Reliability and Validity of a Standardized Measure of Influenza Vaccination Coverage among Healthcare Personnel

2013 ◽  
Vol 34 (4) ◽  
pp. 335-345 ◽  
Author(s):  
Tanya E. Libby ◽  
Megan C. Lindley ◽  
Suchita A. Lorick ◽  
Taranisia MacCannell ◽  
Soo-Jeong Lee ◽  
...  
Keyword(s):  
Influenza Vaccination ◽  
Reliability And Validity ◽  
Face Validity ◽  
Healthcare Personnel ◽  
Project Staff ◽  
Term Care ◽  
Physician Practices ◽  
Standardized Measure ◽  
Facility Staff

Objective.To evaluate the reliability and validity of a standardized measure of healthcare personnel (HCP) influenza vaccination.Setting.Acute care hospitals, long-term care facilities, ambulatory surgery centers, physician practices, and dialysis centers from 3 US jurisdictions.Participants.Staff from 96 healthcare facilities randomly sampled from 234 facilities that completed pilot testing to assess the feasibility of the measure.Methods.Reliability was assessed by comparing agreement between facility staff and project staff on the classification of HCP numerator (vaccinated at facility, vaccinated elsewhere, contraindicated, declined) and denominator (employees, credentialed nonemployees, other nonemployees) categories. To assess validity, facility staff completed a series of case studies to evaluate how closely classification of HCP groups aligned with the measure's specifications. In a modified Delphi process, experts rated face validity of the proposed measure elements on a Likert-type scale.Results.Percent agreement was high for HCP vaccinated at the facility (99%) and elsewhere (95%) and was lower for HCP who declined vaccination (64%) or were medically contraindicated (64%). While agreement was high (more than 90%) for all denominator categories, many facilities' staff excluded nonemployees for whom numerator and denominator status was difficult to determine. Validity was lowest for credentialed and other nonemployees.Conclusions.The standardized measure of HCP influenza vaccination yields reproducible results for employees vaccinated at the facility and elsewhere. Adhering to true medical contraindications and tracking decimations should improve reliability. Difficulties in establishing denominators and determining vaccination status for credentialed and other nonemployees challenged the measure's validity and prompted revision to include a more limited group of nonemployees.

scholarly journals Support for Seasonal Influenza Vaccination Requirements among US Healthcare Personnel

2012 ◽  
Vol 33 (3) ◽  
pp. 213-221 ◽  
Author(s):  
Jürgen Maurer ◽  
Katharine M. Harris ◽  
Carla L. Black ◽  
Gary L. Euler
Keyword(s):  
Influenza Vaccination ◽  
Seasonal Influenza ◽  
Safety Issue ◽  
Healthcare Personnel ◽  
Sampling Frame ◽  
Staff Support ◽  
Term Care ◽  
Seasonal Influenza Vaccination ◽  
Care Facilities ◽  
Serious Disease

Objective.To measure support for seasonal influenza vaccination requirements among US healthcare personnel (HCP) and its associations with attitudes regarding influenza and influenza vaccination and self-reported coverage by existing vaccination requirements.Design.Between lune 1 and June 30, 2010, we surveyed a sample of US HCP (n = 1,664) recruited using an existing probability-based online research panel of participants representing the US general population as a sampling frame.Setting.General community.Participants.Eligible HCP who (1) reported having worked as medical doctors, health technologists, healthcare support staff, or other health practitioners or who (2) reported having worked in hospitals, ambulatory care facilities, long-term care facilities, or other health-related settings.Methods.We analyzed support for seasonal influenza vaccination requirements for HCP using proportion estimation and multivariable probit models.Results.A total of 57.4% (95% confidence interval, 53.3%–61.5%) of US HCP agreed that HCP should be required to be vaccinated for seasonal influenza. Support for mandatory vaccination was statistically significantly higher among HCP who were subject to employer-based influenza vaccination requirements, who considered influenza to be a serious disease, and who agreed that influenza vaccine was safe and effective.Conclusions.A majority of HCP support influenza vaccination requirements. Moreover, providing HCP with information about the safety of influenza vaccination and communicating that immunization of HCP is a patient safety issue may be important for generating staff support for influenza vaccination requirements.Infect Control Hosp Epidemiol 2012;33(3):213-221

scholarly journals Preventing Respiratory Viral Transmission in Long-Term Care: Knowledge, Attitudes, and Practices of Healthcare Personnel

2017 ◽  
Vol 38 (12) ◽  
pp. 1449-1456 ◽  
Author(s):  
Caroline A. O’Neil ◽  
Lindsay Kim ◽  
Mila M. Prill ◽  
Nimalie D. Stone ◽  
Shikha Garg ◽  
...  
Keyword(s):  
Influenza Vaccine ◽  
Influenza Vaccination ◽  
Infection Prevention ◽  
Long Term Care ◽  
Healthcare Personnel ◽  
Patient Contact ◽  
Term Care ◽  
Attitudes And Practices ◽  
Knowledge Attitudes And Practices

