An Ambulance Service evaluation of Quality Control Measures based on patients‘ perception in Qatar

Introduction: In response to anticipated challenges with urgent and emergency healthcare delivery during the early part of the COVID-19 pandemic, Yorkshire Ambulance Service NHS Trust introduced video technology to supplement remote triage and ‘hear and treat’ consultations as a pilot project in the EOC. We conducted a service evaluation with the aim of investigating patient and staff acceptability of video triage, and the safety of the decision-making process.Methods: This service evaluation utilised a mixture of routine and bespoke data collection. We sent postal surveys to patients who were recipients of a video triage, and clinicians who were involved in the video triage pilot logged calls they attempted and undertook.Results: Between 27 March and 25 August 2020, clinicians documented 1073 triage calls. A successful video triage call was achieved in 641 (59.7%) cases. Clinical staff reported that video triage improved clinical assessment and decision making compared to telephone alone, and found the technology accessible for patients. Patients who received a video triage call and responded to the survey (40/201, 19.9%) were also satisfied with the technology and with the care they received. Callers receiving video triage that ended with a disposition of ‘hear and treat’ had a lower rate of re-contacting the service within 24 hours compared to callers that received clinical hub telephone triage alone (16/212, 7.5% vs. 2508/14349, 17.5% respectively).Conclusion: In this single NHS Ambulance Trust evaluation, the use of video triage for low-acuity calls appeared to be safe, with low rates of re-contact and high levels of patient and clinician satisfaction compared to standard telephone triage. However, video triage is not always appropriate for or acceptable to patients and technical issues were not uncommon.

Download Full-text

Microbiological Water Methods: Quality Control Measures for Federal Clean Water Act and Safe Drinking Water Act Regulatory Compliance

Journal of AOAC International ◽

10.5740/jaoacint.13-262 ◽

2014 ◽

Vol 97 (2) ◽

pp. 567-572 ◽

Cited By ~ 4

Author(s):

Patsy Root ◽

Margo Hunt ◽

Karla Fjeld ◽

Laurie Kundrat

Keyword(s):

Quality Control ◽

Drinking Water ◽

Clean Water Act ◽

Regulatory Compliance ◽

Control Measures ◽

Clean Water ◽

Safe Drinking Water ◽

Safe Drinking Water Act ◽

Specificity And Sensitivity ◽

Microbiological Methods

Abstract Quality assurance (QA) and quality control (QC) data are required in order to have confidence in the results from analytical tests and the equipment used to produce those results. Some AOAC water methods include specific QA/QC procedures, frequencies, and acceptance criteria, but these are considered to be the minimum controls needed to perform a microbiological method successfully. Some regulatory programs, such as those at Code of Federal Regulations (CFR), Title 40, Part 136.7 for chemistry methods, require additional QA/QC measures beyond those listed in the method, which can also apply to microbiological methods. Essential QA/QC measures include sterility checks, reagent specificity and sensitivity checks, assessment of each analyst's capabilities, analysis of blind check samples, and evaluation of the presence of laboratory contamination and instrument calibration and checks. The details of these procedures, their performance frequency, and expected results are set out in this report as they apply to microbiological methods. The specific regulatory requirements of CFR Title 40 Part 136.7 for the Clean Water Act, the laboratory certification requirements of CFR Title 40 Part 141 for the Safe Drinking Water Act, and the International Organization for Standardization 17025 accreditation requirements under The NELAC Institute are also discussed.

Download Full-text

Standardized quality control workflow to evaluate the reproducibility and differentiation potential of human iPSCs into neurons

10.1101/2021.01.13.426620 ◽

2021 ◽

Cited By ~ 1

Author(s):

Carol X.-Q. Chen ◽

Narges Abdian ◽

Gilles Maussion ◽

Rhalena A. Thomas ◽

Iveta Demirova ◽

...

Keyword(s):

Stem Cells ◽

Quality Control ◽

Cortical Neurons ◽

Genomic Stability ◽

Control Measures ◽

List Type ◽

Ipsc Line ◽

Differentiation Potential ◽

Germ Layers ◽

Human Ipscs

AbstractInduced pluripotent stem cells (iPSCs) derived from human somatic cells have created new opportunities to generate disease-relevant cells. Thus, as the use of patient-derived stem cells has become more widespread, having a workflow to monitor each line is critical. This ensures iPSCs pass a suite of quality control measures, promoting reproducibility across experiments and between labs. With this in mind, we established a four-step workflow to assess our newly generated iPSCs for variations and reproducibility relative to each other and iPSCs obtained from external sources. Our benchmarks for evaluating iPSCs include examining iPSC morphology and proliferation in two different media conditions (mTeSR1 and Essential 8) and evaluating their ability to differentiate into each of the three germ layers, with a particular focus on neurons. Genomic stability in the human iPSCs was analyzed by G-band karyotyping and a qPCR-based stability test, and cell-line identity authenticated by Short Tandem Repeat (STR) analysis. Using standardized dual SMAD inhibition methods, all iPSC lines gave rise to neural progenitors that could subsequently be differentiated into cortical neurons. Neural differentiation was analyzed qualitatively by immunocytochemistry and quantitatively by q-PCR for progenitor, neuronal, cortical and glial markers. Taken together, we present a standardized quality control workflow to evaluate variability and reproducibility across and between iPSCs.HighlightsValidation of culture conditions is critical in the expansion and maintenance of an iPSC line.Characterization of pluripotency and genomic stability ensures each line is free of defects at the DNA level, while maintaining its ability to be directed into any of the three germ layers.Forebrain cortical neurons can be generated from all iPSC line tested; however, the morphology and expression pattern of these neurons can vary from line to line.

Download Full-text