Successfully reported this slideshow.
We use your LinkedIn profile and activity data to personalize ads and to show you more relevant ads. You can change your ad preferences anytime.

The impact of digital technologies on point of care diagnostics in resource limited settings

237 views

Published on

The impact of digital technologies on point of care diagnostics in resource limited settings from Expert Reviews in Molecular Diagnostics, April 2018

Published in: Healthcare
  • Be the first to comment

  • Be the first to like this

The impact of digital technologies on point of care diagnostics in resource limited settings

  1. 1. Full Terms & Conditions of access and use can be found at http://www.tandfonline.com/action/journalInformation?journalCode=iero20 Expert Review of Molecular Diagnostics ISSN: 1473-7159 (Print) 1744-8352 (Online) Journal homepage: http://www.tandfonline.com/loi/iero20 The impact of digital technologies on point-of-care diagnostics in resource-limited settings Natasha Gous, Debrah I. Boeras, Ben Cheng, Jeff Takle, Brad Cunningham & Rosanna W. Peeling To cite this article: Natasha Gous, Debrah I. Boeras, Ben Cheng, Jeff Takle, Brad Cunningham & Rosanna W. Peeling (2018): The impact of digital technologies on point-of- care diagnostics in resource-limited settings, Expert Review of Molecular Diagnostics, DOI: 10.1080/14737159.2018.1460205 To link to this article: https://doi.org/10.1080/14737159.2018.1460205 Published online: 10 Apr 2018. Submit your article to this journal View related articles View Crossmark data
  2. 2. REVIEW The impact of digital technologies on point-of-care diagnostics in resource-limited settings Natasha Gousa , Debrah I. Boerasb,c , Ben Chengc , Jeff Takled , Brad Cunninghama and Rosanna W. Peelinge a Global Health Department, SystemOne LLC, Johannesburg, South Africa; b Global Health Impact Group, Atlanta, GA, USA; c International Diagnostics Centre, London, UK; d Global Health Department, SystemOne LLC, Springfield, MA, USA; e Department of Clinical Research, London School of Hygiene and Tropical Medicine, London, UK ABSTRACT Introduction: Simple, rapid tests that can be used at the point-of-care (POC) can improve access to diagnostic services and overall patient management in resource-limited settings where laboratory infrastructure is limited. Implementation of POC tests places tremendous strain on already fragile health systems as the demand for training, supply management and quality assurance are amplified. Digital health has a major role to play in ensuring effective delivery and management of POC testing services. Area covered: The ability to digitise laboratory and POC platforms, including lateral flow rapid diagnostic test results, can standardize the interpretation of results and allows data to be linked to proficiency testing to ensure testing quality, reducing interpretation and transcription errors. Remote monitoring of POC instrument functionality and utilization through connectivity, allows programs to optimize instrument placement, algorithm adoption and supply management. Alerts can be built into the system to raise alarm at unusual trends such as outbreaks. Expert commentary: Digital technology has had a powerful impact on POC testing in resource limited settings. Technology, markets, and medical devices have matured to enable connected diagnostics to become a useful tool for epidemiology, patient care and tracking, research, and antimicrobial resistance and outbreak surveillance. However, to unlock this potential, digital tools must first add value at the point of patient care. The global health community need to propose models for protecting intellectual property to foster innovation and for safeguarding data confidentiality. ARTICLE HISTORY Received 27 November 2017 Accepted 29 March 2018 KEYWORDS Digital technology; connected diagnostic system; health system strengthening; quality assurance; data governance 1. Introduction Infectious diseases impose a huge burden in the developing world. Every year, millions of people worldwide die from infec- tious diseases such as human immunodeficiency virus (HIV), tuberculosis (TB), malaria, pneumonia, and diarrhoea [1]. Diagnostics play a critical role in clinical decision-making and disease control and prevention. Sensitive and specific laboratory- based diagnostic assays are commercially available for the detec- tion of most infectious diseases of public health importance, but they are costly and often not accessible to patients in the devel- oping world where laboratory services are often limited. Laboratory networks in resource-limited settings (RLS) may struggle with sustaining the basics needed to support centra- lized testing, and infrastructure for surveillance of infectious pathogens, and outbreak detection and response, is often lacking. Point-of-care (POC) testing (POCT) refers to testing that can be performed at the site of patient care and can improve access to diagnostic services, turnaround time for results, and overall patient management. The development and deployment of simple, rapid tests and devices that can be used at the POC to screen for HIV, diagnose TB, and guide malaria treatment has led to significant reductions in morbidity and mortality in the developing world where access to laboratory services is limited. However, despite its many benefits, a number of challenges exist, mostly related to the quality of tests and of decentralized testing, the management and oversight of POC programs, and the high cost and utiliza- tion of POCT services [2,3]. The Joint United Nations Programme of HIV/AIDS (UNAIDS) have a set of ambitious targets for HIV known as the 90-90-90 targets, calling on countries to ensure 90% of infected indivi- duals know their HIV status, 90% of those known to be infected are on antiretroviral treatment (ART), and 90% of those on treatment are virally suppressed by 2020 [4]. Attainment of these 90-90-90 targets depends on increasing access to POC tests for marginalized and hard-to-reach popu- lations, POC molecular assays for early infant diagnosis (EID), and HIV viral load (VL) monitoring. Similarly, the global com- mitment to eliminate mother-to-child transmission of HIV and syphilis requires ensuring access to POC tests for screening pregnant women at every antenatal clinic [4]. In 2015, coun- tries committed to a Sustainable Development Agenda with 17 Sustainable Development Goals (SDGs) calling for the United Nations and its partners to build a better world with no one left behind [5]. The efforts toward Universal Health CONTACT Rosanna W. Peeling Rosanna.peeling@lshtm.ac.uk Department of Clinical Research, London School of Hygiene and Tropical Medicine, Keppel Street, London, UK EXPERT REVIEW OF MOLECULAR DIAGNOSTICS, 2018 https://doi.org/10.1080/14737159.2018.1460205 © 2018 Informa UK Limited, trading as Taylor & Francis Group
  3. 3. Care coverage to achieve the SDGs will need to be under- pinned by affordable and accessible POC tests. The WHO End TB Strategy, that aims to bring the global TB epidemic to an end by 2035, is the first to acknowledge the role of digital health in ensuring more effective and efficient service delivery and ultimately achieving global health targets [6]. Digital health refers to the convergence of information technology, digital media, and mobile devices with health care and is enabling patients and health-care providers easier access to data and health information in order to improve quality and outcomes [7]. Various digital technologies, including but not limited to, connected diagnostics devices, decision support systems, mobile health Applications (Apps), connected biometric sensors, and electronic health records [8], are able to gen- erate and transmit electronic data (whether it be wirelessly or by wired connection) to the Internet to digitally report results in real time and hold great promise to improve the efficiency of the health-care system. With the increasing demand for POC diagnostics, the con- vergence of digital technologies with a range of POC plat- forms that vary from simple rapid diagnostic tests (RDTs) in lateral flow formats to POC molecular devices is transforming patient care and disease surveillance in RLS beyond that of data transmission. This review presents the potential impact and benefits of digitizing POC diagnostics in RLS by discussing the role of digital technologies in improving linkage to care and data collection, optimizing placement and usage within the health-care system, facilitating outbreak control and remote program management, addressing quality concerns, and improving overall return of investment for programs and funders. The review also highlights the importance of data governance frameworks for effective data management when considering digital technologies. 