scholarly journals Guidelines, training and quality assurance: influence on general practitioner MRI referral quality

2019 ◽  
Vol 11 (3) ◽  
pp. 235 ◽  
Author(s):  
Stephen Kara ◽  
Alexandra Smart ◽  
Tara Officer ◽  
Chan Dassanayake ◽  
Phil Clark ◽  
...  
Keyword(s):  
Primary Care ◽  
Quality Assurance ◽  
Odds Ratio ◽  
Patient Management ◽  
Kappa Statistic ◽  
Weighted Kappa ◽  
Direct Access ◽  
High Tech ◽  
Rater Agreement ◽  
Mri Scans

ABSTRACT INTRODUCTIONMagnetic resonance imaging (MRI) is an accurate diagnostic test used mainly in secondary care. Uncertainty exists regarding the ability of general practitioners (GPs) to use direct access high-tech imaging pathways appropriately when managing musculoskeletal injury. AIMTo evaluate the use of primary care-centric guidelines, training and quality assurance on the appropriateness of GP MRI referrals for patients with selected musculoskeletal injuries. METHODSThis is an 18-month primary care retrospective study. GPs participated in clinical musculoskeletal training, enabling patient referral for MRI on four body sites. Two reviewers categorised referral appropriateness independently, and reviewer inter-rater agreement between categorisations was measured. MRI results and patient management pathways were described. Associations of scan status and patient management were examined using logistic regression. RESULTSIn total, 273 GPs from 72 practices attended training sessions to receive MRI referral accreditation. Of these, 150 (55%) GPs requested 550 MRI scans, with 527 (96%) eligible for analysis, resulting in 86% considered appropriate; 79% consistent with guidelines and 7% clinically useful but for conditions outside of guidelines. Inter-rater agreement was 75%. Cohen’s weighted kappa statistic was 0.38 (95% CI: 0.28–0.48). MRI referrals consistent with guidelines were more likely to show pathology requiring specialist intervention (reviewer 1: odds ratio=2.64, 95% CI 1.51–4.62; reviewer 2: odds ratio=4.44, 95% CI 2.47–7.99), compared to scan requests graded not consistent. DISCUSSIONStudy findings indicate GPs use decision support guidance well, and this has resulted in appropriate MRI referrals and higher specialist intervention rates for selected conditions.

scholarly journals Corrigendum to: Guidelines, training and quality assurance: influence on general practitioner MRI referral quality

2019 ◽  
Vol 11 (4) ◽  
pp. 387
Author(s):  
Stephen Kara ◽  
Alexandra Smart ◽  
Tara Officer ◽  
Chan Dassanayake ◽  
Phil Clark ◽  
...  
Keyword(s):  
Primary Care ◽  
Quality Assurance ◽  
Odds Ratio ◽  
Patient Management ◽  
Kappa Statistic ◽  
Weighted Kappa ◽  
Direct Access ◽  
High Tech ◽  
Rater Agreement ◽  
Mri Scans

ABSTRACT INTRODUCTIONMagnetic resonance imaging (MRI) is an accurate diagnostic test used mainly in secondary care. Uncertainty exists regarding the ability of general practitioners (GPs) to use direct access high-tech imaging pathways appropriately when managing musculoskeletal injury. AIMTo evaluate the use of primary care-centric guidelines, training and quality assurance on the appropriateness of GP MRI referrals for patients with selected musculoskeletal injuries. METHODSThis is an 18-month primary care retrospective study. GPs participated in clinical musculoskeletal training, enabling patient referral for MRI on four body sites. Two reviewers categorised referral appropriateness independently, and reviewer inter-rater agreement between categorisations was measured. MRI results and patient management pathways were described. Associations of scan status and patient management were examined using logistic regression. RESULTSIn total, 273 GPs from 72 practices attended training sessions to receive MRI referral accreditation. Of these, 150 (55%) GPs requested 550 MRI scans, with 527 (96%) eligible for analysis, resulting in 86% considered appropriate; 79% consistent with guidelines and 7% clinically useful but for conditions outside of guidelines. Inter-rater agreement was 75%. Cohen's weighted kappa statistic was 0.38 (95% CI: 0.28–0.48). MRI referrals consistent with guidelines were more likely to show pathology requiring specialist intervention (reviewer 1: odds ratio=2.64, 95% CI 1.51–4.62; reviewer 2: odds ratio=4.44, 95% CI 2.47–7.99), compared to scan requests graded not consistent. DISCUSSIONStudy findings indicate GPs use decision support guidance well, and this has resulted in appropriate MRI referrals and higher specialist intervention rates for selected conditions.

