Point of Care: The Journal of Near-Patient Testing & Technology最新文献

{"title":"Empirical Framework for Point-of-Care Diagnostics Supply Chain Management for Accessibility and Sustainability of Diagnostic Services in Ghana's Primary Health Care Clinics","authors":"Desmond Kuupiel, Vitalis Bawontuo, Addai Donkoh, P. Drain, T. Mashamba-Thompson","doi":"10.1097/POC.0000000000000186","DOIUrl":"https://doi.org/10.1097/POC.0000000000000186","url":null,"abstract":"Abstract Achievement of universal health coverage may be a mirage if supply chain management challenges of point-of-care (POC) diagnostics are not addressed to ensure accessibility and sustainability of POC diagnostic services in rural primary health care (PHC) clinics. Many patients accessing health care services in rural PHC clinics are likely to be undiagnosed and treated only based on syndromic management, due to stock-outs of POC tests. This potentially may result in complications such as wrong treatment, drug resistant to some infections, increased morbidities and mortalities, and many others. Public health activities for priority diseases such as tuberculosis, malaria, and human immunodeficiency virus, as well as maternal health services, may be affected. We have proposed an empirical model framework for POC diagnostics supply chain management to ensure accessibility and sustainability of POC diagnostic service in PHC clinics in Ghana based on evidence generated from our primary studies nested in a broader doctoral study entitled “Assessing the Accessibility of Antenatal Clinic Point-of-Care Diagnostic Services in Rural Ghana.” Prior to the development of this model framework, we conducted a literature review to identify the barriers and challenges of POC diagnostic services in low- and middle-income countries. We also conducted a cross-sectional survey to assess the accessibility of pregnancy-related POC diagnostic tests for maternal health care in the Upper East Region, Ghana. Finally, we conducted a formalized audit of the supply chain management of POC diagnostic tests also in the Upper East Region to investigate causes of deficiencies.","PeriodicalId":20262,"journal":{"name":"Point of Care: The Journal of Near-Patient Testing & Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89742258","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Extrapolation of the R-T Estimation in CoaguChek International Normalized Ratio Results Below 4","authors":"C. Richter","doi":"10.1097/POC.0000000000000189","DOIUrl":"https://doi.org/10.1097/POC.0000000000000189","url":null,"abstract":"Abstract While extensive literature has documented that the CoaguChek XS device results are not an accurate reflection of a patient's international normalized ratio (INR) when the values are elevated, only 1 equation has been able to consistently correct these results in the clinical setting. Data obtained from a previous study were used to apply the R-T Estimation to INR values below 4 to assess an extrapolation of this equation to an INR of 1. The results were consistent with previous studies using the R-T Estimation and demonstrate the correlation of this equation with venipuncture results with 95% confidence within 20% difference. This may be clinically relevant as a CoaguChek XS result of 3.8 is corrected using the R-T Estimation to an INR of 3.0.","PeriodicalId":20262,"journal":{"name":"Point of Care: The Journal of Near-Patient Testing & Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91309186","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Point-of-Care Creatinine to Assist Clinical Decision Making in Suspected Sepsis in the Community","authors":"S. Simpson, J. Storrar, J. Ritchie, Khalid Alshawy, L. Ebah, S. Sinha, P. Elton, D. Darby, D. Poulikakos","doi":"10.1097/POC.0000000000000184","DOIUrl":"https://doi.org/10.1097/POC.0000000000000184","url":null,"abstract":"Abstract Guidance published from the National Institute for Health and Care Excellence in the United Kingdom for recognition and management for sepsis in acute hospital settings dictates that patients who present with suspected sepsis who are found to have acute kidney injury are high risk and should receive urgent treatment. We aimed at evaluating point-of-care (POC) creatinine (Cr) testing for diagnosis of acute kidney injury in the context of suspected sepsis out of hospital. Correlation was calculated using Pearson correlation coefficient, and agreement using Bland-Altman plot analysis was performed between StatSensor (Nova) handheld analyzer measurement in capillary samples and concurrent serum Cr measurement measured by laboratory method using Siemens Advia 2400 Jaffe from patients presenting in the emergency department and nursing home residents. Altogether 59 paired samples from 57 patients were obtained. Mean age was 76.6 years, and 29% were females. Pearson correlation between POC and serum Cr was r = 0.812, P < 0.001. Fifty-five of 59 were within the 95% limits of agreement. Three values outside the limits of agreement were observed in mean Cr values greater than 200 μmol/L. The POC Cr was higher than serum Cr in 85% of cases with an average difference between POC Cr and serum Cr of 32.5 μmol/L. An algorithm was agreed defining high-risk patients with suspected sepsis