Utilizing connectivity and data management system for effective quality management and regulatory compliance in point of care testing

Pitfalls in the diagnosis and management of acid-base disorders in humans: a laboratory medicine perspective

Diagnostic errors affect patient management, and as blood gas analysis is mainly performed without the laboratory, users must be aware of the potential pitfalls. The aim was to provide a summary of common issues users should be aware of.A narrative review was performed using online databases such as PubMed, Google Scholar and reference lists of identified papers. Language was limited to English.Errors can be pre-analytical, analytical or post-analytical. Samples should be analysed within 15 min and kept at room temperature and taken at least 15-30 min after changes to inspired oxygen and ventilator settings, for accurate oxygen measurement. Plastic syringes are more oxygen permeable if chilled. Currently, analysers run arterial, venous, capillary and intraosseous samples, but variations in reference intervals may not be appreciated or reported. Analytical issues can arise from interference secondary to drugs, such as spurious hyperchloraemia with salicylate and hyperlactataemia with ethylene glycol, or pathology, such as spurious hypoxaemia with leucocytosis and alkalosis in hypoalbuminaemia. Interpretation is complicated by result adjustment, for example, temperature (alpha-stat adjustment may overestimate partial pressure of carbon dioxide (pCO2) in hypothermia, for example), and inappropriate reference intervals, for example, in pregnancy bicarbonate, and pCO2 ranges should be lowered.Lack of appreciation for patient-specific and circumstance-specific reference intervals, including extremes of age and altitude, and transformation of measurements to standard conditions can lead to inappropriate assumptions. It is vitally important for users to optimise specimen collection, appreciate the analytical methods and understand when reference intervals are applicable to their specimen type, clinical question or patient.

We have reached single-visit testing, diagnosis, and treatment for hepatitis C infection, now what?

INTRODUCTION

Progress toward hepatitis C virus (HCV) elimination is impeded by low testing and treatment due to the current diagnostic pathway requiring multiple visits leading to loss to follow-up. Point-of-care testing technologies capable of detecting current HCV infection in one hour are a 'game-changer.' These tests enable diagnosis and treatment in a single visit, overcoming the barrier of multiple visits that frequently leads to loss to follow-up. Combining point-of-care HCV antibody and RNA tests should improve cost-effectiveness, patient/provider acceptability, and testing efficiency. However, implementing HCV point-of-care testing programs at scale requires multiple considerations.

AREAS COVERED

This commentary explores the need for point-of-care HCV tests, diagnostic strategies to improve HCV testing, key considerations for implementing point-of-care HCV testing programs, and remaining challenges for point-of-care testing (including operator training, quality management, connectivity and reporting systems, regulatory approval processes, and the need for more efficient tests).

EXPERT OPINION

It is exciting that single-visit testing, diagnosis, and treatment for HCV infection have been achieved. Innovations afforded through COVID-19 should facilitate the accelerated development of low-cost, rapid, and accurate tests to improve HCV testing. The next challenge will be to address barriers and facilitators for implementing point-of-care testing to deliver them at scale.

Practical Challenges of Point-of-Care Testing

The practical challenges of point-of-care testing (POCT) include analytical performance and quality compared with testing performed in a central laboratory and higher cost per test compared with laboratory-based tests. These challenges can be addressed with new test technology, consensus, and practice guidelines for the use of POCT, instituting a quality management system and data connectivity in the POCT setting, and studies that demonstrate evidence of clinical and economic value of POCT.

Quality Assurance for Hepatitis C Virus Point-of-Care Diagnostics in Sub-Saharan Africa

As part of a multinational study to evaluate the Bioline Hepatitis C virus (HCV) point-of-care (POC) testing in sub-Saharan Africa (SSA), this narrative review summarises regulatory standards and quality indicators for validating and approving HCV clinical diagnostics. In addition, this review also provides a summary of their diagnostic evaluations using the REASSURED criteria as the benchmark and its implications on the WHO HCV elimination goals 2030.

Health information exchange in relation to point-of-care testing in home care: Issues in Japan

BACKGROUND

Laboratory tests, especially point-of-care testing (POCT), and related health information exchange (HIE) are necessary for patient management in the home care setting, where clinic-hospital cooperation and interprofessional collaboration are important.

METHODS

We raised the issues ahead of HIE in relation to POCT in home care in Japan, including issues in electronic medical record use, localized interprofessional collaboration networks with information and communication technology, personal health record use and open connectivity.

