; Meryl Bloomrosen; Mark A Dente; Bill Hashmat; Ross Koppel; J Marc Overhage; Thomas H Payne; S Trent Rosenbloom; Charlotte Weaver; Jiajie Zhang Journal: J Am Med Inform Assoc Date: 2013-01-25 Impact factor: 4.497
Authors: M H Trivedi; J K Kern; A Marcee; B Grannemann; B Kleiber; T Bettinger; K Z Altshuler; A McClelland Journal: Methods Inf Med Date: 2002 Impact factor: 2.176
Authors: Pavel S Roshanov; Shikha Misra; Hertzel C Gerstein; Amit X Garg; Rolf J Sebaldt; Jean A Mackay; Lorraine Weise-Kelly; Tamara Navarro; Nancy L Wilczynski; R Brian Haynes Journal: Implement Sci Date: 2011-08-03 Impact factor: 7.327
Authors: Alexander A Vinks; Nieko C Punt; Frank Menke; Eric Kirkendall; Dawn Butler; Thomas J Duggan; DonnaMaria E Cortezzo; Sam Kiger; Tom Dietrich; Paul Spencer; Rob Keefer; Kenneth D R Setchell; Junfang Zhao; Joshua C Euteneuer; Tomoyuki Mizuno; Kevin R Dufendach Journal: Clin Pharmacol Ther Date: 2019-12-11 Impact factor: 6.875
Authors: Pascale Carayon; Peter Hoonakker; Ann Schoofs Hundt; Megan Salwei; Douglas Wiegmann; Roger L Brown; Peter Kleinschmidt; Clair Novak; Michael Pulia; Yudi Wang; Emily Wirkus; Brian Patterson Journal: BMJ Qual Saf Date: 2019-11-27 Impact factor: 7.035
Authors: Michael C Brunner; Scott E Sheehan; Eric M Yanke; Dean F Sittig; Nasia Safdar; Barbara Hill; Kenneth S Lee; John F Orwin; David J Vanness; Christopher J Hildebrand; Michael A Bruno; Timothy J Erickson; Ryan Zea; D Paul Moberg Journal: Appl Clin Inform Date: 2020-02-19 Impact factor: 2.342
Authors: Kristen Miller; Muge Capan; Danielle Weldon; Yaman Noaiseh; Rebecca Kowalski; Rachel Kraft; Sanford Schwartz; William S Weintraub; Ryan Arnold Journal: Int J Med Inform Date: 2018-05-21 Impact factor: 4.046