scholarly journals Best Paper Selection

2018 ◽  
Vol 27 (01) ◽  
pp. 082-082 ◽  
Keyword(s):  
Participatory Design ◽  
Information Technologies ◽  
Clinical Decision ◽  
Electronic Prescribing ◽  
Experimental Comparison ◽  
User Centered Design ◽  
Record System ◽  
Health Information Technologies ◽  
Safety Risks ◽  
User Centered

Ancker JS, Edwards A, Nosal S, Hauser D, Mauer E, Kaushal R, with the HITEC Investigators. Effects of workload, work complexity, and repeated alerts on alert fatigue in a clinical decision support system. BMC Med Inform Decis Mak 2017 Apr 10;17(1):36 https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5387195/ Blijleven V, Koelemeijer K, Wetzels M, Jaspers M. Workarounds emerging from electronic health record system usage: consequences for patient safety, effectiveness of care, and efficiency of care. JMIR Hum Factors 2017 Oct 5;4(4):e27 https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/28982645/ Cresswell KM, Mozaffar H, Lee L, Williams R, Sheikh A. Safety risks associated with the lack of integration and interfacing of hospital health information technologies: a qualitative study of hospital electronic prescribing systems in England. BMJ Qual Saf 2017 Jul;26(7):530-41 http://qhc.bmj.com/cgi/pmidlookup?view=long&pmid=27037303 Dufendach KR, Koch S, Unertl KM, Lehmann CU. A randomized trial comparing classical participatory design to VandAID, an interactive crowdsourcing platform to facilitate user-centered design. Methods Inf Med 2017 Oct 26;56(5):344-9 http://www.thieme-connect.com/DOI/DOI?10.3414/ME16-01-0098 Luna DR, Rizzato Lede DA, Otero CM, Risk MR, González Bernaldo de Quirós F. User-centered design improves the usability of drug-drug interaction alerts: experimental comparison of interfaces. J Biomed Inform 2017 Feb;66:204-13 https://linkinghub.elsevier.com/retrieve/pii/S1532-0464(17)30009-6

How prescribers can use technology to improve patient care

2019 ◽  
Vol 1 (4) ◽  
pp. 198-203
Author(s):  
Sam Shah ◽  
James Coughlan
Keyword(s):  
Primary Care ◽  
Patient Outcomes ◽  
Information Technologies ◽  
Mobile Apps ◽  
Clinical Decision Support Systems ◽  
Improve Patient Care ◽  
Clinical Decision ◽  
Electronic Prescribing ◽  
Health Information Technologies ◽  
Improve Patient

Health information technologies (HITs) have become increasingly used in the NHS and offer prescribers the opportunity to prescribe in a more consistent and reliable way. There is a growing use of electronic prescribing systems, especially in primary care. This will likely reduce prescription errors, but evidence is unclear if it will improve patient outcomes. Clinical decision support systems can reduce variability and alert clinicians when prescriptions could cause patients harm; however, automation bias can create new errors to prescribers who over-rely on the system. HITs can better communication by improving discharge letters, facilitating telehealth appointments and supporting those working in remote settings. Mobile apps offer a way to engage patients in their own care and allow remote monitoring of chronic conditions in primary care, and acute conditions in emergency care settings. There are challenges in realising these benefits, with inconsistent infrastructure and a 10-year delay in realising predicted efficiency savings.

Managing User-Centered Design Activities in Distributed Agile Development

2021 ◽  
Author(s):  
Sultan Alyahya ◽  
Ohoud Almughram
Keyword(s):  
Participatory Design ◽  
Agile Development ◽  
Design Teams ◽  
User Centered Design ◽  
Management Tools ◽  
Daily Work ◽  
Development Teams ◽  
Design Activities ◽  
Computer Based ◽  
User Centered

