scholarly journals The impact of lung ultrasound on clinical-decision making across departments: a systematic review

2022 ◽  
Vol 14 (1) ◽  
Author(s):  
Micah L. A. Heldeweg ◽  
Lian Vermue ◽  
Max Kant ◽  
Michelle Brouwer ◽  
Armand R. J. Girbes ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Lung Ultrasound ◽  
Clinical Decision ◽  
Current Evidence ◽  
Substantial Impact ◽  
Thoracic Ultrasound ◽  
Newcastle Ottawa Scale ◽  
The Impact

Abstract Background Lung ultrasound has established itself as an accurate diagnostic tool in different clinical settings. However, its effects on clinical-decision making are insufficiently described. This systematic review aims to investigate the impact of lung ultrasound, exclusively or as part of an integrated thoracic ultrasound examination, on clinical-decision making in different departments, especially the emergency department (ED), intensive care unit (ICU), and general ward (GW). Methods This systematic review was registered at PROSPERO (CRD42021242977). PubMed, EMBASE, and Web of Science were searched for original studies reporting changes in clinical-decision making (e.g. diagnosis, management, or therapy) after using lung ultrasound. Inclusion criteria were a recorded change of management (in percentage of cases) and with a clinical presentation to the ED, ICU, or GW. Studies were excluded if examinations were beyond the scope of thoracic ultrasound or to guide procedures. Mean changes with range (%) in clinical-decision making were reported. Methodological data on lung ultrasound were also collected. Study quality was scored using the Newcastle–Ottawa scale. Results A total of 13 studies were included: five studies on the ED (546 patients), five studies on the ICU (504 patients), two studies on the GW (1150 patients), and one study across all three wards (41 patients). Lung ultrasound changed the diagnosis in mean 33% (15–44%) and 44% (34–58%) of patients in the ED and ICU, respectively. Lung ultrasound changed the management in mean 48% (20–80%), 42% (30–68%) and 48% (48–48%) of patients in the ED, in the ICU and in the GW, respectively. Changes in management were non-invasive in 92% and 51% of patients in the ED and ICU, respectively. Lung ultrasound methodology was heterogeneous across studies. Risk of bias was moderate to high in all studies. Conclusions Lung ultrasound, exclusively or as a part of thoracic ultrasound, has substantial impact on clinical-decision making by changing diagnosis and management in the EDs, ICUs, and GWs. The current evidence level and methodological heterogeneity underline the necessity for well-designed trials and standardization of methodology.

scholarly journals A Systematic Review of the Impact of Physician Implicit Racial Bias on Clinical Decision Making

2017 ◽  
Vol 24 (8) ◽  
pp. 895-904 ◽  
Author(s):  
Erin Dehon ◽  
Nicole Weiss ◽  
Jonathan Jones ◽  
Whitney Faulconer ◽  
Elizabeth Hinton ◽  
...  
Keyword(s):  
Systematic Review ◽  
Decision Making ◽  
Clinical Decision Making ◽  
Racial Bias ◽  
Clinical Decision ◽  
Implicit Racial Bias ◽  
The Impact

scholarly journals Can Alveolar-Arterial Difference and Lung Ultrasound Help the Clinical Decision Making in Patients with COVID-19?

Diagnostics ◽  
2021 ◽  
Vol 11 (5) ◽  
pp. 761
Author(s):  
Gianmarco Secco ◽  
Francesco Salinaro ◽  
Carlo Bellazzi ◽  
Marco La Salvia ◽  
Marzia Delorenzo ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Lung Ultrasound ◽  
Signs And Symptoms ◽  
Clinical Decision ◽  
Arterial Oxygen ◽  
Arterial Blood Gas ◽  
Arterial Blood ◽  
Lung Dysfunction ◽  
Close Relationship