2. Digitizing POCT programs 2.1. Application to rapid diagnostic testing RDTs are a double-edged sword. While RDTs can greatly improve access to testing services, the implementation of RDT programs places tremendous strain on already fragile health systems as the demand for training, supply chain man- agement, and quality assurance are amplified. RDT results have to be read visually and this subjective interpretation can result in reader variation in interpretation of results. New innovations and strategies to digitize RDT result inter- pretation using optical readers and mobile phones may improve the interpretation and allow result data to be trans- mitted in an electronic format. FIONET (Fio Corporation, Toronto, Canada), as an example, combines a device-based RDT reader, termed Deki, with a configurable cloud informa- tion system to ensure that program managers can remotely monitor field activities and performance. This system has been deployed in Ghana to collect data on malaria RDTs as well as microscopy results for quality and comprehensive reporting [9]. The Deki Reader provides guidance on the testing process and objectively interprets RDT results based on line intensity thus reducing or eliminating common processing errors and improving diagnostic accuracy. In Cameroon, the Deki Reader is showing potential for strengthening their RDT malaria pro- gram and initial trials demonstrated >98% agreement with visual result interpretation of malaria RDTs [10]. Similarly, for HIV, RDTs are the critical entry point for the HIV treatment and care cascade and the cornerstone of national reporting on country epidemiological and surveil- lance data. However, although the HIV RDT is one of the easiest and least expensive tests to perform, it has been shown to pose great challenges with regards to ensuring compliance to the testing algorithm, external quality con- trol, and accuracy of reading the visual result [11–13]. Various mobile applications have been developed, or are in development, for application to HIV RDT programs in RLS to improve the overall quality and reliability of results (Table 1) [14]. One such platform, developed by Global Solutions for Infectious Diseases, is an App-based reader that was piloted in Zimbabwe for HIV and malaria test result interpretation and real-time reporting [15]. By uploading test result images through the App, the central laboratory is able to monitor nurses test administration and quickly identify issues related to result reporting and data collection. Electronic self-testing instruments for sexually transmitted infections (STI) are also in development [16]. The UK Clinical Research Collaboration Translational Infection Research Initiative Consortium is supporting research to reduce burden of STI (current test for chlamydia) by developing rapid POC tests that can work with a noninvasive, easyto-use sample collection device (p-stick) – 4 mL urine, vaginal swab for Table 1. Examples of automated RDT readers either commercially available or in the developmental pipeline. Reader Reader format Data format Deki Reader (Fio Corporation, Toronto, Canada) Commercially available, universal device-based reader that can interpret commercially available RDTs Results can be automatically transmitted to FIONET cloud database via 3G or Wi-Fi Infectious Disease Reader (iStoc, Koulukatu, Finland) Commercially available, universal reader consists of software that runs on standard smartphone or iPad Results can be sent to a Immediate Diagnostics and Analytics (IDA) cloud- based server Holomic LLC (Holomic, Los Angeles, CA, USA) Commercially available, universal reader that consists of an attachment that clips onto a mobile phone An application on phone transmits data to a central server and can interface with Holomics Cloud mReader (MobileAssay™, Denver, CO, USA) Commercially available, universal reader that consists of software that runs on a standard smartphone or iPad device Results can be uploaded via Wi-Fi or cellular network to Mobile Assay cloud server Global Solutions for Infectious Diseases system (University of Washington, Dimagi, Boston, MA, USA) Universal reader consists of software that runs on standard smartphone or iPad. SIM card can be used to store and transmit results NovarumDx (BBI Solutions and Albagaia, Scotland and Wales, UK) Commercially available, customizable software that runs on a smartphone device Results can be transmitted to a BBI server RDTs: rapid diagnostic tests. 2 N. GOUS ET AL.
  4. 4. females with a time to result of 30 min. Patients are then linked to an electronic pathway for treatment and contract tracing without having to see a doctor. In general, automated RDT readers, through their ability to capture, digitize, and transmit RDT results, will have a critical role to play in not only strengthening data collection and manage- ment for RDT programs but also improve the overall quality of POC RDT testing and surveillance efforts [14]. Thus, it seems that investments in digital technologies to enhance visual readings of lateral flow assays and improve result reporting could provide huge returns on investment for RDT programs. 2.2. Application to POC molecular diagnostic platforms Underneath a medical instrument’s diagnostic result is a rich set of sub-result data (‘deep instrument data’) that are still largely untapped as a resource. Pathogen or human genetic profiles, thermal temperatures, cycle threshold (Ct) values, and similar data are merged, analyzed, and distilled into a ‘Positive’ or ‘Negative’ result in many instruments and this is typically where the health-care system steps in to take action. But those genetics, temperatures, curves, and values indicate clusters of genetic mutations when matched to age, sex, or prior treat- ment history; or over time can indicate an emerging resistance to antibiotics in a rural province; or when married to treat- ments and outcome monitoring, hold the potential for perso- nalized medicine. Accessing this data was impossible before as the data were either entirely inaccessible or manually imprac- tical to record, e.g. thousands of interim measurements that compile a curve. However, through emerging digital technologies in the new generation of POC molecular devices (most have inbuilt con- nectivity capabilities), the ability to natively collect electronic diagnostic and deep instrument data is now possible. Programs with connected diagnostic platforms are able to remotely col- lect data coming from both decentralized POC technologies and readers in near real time. These data can potentially be merged through a middleware solution and linked to Ministries of Health (MoH) and used to provide critical information on testing coverage, disease trends, epidemiological surveillance, supply chain management, and quality monitoring of the tests and testing process (Table 2) across national programs, as well as international systems thus increasing the efficiency of health- care systems and improving patient outcomes. In RLS, these advances can also form the basis of early warning systems to optimize control and elimination interventions through building in automated alerts to raise alarms for outliers and erroneous results and to monitor the performance of instruments. With Global Positioning System data transmission capabil- ities, diagnostic data can be linked to geographical locations to report national and global testing trends to central data- bases to optimize programs, report on outbreaks, inform dis- ease control strategies, and monitor progress towards elimination. Geographic Information Systems (GIS) are also being used to map existing laboratory networks, collect infor- mation on testing volumes and needs, in order to appropri- ately place POC instruments within the network, and improve the overall health system. Such systems can also be used for tracking progress towards elimination of diseases. 