based on doubling of baseline Cr for individuals with known or suspected baseline values of less than 200 μmol/L.","PeriodicalId":20262,"journal":{"name":"Point of Care: The Journal of Near-Patient Testing & Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80517600","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Using α-Angle and A10 ROTEM Parameters for Earlier Information on Clotting Status in Surgery, Postpartum Hemorrhage, and ICU Patients","authors":"J. Toffaletti, K. Buckner","doi":"10.1097/POC.0000000000000188","DOIUrl":"https://doi.org/10.1097/POC.0000000000000188","url":null,"abstract":"Background We determined if the earlier ROTEM (rotational thromboelastometry) parameters (α-angle and amplitude at 10 minutes [A10]) could replace the later-reported maximum amplitude (maximum clot firmness [MCF]) in cardiothoracic surgery (C/T OR), postpartum hemorrhage (PPH), and intensive care unit (ICU) patients. Methods We retrospectively analyzed 300 sets of EXTEM and FIBTEM results ordered on 100 C/T OR, 100 PPH, and 100 ICU patients for correlations among the α-angle, A10, MCF, fibrinogen, and platelet counts. Results The A10EX and A10FIB correlated highly to the respective MCFEX and MCFFIB in all patient groups. The A10EX parameter correlated significantly to both fibrinogen and platelet levels, and the A10FIB correlated highly to the fibrinogen levels. Because the difference between the A10EX and the A10FIB (PLTEM) is related to platelet activity, we found that the PLTEM correlated highly to the platelet count for all PPH (r = 0.80), C/T OR (r = 0.70), and ICU patients (r = 0.66). The EXTEM α-angle (α-EX) is an excellent indicator of the A10EX, with an α-EX of 65 degrees or greater (ie, normal) giving a greater than 96% probability that the A10EX was 44 mm or greater and an α-EX value below 65 mm giving an 86% probability that the A10EX was less than 44 mm. Conclusions The A10EX and A10FIB could replace the MCF results in all patient groups, and the α-EX was an early indicator of the A10EX. Finally, in a separate group of 62 comparisons, the α-FIB showed promise as an early indicator of the A10FIB and the fibrinogen levels.","PeriodicalId":20262,"journal":{"name":"Point of Care: The Journal of Near-Patient Testing & Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79605410","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Clinical Performance and Utility of Point-of-Care Lactate Technology in Patient Care Pathways","authors":"A. Malic, E. Ntrivalas, J. Dubois","doi":"10.1097/POC.0000000000000185","DOIUrl":"https://doi.org/10.1097/POC.0000000000000185","url":null,"abstract":"Abstract Lactate is a commonly evaluated analyte in acutely ill patients. It is used as a prognostic, diagnostic, and monitoring tool in a variety of clinical conditions including sepsis, trauma, infectious diseases, and perinatal conditions. Elevated lactate levels, above specific thresholds for each condition, are considered critical values necessitating intervention. In certain of these cases, a fast lactate result by point-of-care (POC) devices is crucial in assisting with the medical management of the underlying condition. It is becoming increasingly evident that POC technologies are part of the transformation that is being observed in health care. Rapid results of certain analytes at the point of care enable clinicians to make immediate treatment decisions without having to wait for results from centralized laboratories. Lactate, as a critical marker, is a perfect candidate for POC testing and has been utilized as such in a variety of clinical settings, including prehospital and emergency medical services, emergency departments, and intensive care units. The StatStrip Lactate Hospital Meter System (Nova Biomedical, Waltham, Mass) is a POC device that combines a precalibrated, single-test biosensor with a handheld meter. It has been used extensively in various clinical settings to aid in the early identification of elevated lactate levels. StatStrip Lactate utilizes whole-blood measurement technology to provide a lactate result that is equivalent to central laboratory plasma lactate testing. Its rapid results have been demonstrated as useful in a number of studies. This mini review will present the clinical pathways in which lactate is used and describe the clinical utility of StatStrip Lactate in these pathways.","PeriodicalId":20262,"journal":{"name":"Point of Care: The Journal of Near-Patient Testing & Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86142498","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Invited Product Profile – GeneXpert Xpress System for Respiratory Testing","authors":"E. Baron, D. Persing","doi":"10.1097/POC.0000000000000187","DOIUrl":"https://doi.org/10.1097/POC.0000000000000187","url":null,"abstract":"Abstract Viral and bacterial respiratory infections represent a significant source of morbidity and mortality in the United States. Lateral flow immunoassays, frequently used to detect influenza, respiratory syncytial virus (RSV), and streptococcus group A infections, yield lower sensitivity (50%–70%) than testing other methods and often require culture confirmation for patients who test negative. The Clinical Laboratory Improvement Amendments–waived GeneXpert Xpress