Background: COVID-19 is an emerging infectious disease, that is heavily challenging health systems worldwide. Admission Arterial Blood Gas (ABG) and Lung Ultrasound (LUS) can be of great help in clinical decision making, especially during the current pandemic and the consequent overcrowding of the Emergency Department (ED). The aim of the study was to demonstrate the capability of alveolar-to-arterial oxygen difference (AaDO2) in predicting the need for subsequent oxygen support and survival in patients with COVID-19 infection, especially in the presence of baseline normal PaO2/FiO2 ratio (P/F) values. Methods: A cohort of 223 swab-confirmed COVID-19 patients underwent clinical evaluation, blood tests, ABG and LUS in the ED. LUS score was derived from 12 ultrasound lung windows. AaDO2 was derived as AaDO2 = ((FiO2) (Atmospheric pressure − H2O pressure) − (PaCO2/R)) − PaO2. Endpoints were subsequent oxygen support need and survival. Results: A close relationship between AaDO2 and P/F and between AaDO2 and LUS score was observed (R2 = 0.88 and R2 = 0.67, respectively; p < 0.001 for both). In the subgroup of patients with P/F between 300 and 400, 94.7% (n = 107) had high AaDO2 values, and 51.4% (n = 55) received oxygen support, with 2 ICU admissions and 10 deaths. According to ROC analysis, AaDO2 > 39.4 had 83.6% sensitivity and 90.5% specificity (AUC 0.936; p < 0.001) in predicting subsequent oxygen support, whereas a LUS score > 6 showed 89.7% sensitivity and 75.0% specificity (AUC 0.896; p < 0.001). Kaplan–Meier curves showed different mortality in the AaDO2 subgroups (p = 0.0025). Conclusions: LUS and AaDO2 are easy and effective tools, which allow bedside risk stratification in patients with COVID-19, especially when P/F values, signs, and symptoms are not indicative of severe lung dysfunction.

AAC Assessment and Clinical-Decision Making: The Impact of Experience

2012 ◽  
Vol 28 (3) ◽  
pp. 148-159 ◽  
Author(s):  
Aimee Dietz ◽  
Wendy Quach ◽  
Shelley K. Lund ◽  
Miechelle McKelvey
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
The Impact

Standardized Synoptic Cancer Pathology Reports — So What and Who Cares?: A Population-Based Satisfaction Survey of 970 Pathologists, Surgeons, and Oncologists

2013 ◽  
Vol 137 (11) ◽  
pp. 1599-1602 ◽  
Author(s):  
Sara Lankshear ◽  
John Srigley ◽  
Thomas McGowan ◽  
Marta Yurcan ◽  
Carol Sawka
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Physician Satisfaction ◽  
Cross Sectional ◽  
Cancer Pathology ◽  
Report Turnaround Time ◽  
Significant Difference ◽  
Pathology Reporting ◽  
The Impact

Context.—Cancer Care Ontario implemented synoptic pathology reporting across Ontario, impacting the practice of pathologists, surgeons, and medical and radiation oncologists. The benefits of standardized synoptic pathology reporting include enhanced completeness and improved consistency in comparison with narrative reports, with reported challenges including increased workload and report turnaround time. Objective.—To determine the impact of synoptic pathology reporting on physician satisfaction specific to practice and process. Design.—A descriptive, cross-sectional design was utilized involving 970 clinicians across 27 hospitals. An 11-item survey was developed to obtain information regarding timeliness, completeness, clarity, and usability. Open-ended questions were also employed to obtain qualitative comments. Results.—A 51% response rate was obtained, with descriptive statistics reporting that physicians perceive synoptic reports as significantly better than narrative reports. Correlation analysis revealed a moderately strong, positive relationship between respondents' perceptions of overall satisfaction with the level of information provided and perceptions of completeness for clinical decision making (r = 0.750, P &lt; .001) and ease of finding information for clinical decision making (r = 0.663, P &lt; .001). Dependent t tests showed a statistically significant difference in the satisfaction scores of pathologists and oncologists (t169 = 3.044, P = .003). Qualitative comments revealed technology-related issues as the most frequently cited factor impacting timeliness of report completion. Conclusion.—This study provides evidence of strong physician satisfaction with synoptic cancer pathology reporting as a clinical decision support tool in the diagnosis, prognosis, and treatment of cancer patients.