Abstract The integration of user-centered design (UCD) activities into agile information systems development has become more popular recently. Despite the fact that there are many ways the merging of UCD activities into agile development can be carried out, it has been widely recognized that coordinating design activities with development activities is one of the most common problems, especially in distributed environments where designers, developers and users are spread over several sites. The main approach to coordinate UCD activities with distributed agile development is the use of informal methods (e.g. communication through using video conference tools). In addition to the temporal, geographical and socio-cultural barriers associated with this type of methods, a major limitation is a lack of awareness of how UCD activities and development activities affect each other. Furthermore, some agile project management tools are integrated with design platforms but fail to provide the necessary coordination that helps team members understand how the design and development activities affect their daily work. This research aims to support the effective management of integrating UCD activities into distributed agile development by (i) identifying the key activity dependencies between UX design teams and development teams during distributed UCD/agile development and (ii) designing a computer-based system to provide coordination support through managing these activity dependencies. In order to achieve these objectives, two case studies are carried out. Our findings revealed 10 main dependencies between UCD design teams and development teams as shown by six types of activity. In addition, the participatory design approach shows that developing a computer-based system to manage seven of these selected dependencies is achievable.

Developing Clinical Decision Support System for Sleep Staging Tasks by Formulating Explanations from Artificial Intelligence: User-Centered Design and Evaluation. (Preprint)

2021 ◽  
Author(s):  
Jeonghwan Hwang ◽  
Taeheon Lee ◽  
Honggu Lee ◽  
Seonjeong Byun
Keyword(s):  
Artificial Intelligence ◽  
Decision Support ◽  
Design Process ◽  
Clinical Decision Support ◽  
User Study ◽  
Clinical Decision ◽  
Sleep Staging ◽  
User Centered Design ◽  
Iterative Design ◽  
User Centered

BACKGROUND Despite the unprecedented performances of deep learning algorithms in clinical domains, full reviews of algorithmic predictions by human experts remain mandatory. Under these circumstances, artificial intelligence (AI) models are primarily designed as clinical decision support systems (CDSSs). However, from the perspective of clinical practitioners, the lack of clinical interpretability and user-centered interfaces block the adoption of these AI systems in practice. OBJECTIVE The aim of this study was to develop an AI-based CDSS for assisting polysomnographic technicians in reviewing AI-predicted sleep staging results. This study proposed and evaluated a CDSS that provides clinically sound explanations for AI predictions in a user-centered fashion. METHODS User needs for the system were identified during interviews with polysomnographic technicians. User observation sessions were conducted to understand the workflow of the practitioners during sleep scoring. Iterative design process was performed to ensure easy integration of the tool into clinical workflows. Then, we evaluated the system with polysomnographic technicians. We measured the improvements in sleep staging accuracies after adopting our tool and assessed qualitatively how the participants perceived and used the tool. RESULTS The user study revealed that technicians desire explanations relevant to key electroencephalogram (EEG) patterns for sleep staging when assessing the correctness of the AI predictions. Here, technicians could evaluate whether AI models properly locate and use those patterns during prediction. Based on this, information in AI models that is closely related to sleep EEG patterns was formulated and visualized during the iterative design process. Furthermore, we developed a different visualization strategy for each pattern based on the way the technicians interpreted the EEG recordings with these patterns during their workflows. Generally, the tool evaluation results from the nine polysomnographic technicians were positive. Quantitatively, technicians achieved better classification performances after reviewing the AI-generated predictions with the proposed system; classification accuracies measured with Macro-F1 scores improved from 60.20 to 62.71. Qualitatively, participants reported that the provided information from the tool effectively supported them, and they were able to develop notable adoption strategies for the tool. CONCLUSIONS Our findings indicate that formulating clinical explanations for automated predictions using the information in the AI with a user-centered design process is an effective strategy for developing a CDSS for sleep staging.

scholarly journals Computerized Clinical Decision Support: Contributions from 2014

2015 ◽  
Vol 24 (01) ◽  
pp. 119-124 ◽  
Author(s):  
V. Koutkias ◽  
J. Bouaud ◽  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Information Technologies ◽  
Clinical Decision Support Systems ◽  
Clinical Decision ◽  
Editorial Team ◽  
Bibliographic Databases ◽  
Health Information Technologies ◽  
Selection Of