platform offers point-of-care influenza, RSV, and streptococcus group A nucleic acid amplification testing in a variety of health care settings. The system requires minimal training, and the user interface provides straightforward step-by-step video instructions that illustrate each phase of the testing procedure. The universal cartridge design allows simple sample loading that minimizes hands-on time and risk of contamination as well as the need for additional staff training. Test results generated by the Xpress System have high sensitivity and specificity and are available in 18 to 30 minutes. Together these features make the GeneXpert Xpress an attractive option to provide simple, rapid, and effective point-of-care testing to identify influenza, RSV, and streptococcus group A infections to better inform patient management and treatment decisions.","PeriodicalId":20262,"journal":{"name":"Point of Care: The Journal of Near-Patient Testing & Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"91391374","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Evaluation of the i-STAT Alinity Point-of-Care Analyzer","authors":"Mee-Yin Lee, Sian-Foong Lim, L. Lam","doi":"10.1097/POC.0000000000000190","DOIUrl":"https://doi.org/10.1097/POC.0000000000000190","url":null,"abstract":"Objectives The objective of this study was to evaluate the analytical performance of CG4+ and CHEM8+ cartridges on the i-STAT Alinity analyzer prior to use in patient testing. We also evaluated the ease of use, design, and safety features to determine its suitability for use by the clinicians in our hospital. Methods The Abbott i-STAT System Performance Verification Protocol was observed for the imprecision study and was performed over the course of 2 days using 2 levels of control material (Abbott i-STAT TriControl Level 1 and Level 3). The CLSI-EP6-A guideline was used to verify the assay reportable range performance using 5 levels of linearity material (Abbott i-Stat TriControl Calibration Verification Set). The method comparison study was performed using up to 60 leftover anonymized heparinized whole-blood samples and serum samples against existing laboratory instruments (Siemens Rapidpoint 500, Abbott Architect C16000, and Sysmex XN9000). Results Precision was good (coefficient of variation <2%) for electrolytes, glucose, lactate, and pH, and satisfactory (coefficient of variation <5.2%) for blood gases, urea, creatinine, and hematocrit. Linearity concentrations spanning the analytical measuring ranges were demonstrated for all analytes. Method comparison studies revealed that agreement between the i-STAT Alinity analyzer and the central laboratory analyzers was good and clinically acceptable. Conclusions The i-STAT Alinity analyzer has good analytical performance, and we established the analyzer meets our safety and regulatory requirements and therefore suitable for use in our hospital as a point-of-care testing device.","PeriodicalId":20262,"journal":{"name":"Point of Care: The Journal of Near-Patient Testing & Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"86999620","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Invited Product Profile: Increasing Workflow Productivity With POCcelerator Data Management System","authors":"K. Nissen, Connie Mardis, Daniel C Gundler","doi":"10.1097/POC.0000000000000182","DOIUrl":"https://doi.org/10.1097/POC.0000000000000182","url":null,"abstract":"A s the health care industry moves closer to the patient's side, point-of-care testing (POCT) is becoming more relevant than ever. With faster and easier access to results, health care providers can reduce lengths of stay and increase patient satisfaction by avoiding extended wait times for central laboratory results. With this new positive trend come new challenges, how do point-of-care (POC) coordinators keep hundreds of devices up and running while managing training and certification and enabling secure access for thousands of operators? How do health care systems enforce quality control (QC) so that compliance and accreditation requirements are being satisfied?","PeriodicalId":20262,"journal":{"name":"Point of Care: The Journal of Near-Patient Testing & Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84329028","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Diabetic Retinal Examinations in Frontline Care Using RetinaVue Care Delivery Model","authors":"K. Stebbins","doi":"10.1097/POC.0000000000000183","DOIUrl":"https://doi.org/10.1097/POC.0000000000000183","url":null,"abstract":"P oint-of-care testing is now possible in many areas of clinical medicine. The ability to move testing closer to the patient has been possible for three decades with continuing advances in technology that have steadily produced more sophisticated devices. Diabetic retinopathy (DR) is the leading cause of blindness among working-age adults in the United States. Diabetic retinopathy is caused by high blood glucose levels that damage the small vessels in the retina of the eye—over time resulting in bleeding, fluid leakage, and swelling. There are typically few or no symptoms in the early stages. Once vision loss begins to occur, the disease is often too advanced to treat effectively. Because of the lack of early symptoms, early detection of