scholarly journals Clinicians’ experiences of using and implementing a medical mobile phone app (QUiPP V2) designed to predict the risk of preterm birth and aid clinical decision making

2021 ◽  
Vol 21 (1) ◽  
Author(s):  
N. Carlisle ◽  
H. A. Watson ◽  
J. Carter ◽  
K. Kuhrt ◽  
P. T. Seed ◽  
...  
Keyword(s):  
Decision Making ◽  
Preterm Birth ◽  
Cultural Context ◽  
Clinical Decision Making ◽  
Qualitative Interviews ◽  
Scale Up ◽  
Clinical Decision ◽  
Clinical Trial Registry ◽  
Support Tool ◽  
The Impact

Abstract Background As the vast majority of women who present in threatened preterm labour (TPTL) will not deliver early, clinicians need to balance the risks of over-medicalising the majority of women, against the potential risk of preterm delivery for those discharged home. The QUiPP app is a free, validated app which can support clinical decision-making as it produces individualised risks of delivery within relevant timeframes. Recent evidence has highlighted that clinicians would welcome a decision-support tool that accurately predicts preterm birth. Methods Qualitative interviews were undertaken as part of the EQUIPTT study (The Evaluation of the QUiPP app for Triage and Transfer) (REC: 17/LO/1802) which aimed to evaluate the impact of the QUiPP app on management of TPTL. Individual semi-structured telephone interviews were used to explore clinicians’ (obstetricians’ and midwives’) experiences of using the QUiPP app and how it was implemented at their hospital sites. Thematic analysis was chosen to explore the meaning of the data, through a framework approach. Results Nineteen participants from 10 hospital sites in England took part. Data analysis revealed three overarching themes which were: ‘experience of using the app’, ‘how QUiPP risk changes practice’ and ‘successfully adopting QUiPP: context is everything’. With these final themes we appeared to have achieved our aim of exploring the clinicians’ experiences of using and implementing the QUiPP app. Conclusion This study explored different clinician’s experiences of implementing the app. The organizational and cultural context at different sites appeared to have a large impact on how well the QUiPP app was implemented. Future work needs to be undertaken to understand how best to embed the intervention within different settings. This will inform scale up of QUiPP app use across the UK and ensure that clinicians have access to this free, easy-to-use tool which can positively aid clinical decision making when caring for women in TPTL. Clinical trial registry and registration number ISRCTN 17846337, registered 08th January 2018, https://doi.org/10.1186/ISRCTN17846337.

scholarly journals Exploring the role of the Care and Health Information Exchange (CHIE) in clinical decision-making: a realist evaluation

2020 ◽  
Author(s):  
Philip Scott ◽  
Elisavet Andrikopoulou ◽  
Haythem Nakkas ◽  
Paul Roderick
Keyword(s):  
Decision Making ◽  
Health Information ◽  
Information Exchange ◽  
Healthcare Professionals ◽  
Clinical Decision Making ◽  
Social Care ◽  
Health Information Exchange ◽  
Clinical Decision ◽  
Health And Social Care ◽  
The Impact

