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.

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 The Changing Nature of Clinical Decision Support Systems: a Focus on Consumers, Genomics, Public Health and Decision Safety

2009 ◽  
Vol 18 (01) ◽  
pp. 84-95 ◽  
Author(s):  
A. Y. S. Lau ◽  
G. Tsafnat ◽  
V. Sintchenko ◽  
F. Magrabi ◽  
E. Coiera
Keyword(s):  
Public Health ◽  
Decision Support ◽  
Decision Support Systems ◽  
Clinical Decision Support ◽  
Support Systems ◽  
Clinical Decision Support Systems ◽  
Genetic Data ◽  
Clinical Decision ◽  
Translational Bioinformatics ◽  
The Impact

Summary Objectives To review the recent research literature in clinical decision support systems (CDSS). Methods A review of recent literature was undertaken, focussing on CDSS evaluation, consumers and public health, the impact of translational bioinformatics on CDSS design, and CDSS safety. Results In recent years, researchers have concentrated much less on the development of decision technologies, and have focussed more on the impact of CDSS in the clinical world. Recent work highlights that traditional process measures of CDSS effectiveness, such as document relevance are poor proxy measures for decision outcomes. Measuring the dynamics of decision making, for example via decision velocity, may produce a more accurate picture of effectiveness. Another trend is the broadening of user base for CDSS beyond front line clinicians. Consumers are now a major focus for biomedical informatics, as are public health officials, tasked with detecting and managing disease outbreaks at a health system, rather than individual patient level. Bioinformatics is also changing the nature of CDSS. Apart from personalisation of therapy recommendations, translational bioinformatics is creating new challenges in the interpretation of the meaning of genetic data. Finally, there is much recent interest in the safety and effectiveness of computerised physicianorderentry (CPOE) systems, given that prescribing and administration errors are a significant cause of morbidity and mortality. Of note, there is still much controversy surrounding the contention that poorly designed, implemented or used CDSS may actually lead to harm. Conclusions CDSS research remains an active and evolving area of research, as CDSS penetrate more widely beyond their traditional domain into consumer decision support, and as decisions become more complex, for example by involving sequence level genetic data.

“Send & hold” clinical decision support rules improvement to reduce unnecessary testing of vitamins A, E, K, B1, B2, B3, B6 and C

2018 ◽  
Vol 56 (7) ◽  
pp. 1063-1070 ◽  
Author(s):  
Enrique Rodriguez-Borja ◽  
Africa Corchon-Peyrallo ◽  
Esther Barba-Serrano ◽  
Celia Villalba Martínez ◽  
Arturo Carratala Calvo
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Primary Care Physicians ◽  
Vitamin B1 ◽  
Clinical Decision ◽  
Health Department ◽  
Leadership Role ◽  
Control Group ◽  
Vitamin B3 ◽  
The Impact

Abstract Background: We assessed the impact of several “send & hold” clinical decision support rules (CDSRs) within the electronical request system for vitamins A, E, K, B1, B2, B3, B6 and C for all outpatients at a large health department. Methods: When ordered through electronical request, providers (except for all our primary care physicians who worked as a non-intervention control group) were always asked to answer several compulsory questions regarding main indication, symptomatology, suspected diagnosis, vitamin active treatments, etc., for each vitamin test using a drop-down list format. After samples arrival, tests were later put on hold internally by our laboratory information system (LIS) until review for their appropriateness was made by two staff pathologists according to the provided answers and LIS records (i.e. “send & hold”). The number of tests for each analyte was compared between the 10-month period before and after CDSRs implementation in both groups. Results: After implementation, vitamins test volumes decreased by 40% for vitamin A, 29% for vitamin E, 42% for vitamin K, 37% for vitamin B1, 85% for vitamin B2, 68% for vitamin B3, 65% for vitamin B6 and 59% for vitamin C (all p values 0.03 or lower except for vitamin B3), whereas in control group, the majority increased or remained stable. In patients with rejected vitamins, no new requests and/or adverse clinical outcome comments due to this fact were identified. Conclusions: “Send & hold” CDSRs are a promising informatics tool that can support in utilization management and enhance the pathologist’s leadership role as tests specialist.

scholarly journals A Closer Look at the “Right” Format for Clinical Decision Support: Methods for Evaluating a Storyboard BestPractice Advisory

2020 ◽  
Vol 10 (4) ◽  
pp. 142
Author(s):  
Brian J. Douthit ◽  
R. Clayton Musser ◽  
Kay S. Lytle ◽  
Rachel L. Richesson
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Local Level ◽  
Clinical Decision ◽  
System Level ◽  
Evaluation Methodology ◽  
Task Completion ◽  
Free Text ◽  
Alert Fatigue ◽  
The Impact

(1) Background: The five rights of clinical decision support (CDS) are a well-known framework for planning the nuances of CDS, but recent advancements have given us more options to modify the format of the alert. One-size-fits-all assessments fail to capture the nuance of different BestPractice Advisory (BPA) formats. To demonstrate a tailored evaluation methodology, we assessed a BPA after implementation of Storyboard for changes in alert fatigue, behavior influence, and task completion; (2) Methods: Data from 19 weeks before and after implementation were used to evaluate differences in each domain. Individual clinics were evaluated for task completion and compared for changes pre- and post-redesign; (3) Results: The change in format was correlated with an increase in alert fatigue, a decrease in erroneous free text answers, and worsened task completion at a system level. At a local level, however, 14% of clinics had improved task completion; (4) Conclusions: While the change in BPA format was correlated with decreased performance, the changes may have been driven primarily by the COVID-19 pandemic. The framework and metrics proposed can be used in future studies to assess the impact of new CDS formats. Although the changes in this study seemed undesirable in aggregate, some positive changes were observed at the level of individual clinics. Personalized implementations of CDS tools based on local need should be considered.

