Comparative performance of two point-of-care analysers for lipid testing

The aim of this study was to compare the analytical performance of the Cholestech LDX and CardioChek PA lipid point-of-care devices to a CDC-certified laboratory. Inter-assay imprecision (n=10) for blood samples from 2 patients with different lipid profiles was 3.0% for total cholesterol, 2.6% for triglyceride, 5.2% for HDL cholesterol and 6.2% for calculated LDL cholesterol on the Cholestech, and 4.4% for total cholesterol, 4.8% for triglyceride, 7.0% for HDL cholesterol and 7.4% for calculated LDL cholesterol on the Cardiochek. In a patient comparison study (n=100), correlation coefficients (r) between the POCT and laboratory methods were greater than 0.90 for all tests for the Cholestech and greater than 0.84 for all tests for the Cardiochek. The mean difference (bias) between the results obtained on the Cholestech LDX and the laboratory method was not statistically significant; however the mean difference between the CardioChek and the laboratory method was statistically significant for total, HDL and LDL cholesterol (one way analysis of variance with Scheffe post-hoc test). The Cholestech LDX met the NCEP goal for total error for all analytes except LDL cholesterol. The CardioChek PA system met the NCEP total error goal for triglyceride but not the other lipid analytes. We conclude that the Cholestech LDX device is a suitable POCT device for cardiovascular risk assessment in the primary care setting, while the Cardiochek device requires more study and refinement

Evaluation of a training program for device operators in the Australian Government's Point of Care Testing in General Practice Trial: issues and implications for rural and remote practices

From September 2005 to February 2007 the Australian Government funded the Point of Care Testing (PoCT) in General Practice Trial, a multi-centre, cluster randomised controlled trial to determine the safety, clinical effectiveness, cost-effectiveness and satisfaction of PoCT in General Practice. In total, 53 practices (23 control and 30 intervention) based in urban, rural or remote locations across three states (South Australia [SA], New South Wales [NSW] and Victoria [VIC]) participated in the Trial. Control practices had pathology testing performed by their local laboratory, while intervention practices conducted pathology testing by PoCT. In total, 4968 patients (1958 control and 3010 intervention) participated in the Trial. The point-of-care (PoC) tests performed by intervention practices were: haemoglobin A1c (HbA1c) and urine albumin:creatinine ratio (ACR) on patients with diabetes, total cholesterol, triglyceride and high density lipoprotein (HDL) cholesterol on patients with hyperlipidaemia, and international normalised ratio (INR) on patients on anticoagulant therapy. Three PoCT devices measured these tests: the Siemens DCA 2000 (Siemens HealthCare Diagnostics, Melbourne, VIC, Australia) for HbA1c and urine ACR; Point of Care Diagnostics Cholestech LDX analyser (Point of Care Diagnostics; Sydney, NSW, Australia) for lipids; and the Roche CoaguChek S (Roche Diagnostics; Sydney, NSW, Australia) for INR. Point-of-care testing in the General Practice Trial was underpinned by a quality management framework which included an on-going training and competency program for PoCT device operators. This article describes the design, implementation and results of the training and competency program

Results from 15 years of quality surveillance for a National Indigenous Point-of-Care Testing Program for diabetes

© 2017 The Canadian Society of Clinical Chemists. Published by Elsevier Inc. This manuscript version is made available under the CC-BY-NC-ND 4.0 license http://creativecommons.org/licenses/by-nc-nd/4.0/ This author accepted manuscript is made available following 12 month embargo from date of publication (July 2017) in accordance with the publisher’s archiving policyIntroduction Diabetes is a major health problem for Australia's Aboriginal and Torres Strait Islander peoples. Point-of-care testing for haemoglobin A1c (HbA1c) has been the cornerstone of a long-standing program (QAAMS) to manage glycaemic control in Indigenous people with diabetes and recently, to diagnose diabetes. Methods The QAAMS quality management framework includes monthly testing of quality control (QC) and external quality assurance (EQA) samples. Key performance indicators of quality include imprecision (coefficient of variation [CV%]) and percentage acceptable results. This paper reports on the past 15 years of quality testing in QAAMS and examines the performance of HbA1c POC testing at the 6.5% cut-off recommended for diagnosis. Results The total number of HbA1c EQA results submitted from 2002 to 2016 was 29,093. The median imprecision for EQA testing by QAAMS device operators averaged 2.81% (SD 0.50; range 2.2 to 3.9%) from 2002 to 2016 and 2.44% (SD 0.22; range 2.2 to 2.9%) from 2009 to 2016. No significant difference was observed between the median imprecision achieved in QAAMS and by Australasian laboratories from 2002 to 2016 (p = 0.05; two-tailed paired t-test) and from 2009 to 2016 (p = 0.17; two-tailed paired t-test). For QC testing from 2009 to 2016, imprecision averaged 2.5% and 3.0% for the two levels of QC tested. Percentage acceptable results averaged 90% for QA testing from 2002 to 2016 and 96% for QC testing from 2009 to 2016. The DCA Vantage was able to measure a patient and an EQA sample with an HbA1c value close to 6.5% both accurately and precisely. Conclusion HbA1c POC testing in QAAMS has remained analytically sound, matched the quality achieved by Australasian laboratories and met profession-derived analytical goals for 15 years

