key: cord-0985391-i0586vfw
authors: Weemaes, Matthias; Martens, Steven; Cuypers, Lize; Van Elslande, Jan; Hoet, Katrien; Welkenhuysen, Joris; Goossens, Ria; Wouters, Stijn; Houben, Els; Jeuris, Kirsten; Laenen, Lies; Bruyninckx, Katrien; Beuselinck, Kurt; André, Emmanuel; Depypere, Melissa; Desmet, Stefanie; Lagrou, Katrien; Van Ranst, Marc; Verdonck, Ann K L C; Goveia, Jermaine
title: Laboratory information system requirements to manage the COVID-19 pandemic: a report from the Belgian national reference testing center
date: 2020-04-29
journal: J Am Med Inform Assoc
DOI: 10.1093/jamia/ocaa081
sha: 8eb5fba2b7c8dc5f552903ea4b353f0c614dc986
doc_id: 985391
cord_uid: i0586vfw

OBJECTIVE: To describe the development, implementation and requirements of laboratory information system (LIS) functionality to manage test ordering, registration, sample flow, and result reporting during the COVID-19 pandemic. CONTEXT AND SETTING: Our large (>12,000,000 tests/year) academic hospital laboratory is the Belgian National Reference Center (NRC) for severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) testing. We performed a moving total of > 25,000 SARS-CoV-2 PCR tests in parallel to standard routine testing since the start of the outbreak. A LIS implementation team dedicated to develop tools to remove the bottlenecks, primarily situated in the pre- and post-analytical phase, was established early in the crisis. RESULTS: We outline the design, implementation and requirements of LIS functionality related to managing increased test demand during the COVID-19 crisis, including tools for test ordering, standardized order sets integrated into a computerized provider order entry module, notifications on shipping requirements, automated triaging based on digital metadata forms, and the establishment of databases with contact details of other laboratories and primary care physicians to enable automated reporting. We also describe our approach to data mining and reporting of actionable daily summary statistics to governing bodies and other policymakers. DISCUSSION: Rapidly developed, agile extendable LIS functionality and its meaningful use alleviates the administrative burden on laboratory personnel and improves turn-around-time of SARS-CoV-2 testing. It will be important to maintain an environment that is conducive for the rapid adoption of meaningful LIS tools post-COVID crisis.

The novel severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus has caused a pandemic with unprecedented medical and socioeconomic adversity.

Second and third wave outbreaks are becoming a reality in several countries, at least partially, due to low herd immunity. [1] Laboratory testing to rapidly detect SARS-CoV-2 using polymerase chain reaction (PCR) is essential to guide proper patient management [2] , while serological assays will soon be required to assess population immunity (e.g. antibody tests) and guide national COVID-19 pandemic policies. [1] The increased demand for round-the-clock laboratory testing during the COVID-19 pandemic has surpassed surge capacity in many clinical laboratories, resulting in significant strain on laboratory personnel and infrastructure. [3 4 ] These developments are especially undesirable when laboratories already have to process a large numbers of potentially biohazardous samples every day, and delays in testing directly translate into delayed clinical decision-making and consequently congest emergency departments and isolation units. [3] Therefore, leveraging the capabilities of electronic laboratory information systems (LIS) to streamline all phases of laboratory testing (preanalytical, analytical and post-analytical) has proven essential.

To our knowledge, only a single report has been published that discusses the implementation of health informatics to support clinical management of the COVID-19 pandemic through novel electronic health record (EHR) functionality. [5] COVID-19 is a laboratory diagnosis with immediate consequences in the health sector (hospitalization, patient isolation, postponing surgery, etc.). Therefore, clinical laboratories face specific challenges that require dedicated LIS functionality to ensure safe, reliable testing and acceptable turn-around-times. [3] However, no literature exists on tools that leverage the LIS in order to alleviate burden on laboratory personnel, streamline laboratory testing, improve test reporting, facilitate epidemiological and translational research, and enable data-driven policy making.

https://mc.manuscriptcentral.com/jamia OBJECTIVES Here we describe the challenges faced by the Belgian National Reference Center (NRC) for COVID-19 testing when demand passed allocated surge capacity during the initial phases of the COVID-19 pandemic. We used Kotter's principles as a framework to rapidly develop and implement additional LIS functionality (Table 1) . [6] We implemented tools to manage sample and data streams, and detail functionality to improve: i) the pre-laboratory phase (test ordering, sample packaging and shipping);

ii) the pre-analytical phase (sample registration, tracking, and test prioritization (triaging)); and iii) the post-analytical phase (automated reporting and facilitating datadriven policy-making). We also briefly discuss unexpected opportunities where the COVID-19 crisis accelerated the adoption of practices that promote the meaningful use of LIS systems.