Background: The overall evidence for the impact of electronic information systems on cost, quality and safety of healthcare remains contested. Whilst it seems intuitively obvious that having more data about a patient will improve care, the mechanisms by which information availability is translated into better decision-making are not well understood. Furthermore, there is the risk of data overload creating a negative outcome. There are situations where a key information summary can be more useful than a rich record. The Care and Health Information Exchange (CHIE) is a shared electronic health record for Hampshire and the Isle of Wight that combines key information from hospital, general practice, community care and social services. Its purpose is to provide clinical and care professionals with complete, accurate and up-to-date information when caring for patients. CHIE is used by GP out-of-hours services, acute hospital doctors, ambulance service, GPs and others in caring for patients. Research questions: The fundamental question was How does awareness of CHIE or usage of CHIE affect clinical decision-making? The secondary questions were What are the latent benefits of CHIE in frontline NHS operations? and What is the potential of CHIE to have an impact on major NHS cost pressures? The NHS funders decided to focus on acute medical inpatient admissions as the initial scope, given the high costs associated with hospital stays and the patient complexities (and therefore information requirements) often associated with unscheduled admissions. Methods: Semi-structured interviews with healthcare professionals to explore their experience about the utility of CHIE in their clinical scenario, whether and how it has affected their decision-making practices and the barriers and facilitators for their use of CHIE. The Framework Method was used for qualitative analysis, supported by the software tool Atlas.ti. Results: 21 healthcare professionals were interviewed. Three main functions were identified as useful: extensive medication prescribing history, information sharing between primary, secondary and social care and access to laboratory test results. We inferred two positive cognitive mechanisms: knowledge confidence and collaboration assurance, and three negative ones: consent anxiety, search anxiety and data mistrust. Conclusions: CHIE gives clinicians the bigger picture to understand the patient's health and social care history and circumstances so as to make confident and informed decisions. CHIE is very beneficial for medicines reconciliation on admission, especially for patients that are unable to speak or act for themselves or who cannot remember their precise medication or allergies. We found no clear evidence that CHIE has a significant impact on admission or discharge decisions. We propose the use of recommender systems to help clinicians navigate such large volumes of patient data, which will only grow as additional data is collected.

scholarly journals QOLP-03. MEASURING CHANGE IN HEALTH-RELATED QUALITY OF LIFE: THE ADDED VALUE OF ANALYSIS ON THE INDIVIDUAL PATIENT LEVEL IN GLIOMA PATIENTS IN CLINICAL DECISION MAKING

2019 ◽  
Vol 21 (Supplement_6) ◽  
pp. vi197-vi198 ◽  
Author(s):  
Marijke Coomans ◽  
Martin Taphoorn ◽  
Neil Aaronson ◽  
Brigitta Baumert ◽  
Martin van den Bent ◽  
...  
Keyword(s):  
Decision Making ◽  
Clinical Decision Making ◽  
Clinical Decision ◽  
Scale Item ◽  
Individual Patient Level ◽  
Patient Level ◽  
Related Quality ◽  
The Individual ◽  
The Impact ◽  
Over Time

Abstract BACKGROUND: Health-related quality of life (HRQoL) is an important outcome in glioma research, reflecting the impact of disease and treatment on a patient’s functioning and wellbeing. Data on changes in HRQoL scores provide important information for clinical decision-making, but different analytical methods may lead to different interpretations of the impact of treatment on HRQoL. This study aimed to study whether different methods to evaluate change in HRQoL result in different interpretations. Methods: HRQoL and sociodemographical/clinical data from 15 randomized clinical trials were combined. Change in HRQoL scores was analyzed: (1)at the group level, comparing mean changes in scale/item scores between treatment arms over time, (2)at the patient level per scale/item by calculating the percentage of patients that deteriorated, improved or remained stable on a scale/item per scale/item, and (3)at the individual patient level combining all scales/items. Results: Data were available for 3727 patients. At the group scale/item level (method 1), only the item ‘hair loss’ showed a significant and clinically relevant change (i.e. ≥10 points) over time, whereas change scores on the other scales/items showed a statistically significant change only (all p< .001, range in change score:0.1–6.2). Analyses on the patient level per scale (method 2) indicated that, while a large proportion of patients had stable HRQoL over time (range:27–84%), many patients deteriorated (range:6–43%) or improved (range:8–32%) on a specific scale/item. At the individual patient level (method 3), the majority of patients (86%) showed both deterioration and improvement, while only 1% of the patients remained stable on all scales. Conclusion: Different analytical methods of changes in HRQoL result in distinct interpretations of treatment effects, all of which may be relevant for clinical decision-making. Additional information about the joint impact of treatment on all outcomes may help patients and physicians to make the best treatment decision.

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