scholarly journals 978. Assessing the Impact of a Mobile Device-Based Clinical Decision Support Tool on Guideline Adherence and Mental Workload

2018 ◽  
Vol 5 (suppl_1) ◽  
pp. S40-S40
Author(s):  
Katherine Richardson ◽  
Sarah Fouquet ◽  
Ellen Kerns ◽  
Russell Mcculloh
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Mental Workload ◽  
Clinical Decision ◽  
Medical Decision ◽  
Evidence Based ◽  
System Usability Scale ◽  
Nasa Tlx ◽  
Evidence Based Guidelines ◽  
The Impact

Abstract Background Fever in infants <90 days old can indicate a serious bacterial infection (SBI) such as urinary tract infection, bacteremia, or meningitis. Clinical management of febrile infants varies widely. Implementing clinical practice guidelines (CPGs) can help standardize care, and electronic clinical decision support (eCDS) tools are a potential means of distributing CPGs. Little is known regarding the individual-level impact of eCDS tool use on medical decision-making. Children’s Mercy Kansas City developed a mobile eCDS tool (CMPeDS: Pediatric Decision Support) that was used internationally in a practice standardization project focused on the management of febrile infants. Methods We conducted a prospective cross-over simulation study amongst pediatric healthcare providers. Attending and resident physicians performed simulated patient scenarios using either CMPeDS or a standard text reference (the Harriet Lane Handbook). Participants’ responses in the simulation were evaluated based on adherence to evidence-based guidelines. Participants’ mental workload was assessed using the NASA Task Load Index survey (NASA-TLX, in which lower scores are optimal) to assesses mental, physical, and temporal demand, as well as performance, effort, and frustration when completing a series of tasks. Paired t-test and ANOVA were used to determine significance for case performance scores and NASA-TLX scores, respectively. A System Usability Scale (SUS) was used to determine usability of the CMPeDS app. Results A total 28 of 32 planned participants have completed trial procedures to date. Mean performance scores on the cases were significantly higher with CMPeDS vs. standard reference, (87.7% vs. 72.4% [t(27) 3.22, P = 0.003]). Participants reported lower scores on the NASA-TLX when using CMPeDS compared with standard reference tool (Figure 1). Mean score on SUS was 88.2 (scale 0–100) indicating excellent tool usability (Figure 2). Conclusion Using the eCDS tool CMPeDS was associated with significantly increased adherence to evidence-based guidelines for febrile infant management and decreased mental workload in simulation. Our findings highlight the potential value of eCDS deployment as part of CPG implementation projects. Disclosures All authors: No reported disclosures.

Driving quality improvement: How clinical decision support can facilitate compliance with evidence-based pathways.

2020 ◽  
Vol 38 (15_suppl) ◽  
pp. 2045-2045
Author(s):  
Debra A. Patt ◽  
Bo He ◽  
Jody S. Garey ◽  
Paul Rowan ◽  
Michael D Swartz ◽  
...  
Keyword(s):  
Quality Improvement ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Cancer Care ◽  
Care Delivery ◽  
Clinical Decision ◽  
Clinical Informatics ◽  
Evidence Based ◽  
Large Network ◽  
The Impact