Cohen’s Weighted Kappa Statistic in Quality Control–Quality Assurance Procedures: Application to Network-Level Contract Pavement Surface Condition Surveys in British Columbia, Canada

2003 ◽  
Vol 1860 (1) ◽  
pp. 103-108 ◽  
Author(s):  
Shawn Landers ◽  
Wael Bekheet ◽  
Lynne Falls
Keyword(s):  
Quality Assurance ◽  
Surface Condition ◽  
Composite Index ◽  
Kappa Statistic ◽  
Weighted Kappa ◽  
Weighted Kappa Statistic ◽  
Testing Procedures ◽  
Pavement Surface ◽  
Surface Distress ◽  
Level Of Agreement

Like many provincial and municipal agencies, the British Columbia Ministry of Transportation (BCMoT) contracts out the collection of pavement surface condition data. Because BCMoT is committed to contracts with multiple private contractors, quality assurance (QA) plays a critical role in ensuring that the data are collected accurately and repeatably from year to year. Comprehensive QA testing procedures for surface distress data have been developed and implemented since the data collection has been based on visual ratings with event boards. Control sites that are manually surveyed are used to evaluate whether the contractor is correctly applying the BCMoT pavement surface distress rating system. To date, the QA testing has been based on a composite-index–based criterion for assessing the level of agreement and supplemented with the detailed severity and density rating data. However, the use of a composite index presents some limitations related to the model formulation and weightings assigned to particular distress types. Although the detailed ratings are useful as a diagnostic tool to pinpoint discrepancies, in the disaggregated format, they are not conducive as acceptance criteria for QA testing. Not widely used in the field of engineering, Cohen’s weighted kappa statistic has been applied since the 1960s in other areas to assess the level of agreement beyond chance among raters. The statistic was therefore identified as a possible solution for improving the ministry’s QA surface distress testing process by providing an overall measure of the level of agreement between the detailed manual benchmark survey and the contractor severity and density ratings. The application is described of Cohen’s weighted kappa statistic for visual surface distress survey QA testing using the BCMoT survey and testing procedures as a case study.

Abstract WP395: Classification of Periventricular White Matter Disease (WMD) in Clinical Radiology Reports vs. Direct Film Review in Ischemic Stroke Patients

Stroke ◽  
2013 ◽  
Vol 44 (suppl_1) ◽  
Author(s):  
Jonathan Hancher ◽  
Jane Eilerman ◽  
Kathleen Alwell ◽  
Heidi Sucharew ◽  
Charles J Moomaw ◽  
...  
Keyword(s):  
Factor Analysis ◽  
Ischemic Stroke ◽  
Recurrent Stroke ◽  
Kappa Statistic ◽  
Weighted Kappa ◽  
Periventricular White Matter ◽  
Kappa Score ◽  
Radiology Reports ◽  
Clinical Radiology ◽  
Mri Scans

Background: Severe WMD is associated with post-stroke mortality, recurrent stroke risk, cognitive decline, and poor functional outcomes. We have previously reported that “severe” WMD grade is likely when the clinical radiology report includes the words “severe, extensive, advanced, or diffuse”. We examined whether terms consistent with the Fazekas WMD grading scale (none, mild, moderate, or severe) in clinical radiology reports can be used to categorize WMD severity in epidemiologic stroke studies, and sought to repeat our factor analysis with descriptive terms. Methods: Clinical reports from 688 ischemic stroke subjects with MRI or CT films from 2010 were reviewed by physician investigators, who recorded whether WMD was described and whether the Fazekas terms or similar descriptors (such as diffuse, patchy, extensive, etc.) were used. A stroke neurologist and a research assistant independently evaluated available neuroimaging studies and categorized WMD severity according to the Fazekas grades. WMD was preferentially graded on MRI scans; CT scans were assessed if MRIs were unavailable or not performed. Kappa statistic was used to compare the grade mentioned in the report with our direct review; factor analysis was applied to the descriptor terms and logistic regression performed to examine predictive value of descriptor terms with WMD grade from direct review. Results: Of the 688, 276 had WMD radiologist grades available, 222 had no grades and no descriptors, and 190 had no grades but had descriptors. For all films with grades available, the weighted kappa score was 0.30, indicating poor agreement between the radiologist’s WMD grade and the reviewer’s WMD grade. Examining only the 231 MRI studies with WMD grades did not improve the weighted kappa score (0.34). Factor analysis found clusters of descriptors that were significantly associated with WMD grades: “scattered, minimal, tiny, punctate, spotty” with mild (p=0.0001); “multiple, patchy, diffuse” with moderate (p=0.01); and “advanced, confluent, extensive” with severe (p = 0.002). Discussion: Fazekas terms in clinical radiology reports do not seem to be useful by themselves, but descriptors used in clinical radiology reports may be utilized to approximate PVWMD severity.

