Exploring the Impact of a Clinical Decision Support Tool from the Perspective of Service Users & Carers

2008 ◽  
Vol 5 (1) ◽  
pp. 147-161
Author(s):  
Nicola Roberts ◽  
Virginia Minogue ◽  
Mike Lucock ◽  
Lesley Dale ◽  
Rom Glen
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Service Users ◽  
Support Tool ◽  
Clinical Decision Support Tool ◽  
The Impact

scholarly journals Impact of an electronic hard-stop clinical decision support tool to limit repeat Clostridioides difficile toxin enzyme immunoassay testing on test utilization

2019 ◽  
Vol 40 (12) ◽  
pp. 1423-1426 ◽  
Author(s):  
Jennie H. Kwon ◽  
Kimberly A. Reske ◽  
Tiffany Hink ◽  
Ronald Jackups ◽  
Carey-Ann D. Burnham ◽  
...  
Keyword(s):  
Decision Support ◽  
Enzyme Immunoassay ◽  
Clinical Decision Support ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Testing Rate ◽  
Clostridioides Difficile ◽  
Clinical Decision Support Tool ◽  
The Impact

AbstractWe performed an intervention evaluating the impact of an electronic hard-stop clinical decision support tool on repeat Clostridioides difficile (CD) toxin enzyme immunoassay (T-EIA) testing. The CD testing rate and number of admissions with repeat tests decreased significantly postintervention (P < .01 for both); the percentage of positive tests was unchanged (P = .27).

scholarly journals Implementation of a Clinical Decision Support Tool for Stool Cultures and Parasitological Studies in Hospitalized Patients

2017 ◽  
Vol 55 (12) ◽  
pp. 3350-3354 ◽  
Author(s):  
D. Nikolic ◽  
S. S. Richter ◽  
K. Asamoto ◽  
R. Wyllie ◽  
R. Tuttle ◽  
...  
Keyword(s):  
Decision Support ◽  
Clinical Decision Support ◽  
Cost Savings ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Content Type ◽  
Support Tool ◽  
Clinical Decision Support Tool ◽  
The Impact ◽  
Stool Cultures

ABSTRACTThere is substantial evidence that stool culture and parasitological examinations are of minimal to no value after 3 days of hospitalization. We implemented and studied the impact of a clinical decision support tool (CDST) to decrease the number of unnecessary stool cultures (STCUL), ova/parasite (O&P) examinations, andGiardia/Cryptosporidiumenzyme immunoassay screens (GC-EIA) performed for patients hospitalized >3 days. We studied the frequency of stool studies ordered before or on day 3 and after day 3 of hospitalization (i.e., categorical orders/total number of orders) before and after this intervention and denoted the numbers and types of microorganisms detected within those time frames. This intervention, which corresponded to a custom-programmed hard-stop alert tool in the Epic hospital information system, allowed providers to override the intervention by calling the laboratory, if testing was deemed medically necessary. Comparative statistics were employed to determine significance, and cost savings were estimated based on our internal costs. Before the intervention, 129/670 (19.25%) O&P examinations, 47/204 (23.04%) GC-EIA, and 249/1,229 (20.26%) STCUL were ordered after 3 days of hospitalization. After the intervention, 46/521 (8.83%) O&P examinations, 27/157 (17.20%) GC-EIA, and 106/1,028 (10.31%) STCUL were ordered after 3 days of hospitalization. The proportions of reductions in the number of tests performed after 3 days and the associatedPvalues were 54.1% for O&P examinations (P< 0.0001), 22.58% for GC-EIA (P= 0.2807), and 49.1% for STCUL (P< 0.0001). This was estimated to have resulted in $8,108.84 of cost savings. The electronic CDST resulted in a substantial reduction in the number of evaluations of stool cultures and the number of parasitological examinations for patients hospitalized for more than 3 days and in a cost savings while retaining the ability of the clinician to obtain these tests if clinically indicated.

scholarly journals Challenges involved in establishing a web-based clinical decision support tool in community health centers

Healthcare ◽  
2020 ◽  
Vol 8 (4) ◽  
pp. 100488
Author(s):  
Rachel Gold ◽  
Mary Middendorf ◽  
John Heintzman ◽  
Joan Nelson ◽  
Patrick O'Connor ◽  
...  
Keyword(s):  
Decision Support ◽  
Community Health ◽  
Clinical Decision Support ◽  
Community Health Centers ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Health Centers ◽  
Web Based ◽  
Support Tool ◽  
Clinical Decision Support Tool

scholarly journals Duplicate Laboratory Test Reduction Using a Clinical Decision Support Tool

2014 ◽  
Vol 141 (5) ◽  
pp. 718-723 ◽  
Author(s):  
Gary W. Procop ◽  
Lisa M. Yerian ◽  
Robert Wyllie ◽  
A. Marc Harrison ◽  
Kandice Kottke-Marchant
Keyword(s):  
Decision Support ◽  
Laboratory Test ◽  
Clinical Decision Support ◽  
Decision Support Tool ◽  
Clinical Decision ◽  
Support Tool ◽  
Clinical Decision Support Tool

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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