3. The impact of digital technologies on POCT programs 3.1. Rapid return of diagnostic results and linkage to care Reduced time to diagnosis and rapid treatment initiation have been shown to improve TB patient outcomes and reduce transmission rates [17]. However, one of the weaknesses of many health systems is that they are oftentimes not equipped to support rapid diagnostic systems, such as the GeneXpert, with prompt return of patient results and thus end up negat- ing the impact of the technology [18,19]. This is especially pertinent with many countries opting for centralized GeneXpert testing. Although laboratory turnaround times are short, the return of paper-based results back to referring clinics has been reported to delay patient initiation onto treatment [20]. Even though POCT is designed to provide rapid return of results during the patient visit, a few studies have shown that in reality, same-day results are not always possible due to device throughput, logistics, and clinical work- flows [21,22]. Thus, one of the most compelling arguments for digital technologies is the capability to return diagnostic test results to the health-care provider or even the patient, in real-time, via short message service (SMS) or e-mail notifications to link them to care. An exciting application of this is in HIV RDT self- testing programs. The standard algorithm for HIV diagnosis is Table 2. Summary of the potential impact of digitizing data on POC technologies. Parameters Local impact Health system impact Rapid return of diagnostic results Reducing time for management of patients Increasing health systems efficiency Improving data quality/ reliability Reducing transcription errors Monitoring POC instrument placement and utilization Reduce stock outs by optimizing instrument placement and supply management Quality assurance Improving diagnostic accuracy by linking proficiency results to testing centers allows for corrective action and remedial training Improving patient outcomes Monitoring adherence to diagnostic algorithms Improving the correct use of diagnostics to guide patient management Alerts for unusual trends Faster recognition of emerging or reemerging health security issues Allowing timely surveillance and alerts for outbreaks and antimicrobial resistance POC instrument operation Alerts for instrument errors Facilitates innovation; improving return on investment on POC instruments Alerts for instrument breakdown Reminders for maintenance and warranty EXPERT REVIEW OF MOLECULAR DIAGNOSTICS 3
  5. 5. two sequential RDTs; one for screening and one for confirma- tion. For HIV self-testing, the same algorithm applies but, in this case, the person self-tests in private and needs to be linked to care for their confirmatory testing. New digital inno- vations, such as the HIVSmart! App developed by McGill University, allow persons to download an open-source App on their mobile phone, which provides guidance on testing and result interpretation, educational information and attempts to link positive patients to health-care facilities to ensure confirmatory testing [23]. In Nigeria, the GxAlert connectivity platform by SystemOne (Boston, MA, USA) is being used to reduce the turnaround time for reporting of GeneXpert multidrug resistant (MDR)-TB results, whether they initiate from centralized or POC sites, to the TB government supervisor, state program manager, and national program enrolment officer [24,25]. Since implementa- tion of the GxAlert system for real-time reporting of drug resistant-TB results via SMS alerts, the proportion of patients initiated onto treatment has significantly increased from 20% in 2014 to 85% in 2015 [11]. A further concern with POCT is that results are often not captured electronically, and once the patient leaves the health facility, are no longer available for reporting, statistical analy- sis, monitoring, and billing purposes [26]. Traditionally, POC results are manually captured in paper registers that may or may not be transcribed into the laboratory information system (LIS) or electronic medical record (EMR). The advantage of a connected POC device is that results will automatically be incorporated into the LIS or EMR to ensure better manage- ment, faster response, automated billing, and inclusion of data for reporting. 3.2. Improved data quality To ensure the appropriate planning, monitoring, and resource allocation to meet global HIV and TB diagnostic and treatment goals, the need for collection of data representative of the populations being served, as well as geographic locations of services being offered, is imperative to understanding pro- gram performance and future planning needs [27]. It is worth noting, however, that nationwide EMR or nationwide LIS are generally not present in the developing world and continue to have little penetration. Lacking a nationwide underpinning of these systems, which typically capture demo- graphic patient data, treatment history, and other important metadata about a patient or diagnosis, emerging connectivity solutions are filling those gaps by making modest adjustments to which data are collected at the diagnostic instrument itself. By prompting the capture of additional information alongside the diagnostic test result, for example, indicators such as gender, age, HIV/TB status, previous treatment history, and referring facility, programmatic reporting is enriched and allows monitoring of which populations are being reached and those that are missed. As an example, the National TB program in the Philippines is capturing very granular data alongside their GeneXpert TB results such as gender, age, specimen, and facility details, etc. and in doing so, is collecting a rich data set to improve on their programmatic reporting. Capture of this information is facilitated through GxConnect (SystemOne), a small piece of software installed on the GeneXpert instrument which is able to collect these custom fields together with the TB result, transmit it to the in-county server and then displays all data on the GxAlert dashboard. Program managers can remotely monitor what populations are being tested and where, identify gaps, determine if inter- ventions are working and further intervention needs. 3.3. Optimizing POC technology placement and remote oversight Countries often struggle with the optimal placement of POC instruments. When the decision to adopt a new digital tech- nology is made, it is important to understand the necessary infrastructure and systems needed to maintain these new technologies and ensure optimal usage. Most POC devices for CD4 enumeration, as an example, have inherent connec- tivity capabilities but countries have lacked the necessary resources to support the information technology and trouble- shooting, such as lack of data plans and skilled human resources. This resulted in inappropriate placement of devices, inoperative devices, and fragmented laboratory networks. In South Africa, the National Health Laboratory Service gathered electronic data on CD4 testing volumes, instrument place- ment, and GIS-mapped clinical locations to develop a tiered CD4 testing model, incorporating both centralized and POCT [28]. Through this model, they have successfully managed to improve not only the turnaround times for CD4 service deliv- ery but also have the potential to save in HIV programmatic costs. The ‘optimal’ pace for adding new instruments into a country should be a balance between the need to increase catchment, the speed with which underlying demand genera- tion strategies are employed (e.g. clinical sensitization and specimen referral), and the rate at which the population of instruments’ utilization rate climbs. Lack of reporting on commodity consumption can also result in major stock outs and delays in issuing of new stock, leading to instrument downtimes, as was experienced in Kenya during the rollout of the Pima™ CD4 (Alere Technologies, GmbH) and BD FACSPresto™ CD4 devices (BD Biosciences) [29]. Test purchasing and consumption rate can also be tracked in real time against purchases using connec- tivity software if procurement data are captured and can help avoid interruptions in service delivery and wastage of resources [27]. For example, by analyzing the average useful life left in Xpert® MTB/RIF cartridges at the time they are consumed, the government can extrapolate whether they are purchasing fre- quently enough or receiving stock with sufficient lifespan remaining to prevent expired cartridges. Ideally, one would want to see smaller more frequent procurements to ensure fewer stock outs (Figure 1). Similarly, the monitoring of instruments or modules on a monthly basis quickly allows central program managers to identify if a diagnostic instrument is out of service and prompt appropriate action (Figure 2). Interruptions in diagnostic test- ing may be due to several possible causes, including 4 N. GOUS ET AL.