Assessing the inter-rater agreement for ordinal data through weighted indexes

2016 ◽  
Vol 25 (6) ◽  
pp. 2611-2633 ◽  
Author(s):  
Donata Marasini ◽  
Piero Quatto ◽  
Enrico Ripamonti
Keyword(s):  
Carcinoma In Situ ◽  
Ordinal Data ◽  
Biomedical Applications ◽  
Kappa Statistic ◽  
Weighted Kappa ◽  
Rater Agreement ◽  
Ordinal Variables ◽  
Statistical Hypotheses ◽  
Nominal Variables

Assessing the inter-rater agreement between observers, in the case of ordinal variables, is an important issue in both the statistical theory and biomedical applications. Typically, this problem has been dealt with the use of Cohen’s weighted kappa, which is a modification of the original kappa statistic, proposed for nominal variables in the case of two observers. Fleiss (1971) put forth a generalization of kappa in the case of multiple observers, but both Cohen’s and Fleiss’ kappa could have a paradoxical behavior, which may lead to a difficult interpretation of their magnitude. In this paper, a modification of Fleiss’ kappa, not affected by paradoxes, is proposed, and subsequently generalized to the case of ordinal variables. Monte Carlo simulations are used both to testing statistical hypotheses and to calculating percentile and bootstrap-t confidence intervals based on this statistic. The normal asymptotic distribution of the proposed statistic is demonstrated. Our results are applied to the classical Holmquist et al.’s (1967) dataset on the classification, by multiple observers, of carcinoma in situ of the uterine cervix. Finally, we generalize the use of s* to a bivariate case.

scholarly journals Primary care management of headaches and how direct-access MRI fits: a qualitative study of UK general practitioners’ views

BMJ Open ◽  
2017 ◽  
Vol 7 (11) ◽  
pp. e018169 ◽  
Author(s):  
Raphael Underwood ◽  
Rachael Kilner ◽  
Leone Ridsdale
Keyword(s):  
Primary Care ◽  
Qualitative Study ◽  
General Practitioners ◽  
Psychological Symptoms ◽  
Direct Access ◽  
Radiology Reports ◽  
Semistructured Interviews ◽  
Care Family ◽  
Mri Scans ◽  
Headache Management

ObjectivesTo develop a better understanding of general practitioners’ (GPs) views and experiences of the management of patients with headaches and use of direct-access MRI scans, and observe outcomes of an educational session offered by a GP with a special interest (GPwSI) to GPs.DesignA qualitative study using semistructured interviews, analysed using thematic analysis. A GPwSI in headaches visited practices delivering a talk on headache medication, diagnosis and management.SettingSixteen (16) primary care family practices in South London, UK.ParticipantsTwenty (20) GPs.ResultsNot all GPs were aware of the availability of direct-access MRI, but all acknowledged having used referral or direct scans to manage patients’ concern about their headaches. A normal scan result helped resolve uncertainty for patient and GP and helped management towards discussion of preventative treatment. However, patients with psychological and/or severe headache symptoms could not necessarily be reassured. GPs reported difficulty interpreting radiology reports, particularly incidental abnormalities. Those who received the educational talk gained knowledge in diagnosis and medication, improving their confidence in management.ConclusionsIncreased access to imaging, training in headache management, addressing physical and psychological symptoms and standardised reporting of scans may improve GPs’ use of direct-access MRI in the future.

scholarly journals Smart Health System to Detect Dementia Disorders Using Virtual Reality

Healthcare ◽  
2021 ◽  
Vol 9 (7) ◽  
pp. 810
Author(s):  
Areej Y. Bayahya ◽  
Wadee Alhalabi ◽  
Sultan H. AlAmri
Keyword(s):  
Virtual Reality ◽  
Clinical Diagnosis ◽  
Kappa Statistic ◽  
Weighted Kappa ◽  
Health Technology ◽  
P Value ◽  
Functional Evaluation ◽  
Medical Specialties ◽  
Weighted Kappa Statistic ◽  
Smart Health

Smart health technology includes physical sensors, intelligent sensors, and output advice to help monitor patients’ health and adjust their behavior. Virtual reality (VR) plays an increasingly larger role to improve health outcomes, being used in a variety of medical specialties including robotic surgery, diagnosis of some difficult diseases, and virtual reality pain distraction for severe burn patients. Smart VR health technology acts as a decision support system in the diseases diagnostic test of patients as they perform real world tasks in virtual reality (e.g., navigation). In this study, a non-invasive, cognitive computerized test based on 3D virtual environments for detecting the main symptoms of dementia (memory loss, visuospatial defects, and spatial navigation) is proposed. In a recent study, the system was tested on 115 real patients of which thirty had a dementia, sixty-five were cognitively healthy, and twenty had a mild cognitive impairment (MCI). The performance of the VR system was compared with Mini-Cog test, where the latter is used to measure cognitive impaired patients in the traditional diagnosis system at the clinic. It was observed that visuospatial and memory recall scores in both clinical diagnosis and VR system of dementia patients were less than those of MCI patients, and the scores of MCI patients were less than those of the control group. Furthermore, there is a perfect agreement between the standard methods in functional evaluation and navigational ability in our system where P-value in weighted Kappa statistic= 100% and between Mini-Cog-clinical diagnosis vs. VR scores where P-value in weighted Kappa statistic= 93%.