OBJECTIVETo examine knowledge and attitudes about influenza vaccination and infection prevention practices among healthcare personnel (HCP) in a long-term-care (LTC) setting.DESIGNKnowledge, attitudes, and practices (KAP) survey.SETTINGAn LTC facility in St Louis, Missouri.PARTICIPANTSAll HCP working at the LTC facility were eligible to participate, regardless of department or position. Of 170 full- and part-time HCP working at the facility, 73 completed the survey, a 42.9% response rate.RESULTSMost HCP agreed that respiratory viral infections were serious and that hand hygiene and face mask use were protective. However, only 46% could describe the correct transmission-based precautions for an influenza patient. Correctly answering infection prevention knowledge questions did not vary by years of experience but did vary for HCP with more direct patient contact versus less patient contact. Furthermore, 42% of respondents reported working while sick, and 56% reported that their coworkers did. In addition, 54% reported that facility policies made staying home while ill difficult. Some respondents expressed concerns about the safety (22%) and effectiveness (27%) of the influenza vaccine, and 28% of respondents stated that they would not get the influenza vaccine if it was not required.CONCLUSIONSThis survey of staff in an LTC facility identified several areas for policy improvement, particularly sick leave, as well as potential targets for interventions to improve infection prevention knowledge and to address HCP concerns about influenza vaccination to improve HCP vaccination rates in LTCs.Infect Control Hosp Epidemiol 2017;38:1449–1456

scholarly journals Evaluating a Standardized Measure of Healthcare Personnel Influenza Vaccination

2013 ◽  
Vol 45 (3) ◽  
pp. 297-303 ◽  
Author(s):  
Megan C. Lindley ◽  
Suchita A. Lorick ◽  
Anita Geevarughese ◽  
Soo-Jeong Lee ◽  
Monear Makvandi ◽  
...  
Keyword(s):  
Influenza Vaccination ◽  
Healthcare Personnel ◽  
Standardized Measure

scholarly journals The Multifocal Approach to Sharing in Shared Decision Making: A Critical Appraisal of the MAPPIN’SDM

2021 ◽  
pp. 0272989X2110107
Author(s):  
David Forner ◽  
Christopher W. Noel ◽  
Laura Boland ◽  
Arwen H. Pieterse ◽  
Cornelia M. Borkhoff ◽  
...  
Keyword(s):  
Decision Making ◽  
Shared Decision Making ◽  
Critical Appraisal ◽  
Reliability And Validity ◽  
Measurement Instrument ◽  
Face Validity ◽  
Shared Decision ◽  
Measurement Instruments ◽  
Multiple Perspectives ◽  
Property Assessment

Objective Shared decision making integrates health care provider expertise with patient values and preferences. The MAPPIN’SDM is a recently developed measurement instrument that incorporates physician, patient, and observer perspectives during medical consultations. This review sought to critically appraise the development, sensibility, reliability, and validity of the MAPPIN’SDM and to determine in which settings it has been used. Methods This critical appraisal was performed through a targeted review of the literature. Articles outlining the development or measurement property assessment of the MAPPIN’SDM or that used the instrument for predictor or outcome purposes were identified. Results Thirteen studies were included. The MAPPIN’SDM was developed by both adapting and building on previous shared decision making measurement instruments, as well as through creation of novel items. Content validity, face validity, and item quality of the MAPPIN’SDM are adequate. Internal consistency ranged from 0.91 to 0.94 and agreement statistics from 0.41 to 0.92. The MAPPIN’SDM has been evaluated in several populations and settings, ranging from chronic disease to acute oncological settings. Limitations include high reading levels required for self-administered patient questionnaires and the small number of studies that have employed the instrument to date. Conclusion The MAPPIN’SDM generally shows adequate development, sensibility, reliability, and validity in preliminary testing and holds promise for shared decision making research integrating multiple perspectives. Further research is needed to develop its use in other patient populations and to assess patient understanding of complex item wording.

scholarly journals Artificial Intelligence in Fractured Dental Implant Detection and Classification: Evaluation Using Dataset from Two Dental Hospitals

Diagnostics ◽  
2021 ◽  
Vol 11 (2) ◽  
pp. 233
Author(s):  
Dong-Woon Lee ◽  
Sung-Yong Kim ◽  
Seong-Nyum Jeong ◽  
Jae-Hong Lee
Keyword(s):  
Dental Implant ◽  
Classification Accuracy ◽  
Reliability And Validity ◽  
Mechanical Complication ◽  
Radiographic Images ◽  
Acceptable Accuracy ◽  
Reliable Detection ◽  
Classification Evaluation ◽  
Accuracy Performance