The University Hospitals Leuven is a 2,000-bed hospital providing nation-wide services via approximately 700,000 consultations, 55,000 admissions, 60,000 emergencies, and 55,000 surgeries annually. The hospital uses a fully in-house developed electronic health record (EHR) that is also commercially available [7] and used in approximately 50% of hospitals in the Flemish Region of Belgium. The clinical laboratory department annually performs around 12,000,000 tests and has national reference functions for several infectious diseases, including the respiratory disease COVID-19. The laboratory performed a total of >25,000 SARS-CoV-2 PCR tests on respiratory samples between February 1 st and April 20 th 2020. Samples were sent to the reference laboratory from across Belgium, and once analyzed results were reported to referring clinical laboratories as well as hospitals and primary care physicians. The LIS is inhouse developed and maintained by a dedicated team of computer science engineers and implementation staff. Our LIS includes a computerized provider order entry (CPOE) module for in-house test ordering, which is fully integrated into the EHR. 

During the early stages of the COVID-19 outbreak, our laboratory was the only SARS- Notably, the large majority of our expanded work force (30 of the 38 additional FTE) was assigned to help with administrative tasks (sample reception, triaging, patient registration, result validation and reporting, and epidemiological studies), and not directly involved in expanding analytical capacity (i.e. PCR analysis) ( Figure 2 ). By April 2020 reagent supply and machine capacity were more adequate ( Figure 1 ), but pre-and post-analytical bottlenecks could only be resolved by the implementation of dedicated peri-analytical IT solutions that reduced administrative burden on laboratory staff by streamlining data flows (Table 2) .

During the early stages of the COVID-19 pandemic, laboratory tests (SARS-CoV-2 PCR) were requested via paper forms and entered into the LIS by dedicated administrative personnel. To capture any accompanying clinical information and contact details of the requesting physicians, which were handwritten on the forms, each document was digitized using an image scanner and uploaded to the LIS in PDF format.

LIMITATIONS OF PAPER-BASED ORDER SYSTEM: The on-paper request system proved a major bottleneck to the COVID-19 sample flow. First, critical clinical information and contact details were often not provided, significantly delaying sample triaging and reporting, respectively. Second, because clinical information and triage categorizations were not registered into our LIS database, epidemiological and research studies were only possible after additional administrative personnel retrospectively entered those data using an ad hoc developed structured data entry module Third, too often, pre-analytical and shipping biosafety procedures (triple packaging) for suspected SARS-CoV-2 infected specimen were not strictly followed.

Fourth, the paper-based order system did not allow to rapidly and immediately change test ordering behavior in function of evolving criteria and scientific insight.

EVIDENCE-BASED COVID-19 TEST PANEL: To address problems stemming from paper-based ordering systems, we designed a CPOE-based COVID-19-specific order set in joint collaboration with the CMT, the directors of infectious disease and emergency departments. This laboratory set could be ordered for COVID-19 positive patients (Supplementary Table 1 ). The COVID-19 set contained classical pneumoniaassociated parameters (C-reactive protein, white blood cell count), parameters associated with COVID-19 pathophysiology (prekallikrein, complement), as well as PRE-ANALYTICAL DECISION SUPPORT: The COVID-19 ordering tool not only improved data quality but also allowed the laboratory to pro-actively guide sample preparation and shipping procedures through automated notifications. For example, the system algorithmically calculated the minimum number of blood tubes required to perform all analyses (taking into consideration not only the total volume of blood, but also intra-laboratory sample handling and aliquoting). The tool then notified the phlebotomist on the optimal sampling strategy. The tool also prompted the phlebotomist with packaging instructions, explaining triple packaging requirements.

Finally, the COVID-19 ordering tool was effectively used by the CMT to implement updated triage criteria with immediate effect (Figure 1) 

Our laboratory has national reference functions for respiratory pathogens and several other specialized in vitro tests, but does not perform referred testing for routine parameters. Under normal circumstances, approximately 2.5% of our testing is performed for external laboratories or health care professionals outside of the hospital, and consequently our laboratory did not invest in, nor has access to, a web-based CPOE that could have been be utilized to streamline test ordering during the COVID-19 pandemic. We therefore implemented an alternative system to manage data streams for referred testing.

We developed a LIS specific DDEF tool that allowed administrative personnel to register clinical information that was written on request forms. We also compiled a database with contact details and preferred reporting methods (fax, email, electronic mailbox system, etc.) of every laboratory in Belgium, to enable automated test reporting. Using this ad hoc system, we were able to automatically report the large majority (>98%) of test results. Although technically simple, this system dramatically reduced the number of patients and physicians that called our laboratory to inquire about test results, in turn significantly reducing administrative burden on our call center and staff.

