Perceived feasibility, facilitators and barriers to incorporating point-of-care testing for SARS-CoV-2 into emergency medical services by ambulance service staff: a survey-based approach
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Abstract
Objectives
This body of work aimed to elicit ambulance service staff’s perceptions on the barriers
and facilitators to adoption, and clinical utility of incorporating rapid SARS-CoV-2
testing during ambulance assessments.
Design
A mixed-methods survey-based project using a framework analysis method to organise
qualitative data.
Setting
Emergency and non-emergency care ambulatory services in the UK were approached to
take part.
Participants
Current, practising members of the UK ambulance service (paramedics, technicians,
assistants and other staff) were included in this body of work.
Results
Survey 1: 226 responses were collected between 3 December 2020 and 11 January 2021,
179 (79.2%) of which were completed in full. While the majority of respondents indicated
that an ambulance-based testing strategy was feasible in concept (143/190, 75.3%),
major barriers to adoption were noted. Many open-ended responses cited concerns regarding
misuse of the service by the general public and other healthcare services, timing
and conveyance issues, and increased workloads, alongside training and safety concerns.
Survey 2: 26 responses were received between 8 February 2021 and 22 February 2021
to this follow-up survey. Survey 2 revealed conveyance decision-making, and risk stratification
to be the most frequently prioritised use cases among ambulance service staff. Optimal
test characteristics for clinical adoption according to respondents were; accuracy
(above 90% sensitivity and specificity), rapidity (<30 min time to results) and ease
of sample acquisition.
Conclusions
The majority of commercially available lateral flow devices are unlikely to be supported
by paramedics as their duty of care requires both rapid and accurate results that
can inform clinical decision making in an emergency situation. Further investigation
is needed to define acceptable test characteristics and criteria required for ambulance
service staff to be confident and supportive of deployment of a SARS-CoV-2 test in
an emergency care setting.
Standards for reporting exist for many types of quantitative research, but currently none exist for the broad spectrum of qualitative research. The purpose of the present study was to formulate and define standards for reporting qualitative research while preserving the requisite flexibility to accommodate various paradigms, approaches, and methods.
Analogous to checklists of recommendations such as the CONSORT statement (for randomized trials), or the QUORUM statement (for systematic reviews), which are designed to ensure the quality of reports in the medical literature, a checklist of recommendations for authors is being presented by the Journal of Medical Internet Research (JMIR) in an effort to ensure complete descriptions of Web-based surveys. Papers on Web-based surveys reported according to the CHERRIES statement will give readers a better understanding of the sample (self-)selection and its possible differences from a “representative” sample. It is hoped that author adherence to the checklist will increase the usefulness of such reports.
Background Severe acute respiratory syndrome coronavirus 2 (SARS‐CoV‐2) and the resulting COVID‐19 pandemic present important diagnostic challenges. Several diagnostic strategies are available to identify or rule out current infection, identify people in need of care escalation, or to test for past infection and immune response. Point‐of‐care antigen and molecular tests to detect current SARS‐CoV‐2 infection have the potential to allow earlier detection and isolation of confirmed cases compared to laboratory‐based diagnostic methods, with the aim of reducing household and community transmission. Objectives To assess the diagnostic accuracy of point‐of‐care antigen and molecular‐based tests to determine if a person presenting in the community or in primary or secondary care has current SARS‐CoV‐2 infection. Search methods On 25 May 2020 we undertook electronic searches in the Cochrane COVID‐19 Study Register and the COVID‐19 Living Evidence Database from the University of Bern, which is updated daily with published articles from PubMed and Embase and with preprints from medRxiv and bioRxiv. In addition, we checked repositories of COVID‐19 publications. We did not apply any language restrictions. Selection criteria We included studies of people with suspected current SARS‐CoV‐2 infection, known to have, or not to have SARS‐CoV‐2 infection, or where tests were used to screen for infection. We included test accuracy studies of any design that evaluated antigen or molecular tests suitable for a point‐of‐care setting (minimal equipment, sample preparation, and biosafety requirements, with results available within two hours of sample collection). We included all reference standards to define the presence or absence of SARS‐CoV‐2 (including reverse transcription polymerase chain reaction (RT‐PCR) tests and established clinical diagnostic criteria). Data collection and analysis Two review authors independently screened studies and resolved any disagreements by discussion with a third review author. One review author independently extracted study characteristics, which were checked by a second review author. Two