RESULTS

HIE system may depend on the initiatives of expert communities with non-expert partnership, as well as national healthcare policies.

CONCLUSION

We promote future challenges in this growing area.

Impact of Interfacing Near Point of Care Clinical Chemistry and Hematology Analyzers at Urgent Care Clinics at an Academic Health System

Background

Point-of-care (POC) testing equipment is commonly utilized in outpatient clinics. Our institution recently interfaced POC chemistry and hematology devices at two outpatient clinics via middleware software to the central electronic health record (EHR), facilitating a comparison of manual transcription versus automatic reporting via interface. This allowed for estimation of serious/obvious error rates and manual time savings. Additional goals were to develop autoverification rules and analyze broad trends of results in response to common clinician complaints on the POC testing.

Material and Methods

Data were obtained from two satellite clinic sites providing both primary and urgent care within an academic health system. Interface of devices was accomplished via Instrument Manager middleware software and occurred approximately halfway through the 38 month retrospective timeframe. Laboratory results for three testing POC chemistry and hematology panels were extracted with EHR tools.

Results

Nearly 100,000 lab values were analyzed and revealed that the rate of laboratory values outside reference range was essentially unchanged before and after interface of POC testing devices (2.0–2.1%). Serious/obvious errors, while rare overall, declined significantly, with none recorded after the interface with autoverified results and only three related to manual edits of results that failed autoverification. Fewer duplicated test results were identified after the interface, most notably with the hematology testing. Anion gap values of less than zero were observed more frequently in POC device tests when compared to central laboratory tests and are attributed to a higher proportion of Cl values greater than 110 mEq/L and CO₂ values greater than 30 mEq/L with POC results. Time savings of eliminating manual data entry were calculated to be 21.6 employee hours per month.

Conclusions

In a switch from manual entry to automatic interface for POC chemistry and hematology, the most notable changes were reduction of serious/obvious errors and duplicate results. Significant time employee time savings highlight an additional benefit of instrument interfacing. Lastly, a difference between POC and central laboratory instruments is a higher rate of high Cl and CO₂ values relative to the central laboratory.

Connectivity Strategies in Managing a POCT Service

Point of Care Testing is increasingly being used for diagnosis and management of various disease states. Management of different Point of Care instruments at multiple sites can be challenging, particularly when such instruments are operated by non technical staff. Connectivity is critical for optimal management of these services which are intimately linked to operator training and competency and are important in minimising harm to the patient by reducing analytical errors. Furthermore, connectivity improves turn around time leading to faster decision making by physicians. Recent advances in technology such as 5G and artificial intelligence are likely to lead to a greater focus on personalized care as a result of big data analysis and development of algorithms.

Six Sigma performance of quality indicators in total testing process of point-of-care glucose measurement: A two-year review

Objectives

The error rate in the total testing process (TTP) of point-of-care (POC) glucose measurement remains high although a total quality management system has been applied. Quality indicators (QIs) in the TTP of glucose meter were established via risk assessment. Their two-year Six Sigma values were reviewed for quality improvement.

Design

The TTP of POC glucose measurement was mapped to identify risks in key steps. The risks were assessed for their frequency and severity of impact on patient safety. Whenever possible, measurable data from the data management system and other sources was collected to establish QIs for risk monitoring. Average Six Sigma value of each QI in the last two years was calculated for acceptance and for determining corrective action.

Results

29 risks were identified in eight key steps of the TTP. Eight QIs were established for monitoring six risks and three QIs for two accepted risks were established for improving operator testing skill. The QIs had a good coverage to key steps. Two, five and four QIs showed Six Sigma values <3, 3-4 and >4 respectively. Six Sigma values of two QIs related to quality control (QC) testing were improved by using meters with accurate QC sample loading.

Conclusions

The establishment of QIs for glucose measurement by risk assessment with measurable data from the data management system and on Six sigma scale was effective, efficient, and manageable. Most of QIs’ Six Sigma values were between 3 and 5, which could be improved by using upgraded meters.

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The total testing process of POC glucose measurement was assessed to identify all risks that might impact patient safety.

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QIs that established from data management system monitored the risks related to all of the meters and operators.

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Six Sigma values of QIs provided a straightforward acceptance in their performance evaluation.

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Most of the Six Sigma values of QIs for glucose meters were between 3 and 5 under current total quality management system.