2045 Background: Cancer care is changing rapidly with more detailed understanding of disease and more numerous therapeutic choices. As treatment choice is more complex, mechanisms to improve compliance with evidence based treatment can improve the quality of cancer care. Methods: A retrospective cohort study was conducted from January 2014-May 2016 evaluating the impact of a clinical decision support system (CDSS) on compliance with evidence based pathways (EBP) across 9 statewide community based oncology practices. These EBP are developed with physician input on efficacy toxicity and value and incorporated in to a CDSS that is used within the Electronic Health Record (EHR) at point of care to alter the choice architecture a clinician sees when prescribing therapy. A multi-level logistic regression model was used to adjust for group effects on physician or practice behavior. SAS 9.4 software was used and GLIMMIX was applied. Individual physician benchmark compliance was evaluated using McNemar's test. Results: Regimen compliance with EBP was measured pre- and post- implementation of the CDSS tool across a large network encompassing 9 statewide practices and 633 physicians who prescribed over 30,000 individual patient treatment regimens over a 6 month period. The CDSS that is incorporated within the EHR significantly improved compliance with EBP across the entire cohort of practices, and in individual practices (see Table). Individual oncologists reached a target of 75% compliance more often (58% vs 72%) after implementation of the tool (p < 0.001). Conclusions: CDSS is a tool that improves compliance with EBP that is effective at improving targets of compliance broadly, at the practice, and at the individual clinician level. Clinical informatics solutions that influence physician behavior can be inclusive of physicians in design, iterative in process, and nudge as opposed to force clinician behavior to drive quality improvement. These clinical informatics solutions grow in importance as the complexity of cancer care continues to increase and we seek to improve upon the quality and value of care delivery. [Table: see text]

Developing a Clinical Decision Support Tool for Appropriate Antibiotic Prescribing in Australian General Practice: A Simulation Study

2020 ◽  
Vol 40 (4) ◽  
pp. 428-437 ◽  
Author(s):  
Jo-Anne Manski-Nankervis ◽  
Ruby Biezen ◽  
Karin Thursky ◽  
Douglas Boyle ◽  
Malcolm Clark ◽  
...  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Video Data ◽  
Consumer Information ◽  
Antibiotic Prescribing ◽  
Clinical Workflow ◽  
System Usability Scale ◽  
System Usability ◽  
The Impact

Background. Inappropriate antibiotic prescribing can lead to antimicrobial resistance and drug side effects. Tools that assist general practitioners (GPs) in prescribing decisions may help to optimize prescribing. The aim of this study was to explore the use, acceptability, and feasibility of a clinical decision support (CDS) tool that incorporates evidence-based guidelines and consumer information that integrates with the electronic medical record (EMR). Methods. Eight GPs completed an interview and brief survey after participating in 2 simulated consultations. The survey consisted of demographic questions, perception of realism and representativeness of consultations, Post-Study System Usability Questionnaire, and System Usability Scale. Qualitative data were analyzed using framework analysis. Video data were reviewed, with length of consultation and time spent using the CDS tool documented. Results. Survey responses indicated that all GPs thought the consultations were “real” and representative of real-life consultations; 7 of 8 GPs were satisfied with usability of the tool. Key qualitative findings included that the tool assisted with clinical decision making and informed appropriate antibiotic prescribing. Accessibility and ease of use, including content (guideline and patient education resources), layout, and format, were key factors that determined whether GPs said that they would access the tool in everyday practice. Integration of the tool at multiple sites within the EMR facilitated access to guidelines and assisted in ensuring that the tool fit the clinical workflow. Conclusion. Our CDS tool was acceptable to GPs. Key features required for the tool were easy navigation, clear and useful guideline content, ability to fit into the clinical workflow, and incorporation into the EMR. Piloting of the tool in general practices to assess the impact and feasibility of use in real-world consultations will now be undertaken.

Computerized Clinical Decision Support: A Technology to Implement and Validate Evidence Based Guidelines

2008 ◽  
Vol 64 (2) ◽  
pp. 520-537 ◽  
Author(s):  
Joseph F. Sucher ◽  
Frederick A. Moore ◽  
S Rob Todd ◽  
R Matthew Sailors ◽  
Bruce A. McKinley
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Evidence Based ◽  
Evidence Based Guidelines

Why provision of clinical decision support (CDS) is not enough? Factors influencing the CDS adoption

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M Laka ◽  
A Milazzo ◽  
T Merlin
Keyword(s):  
Primary Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Professional Autonomy ◽  
Ease Of Use ◽  
Barriers And Facilitators ◽  
Clinical Settings ◽  
Evidence Based ◽  
The Impact