  6. 6. instrument failures, laptop/computer issues, or test/consum- able stock-outs, absence of testing personnel, and each will display a different pattern of interruption. If diagnostic instruments are connected, these patterns can be identified and rectified [30]. This would allow automated notifications to the in-country service provider to fast track and improve Figure 1. Cartridge useful life left. Red bars indicate Xpert cartridge stock with less than 2 months to expiry. Green bars indicate stock with more than 6 months expiry. By monitoring useful life, test purchasing practices can be better informed. (a) When smaller, more frequent purchases are made, stock is less likely to expire before use, but this will have supply chain and logistical implications. (b) Larger, less frequent purchases may result in stock expiring before it can be used. Full color available online. Figure 2. Monitoring of instrument down-time: Stoppages in testing can easily be identified and prompt investigation as to possible causes. EXPERT REVIEW OF MOLECULAR DIAGNOSTICS 5
  7. 7. service and maintenance and facilitate backup plans such as reallocation of samples to other laboratories for testing. 3.4. Quality assurance Ensuring the accuracy of diagnostic testing improves patient outcomes. The quality of tests and testing can be monitored through the use of external quality assessment (EQA) or Proficiency Testing (PT). EQA for POCT is often difficult due to a range of factors including the cadre of staff performing the EQA (non-laboratory or non-technical), difficulty in ensur- ing compliance with EQA schedules and protocols, obtaining EQA results back in a timely manner, and reporting back to POC sites [31]. Connectivity solutions that can link EQA/PT results to POCT sites would allow assessment of adequacy of training, need for corrective action and/or remedial training, and should be seen as a complementary approach to EQA [32,33]. This is especially important in POC sites with high staff turnovers. The benefit of having connected POC devices was demon- strated in Zimbabwe for managing their CD4 EQA program. Usually, the Pima CD4 EQA program is a time-intensive pro- cess requiring sample shipping to remote sites, testing and reporting back to the central facility, a process which can take up to 12 weeks [33]. In 2015, an automated EQA program was piloted with Oneworld Accuracy, whereby an application pro- gram interface for their informatics system, OASYS (Oneworld Accuracy System), was developed to automatically query Alere Data Point every hour for any new data that had been identi- fied as an EQA sample. This automated system resulted in a significant reduction in time to reporting, with Oneworld Accuracy receiving EQA results within 60 min of the test being performed on the PIMA [33]. Monitoring of device errors is also an important way to monitor the quality of POCT programs. As with laboratory test- ing, errors can occur during any stage of the POCT process and much focus has been applied to the analytical and post-analy- tical phases. Connected POC devices allow remote monitoring of test failures or unsuccessful tests (operator and instrument errors, no or invalid results). Instrument failure rates can vary significantly within countries, across instruments, regions, or time. Given the ability to have all unsuccessful test data auto- matically reporting to a server allows central monitoring of distribution, frequency, and trends. These data can be visua- lized down to a peripheral site-level and on a per user basis, without ever having to travel to those sites and without the missing or erroneous data typical of paper-based self-reporting. General patterns exist in terms of expected errors, what per- centages to anticipate, and what remediation might be most effective. Figure 3 illustrates how monitoring of error rates by testing sites over a specific period of time can facilitate rapid identification of problem sites and (automatically) trigger an investigation into potential causes [34]. This process can serve to proactively alert National Reference Laboratories (NRLs), quality assurance teams, and partners when an instrument is ‘out of the norm.’ The cate- gorization of errors according to their cause (instrument, user, assay) is also an important activity for NRLs to facilitate rapid response and implement corrective actions. 3.5. Monitoring adherence to diagnostic testing algorithms Through a connectivity system, a health-care system can moni- tor the adoption of new algorithms and report on the interven- tion to determine if it is being implemented appropriately, Figure 3. Bar chart showing the diagnostic instrument error rates for 16 laboratories over a specific time period. Red bars show laboratories with higher than the average national error rate of 6.3% (grey line), whilst green bars depict laboratories performing below the acceptable benchmark of 5% (green dashed line). Full color available online. 6 N. GOUS ET AL.
  8. 8. whether it is cost-effective, and what other factors are needed for implementation to be successful [35]. Connectivity can also inform scalability and adoption of a diagnostic program by providing information on adherence and/or any deviations at a country, regional, or site level [36]. The Global Laboratory Initiative has stated that the GeneXpert TB diagnostic algorithm should be dictated by the epidemiological disease profile of the country [37]; however, a few studies in Africa have shown poor adherence to TB diagnostic algorithms [38–40]. Figure 4. Example of how a connectivity solution can facilitate monitoring of a new diagnostic algorithm adopted within a given country. One would expect to see variability in certain indicators, in this case TB positivity rates, at programme adoption (2013) due to unfamiliarity and novelty of the diagnostic algorithm. However, as the programme evolves and compliance with the algorithm is achieved, the TB positivity pattern should become more uniform and meet expected rates (2016). Figure 5. Identifying outliers. Scatter plots can be used to identify whether indicators such as TB and Rifampicin resistance fall within expected rates for given countries/regions/laboratories. EXPERT REVIEW OF MOLECULAR DIAGNOSTICS 7
  9. 9. To illustrate, Figure 4 shows the adoption of the GeneXpert MTB/RIF® assay as the national first-line TB diagnostic in a new setting. Connectivity was instrumental for monitoring specific indicators. For example, connectivity monitored if the pre- sumed TB or MDR-TB prevalence is within the range expected [41] given the new intervention, and hence if the country algorithm is being followed. By delving deeper and observing data on a per-facility basis, one can quickly identify outliers or particular testing sites that are not following the diagnostic process appropri- ately, i.e. if their rates of disease do not fall within expected ranges (Figure 5). For example, if an instrument or site is focused on screening all prisoners for TB regardless of whether they are symptomatic or not, one would expect that site to have very low TB positivity rates. In contrast, sites attached to MDR treatment wards or in-country algorithms using the GeneXpert primarily for rifampicin resistance confirmation would display very high TB positivity and rifampicin resistance rates several times higher than the average. Rates falling out- side of expected ranges could therefore prompt further inves- tigation. Ideally, if all instruments in all countries were reporting to a connected diagnostic solution, the algorithm could be much more precise, country-specific, and evolving as the situation evolves. This is the focus of some connectivity software platforms like GxAlert™ that are not only connecting the GeneXpert for TB diagnosis, but also the GenoScan for Line Probe Assay (Hain LifeScience, GmbH) drug resistance testing and MGIT liquid culture system (Becton Dickinson) for monitoring response to treatment. Under a Challenge TB pro- ject in Mozambique, the integration of all three TB diagnostics within the algorithm will allow the treatment cascade across instruments to be looked at in more detail and provide a unified view of drug resistance by tracking patients using a connected diagnostics patient ID solution. 