Effective interventions to improve the quality of critically high point-of-care glucose meter results

Using geographic rescue time contours, point-of-care strategies, and spatial care paths to prepare island communities for global warming, rising oceans, and weather disasters

OBJECTIVES

To perform geographic contour analysis of sea and land ambulance rescue times in an archipelago subject to super typhoons; to design point-of-care testing strategies for medical emergencies and weather disasters made more intense by global warming and rising oceans; and to assess needs for prehospital testing on spatial care paths that accelerate decision making, increase efficiency, improve outcomes, and enhance standards of care in island nations.

METHODS

We performed needs assessments, inspected healthcare facilities, and collected ambulance rescue times from professionals in the Bantayan Archipelago, Philippines. We mapped sea/land ambulance rescue routes and time contours. To reveal gaps, we statistically compared the fastest and slowest patient rescue times from islands/islets and barangays to the District Hospital on Bantayan Island. We developed spatial care paths (the fastest routes to care) for acute myocardial infarction, community care, and infectious diseases. We generated a compendium of prehospital diagnostic testing and integrated outcomes evidence, diagnostic needs, and public health goals to recommend point-of-care strategies that build geographic health resilience.

RESULTS

We observed limited access to COVID-19 assays, absence of blood gas/pH testing for critical care support, and spatial gaps in land and airborne rescues that worsened during inclement weather and sea swells. Mean paired differences (slowest-fastest) in ambulance rescue times to the District Hospital for both islands and barangays were significant (P < 0.0001). Spatial care path analysis showed where point-of-care cardiac troponin testing should be implemented for expedited care of acute myocardial infarction. Geospatial strengths comprised distributed primary care that can be facilitated by point-of-care testing, logical interisland transfers for which decision making and triage could be accelerated with onboard diagnostics, and healthcare networks amenable to medical advances in prehospital testing that accelerate treatment.

CONCLUSIONS

Point-of-care testing should be positioned upstream close to homes and island populations that have prolonged rescue time contours. Geospatially optimized point-of-need diagnostics and distributed prehospital testing have high potential to improve outcomes. These improvements will potentially decrease disparities in mortality among archipelago versus urban dwellers, help improve island public health, and enhance resilience for increasingly adverse and frequent climate change weather disasters that impact vulnerable coastal areas. [350 words].

Establishing quality indicators for point of care glucose testing: recommendations from the Canadian Society for Clinical Chemists Point of Care Testing and Quality Indicators Special Interest Groups

OBJECTIVES

Monitoring quality indicators (QIs) is an important part of laboratory quality assurance (QA). Here, the Canadian Society of Clinical Chemists (CSCC) Point of Care Testing (POCT) and QI Special Interest Groups describe a process for establishing and monitoring QIs for POCT glucose testing.

METHODS

Key, error prone steps in the POCT glucose testing process were collaboratively mapped out, followed by risk assessment for each step. Steps with the highest risk and ability to detect a non-conformance were chosen for follow-up. These were positive patient identification (PPID) and repeat of critically high glucose measurements. Participating sites were asked to submit aggregate data for these indicators from their site(s) for a one-month period. The PPID QI was also included as part of a national QI monitoring program for which fifty-seven sites submitted data.

RESULTS

The percentage of POCT glucose tests performed without valid PPID ranged from 0-87%. Sites without Admission-Discharge-Transfer (ADT) connectivity to POCT meters were among those with the highest percentage of POCT glucose tests performed without valid PPID. The percentage repeated critically high glucose measurements ranged from 0-50%, indicating low compliance with this recommendation. A high rate of discordance was also noted when critically high POCT glucose measurements were repeated, demonstrating the importance of repeat testing prior to insulin administration.

CONCLUSIONS

Here, a process for establishing these QIs is described, with preliminary data for two QIs chosen from this process. The findings demonstrate the importance of QIs for identification and comparative performance monitoring of non-conformances to improve POCT quality.

Performance analysis of the compact haematology analyser Sight OLO

INTRODUCTION

Sight OLO is a compact full blood count (FBC) analyser that uses digital imaging techniques and artificial intelligence to count and assess cellular components of capillary or venous blood. It provides a FBC with a 5-part white blood cell differential count. Our aim was to evaluate its performance against our standard analyser and optical microscopy.

METHODS

Comparative studies for the FBC parameters were done between the Sight OLO and the Unicel DxH800 analyser (Beckman Coulter). Evaluation comprised also repeatability studies and reproducibility studies. The flagging efficiency of the Sight OLO was assessed against the reference method (optical microscopy).

RESULTS

The SIGHT OLO showed a good comparability with the Unicel DxH800 analyser for most of the FBC parameters (r > 0.9). The biases recorded between both equipments were within the manufacturer's target specifications for all the FBC parameters. The standard deviation and coefficient of variation calculated per parameter for the precision studies were within the manufacturer's target specifications for all FBC parameters, for all the variation components tested. The five alert flags assessed showed an overall efficiency above 75%, however, high frequency of false negatives was noted for some of the flags assessed.

CONCLUSION

The evaluation of the Sight OLO showed that it can produce accurate FBC results, making it a suitable option for integration in several setups. Its innovative methodology gives it further potential to refine its capabilities.

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.