Abstract Background Clinical decision support (CDS) can improve the quality and efficiency of care by increasing access to evidence-based data at the point-of-care. However, CDS adoption is limited in clinical settings. The focus on the technical design have overlooked end-users’ perceptions, social and organisational factors that may influence uptake. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) model, we aimed to identify different challenges and opportunities for CDSS adoption in clinical settings. Methods A cross-sectional online survey was conducted from June-October 2019 with general practitioners, physicians and surgeons in Australia. To measure the impact of UTAUT moderators (age, gender and experience) and care settings (primary care vs. hospitals) on perceived barriers and facilitators to CDS implementation, multivariate logistic regression was carried out. Qualitative data was thematically analysed for emerging patterns and themes. Results Many respondents indicated that CDS can promote evidence-based care (79%) and improve quality and safety (52%). Overall CDS adoption is dependent on factors such as effort expectancy (ease of use), performance expectancy and a facilitating environment for system use. Clinician perceptions of barriers and facilitators to uptake are associated with type of care setting. There was higher likelihood of perceiving ease of use (OR 1.39, 95% CI 1.15-2.07), time limitations (OR 1.95, 95%CI 1.10-3.77), patient' preferences (OR 2.17, 95% CI 1.14-3.37) and threat to professional autonomy (OR 2.15, 95%CI 1.39-3.41) as factors that influence adoption in primary care. Providing relevant information in right format at right time is critical for successful CDS use. Conclusions CDS implementation requires a holistic approach addressing users' perceptions and preferences determined through stakeholder consultation. The system design must be easy to use but also facilitated through the provision of on-site training and support. Key messages CDS adoption is determined by systems’ ease of use and provision of enabling environment. Users and setting characteristics are important moderators and must be considered in CDS implementation.

scholarly journals A Narrative Review of Clinical Decision Support for Inpatient Clinical Pharmacists

2021 ◽  
Vol 12 (02) ◽  
pp. 199-207
Author(s):  
Liang Yan ◽  
Thomas Reese ◽  
Scott D. Nelson
Keyword(s):  
Patient Safety ◽  
Quality Of Care ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Controlled Trials ◽  
Clinical Pharmacists ◽  
Randomized Controlled ◽  
The Impact

Abstract Objective Increasingly, pharmacists provide team-based care that impacts patient care; however, the extent of recent clinical decision support (CDS), targeted to support the evolving roles of pharmacists, is unknown. Our objective was to evaluate the literature to understand the impact of clinical pharmacists using CDS. Methods We searched MEDLINE, EMBASE, and Cochrane Central for randomized controlled trials, nonrandomized trials, and quasi-experimental studies which evaluated CDS tools that were developed for inpatient pharmacists as a target user. The primary outcome of our analysis was the impact of CDS on patient safety, quality use of medication, and quality of care. Outcomes were scored as positive, negative, or neutral. The secondary outcome was the proportion of CDS developed for tasks other than medication order verification. Study quality was assessed using the Newcastle–Ottawa Scale. Results Of 4,365 potentially relevant articles, 15 were included. Five studies were randomized controlled trials. All included studies were rated as good quality. Of the studies evaluating inpatient pharmacists using a CDS tool, four showed significantly improved quality use of medications, four showed significantly improved patient safety, and three showed significantly improved quality of care. Six studies (40%) supported expanded roles of clinical pharmacists. Conclusion These results suggest that CDS can support clinical inpatient pharmacists in preventing medication errors and optimizing pharmacotherapy. Moreover, an increasing number of CDS tools have been developed for pharmacists' roles outside of order verification, whereby further supporting and establishing pharmacists as leaders in safe and effective pharmacotherapy.

scholarly journals Clinical Decision Support for Ovarian Carcinoma Subtype Classification: A Pilot Observer Study With Pathology Trainees

2019 ◽  
Vol 144 (7) ◽  
pp. 869-877 ◽  
Author(s):  
Marios A. Gavrielides ◽  
Meghan Miller ◽  
Ian S. Hagemann ◽  
Heba Abdelal ◽  
Zahra Alipour ◽  
...  
Keyword(s):  
Decision Support ◽  
Ovarian Carcinoma ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Subspecialty Training ◽  
Reference Standard ◽  
Observer Study ◽  
Subtype Classification ◽  
The Impact ◽  
Whole Slide Images