3.6. Harnessing the power of digital technologies for global health security Outbreak response and real-time disease surveillance are an urgent global health priority. The Ebola crisis of 2014–2016 is just one example of a global health crisis that served to demon- strate the importance of integrating digital technologies with the new generation of POC molecular tests that are highly sensitive and specific. During the outbreak, GeneXpert devices located in mobile laboratories in Guinea and Sierra Leone were interfaced to GxAlert. This enabled automatic, real-time report- ing of positively identified cases directly to the laboratory directors via SMS and e-mail alerts giving key decision-makers accurate, reliable, and timely information, improving the time to coordinate a response. Similarly, digitized data from antimi- crobial resistance (AMR) surveillance testing within a connected national surveillance system would allow real-time monitoring of the impact of antibiotic stewardship strategies and contin- uous improvement and optimization. Another benefit of these digital tools is the ability for a country to set outbreak algorithms to automatically trigger based on statistical anomalies in disease data [42] or too many diagnostic results falling outside of preset criteria. Responding immediately – literally within seconds of a confirmed diagnosis – helps the health-care system respond faster and interrupt person-to-person transmission. Tracing of infected contacts and containment of infected persons becomes exponentially more difficult and expensive with each passing day and the ability to have a latent early warning system running in the background can save valuable days that can be used to address the outbreak at 0 instead of Patient 231. In Nigeria, a mobile App, dashboard, and GIS mapping tool have been used to speed up the timeliness of reporting and communication for new Ebola case detection and response [43]. Since implementation of this system, improvement has been seen in reporting of daily follow-ups of contacts, turn- around time between identification of symptomatic contacts and evacuation, and reporting of laboratory results. Furthermore, although many information systems exist today to monitor infectious disease outbreaks, they rely on manually reported information and, as the prior Ebola, H1N1, SARS, and various other outbreaks repeatedly demonstrate, the decision to declare an outbreak has been constrained; either the data was not of sufficient quality to merit a political response sooner, or the data was ‘shaped’ prior to public release in order to minimize the political or economic penalty for being ‘an Ebola country’ [44]. Connected diagnostics equip all stakeholders with the same, unadulterated set of information against which to coordi- nate and take action; namely the actual phenomenon of an outbreak as it happens, rather than personal reporting and interpretation of the outbreak after it happens. Connected diagnostic systems can also improve a county’s ability to monitor disease trends and inform intervention needs. In South Africa, the GeneXpert Xpert MTB/RIF national testing footprint is connected to the in-country LIS, allowing diagnostic and operational data to be collected centrally. The National TB program is using this data, specifically the Ct values, as an audit indicator for program and laboratory per- formance as well as identifying variability in bacterial burden and clusters of drug resistance [45]. Not only does this allow the program to monitor and improve on algorithm adherence but also improves upon molecular surveillance. Similarly, a spatial decision support system is being used in the South West Pacific to automatically locate and map the distribution of confirmed malaria cases in order to rapidly identify hotspots for transmission and guide response efforts [46]. 3.7. Improving return of investment of a diagnostic instrument The benefits of a connected diagnostic platform also become apparent in the ability to inform programmatic implementa- tion of new diagnostic purchases. Typically, POC programs and diagnostic networks, in general, have been plagued by over- capacity and underutilization of instruments [47]. Between 2011 and 2013, a survey of HIV VL, EID, and CD4 instrument availability and utilization was conducted in 127 WHO coun- tries [48]. Major gaps were found; underutilization of VL and CD4 instrumentation was widespread, with only 13.7% utiliza- tion of CD4 capacity and 36.5% utilization of VL capacity being reported in 2013 [48]. 8 N. GOUS ET AL.
  10. 10. The ability to monitor utilization rates in real-time can pro- vide important insights into appropriate purchasing models for instruments and consumables, as well as identify where alter- native investments into infrastructure or specimen transport may be more pertinent. In general, utilization rates will differ by country but tend to cluster into three distinct categories: (1) countries accelerating instrument utilization, (2) countries that have hit a ceiling in instrument utilization, and (3) countries that are lagging or declining in instrument utilization (Figure 6). A country showing an upward trend in utilization may indi- cate that new instruments introduced into this system are being adopted more quickly and effectively due to leveraging of the existing infrastructure; countries with declining utiliza- tion rates may be suggestive that too many instruments are being purchased too quickly for appropriate absorption into the health-care system. In this case, it may be prudent to channel investments into improving and strengthening under- lying demand such as improving specimen referral and trans- port systems or clinical sensitization programs. Over the last 60 years, rapid advances in portable commu- nications devices such as the smart phone have improved the speed, efficiency and cost of data acquisition, processing and storage. Mobile phones are now in widespread use, even in the hardest to reach areas. Smartphone-based devices with the ability to power and interpret serological assays in microfluidic formats have been developed and are in clinical trials [49,50]. Smartphone-based molecular assays are now under develop- ment. Test results can be displayed on the smartphone as well as transmitted to a central database. These are suitable for self- use or by health providers in a facility or in a community setting. Testing using these smartphone-based diagnostic devices will complement laboratory-based diagnostic testing system, espe- cially for outbreak investigations. 4. Data governance Any private or public legal entity processing or storing perso- nal information needs to do so in an appropriate manner to protect the right to privacy of the individuals [51]. Diagnostic and patient identifiable information falls under this category, and as such, a burden of responsibility is placed on protecting this information. The South African Protection of Personal Information (POPI) Act [52] provides (in part) some clarity: To promote the protection of personal information processed by public and private bodies; to introduce certain conditions so as to establish minimum requirements for the processing of personal information. As present, in all industries influenced by continuous advances in information technology, the regulatory and legislative fra- mework which governs the process will always lag behind the current state of technology. Legislation simply cannot be updated at the same rate as technology progresses; and this is a common threat across many industries. The major governance frameworks which influence the con- nected diagnostics industry are General Data Protection Regulation (GDPR) [53], Data Protection Act [54], POPI [52], and the Privacy Shield [55]. All four of these frameworks span from a similar purpose and reflect minor differences in the nuances around the terminology and processes, with the same goal in Figure 6. Illustrative example of trends in diagnostic instrument utilization for the GeneXpert. The bar chart plots the average number of tests performed (Y axis) per instrument per month (X axis). A theoretical maximum utilization of 200 tests is used as the benchmark for a four module GeneXpert instrument. The blue line plot depicts the overall trend in instrument utilization as a percentage (alternative Y axis). EXPERT REVIEW OF MOLECULAR DIAGNOSTICS 9