review authors independently extracted 2x2 contingency table data and assessed risk of bias and applicability of the studies using the QUADAS‐2 tool. We present sensitivity and specificity, with 95% confidence intervals (CIs), for each test using paired forest plots. We pooled data using the bivariate hierarchical model separately for antigen and molecular‐based tests, with simplifications when few studies were available. We tabulated available data by test manufacturer. Main results We included 22 publications reporting on a total of 18 study cohorts with 3198 unique samples, of which 1775 had confirmed SARS‐CoV‐2 infection. Ten studies took place in North America, two in South America, four in Europe, one in China and one was conducted internationally. We identified data for eight commercial tests (four antigen and four molecular) and one in‐house antigen test. Five of the studies included were only available as preprints. We did not find any studies at low risk of bias for all quality domains and had concerns about applicability of results across all studies. We judged patient selection to be at high risk of bias in 50% of the studies because of deliberate over‐sampling of samples with confirmed COVID‐19 infection and unclear in seven out of 18 studies because of poor reporting. Sixteen (89%) studies used only a single, negative RT‐PCR to confirm the absence of COVID‐19 infection, risking missing infection. There was a lack of information on blinding of index test (n = 11), and around participant exclusions from analyses (n = 10). We did not observe differences in methodological quality between antigen and molecular test evaluations. Antigen tests Sensitivity varied considerably across studies (from 0% to 94%): the average sensitivity was 56.2% (95% CI 29.5 to 79.8%) and average specificity was 99.5% (95% CI 98.1% to 99.9%; based on 8 evaluations in 5 studies on 943 samples). Data for individual antigen tests were limited with no more than two studies for any test. Rapid molecular assays Sensitivity showed less variation compared to antigen tests (from 68% to 100%), average sensitivity was 95.2% (95% CI 86.7% to 98.3%) and specificity 98.9% (95% CI 97.3% to 99.5%) based on 13 evaluations in 11 studies of on 2255 samples. Predicted values based on a hypothetical cohort of 1000 people with suspected COVID‐19 infection (with a prevalence of 10%) result in 105 positive test results including 10 false positives (positive predictive value 90%), and 895 negative results including 5 false negatives (negative predictive value 99%). Individual tests We calculated pooled results of individual tests for ID NOW (Abbott Laboratories) (5 evaluations) and Xpert Xpress (Cepheid Inc) (6 evaluations). Summary sensitivity for the Xpert Xpress assay (99.4%, 95% CI 98.0% to 99.8%) was 22.6 (95% CI 18.8 to 26.3) percentage points higher than that of ID NOW (76.8%, (95% CI 72.9% to 80.3%), whilst the specificity of Xpert Xpress (96.8%, 95% CI 90.6% to 99.0%) was marginally lower than ID NOW (99.6%, 95% CI 98.4% to 99.9%; a difference of −2.8% (95% CI −6.4 to 0.8)) Authors' conclusions This review identifies early‐stage evaluations of point‐of‐care tests for detecting SARS‐CoV‐2 infection, largely based on remnant laboratory samples. The findings currently have limited applicability, as we are uncertain whether tests will perform in the same way in clinical practice, and according to symptoms of COVID‐19, duration of symptoms, or in asymptomatic people. Rapid tests have the potential to be used to inform triage of RT‐PCR use, allowing earlier detection of those testing positive, but the evidence currently is not strong enough to determine how useful they are in clinical practice. Prospective and comparative evaluations of rapid tests for COVID‐19 infection in clinically relevant settings are urgently needed. Studies should recruit consecutive series of eligible participants, including both those presenting for testing due to symptoms and asymptomatic people who may have come into contact with confirmed cases. Studies should clearly describe symptomatic status and document time from symptom onset or time since exposure. Point‐of‐care tests must be conducted on samples according to manufacturer instructions for use and be conducted at the point of care. Any future research study report should conform to the Standards for Reporting of Diagnostic Accuracy (STARD) guideline. How accurate are rapid tests, performed during a health‐care visit (point‐of‐care), for diagnosing COVID‐19? Why is this question important? People with suspected COVID‐19 need to know quickly whether they are infected, so that they can self‐isolate, receive treatment, and inform close contacts. Currently, COVID‐19 infection is confirmed by sending away samples, taken from the nose and throat, for laboratory testing. The laboratory test, called RT‐PCR, requires specialist equipment, may require repeat healthcare visits, and typically takes at least 24 hours to produce a result. Rapid point‐of‐care tests can provide a result ‘while you wait’, ideally within two hours of providing a sample. This could help people isolate early and reduce the spread of infection. What did we want to find out? We were interested in two types of rapid point‐of‐care tests, antigen and molecular tests. Antigen tests identify proteins on the virus, often using disposable devices. Molecular tests detect the virus’s genetic material, using small portable or