Context.— Clinical decision support (CDS) systems could assist less experienced pathologists with certain diagnostic tasks for which subspecialty training or extensive experience is typically needed. The effect of decision support on pathologist performance for such diagnostic tasks has not been examined. Objective.— To examine the impact of a CDS tool for the classification of ovarian carcinoma subtypes by pathology trainees in a pilot observer study using digital pathology. Design.— Histologic review on 90 whole slide images from 75 ovarian cancer patients was conducted by 6 pathology residents using: (1) unaided review of whole slide images, and (2) aided review, where in addition to whole slide images observers used a CDS tool that provided information about the presence of 8 histologic features important for subtype classification that were identified previously by an expert in gynecologic pathology. The reference standard of ovarian subtype consisted of majority consensus from a panel of 3 gynecologic pathology experts. Results.— Aided review improved pairwise concordance with the reference standard for 5 of 6 observers by 3.3% to 17.8% (for 2 observers, increase was statistically significant) and mean interobserver agreement by 9.2% (not statistically significant). Observers benefited the most when the CDS tool prompted them to look for missed histologic features that were definitive for a certain subtype. Observer performance varied widely across cases with unanimous and nonunanimous reference classification, supporting the need for balancing data sets in terms of case difficulty. Conclusions.— Findings showed the potential of CDS systems to close the knowledge gap between pathologists for complex diagnostic tasks.

41 Enhancing Burn Medical Care During a Disaster Using a Novel Augmented-Reality Application

2021 ◽  
Vol 42 (Supplement_1) ◽  
pp. S31-S31
Author(s):  
Sena Veazey ◽  
Maria SerioMelvin ◽  
David E Luellen ◽  
Angela Samosorn ◽  
Alexandria Helms ◽  
...  
Keyword(s):  
Decision Support ◽  
Augmented Reality ◽  
Clinical Decision Support ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Burn Injuries ◽  
Medical Decision ◽  
Support Tool ◽  
Burn Care ◽  
Clinical Decision Support Tool

Abstract Introduction In disaster or mass casualty situations, access to remote burn care experts, communication, or resources may be limited. Furthermore, burn injuries are complex and require substantial training and knowledge beyond basic clinical care. Development and use of decision support (DS) technologies may provide a solution for addressing this need. Devices capable of delivering burn management recommendations can enhance the provider’s ability to make decisions and perform interventions in complex care settings. When coupled with merging augmented reality (AR) technologies these tools may provide additional capabilities to enhance medical decision-making, visualization, and workflow when managing burns. For this project, we developed a novel AR-based application with enhanced integrated clinical practice guidelines (CPGs) to manage large burn injuries for use in different environments, such as disasters. Methods We identified an AR system that met our requirements to include portability, infrared camera, gesture and voice control, hands-free control, head-mounted display, and customized application development abilities. Our goal was to adapt burn CPGs to make use of AR concepts as part of an AR-enabled burn clinical decision support system supporting four sub-applications to assist users with specific interventional tasks relevant to burn care. We integrated relevant CPGs and a media library with photos and videos as additional references. Results We successfully developed a clinical decision support tool that integrates burn CPGs with enhanced capabilities utilizing AR technology. The main interface allows input of patient demographics and injuries with step-by-step guidelines that follow typical burn management care and workflow. There are four sub-applications to assist with these tasks, which include: 1) semi-automated burn wound mapping to calculate total body surface area; 2) hourly burn fluid titration and recommendations for resuscitation; 3) medication calculator for accurate dosing in preparation for procedures and 4) escharotomy instructor with holographic overlays. Conclusions We developed a novel AR-based clinical decision support tool for management of burn injuries. Development included adaptation of CPGs into a format to guide the user through burn management using AR concepts. The application will be tested in a prospective research study to determine the effectiveness, timeliness, and performance of subjects using this AR-software compared to standard of care. We fully expect that the tool will reduce cognitive workload and errors, ensuring safety and proper adherence to guidelines.

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