Assessment of the Nova StatSensor whole blood point-of-care creatinine analyser for the measurement of kidney function in screening for chronic kidney disease

Point-of-care testing for creatinine using a fingerprick sample and resultant estimated glomerular filtration rate has potential for screening for chronic kidney disease in community settings. This study assessed the applicability of the Nova StatSensor creatinine analyzer for this purpose. Fingerprick samples from 100 patients (63 renal, 37 healthy volunteers; range 46–962 mmol/L) were assayed using two StatSensor analyzers. Lithium heparin venous plasma samples collected simultaneously were assayed in duplicate using the isotope dilution mass spectrometryaligned Roche Creatinine Plus enzymatic assay on a Hitachi Modular P unit. Method comparison statistics and the ability of the StatSensor to correctly categorise estimated glomerular filtration rate above or below 60 mL/min were calculated pre- and post-alignment with the laboratory method. Isotope dilution mass spectrometry alignment of the StatSensor will identify most patients with estimated glomerular filtration rate -60 mL/min, but there will be many falsely low estimated glomerular filtration rate results that require laboratory validation. Creatinine results need improvement

Proceedings of the 3rd Biennial Conference of the Society for Implementation Research Collaboration (SIRC) 2015: advancing efficient methodologies through community partnerships and team science

It is well documented that the majority of adults, children and families in need of evidence-based behavioral health interventionsi do not receive them [1, 2] and that few robust empirically supported methods for implementing evidence-based practices (EBPs) exist. The Society for Implementation Research Collaboration (SIRC) represents a burgeoning effort to advance the innovation and rigor of implementation research and is uniquely focused on bringing together researchers and stakeholders committed to evaluating the implementation of complex evidence-based behavioral health interventions. Through its diverse activities and membership, SIRC aims to foster the promise of implementation research to better serve the behavioral health needs of the population by identifying rigorous, relevant, and efficient strategies that successfully transfer scientific evidence to clinical knowledge for use in real world settings [3]. SIRC began as a National Institute of Mental Health (NIMH)-funded conference series in 2010 (previously titled the “Seattle Implementation Research Conference”; $150,000 USD for 3 conferences in 2011, 2013, and 2015) with the recognition that there were multiple researchers and stakeholdersi working in parallel on innovative implementation science projects in behavioral health, but that formal channels for communicating and collaborating with one another were relatively unavailable. There was a significant need for a forum within which implementation researchers and stakeholders could learn from one another, refine approaches to science and practice, and develop an implementation research agenda using common measures, methods, and research principles to improve both the frequency and quality with which behavioral health treatment implementation is evaluated. SIRC’s membership growth is a testament to this identified need with more than 1000 members from 2011 to the present.ii SIRC’s primary objectives are to: (1) foster communication and collaboration across diverse groups, including implementation researchers, intermediariesi, as well as community stakeholders (SIRC uses the term “EBP champions” for these groups) – and to do so across multiple career levels (e.g., students, early career faculty, established investigators); and (2) enhance and disseminate rigorous measures and methodologies for implementing EBPs and evaluating EBP implementation efforts. These objectives are well aligned with Glasgow and colleagues’ [4] five core tenets deemed critical for advancing implementation science: collaboration, efficiency and speed, rigor and relevance, improved capacity, and cumulative knowledge. SIRC advances these objectives and tenets through in-person conferences, which bring together multidisciplinary implementation researchers and those implementing evidence-based behavioral health interventions in the community to share their work and create professional connections and collaborations