Summary Objective: To summarize recent research and propose a selection of best papers published in 2014 in the field of computerized clinical decision support for the Decision Support section of the IMIA yearbook.Method: A literature review was performed by searching two bibliographic databases for papers related to clinical decision support systems (CDSSs) and computerized provider order entry systems in order to select a list of candidate best papers to be then peer-reviewed by external reviewers. A consensus meeting between the two section editors and the editorial team was finally organized to conclude on the selection of best papers. Results: Among the 1,254 returned papers published in 2014, the full review process selected four best papers. The first one is an experimental contribution to a better understanding of unintended uses of CDSSs. The second paper describes the effective use of previously collected data to tailor and adapt a CDSS. The third paper presents an innovative application that uses pharmacogenomic information to support personalized medicine. The fourth paper reports on the long-term effect of the routine use of a CDSS for antibiotic therapy. Conclusions: As health information technologies spread more and more meaningfully, CDSSs are improving to answer users’ needs more accurately. The exploitation of previously collected data and the use of genomic data for decision support has started to materialize. However, more work is still needed to address issues related to the correct usage of such technologies, and to assess their effective impact in the long term.

scholarly journals Right Care, First Time: Developing a Theory-Based Automated Protocol to Help Clinically Stage Young People Based on Severity and Persistence of Mental Illness

2021 ◽  
Vol 9 ◽  
Author(s):  
Frank Iorfino ◽  
Vanessa Wan Sze Cheng ◽  
Shane P. Cross ◽  
Hannah F. Yee ◽  
Tracey A. Davenport ◽  
...  
Keyword(s):  
Mental Disorders ◽  
Information Technologies ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Evidence Base ◽  
Clinical Staging ◽  
Health Information Technologies ◽  
Staging Model ◽  
Automated Protocol ◽  
First Time

Most mental disorders emerge before the age of 25 years and, if left untreated, have the potential to lead to considerable lifetime burden of disease. Many services struggle to manage high demand and have difficulty matching individuals to timely interventions due to the heterogeneity of disorders. The technological implementation of clinical staging for youth mental health may assist the early detection and treatment of mental disorders. We describe the development of a theory-based automated protocol to facilitate the initial clinical staging process, its intended use, and strategies for protocol validation and refinement. The automated clinical staging protocol leverages the clinical validation and evidence base of the staging model to improve its standardization, scalability, and utility by deploying it using Health Information Technologies (HIT). Its use has the potential to enhance clinical decision-making and transform existing care pathways, but further validation and evaluation of the tool in real-world settings is needed.

scholarly journals Computerized Clinical Decision Support System for Emergency Department–Initiated Buprenorphine for Opioid Use Disorder: User-Centered Design (Preprint)

2018 ◽  
Author(s):  
Jessica M Ray ◽  
Osama M Ahmed ◽  
Yauheni Solad ◽  
Matthew Maleska ◽  
Shara Martel ◽  
...  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Emergency Care ◽  
Clinical Decision ◽  
Opioid Use Disorder ◽  
Care Pathways ◽  
User Centered Design ◽  
Opioid Use ◽  
Prototype Development ◽  
User Centered

BACKGROUND Emergency departments (EDs) frequently care for individuals with opioid use disorder (OUD). Buprenorphine (BUP) is an effective treatment option for patients with OUD that can safely be initiated in the ED. At present, BUP is rarely initiated as a part of routine ED care. Clinical decision support (CDS) could accelerate adoption of ED-initiated BUP into routine emergency care. OBJECTIVE This study aimed to design and formatively evaluate a user-centered decision support tool for ED initiation of BUP for patients with OUD. METHODS User-centered design with iterative prototype development was used. Initial observations and interviews identified workflows and information needs. The design team and key stakeholders reviewed prototype designs to ensure accuracy. A total of 5 prototypes were evaluated and iteratively refined based on input from 26 attending and resident physicians. RESULTS Early feedback identified concerns with the initial CDS design: an alert with several screens. The timing of the alert led to quick dismissal without using the tool. User feedback on subsequent iterations informed the development of a flexible tool to support clinicians with varied levels of experience with the intervention by providing both one-click options for direct activation of care pathways and user-activated support for critical decision points. The final design resolved challenging navigation issues through targeted placement, color, and design of the decision support modules and care pathways. In final testing, users expressed that the tool could be easily learned without training and was reasonable for use during routine emergency care. CONCLUSIONS A user-centered design process helped designers to better understand users’ needs for a Web-based clinical decision tool to support ED initiation of BUP for OUD. The process identified varying needs across user experience and familiarity with the protocol, leading to a flexible design supporting both direct care pathways and user-initiated decision support.