  11. 11. mind. These policies/acts should not be viewed as mechanisms to thwart or prevent the sharing of diagnostic data. These poli- cies should be regarded as processes which promote the sharing of diagnostic data and information by appropriate means. Although these legislative processes are well established in the developed world, they are generally absent in the devel- oping world, and are not likely to find widespread adoption within the next 5 years. The inherent risk in the lack of legal requirement to ensure appropriate mechanisms for storing, processing, and sharing health-care information is that devel- oped systems may abuse this process. Due diligence should still be conducted to meet international security standards and the responsible and appropriate protection of this information is still required. Failing to do so will likely result in the abuse of this information; or inappropriate dissemination of personal information; data breaches and further reputational and trust violations can stunt the growth of this industry. A number of international companies and organizations such as mSTAR, Foundation for Innovative New Diagnostics, SystemOne, London School of Hygiene and Tropical Medicine are all working to promote the establishment of best practice for connected diagnostic systems to ensure adequate protec- tion which promotes the sharing of information to a new ecosystem being established to process and consume data which the ultimate goal of improving patient treatment and ultimately, patient outcomes. 4.1. Data ownership The legislation referenced above deals with the storage and processing of personal and special personal information and the necessary requirements to do so appropriately. The legis- lation, however, does not delineate data ownership [56]. The entity which owns the data is not necessarily obvious and if often a contentious topic in the developing world due to the nature of the industry and the dynamics of funding agencies, implementing partners, technology providers, and MoH. As an example, a funding agency funds the implementa- tion of a third-party contracted solution, via an implementing partner, to be utilized by the MoH to interface a number of diagnostic instruments. Under this arrangement, at least four different groups would like to have access to various sets of data for different activities, and the right to access this data is determined by the Data Controller using GDPR/POPI parlance [54]. The Data Controller determines the reasons for collection and processing of the data and is legally liable to ensure the protection of this data – but the Data Controller is not neces- sarily the owner of the data. For the industry of connected diagnostics, the most appro- priate assignment would be the entity responsible for the treatment of the patient owns the data. If more than one entity is involved, a joint responsibility model is inherent with both entities responsible for the protection and proces- sing of this information and a written agreement outlining such is required under POPI and the GDPR binding these entities. This assignment of ownership of connected diagnos- tic information to the MoH (or branch thereof) is fair since (a) they are responsible for the care of the patient; and (b) if ever a data breach was identified, the MoH would likely be the liable entity incurring legal damages over the implementing partners, third-party providers, or global funders. 4.2. Data glossary/data dictionary Diagnostic device makers, especially smaller firms, have a singular focus to innovate and invent faster, more sensitive, and cheaper means to provide a diagnosis. However, a nota- ble gap in the development process is the lack of a standard set of information, data, or reportable fields which should be included as part of the diagnostic result. The state of technol- ogy has progressed well beyond the need for a diagnostic device to simply produce a result and an entire ecosystem has been created (the connected diagnostics industry) processing the metadata reported with the test result. The metadata which accompanies a test result is able to provide and inform a wealth of activities which allow MoH’s and organizations the ability to ● Ensure the quality and accuracy of a reported result (first and foremost) ● Track inventory and consumable expiration ● Monitor the quality of consumable lots and inform man- ufacturing requirements ● Analyze the difference in testing quality at high- vs. low- infrastructure facilities ● Inform supply chain and sample logistics ● Identify potential specimen contamination ● Proactively monitor and predict instrument failures, cali- bration, and maintenance requirements. ● Monitor instrument utilization and uptime . . . among many others. Providing a standardized list of requirements for these reportable fields for new devices would significantly improve the remote monitoring and reporting capabilities present in the industry. Similarly, MoHs are discovering the richness of reporting and analysis which additional patient demographic informa- tion (age, gender, region, etc.) can provide national programs and imposing additional requirements on new devices to be flexible enough to support this kind of information. 5. Conclusion Health systems need to evolve to take advantage of this convergence of POC and digital technologies [57, 58]. New technologies and devices should, by default, utilize open inter- face and standards to provide digital output as well any necessary metadata required for quality control verification and analysis. Commonly used open-interface formats such as HL-7, ASTM, and the POC-1A/2A standards are appropriate for these devices. In the future, laboratories need to take on a novel role as the central command of a digitized diagnostic system that extends beyond laboratories across all POCT sites, assuring quality, supply chain, providing training and monitor- ing patient outcomes [59]. The connected diagnostic system is critical in providing data for disease surveillance to inform disease control strategies, and outbreak investigations and in combating AMR. 10 N. GOUS ET AL.
  12. 12. 6. Expert commentary Technology, markets, and medical devices have matured to enable connected diagnostics as a tool for epidemiology, patient care and tracking, research, outbreak control, and AMR surveillance. However, to unlock this potential, digital tools must first add value at the point of the phenomenon, i.e. in a clinical context at the point of patient care. This value could be realized through assisting in automatic referrals for follow- up care, connecting a patient to nearby treatment centers, automatic ordering of drugs, or decision support for the health-care worker. These types of value-added activities encourage adoption of the technologies and, as a by-product, create comprehensive aggregate disease intelligence. Never before have millions of patient diagnoses been accumulated without data loss or integrity issues, geo-located to create real- time heat maps to track disease outbreaks while also triggering automated alerts to the relevant first responders, surrounding nations, national policy makers, and international organizations all automatically. This ability to add value at all levels of the health system simultaneously from a single data source is one of the most promising innovations in health-care. 7. Five-year view The future of disease intelligence will rely on latent outbreak algorithms assisting difficult political decisions that a country must make and allow these decisions to be made as early as possible for the right action to be taken. A faster, smarter response leads to earlier quarantine and a dramatic reduction in the cost of each outbreak as well as impact