CoV-2 is mandatory in Belgium. Under normal circumstances epidemiological reporting is centralized and represents only a limited administrative burden. During the COVID-19 pandemic, however, all laboratories were required to report daily summary statistics not only to government bodies, but also to a variety of policy makers, medical and hospital directors. These laboratory-provided statistics were required to effectively monitor and manage the SARS-CoV-2 outbreak and indeed directly affected national lockdown policies.

Our LIS was designed to enable structured data entry into an underlying Structured Query Language (SQL) database, and to efficiently visualize those data through a graphical user interface. However, the system did not have data mining nor data visualization functionality. To meet epidemiological reporting requirements, we had to develop custom-tailored SQL queries, retrieve the data in flat file format, subsequently analyze the data in a spread sheet program, and then generate several individualized reports that were emailed to specific stakeholders. Consequently, epidemiological reporting and generating infographics quickly became a significant burden requiring fulltime staff ( Figure 2 ).

As an extension of our LIS, we developed a tool for automated report generation and emailing. Briefly, the tool accepted output from SQL queries, interfaced with Google Sheets to access reported statistics from other laboratories, automatically compiled and processed all data, and then send customized emails or text messages to predefined recipients including national governing bodies and policy makers.

Automating the full epidemiological reporting process allowed to send updates with higher frequency and significantly alleviated administrative burden on scientific staff.

Projections of the transmission dynamics of SARS-CoV-2 through the post pandemic period predict recurrent wintertime outbreaks after the current first wave. [9] Absent of any other interventions, prolonged intermittent social distancing may be required for the next 24 months, active SARS-CoV-2 surveillance for at least 48 months. [9] Such measures will inevitably result in significant economic adversity, with fears of a recession growing. [10] Correlating data from clinical laboratories (PCR, serological testing, inflammatory parameters, etc.) with clinical data, diagnostic imaging, and molecular (omics) profiling data has the potential to significantly accelerate the development of predictive models, in vitro diagnostics and provide insight in the mechanism of SARS-CoV-2 spread and infection.

As a first step to facilitate scientific research, we developed a separate database that included results for all parameters in the COVID-19 test panel for all COVID-19

suspected patients (defined as all patients tested by PCR) evaluated in our hospital.

As an extension of our previous work in making large biomedical datasets accessible to non-bioinformatician scientists [11] [12] [13] [14] , we used the R/Shiny web framework to develop an easy-to-use standalone data mining application. This application allowed for selected staff and researchers to quickly interrogate and visualize the data in order to identify previously unknown correlations, without additional informatics support. This tool not only accelerated research but also alleviated the burden on IT-staff, which could then focus on the development and implementation of increasingly tailored COVID-19 related LIS functionality.

We have identified key bottlenecks in the laboratory management of the COVID-19

pandemic. The administrative burden on all staff increased exponentially with peaks in sample volume. IT solutions could effectively reduce administrative burden and streamline sample flow resulting in higher staff engagement and reduced turn-aroundtimes.

OPPORTUNITIES TO PROMOTE THE MEANINGFUL USE OF HEALTH IT: Our COVID-19 specific tools addressed immediate needs, but also highlighted opportunities to leverage the meaningful use of LIS systems to guide policy making and advance biomedical science. So far, the meaningful use of health IT is lagging [15] , despite widespread implementation and adoption of electronic systems. Consistently, in our hospital, the COVID-19 crisis contributed to the accelerated the meaningful use and full advantages of the CPOE-associated tools.

One of the key hurdles in promoting the meaningful use of health IT is the resistance of healthcare professionals to change their daily procedures. 

The COVID-19 pandemic is especially challenging for clinical laboratories that are tasked with rapid and reliable testing of a significantly increased number of samples.

Demand above surge capacity readily clogs standard infrastructure. Alleviating personnel from repetitive and administrative tasks via digitalization and automation using ad hoc developed LIS functionality and reporting tools significantly streamlines sample processing and reduces turn-around-time, features that are also beneficial after the initial phases of the COVID-19 crisis. Indeed, lock down exit strategies will critically depend on laboratory results, including emerging antibody tests. We hope that sharing our experiences in developing these tools will help other LIS implementation teams facing similar challenges. 

None of the authors have competing financial interests to declare.

This work was partially supported by Sciensano which coordinates the financing of the national reference centers in Belgium.

Correspondence and requests for materials should be addressed to JG (jermaine.goveia@uzleuven.be). 

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