Fracture of a dental implant (DI) is a rare mechanical complication that is a critical cause of DI failure and explantation. The purpose of this study was to evaluate the reliability and validity of a three different deep convolutional neural network (DCNN) architectures (VGGNet-19, GoogLeNet Inception-v3, and automated DCNN) for the detection and classification of fractured DI using panoramic and periapical radiographic images. A total of 21,398 DIs were reviewed at two dental hospitals, and 251 intact and 194 fractured DI radiographic images were identified and included as the dataset in this study. All three DCNN architectures achieved a fractured DI detection and classification accuracy of over 0.80 AUC. In particular, automated DCNN architecture using periapical images showed the highest and most reliable detection (AUC = 0.984, 95% CI = 0.900–1.000) and classification (AUC = 0.869, 95% CI = 0.778–0.929) accuracy performance compared to fine-tuned and pre-trained VGGNet-19 and GoogLeNet Inception-v3 architectures. The three DCNN architectures showed acceptable accuracy in the detection and classification of fractured DIs, with the best accuracy performance achieved by the automated DCNN architecture using only periapical images.

Correlates of Improved Influenza Vaccination of Healthcare Personnel: A Survey of Hospitals in Louisiana

2013 ◽  
Vol 34 (7) ◽  
pp. 723-729 ◽  
Author(s):  
Kayla L. Fricke ◽  
Mariella M. Gastañaduy ◽  
Renee Klos ◽  
Rodolfo E. Bégué
Keyword(s):  
Intensive Care Unit ◽  
Intensive Care ◽  
Influenza Vaccination ◽  
Vaccination Campaign ◽  
Vaccination Rate ◽  
Healthcare Personnel ◽  
Patient Contact ◽  
Hospital Type ◽  
Vaccination Rates ◽  
Item Questionnaire

Objective.To describe practices for influenza vaccination of healthcare personnel (HCP) with emphasis on correlates of increased vaccination rates.Design.Survey.Participants.Volunteer sample of hospitals in Louisiana.Methods.All hospitals in Louisiana were invited to participate. A 17-item questionnaire inquired about the hospital type, patients served, characteristics of the vaccination campaign, and the resulting vaccination rate.Results.Of 254 hospitals, 153 (60%) participated and were included in the 124 responses that were received. Most programs (64%) required that HCP either receive the vaccine or sign a declination form, and the rest were exclusively voluntary (36%); no program made vaccination a condition of employment. The median vaccination rate was 67%, and the vaccination rate was higher among hospitals that were accredited by the Joint Commission; provided acute care; served children, pregnant women, oncology patients, or intensive care unit patients; required a signed declination form; or imposed consequences for unvaccinated HCP (the most common of which was to require that a mask be worn on patient contact). Hospitals that provided free vaccine, made vaccine widely available, advertised the program extensively, required a declination form, and imposed consequences had the highest vaccination rates (median, 86%; range, 81%–91%).Conclusions.The rate of influenza vaccination of HCP remains low among the hospitals surveyed. Recommended practices may not be enough to reach 90% vaccination rates unless a signed declination requirement and consequences are implemented. Wearing a mask is a strong consequence. Demanding influenza vaccination as a condition of employment was not reported as a practice by the participating hospitals.

scholarly journals ResCaps: an improved capsule network and its application in ultrasonic image classification of thyroid papillary carcinoma

2021 ◽  
Author(s):  
Xiongzhi Ai ◽  
Jiawei Zhuang ◽  
Yonghua Wang ◽  
Pin Wan ◽  
Yu Fu
Keyword(s):  
Papillary Carcinoma ◽  
Network Model ◽  
Reliability And Validity ◽  
Thyroid Papillary Carcinoma ◽  
Data Set ◽  
Ultrasonic Image ◽  
First Choice ◽  
Thyroid Papillary ◽  
Ultrasonic Images

AbstractUltrasonic image examination is the first choice for the diagnosis of thyroid papillary carcinoma. However, there are some problems in the ultrasonic image of thyroid papillary carcinoma, such as poor definition, tissue overlap and low resolution, which make the ultrasonic image difficult to be diagnosed. Capsule network (CapsNet) can effectively address tissue overlap and other problems. This paper investigates a new network model based on capsule network, which is named as ResCaps network. ResCaps network uses residual modules and enhances the abstract expression of the model. The experimental results reveal that the characteristic classification accuracy of ResCaps3 network model for self-made data set of thyroid papillary carcinoma was $$81.06\%$$ 81.06 % . Furthermore, Fashion-MNIST data set is also tested to show the reliability and validity of ResCaps network model. Notably, the ResCaps network model not only improves the accuracy of CapsNet significantly, but also provides an effective method for the classification of lesion characteristics of thyroid papillary carcinoma ultrasonic images.

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