on morbidity and mortality [57]. Outbreaks cannot be prevented, but pan- demics can be prevented by establishing stronger disease surveillance and intelligence networks. Device makers are, understandably, deeply concerned about the unforeseen exposure of their deep instrument data and the potential for exposing proprietary data and their intellectual prop- erty to competitors. Some companies such as Thermo Fisher are capitalizing on this de-identified research data for their own instruments and are exposing it safely and in a controlled manner through their ‘Thermo Fisher Cloud’ for analytics in hopes of inspiring the next generation of research. Other device makers have responded by attempting to close off access to their deep instrument data, choosing protection over innovation. Careful, thoughtful business models are possible to safely harness this untapped potential in ways that can fundamen- tally transform the role connected diagnostics play in the very near future. It is the role of the global health community to communicate their strong desire for these innovations and to propose safe models that protect device makers’ intellectual property while ushering in personalized medicine 10 years faster into the market. Together, global health partners, MoH, and device manufacturers can bring the potential of connected diagnostic systems to fruition. Key issues ● Simple, rapid tests that can be used at the point-of-care (POC) can improve access to diagnostic services and overall patient management. However, ensuring quality of tests and of decentralized testing, supply chain management, increasing training needs, reporting and monitoring patient outcomes put tremendous stresses on fragile health sys- tems in resource-limited settings ● A connected diagnostic system has positive impact at both local level and for the entire health system. The rapid return of result can reduce delay in appropriate management of patients, including initiating treatment ● Digitising diagnostic results and utilizing data connectivity capacity to transmit diagnostic results from POC instru- ments, linked to quality assurance and supply chain sys- tems can facilitate health system strengthening and improve patient outcomes. ● Data privacy, confidentiality and security issues will become more complex as health data sources become more diverse, including those from mobile phone-based devices ● Digital technology has had a powerful impact on POC test- ing in resource limited settings. However, there are con- cerns about data governance and intellectual property. It is the role of the global health community to communicate their strong desire for these innovations and to propose models that protect device makers’ intellectual property and safeguard data confidentiality. Funding R Peeling would like to acknowledge funding from the UK Engineering and Physical Sciences Research Council, grant EP/K031953/1. Declaration of interest Authors N Gous, J Takle and B Cunningham are all either employees, shareholders or both, of SystemOne LLC, a connected diagnostics com- pany currently operating in the industry. The authors have no other relevant affiliations or financial involvement with any organization or entity with a financial interest in or financial conflict with the subject matter or materials discussed in the manuscript apart from those dis- closed. Peer reviewers on this manuscript have no relevant financial or other relationships to disclose. References Papers of special note have been highlighted as either of interest (•) or of considerable interest (••) to readers. 1. Dye C. After 2015: infectious diseases in a new era of health and development. Phil Trans R Soc B. 2014;369:20130426. 2. Shaw JLV. Practical challenges related to point of care testing. Pract Lab Med. 2016;4:22–29. 3. Nicols JH. Management of point of care testing. Acutecaretesting. org. 1999. [cited 2017 Nov 13]. Available from: https://acutecaretest ing.org/en/articles/management-of-pointofcare-testing 4. UNAIDS 90-90-90: an ambitious treatment target to help end the AIDS epidemic by 2020. [cited 2017 Nov 10]. Available from: www. unaids.org/en/resources/909090 5. United Nations. The sustainable development agenda. United Nations: Department of Public Information. 2016 Jan 1 [cited 2017 Nov 13]. Available from: http://www.un.org/sustainabledeve lopment/development-agenda/ 6. World Health Organization. Digital health for the End TB strategy: progress since 2015 and future perspectives. Meeting report. Geneva: WHO Press. 2017 Feb 7-8. EXPERT REVIEW OF MOLECULAR DIAGNOSTICS 11
  13. 13. 7. Deloitte Centre for Health Solutions. Connected health: how digital technology is transforming health and social care. United Kingdom: Deloitte Centre for Health Solutions. 2015. 8. Duggal R, Brindle I, Bagenal J. Digital healthcare: regulating the revolution. BMJ. 2018;360:k6. 9. Fionet: mobile diagnostics integrated with cloud information ser- vices. USAID mHealth Compendium Vol 2; page 62-63. [cited 2017 Nov 13]. Available from: http://www.africanstrategies4health.org/ uploads/1/3/5/3/13538666/fionet_-_mobile_diagnostics.pdf 10. Shekalanghe S, Cancino M, Mavere C, et al. Clinical performance of an automated reader in interpreting malaria rapid diagnostic tests in Tanzania. Malar J. 2013;12:141. 11. Mwisongo A, Peltzer K, Mohlabane N, et al. The quality of rapid HIV testing in South Africa: an assessment of testers’ compliance. Afr Health Sci. 2016;16(3):646–654. 12. Forsyth BW, Barringer SR, Walls TA, et al. Rapid HIV testing of women in labor: too long a delay. J Acquir Immune Defic Syndr. 2004;35(2):151–154. 13. Granade TC, Parekh BS, Phillips SK, et al. Performance of the OraQuick and Hema-Strip rapid HIV antibody detection assays by non-laboratorians. J Clin Virol. 2004;30(3):229–232. 14. Wedderburn CJ, Murtagh M, Toskin I, et al. Using electronic readers to monitor progress toward elimination of mother to child transmission of HIV and syphilis: an opinionpiece.Int J Gyn Obst. 2015;130:S81–S83. 15. Dimagi and Global Solutions for Infectious Diseases. Case study: reporting rapid diagnostic test results in Zimbabwe. 2014. [cited 2018 April 5]. Available from: https://dimagi.com/case-studies/ mhealth-hiv-zimbabwe/ 16. Sadiq T. (personal communication) 17. Saito S, Howard AA, Reid MJA, et al. TB diagnostic capacity in sub- Saharan African HIV care settings. J Acquir Immune Defic Syndr. 2012;61(2):216–220. 18. Van Gemert W. 2010-2015: uptake and impact of Xpert MTB/RIF. Joint partners forum for strengthening and aligning TB diagnosis and treatment. Geneva: WHO Press. 2015 Apr 27-30. 19. Pathmanathan I, Date A, Coggin WL, et al. Rolling out of Xpert MTB/RIF for tuberculosis detection in HIV-positive populations: an opportunity for systems strengthening. AJLM. 2017;6(2):1–9. •• An excellent article advocating for a patient-centered and systems-based approach to implementation of novel diagnos- tic technologies, such as the Xpert MTB/RIF. The diagnostic cascade should start with finding presumptive patients, to collecting, transporting, and testing sputum specimens; to reporting and receiving results; and to initiating and monitor- ing treatment, with real-time tracking of results and impact. 20. Cohen GM, Drain PK, Noubary F, et al. Diagnostic delays and clinical decision making with centralized Xpert MTB/RIF testing in Durban, South Africa. JAIDS. 2014;67(3):e88–e93. 21. Clouse K, Page-Shipp L, Dansey H, et al. Implementation of Xpert MTB/RIF for routine point-of-care diagnosis of tuberculosis at the primary care level. SAMJ. 2012;102(10):805–807. 22. Stevens WS, Gous NM, MacLeod WB, et al. Multidisciplinary point- of-care testing in South African primary health care clinics accel- erates HIV ART initiation but does not alter retention in care. J Acquir Immune Defic Syndr. 2017 Sep 1;76(1):65–73. 23. McGill University Health Centre foundation. HIVSmart App. 2016. [cited 2017 Nov 10]. Available from: https://www.muhcfoundation. com/current-projects/hiv-smart-app/ 24. Kehinde J. GxAlert SMS improves patient enrollment and manage- ment in Nigeria. 46th Union World Conference on Lung Health; 2015 Dec 2-6; Cape Town, South Africa. 