DR is critical and can prevent permanent vision loss in up to 95% of individuals. Patients can receive treatment via laser therapy or injections to preserve useful vision and stop the advancement of retinal damage. The American Diabetes Association recommends annual eye examinations starting 10 years after diagnosis for type 1 diabetics and starting at diagnosis for type 2 diabetics. Despite the awareness of the risks associated with DR, as many as 50% of patients with diabetes do not receive routine retinal examinations. There are several barriers to patients receiving receipt of an annual diabetic retinal examination, which is traditionally performed via pupil dilation at an ophthalmologist's office. These barriers include existing patient work flow, patient compliance, lack of insurance and health care access, low health literacy, cultural and language barriers, patient logistics, time, and cost for specialist visits. However, capturing patients during routine primary care office visits can achieve up to 90% documented compliance in 12 months. These frontline care-based programs typically use telemedicine to capture retinal images in the office and send the images for remote interpretation. Then, only patients with referable levels of DR are required to follow up with an eye specialist. The Welch Allyn RetinaVue care delivery model is designed to help primary healthcare providers preserve vision in patients with diabetes through early detection of DR. RetinaVue uses specialized cameras (nonmydriatic) that can capture retinal images on patients livingwith diabetes. The images are sent throughHIPAA-compliant RetinaVue Network software to an ophthalmologist for interpretation. The ophthalmologist generates a report, including any disease found and a management plan for the patient, which gets returned to the originating practice. This turnkey (point-of-care testing) solution allows frontline care providers to evaluate for and manage DR directly through their clinic.","PeriodicalId":20262,"journal":{"name":"Point of Care: The Journal of Near-Patient Testing & Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"76181301","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"The Use of Patient Self-Testing in Low- and Middle-Income Countries: A Systematic Scoping Review","authors":"Sbongile Joyce Makhudu, Desmond Kuupiel, Nonjabulo Gwala, T. Mashamba-Thompson","doi":"10.1097/POC.0000000000000179","DOIUrl":"https://doi.org/10.1097/POC.0000000000000179","url":null,"abstract":"Background Improving access to health through use of innovative health technologies such as points-of-care testing is 1 global health priority. Patient self-testing (PST) is one of the point-of-care testing strategies that was shown to have an ability to improve access to diagnostic testing, autonomy and allow access to health care for hard-to-reach populations in resource-limited settings. However, the level of evidence on the use of PST for diagnosis and management of diseases in low- and middle-income countries (LMICs) is unknown. We mapped literature on evidence of the use of PST in LMICs. Methods Data were sourced from the following databases: PubMed; EBSCOhost (Medline, health source: Nursing), WEB of Science; Science Direct; and Google Scholar. Eligibility criteria for this study included: studies that focused on PST, reported on evidence on use of PST, conducted in LMICs, comparing PST with facility-based testing. Thematic analysis was performed to identify the patterns of use of PST. The mixed method quality appraisal tool version 2011 was used to assess the quality of the included primary studies. Results Eight studies met the inclusion criteria. Studies included populations from the following LMICs: Kenya; South Africa; Uganda; Bulgaria; and Malawi. Of the 18,816 total participants in all included primary studies, 57% were males. Overall, 7 (87.5%) of the 8 included studies reported on human immunodeficiency virus (HIV) self-testing using the following: oral fluid HIV self-test (HIVST), OraQuick in Home Rapid HIV-1/2 Antibody Test, OraQuick O-HIVST, oral fluid, and Fingerstick HIV self-tests. One (12.5%) of the 8 included studies reported on colorectal carcinoma using rapid immunochemical fecal occult blood tests. Although the findings of this study shows high usage of HIVST, it also demonstrates poor level of use of PST for other communicable and noncommunicable diseases in LMICs. We extracted the following themes; use of PST, feasibility of PST, and linkage to care from the included studies. Of the 8 included studies, 5 scored the highest quality (76–100%) from the methodological quality assessment. Conclusions The findings of the review revealed a high level of research evidence on the use of HIV self-testing compared to other communicable diseases and noncommunicable diseases in LMICs. Increased implementation of PST for communicable diseases is recommended, particularly for high-risk and hard-to-reach populations.","PeriodicalId":20262,"journal":{"name":"Point of Care: The Journal of Near-Patient Testing & Technology","volume":null,"pages":null},"PeriodicalIF":0.0,"publicationDate":"2019-03-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"84868881","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}