Point of Service / Urgent Care

COVID-19 testing is expanding rapidly in volume and sophistication, with hundreds of COVID -19 testing options currently available globally and more on the way. To address the urgent public health need for increased accessibility to COVID-19 testing, the Point of Service & Urgent Care working group’s goal was to provide recommendations for technologies that could be acquired, assessed, and ideally deployed as quickly as possible to support the near-patient diagnostic needs within the Mass General Brigham (MGB) community and beyond. This effort was distinct from the Direct To Consumer (DTC) effort completed by another team within the Diagnostics Program Area.  

Our group performed horizon scanning for commercially available device-based molecular, antigen, and serology tests, which resulted in a database of over 100 technologies in different phases of development (Fig. 1). The group initially considered a broader range of targets, the most significant of which were viral protein antigens. However, it was decided such assays were not mature enough to be available in the immediate future, and, also, did not yet provide the same degree of confidence as RNA assays. 

Furthermore, to differentiate our efforts with the Direct to Consumer (DTC) working group, with regards to serology COVID-19 testing, only diagnostics with readers were considered. Promising technologies identified by our working group will be evaluated by the Diagnostics Accelerator group, and data will be made available.

Figure 1. Broad horizon scanning criteria and resulting working spreadsheet

Goals

Several criteria were assessed when evaluating which assay systems (reagents + hardware) were well-suited for specific use cases.  Our goals were two-fold:  1. To rapidly identify the most promising technologies to address urgent needs in countering the COVID-19 pandemic;  2. To develop a formalized way to document the decision-making process, both to inform the medical community (and others) by making this process transparent and comprehensible and to support future similar decision-making efforts. An interactive guide is provided, which shows the overall process we used to assess the various technologies. It summarizes a relatively standard systems analysis-based approach to identify possible solutions to a challenging and complex problem. 
Technology Assessment Process Map
Figure 2. Interactive system analysis-based approach

Approach

A rubric/assessment metric system was used to assess the suitability of candidate technologies for use in point-of-service/urgent-care settings. Such settings are often characterized by a limited capacity for laboratory testing because of many reasons like lack of licensure, limited laboratory staffing, or low on-site testing volume. Fig. 3 provides a summary of the different testing locations that may have a need for COVID-19 diagnostics, highlighting the range of testing infrastructure (e.g., expertise, controlled environment, equipment). This review was, therefore, distinct from the DTC criteria used to identify technologies available for home use or mass-produced for broad distribution in a relatively unsupervised environment. 

In addition to understanding the resources available in settings, there was a need to understand the relative advantages/drawbacks of different classes of molecular diagnostics. No single diagnostic test is perfect in all ways; the group spent a significant fraction of its time discussing what ‘good enough’ could be for different metrics and which diagnostic metrics could be relaxed so that others could be optimized. For example, as shown in Fig 3, if speed (minimal time-to-answer) is a top priority, then point-of-care in vitro diagnostics are the most promising category; however, this class of diagnostics has limited availability of EUA assays.

The group acknowledges the vital aspects associated with molecular diagnostics (not shown in the figure), such as being commercial, desired time-to-answer, cost, and positive predictive value (PPV)/negative predictive value (NPV).  These metrics were also considered and are captured in the assessment rubric developed during this effort.

If your product suits the use case and you would like your product to be considered, please fill out this questionnaire to provide us with details. If you need to reach us directly, please send your inquiry to covid_innovation_diagnostics@partners.org

Figure 3. Testing based on location and complexity level key (left), trade space for molecular diagnostics, capturing some (but not all) of the key criteria (right).*Diagram intended for illustrative purposes only. The testing infrastructure of specific practice settings may differ from what is depicted in this diagram.

Methodology

Based on the needs of a particular use-case, we identified, summarized, and then prioritized the key attributes to determine if a given commercially available technology was well suited to address the needs. The critical categories were broadly divided into two main areas: Technical and Operational (Fig.4.). In parallel to developing a rubric for assessing technologies, we collected vital information on candidate technologies. This effort included both literature search as well as active outreach to companies marketing these technologies to acquire more information. A questionnaire was developed to aid this data collection effort. The prioritization of key metrics was also strongly informed by our research; as it became clear that a challenging supply chain was a common concern, the metrics for high/medium/low were modified, and it became a top-tier metric in the current scenario. Please note there were many other criteria collected for these technologies; this extensive data table remains a useful resource for more in-depth analysis. Additionally, Figure 4 highlights the criteria that were developed to accelerate, analyze, and collect information to focus on high-probability technologies.

Figure 4. Attributes and Ranking System for POC Molecular Diagnostics. Metrics Table for Near-Term Development. *Table intended to serve as an example, criteria weighting can be adjusted to the specific use-case as needed

As highlighted, in the previous paragraph, while this process is displayed linearly, feedback loops were developed between boxes to refine our efforts and strengthen the final analysis. Experts in the clinical, industry, and research spheres, including hospital leadership, were consulted frequently to ensure our recommendations would suit the clinical need.