table‐top devices. Both test the same nose or throat samples as RT‐PCR tests. We wanted to know whether rapid point‐of‐care antigen and molecular tests are accurate enough to replace RT‐PCR for diagnosing infection, or to select people for further testing if they have a negative result. What did we do? We looked for studies that measured the accuracy of rapid point‐of‐care tests compared with RT‐PCR tests to detect current COVID‐19 infection. Studies could assess any rapid antigen or molecular point‐of‐care test, compared with a reference standard test. The reference standard is the best available method for diagnosing the infection; we considered RT‐PCR test results and clinically defined COVID‐19 as reference tests. People could be tested in hospital or the community. Studies could test people with or without symptoms. Tests had to use minimal equipment, be performed safely without risking infection from the sample, and have results available within two hours of the sample being collected. Tests could be used in small laboratories or wherever the patient is (in primary care, urgent care facilities, or in hospital). How did studies assess diagnostic test accuracy? Studies tested participants with the rapid point‐of‐care tests. Participants were classified as known to have – and not to have ‐ COVID‐19, by RT‐PCR in all studies. Studies then identified false positive and false negative errors in the point‐of‐care test results, compared to RT‐PCR. False positive tests incorrectly identified COVID‐19 when it was not present, potentially leading to unnecessary self‐isolation and further testing. False negatives missed COVID‐19 when it was present, risking delayed self‐isolation and treatment, and spread of infection. What we found We found 18 relevant studies. Ten studies took place in North America, four in Europe, two in South America, one in China and one in multiple countries. Nine studies deliberately included a high percentage of people with confirmed COVID‐19 or included only people with COVID‐19. Fourteen studies did not provide any information about the people providing the samples for testing and 12 did not provide any information about where people were tested. None of the studies reported includedsamples from people without symptoms. Main results Five studies reported eight evaluations of five different antigen tests. Overall, there was considerable variation between the results of the antigen tests in how well they detected COVID‐19 infection. Tests gave false positive results in less than 1% of samples. Thirteen evaluations of four different molecular tests correctly detected an average of 95% of samples with COVID‐19 infection. Around 1% of samples gave false positive results. If 1000 people had molecular tests, and 100 (10%) of them really had COVID‐19: ‐ 105 people would test positive for COVID‐19. Of these, 10 people (10%) would not have COVID‐19 (false positive result). ‐ 895 people would test negative for COVID‐19. Of these, 5 people (1%) would actually have COVID‐19 (false negative result). We noted a large difference in COVID‐19 detection between the two most commonly evaluated molecular tests. How reliable were the results of the studies? Our confidence in the evidence is limited. ‐ Three‐quarters of studies did not follow the test manufacturers’ instructions, so may have found different results if they had. ‐ Often, studies did not use the most reliable methods or did not report enough information for us to judge their methods. This may have affected estimates of test accuracy, but it is impossible to identify by how much. ‐ A quarter of studies were published early online as ‘preprints’ and are included in the review. Preprints do not undergo the normal rigorous checks of published studies, so we are uncertain how reliable they are. What are the implications of this review? Studies provided little information about their participants, so it is not possible to tell if the results can be applied to people with no symptoms, mild symptoms, or who were hospitalised with COVID‐19. Accurate rapid tests would have the potential to select people for RT‐PCR testing or to be used where RT‐PCR is not available. However, the evidence currently is not strong enough and more studies are urgently needed to be able to say if these tests are good enough to be used in practice. How up‐to‐date is this review? This review includes evidence published up to 25 May 2020. Because new research is being published in this field, we will update this review soon.
[1
]departmentNIHR Newcastle In Vitro Diagnostics Co-operative, Translational and Clinical Research
Institute , Newcastle University , Newcastle Upon Tyne, UK
[2
]departmentNIHR London In Vitro Diagnostics Co-operative , Imperial College London , London, UK
[3
]departmentNIHR Newcastle In Vitro Diagnostics Co-operative , Newcastle Upon Tyne Hospitals NHS Foundation Trust , Newcastle Upon Tyne, UK
[4
]departmentCentre for Genomics and Child Health , Barts and The London NHS Trust, Blizard Institute , London, UK
[5
]departmentAcademic Unit of Health Economics , University of Leeds , Leeds, UK
[6
]departmentStroke Research Group, Population Health Sciences , Newcastle University , Newcastle upon Tyne, UK
[7
]departmentInstitute of Neuroscience , Newcastle University , Newcastle upon Tyne, UK
[8
]departmentHealthcare Associated Infections Research Group , University of Leeds , Leeds, UK
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