scholarly journals Clinical implementation of pharmacogenomics via a health system-wide research biobank: the University of Colorado experience

2020 ◽  
Vol 21 (6) ◽  
pp. 375-386 ◽  
Author(s):  
Christina L Aquilante ◽  
David P Kao ◽  
Katy E Trinkley ◽  
Chen-Tan Lin ◽  
Kristy R Crooks ◽  
...  
Keyword(s):  
Decision Support ◽  
Health System ◽  
Clinical Decision Support ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Clinical Implementation ◽  
Support Tool ◽  
University Of Colorado ◽  
The University ◽  
The Impact

In recent years, the genomics community has witnessed the growth of large research biobanks, which collect DNA samples for research purposes. Depending on how and where the samples are genotyped, biobanks also offer the potential opportunity to return actionable genomic results to the clinical setting. We developed a preemptive clinical pharmacogenomic implementation initiative via a health system-wide research biobank at the University of Colorado. Here, we describe how preemptive return of clinical pharmacogenomic results via a research biobank is feasible, particularly when coupled with strong institutional support to maximize the impact and efficiency of biobank resources, a multidisciplinary implementation team, automated clinical decision support tools, and proactive strategies to engage stakeholders early in the clinical decision support tool development process.

scholarly journals A Quality Improvement Initiative to Decrease Platelet Ordering Errors and a Proposed Model for Evaluating Clinical Decision Support Effectiveness

2019 ◽  
Vol 10 (03) ◽  
pp. 505-512
Author(s):  
Julia Whitlow Yarahuan ◽  
Amy Billet ◽  
Jonathan D. Hron
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Health Care Quality ◽  
Platelet Transfusion ◽  
Tertiary Care ◽  
Clinical Decision ◽  
Care Quality ◽  
Inpatient Service ◽  
The Impact ◽  
Order Set

Background and Objectives Clinical decision support (CDS) and computerized provider order entry have been shown to improve health care quality and safety, but may also generate previously unanticipated errors. We identified multiple CDS tools for platelet transfusion orders. In this study, we sought to evaluate and improve the effectiveness of those CDS tools while creating and testing a framework for future evaluation of other CDS tools. Methods Using a query of an enterprise data warehouse at a tertiary care pediatric hospital, we conducted a retrospective analysis to assess baseline use and performance of existing CDS for platelet transfusion orders. Our outcome measure was the percentage of platelet undertransfusion ordering errors. Errors were defined as platelet transfusion volumes ordered which were less than the amount recommended by the order set used. We then redesigned our CDS and measured the impact of our intervention prospectively using statistical process control methodology. Results We identified that 62% of all platelet transfusion orders were placed with one of two order sets (Inpatient Service 1 and Inpatient Service 2). The Inpatient Service 1 order set had a significantly higher occurrence of ordering errors (3.10% compared with 1.20%). After our interventions, platelet transfusion order error occurrence on Inpatient Service 1 decreased from 3.10 to 0.33%. Conclusion We successfully reduced platelet transfusion ordering errors by redesigning our CDS tools. We suggest that the use of collections of clinical data may help identify patterns in erroneous ordering, which could otherwise go undetected. We have created a framework which can be used to evaluate the effectiveness of other similar CDS tools.

scholarly journals Estimating the impact of deploying an electronic clinical decision support tool as part of a national practice improvement project

2019 ◽  
Vol 26 (7) ◽  
pp. 630-636 ◽  
Author(s):  
Ellen K Kerns ◽  
Vincent S Staggs ◽  
Sarah D Fouquet ◽  
Russell J McCulloh
Keyword(s):  
Clinical Practice ◽  
Decision Support ◽  
Clinical Decision Support ◽  
Clinical Decision ◽  
Market Area ◽  
Improvement Project ◽  
Support Tool ◽  
Febrile Infant ◽  
The Impact ◽  
Electronic Clinical Decision Support

Abstract Objective Estimate the impact on clinical practice of using a mobile device–based electronic clinical decision support (mECDS) tool within a national standardization project. Materials and Methods An mECDS tool (app) was released as part of a change package to provide febrile infant management guidance to clinicians. App usage was analyzed using 2 measures: metric hits per case (metric-related screen view count divided by site-reported febrile infant cases in each designated market area [DMA] monthly) and cumulative prior metric hits per site (DMA metric hits summed from study month 1 until the month preceding the index, divided by sites in the DMA). For each metric, a mixed logistic regression model was fit to model site performance as a function of app usage. Results An increase of 200 cumulative prior metric hits per site was associated with increased odds of adherence to 3 metrics: appropriate admission (odds ratio [OR], 1.12; 95% confidence interval [CI], 1.06-1.18), appropriate length of stay (OR, 1.20; 95% CI, 1.12-1.28), and inappropriate chest x-ray (OR, 0.82; 95% CI, 0.75-0.91). Ten additional metric hits per case were also associated: OR were 1.18 (95% CI, 1.02-1.36), 1.36 (95% CI, 1.14-1.62), and 0.74 (95% CI, 0.62-0.89). Discussion mECDS tools are increasingly being implemented, but their impact on clinical practice is poorly described. To our knowledge, although ecologic in nature, this report is the first to link clinical practice to mECDS use on a national scale and outside of an electronic health record. Conclusions mECDS use was associated with changes in adherence to targeted metrics. Future studies should seek to link mECDS usage more directly to clinical practice and assess other site-level factors.

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