scholarly journals Utilizing a user-centered approach to develop and assess pharmacogenomic clinical decision support for thiopurine methyltransferase

2019 ◽  
Vol 19 (1) ◽  
Author(s):  
Khoa A. Nguyen ◽  
Himalaya Patel ◽  
David A. Haggstrom ◽  
Alan J. Zillich ◽  
Thomas F. Imperiale ◽  
...  
Keyword(s):  
Decision Support ◽  
User Interface ◽  
Phase I ◽  
Clinical Decision Support ◽  
Phase Ii ◽  
Usability Testing ◽  
Clinical Decision ◽  
Thiopurine Methyltransferase ◽  
User Centered Design ◽  
User Centered

Abstract Background A pharmacogenomic clinical decision support tool (PGx-CDS) for thiopurine medications can help physicians incorporate pharmacogenomic results into prescribing decisions by providing up-to-date, real-time decision support. However, the PGx-CDS user interface may introduce errors and promote alert fatigue. The objective of this study was to develop and evaluate a prototype of a PGx-CDS user interface for thiopurine medications with user-centered design methods. Methods This study had two phases: In phase I, we conducted qualitative interviews to assess providers’ information needs. Interview transcripts were analyzed through a combination of inductive and deductive qualitative analysis to develop design requirements for a PGx-CDS user interface. Using these requirements, we developed a user interface prototype and evaluated its usability (phase II). Results In total, 14 providers participated: 10 were interviewed in phase I, and seven providers completed usability testing in phase II (3 providers participated in both phases). Most (90%) participants were interested in PGx-CDS systems to help improve medication efficacy and patient safety. Interviews yielded 11 themes sorted into two main categories: 1) health care providers’ views on PGx-CDS and 2) important design features for PGx-CDS. We organized these findings into guidance for PGx-CDS content and display. Usability testing of the PGx-CDS prototype showed high provider satisfaction. Conclusion This is one of the first studies to utilize a user-centered design approach to develop and assess a PGx-CDS interface prototype for Thiopurine Methyltransferase (TPMT). This study provides guidance for the development of a PGx-CDS, and particularly for biomarkers such as TPMT.

Modeling Patient-Centered Cognitive Work for High-Value Care Goals

2016 ◽  
Vol 5 (1) ◽  
pp. 112-119 ◽  
Author(s):  
Stephanie K. Furniss ◽  
Matthew M. Burton ◽  
David W. Larson ◽  
David R. Kaufman
Keyword(s):  
Information Flow ◽  
Distributed Cognition ◽  
Information Technologies ◽  
Cognitive Resources ◽  
Clinical Workflow ◽  
Patient Centered ◽  
Health Information Technologies ◽  
Care Plans ◽  
Safety Risks ◽  
Effective Use

Patient-centered cognitive support has been shown to be critically important to facilitate the effective use of health information technologies (HIT). There is a well-documented need to better understand HIT-mediated clinical workflow. Current technologies can burden clinicians’ cognitive resources, which is associated with patient safety risks and medical errors. We sought to employ a distributed cognition approach to examine how information flows across the activity system to support clinicians’ problem-solving. Specifically, we studied the propagation of representational states across media, conversations, actors and time in the coordination of patient-care processes. We examined multiple instances of work and information flow in a real-world setting, revealing problems in information flow: a) use of paper artifacts has limitations to facilitating coordination of care, b) clinicians challenged in developing shared awareness, c) responsibility of representing patient states is distributed across documents, d) clinical reasoning that informed care plans was absent from documents. Findings surface a challenge to automated monitoring of care goals; much of the information is present only in clinicians’ minds and in informal documents.

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