25. Mustapha G, Jumoke O, Nwadike P. Assessment of GeneXpert MTB RIF program implementation and the challenges for enhanced tuberculosis diagnosis in Nigeria. SAARC J Tuberculosis, Lung Dis and HIV/AIDS. 2015;XXII(2): 1-7. 26. Futrell K. Laboratory point of care testing: a future outlook. POCT progression and the importance of connectivity. Indiana: Orchard Software. 2015 June. White paper. 27. Albert H, Nathavitharana R, Isaacs C, et al. Development, roll-out and impact of Xpert MTB/RIF for tuberculosis: what lessons have we learnt and how can we do better? ERJ Express. 2016. DOI:10.1183/13993003.00543-2016. 28. Glencross DK, Coetzee LM, Cassim N. An integrated tiered service delivery model (ITSDM) based on local CD4 testing demands can improve turn-around times and save costs whilst ensuring acces- sible and scalable CD4 services across a national programme. PLoS ONE. 2014;9(12):e114727. 29. Mwau M, Umuro M, Odhiambo CO. Experience from a pilot point- of-care CD4 enumeration programme in Kenya. Afr J Lab Med. 2016;5(2):439. 30. Mengesha E. The use of GxAlert eased the monitoring of GeneXpert machine performance in Ethiopia (Ethiopia). 20th Conference of the Union Africa; 2017 Jul 10-13; Ghana. 31. Stavelin A, Sandberg S. Essential aspects of external quality assur- ance for point-of-care testing. Biochemia Med. 2017;27(1):81–85. 32. Morley C. Monitoring, evaluation and reporting (MER 2.0) indicator reference guide. PEPFAR Guidance [Internet]. 2017 Oct 30 [cited 2017 Nov 6]. Available from: https://datim.zendesk.com/hc/en-us/ articles/218140663-Monitoring-Evaluation-and-Reporting-MER-2-0- Indicator-Reference-Guide 33. Cheng B, Cunningham B, Boeras DI, et al. Data connectivity: a critical tool for external quality assessment. Afr J Lab Med. 2016;5(2):a535. 34. Global Laboratory Initiative (GLI). Xpert MTB/RIF training package. Module 9: Troubleshooting. [cited 2017 Nov 13]. Available from: http://www.stoptb.org/wg/gli/TrainingPackage_XPERT_MTB_RIF. asp 35. Cobelens F, van Kampen S, Ochodo E, et al. Research on imple- mentation of interventions in tuberculosis control in low- and middle-income countries: a systematic review. PLoS Med. 2012;9 (12):e1001358. 36. Andre E, Isaacs C, Affolabi D, et al. Connectivity of diagnostic technologies: improving surveillance and accelerating TB elimina- tion. Int J Tuberc Lung Dis. 2016;20(8):999–1003. •• The WHO and research funding agencies have been advocat- ing for, and implementing, data-sharing policies but efforts to increase access to research data for health gains remain diffi- cult. The use of new-generation diagnostic platforms has trig- gered thinking about the potential utility of real-time analysis of national data, and how diagnostic connectivity could further improve epidemiological surveillance and guide tar- geted public health responses. 37. Global Laboratory Initiative (GLI). Quick Guide to TB Diagnostics Connectivity Solutions [Internet]. 2016 Oct [cited 2017 Nov 6]. Available from: http://www.stoptb.org/wg/gli/assets/documents/ gli_connectivity_guide.pdf 38. Alamo ST, Kunutsor S, Walley J, et al. Performance of the new WHO diagnostic algorithm for smear-negative pulmonary tuberculosis in HIV prevalent settings: a multisite study in Uganda. Trop Med Int Health. 2012;17:884–895. 39. Loveday M, Thomson L, Chopra M, et al. A health systems assessment of the KwaZulu-Natal tuberculosis programme in the context of increasing drug resistance. Int J Tuberc Lung Dis. 2008;12:1042–1047. 40. Tafuma TA, Burnett RJ, Huis in ‘T Veld D. National guidelines not always followed when diagnosing smear-negative pulmonary tuber- culosis in patients with HIV in Botswana. PLoS One. 2014;9:e88654. 41. van’t Hoog AH, Onozaki I, Lonnroth K. Choosing algorithms for TB screening: a modelling study to compare yield, predictive value and diagnostic burden. BMC Infect Dis. 2014;14(1):532. 42. Buckeridge DL, Okhmatovskaia A, Tu S, et al. Understanding detec- tion performance in public health surveillance: modeling aber- rancy-detection algorithms. J Am Vet Med Assoc. 2008;15:760–769. 43. Tom-Aba D, Olaleye A, Olayinka AT, et al. Innovative technological approach to ebola virus disease outbreak response in Nigeria using the open data kit and form hub technology. PLoS ONE. 2015;10(6): e0131000. 44. Westcott L Doctors without borders slams slow international response to Ebola. Newsweek [Internet]. 2015 Mar 23 [cited 2017 Nov 6]. World: [About 1 screen]. Available from: http://www.news week.com/doctors-without-borders-slams-slow-international- response-ebola-316089 12 N. GOUS ET AL.
  14. 14. 45. Scott LE, Schnippel K, Ncayiyana J, et al. The use of national Xpert MTB/RIF’s cycle threshold (Ct) as an audit indicator for program and laboratory performance. 46th World Conference on Lung Health; 2015 Dec 2-6; Cape Town, South Africa. 46. Kelly GC, Tanner M, Vallely A, et al. Malaria elimination: moving forward with spatial decision support systems. Trends Parasitol. 2012;28:297–304. 47. Peter T, Zeh C, Katz Z, et al. Scaling up HIV viral load – lessons from the large-scale implementation of HIV early infant diagnosis and CD4 testing. J Int AIDS Soc. 2017;20(S7):e25008. 48. Habiyambere V, Ford N, Low-Beer D, et al. Availability and use of HIV monitoring and early infant diagnosis technologies in WHO member states in 2011–2013: analysis of annual surveys at the facility level. PLoS Med. 2016;13(8):e1002088. • This survey showed that in 2013, only 13.7% of existing CD4 capacity and 36.5% of existing viral load capacity were being utilized across 127 reporting countries for a variety of reasons. Having a dashboard may have allowed investigation into causes and facilitate better utilization. 49. Zarei M. Portable biosensing devices for point-of-care diagnostics: recent development and applications. Trends Anal Chem. 2017;91:26–41. • Good review of recent developments in biosensors that can be used at the point of care with data connectivity capacities. 50. Laksanasopin T, Guo TW, Nayak S, et al. A smartphone dongle for diagnosis of infectious diseases at the point of care. Sci Translational Med Feb. 2015;7(273):273. 51. Prater VS. Confidentiality, privacy and security of health informa- tion: balancing interests. Biomedical and Health Information Sciences. 2014. [cited 2017 Nov 14]. Available from: http://healthin formatics.uic.edu/resources/articles/confidentiality-privacy-and- security-of-health-information-balancing-interests/ •• An informative article that explains the different concepts of confidentiality, privacy, and security with regard to health information. As electronic data is coming from more sources, including mobile phone devices, it is expected that regulatory compliance and ethical considerations will present more chal- lenges for health-care organizations. 52. Republic of South Africa. Government gazette, act no 4 of 2013: protection of personal information act, 2013. Cape Town, South Africa: The South African Government. 2013 Nov 26. 53. The EU General Data Protection Regulation (GDPR) (Regulation (EU) 2016/679). European Parliament and Council. 2016 Apr 27 [cited 2017 Nov 6]. Available from: http://www.eugdpr.org/ 54. Data Protection Act 1998 (c29). United Kingdom Act of Parliament. 1998, Jul 16 [cited 2016 2017 Nov]. Available from: http://www. legislation.gov.uk/ukpga/1998/29/contents 55. EU-US Privacy Shield. Privacy shield program overview [Internet]. Washington (DC): US Department of Commerce. [cited 2017 Nov 6]. Available from: https://www.privacyshield.gov/Program-Overview 56. Kostkova P, Brewer H, de Lusignan S, et al. who owns the data? Open data for healthcare. Front Public Health. 2016;4:7. 57. Zhang H, Lai S, Wang L, et al. Improving the performance of out- break detection algorithms by classifying the levels of disease incidence. PLoS ONE. 2013;8(8):e71803. 58. Jani IV, Peter TF. How point-of-care testing could drive innovation in global health. N Engl J Med. 2013 Jun 13;368(24):2319–2324. 59. Boeras DI, Nkengasong JN, Peeling RW. Implementation science: the laboratory as a command centre. Curr Opin HIV AIDS. 2017;12 (2):171–174. EXPERT REVIEW OF MOLECULAR DIAGNOSTICS 13

×