scholarly journals 22. Patient Satisfaction Remains Unchanged Following Implementation of an Antibiotic Stewardship Intervention in Primary Care

2020 ◽  
Vol 7 (Supplement_1) ◽  
pp. S11-S12
Author(s):  
Zachary Hostetler ◽  
Keith W Hamilton ◽  
Leigh Cressman ◽  
McWelling H Todman ◽  
Ebbing Lautenbach ◽  
...  
Keyword(s):  
Primary Care ◽  
Patient Satisfaction ◽  
Odds Ratio ◽  
Logistic Regression Model ◽  
Adjusted Odds Ratio ◽  
Primary Care Providers ◽  
Mixed Effects ◽  
Antibiotic Prescribing ◽  
Care Providers ◽  
Targeted Intervention

Abstract Background Inappropriate prescription of antibiotics for respiratory tract infections (RTIs) in ambulatory care settings is common, increasing the risk of adverse health outcomes. Behavioral and educational interventions targeting primary care providers (PCPs) have shown promise in reducing inappropriate antibiotic prescribing for RTIs. While one perceived barrier to such interventions is the concern that these adversely impact patient satisfaction, few data exist in this area. Here, we examine whether a recent PCP-targeted intervention that significantly reduced antibiotic prescribing for RTIs was associated with a change in patient satisfaction. Methods The PCP-targeted intervention involved monthly education sessions and peer benchmarking reports delivered to 31 clinics within an academic health system, and was previously shown to reduce antibiotic prescribing. Here, we performed a retrospective, secondary analysis of Press Ganey (PG) surveys associated with the outpatient encounters in the pre- and post-intervention periods. We evaluated the impact on patient perceptions of PCPs based on provider exposure to the intervention using a mixed effects logistic regression model. Results There were 17,416 out of 197,744 encounters (8.8%) with associated PG surveys for the study time period (July 2016 to September 2018). In the multivariate model, patient satisfaction with PCPs was most strongly associated with patient-level characteristics (age, race, health status, education status) and survey-level characteristics (survey response time, patient’s usual provider) (Figure 1). Satisfaction with PCPs did not change following delivery of the provider-based intervention even after adjusting for patient- and survey-level characteristics [adjusted odds ratio (95% CI): 1.005 (0.928, 1.087)]. However, a small increase in satisfaction associated with receiving antibiotics during the entire study period was seen [adjusted odds ratio (95% CI): 1.146 (1.06, 1.244)]. Figure 1: Association of a provider-targeted intervention as well as patient, provider, and practice characteristics with patient satisfaction in a multivariable mixed effects logistic regression model Conclusion Patient perceptions of PCPs remain unchanged following the delivery of a behavioral and educational intervention to primary care providers that resulted in observable decreases in antibiotic prescribing practices for RTIs. Disclosures All Authors: No reported disclosures

scholarly journals Development of an Automatic Functional Movement Screening System with Inertial Measurement Unit Sensors

2020 ◽  
Vol 11 (1) ◽  
pp. 96
Author(s):  
Wen-Lan Wu ◽  
Meng-Hua Lee ◽  
Hsiu-Tao Hsu ◽  
Wen-Hsien Ho ◽  
Jing-Min Liang
Keyword(s):  
Feature Selection ◽  
Inertial Measurement Unit ◽  
Learning Algorithm ◽  
Kappa Statistic ◽  
Weighted Kappa ◽  
Classification Model ◽  
Measurement Unit ◽  
Functional Movement ◽  
Inertial Measurement ◽  
Movement Screening

Background: In this study, an automatic scoring system for the functional movement screen (FMS) was developed. Methods: Thirty healthy adults fitted with full-body inertial measurement unit sensors completed six FMS exercises. The system recorded kinematics data, and a professional athletic trainer graded each participant. To reduce the number of input variables for the predictive model, ordinal logistic regression was used for subset feature selection. The ensemble learning algorithm AdaBoost.M1 was used to construct classifiers. Accuracy and F score were used for classification model evaluation. The consistency between automatic and manual scoring was assessed using a weighted kappa statistic. Results: When all the features were used, the predict model presented moderate to high accuracy, with kappa values between fair to very good agreement. After feature selection, model accuracy decreased about 10%, with kappa values between poor to moderate agreement. Conclusions: The results indicate that higher prediction accuracy was achieved using the full feature set compared with using the reduced feature set.

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