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<h2 class="hd hd-2 unit-title">Disruption of Global Health by Information and Communication Technologies</h2>
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<h4>The Birth of Mobile Telehealth</h4>
<p>The arena of global health has, perhaps, seen the most explosive growth in mobile tele-heath applications in the last decade, due to the ever expanding mobile phone ownership and connectivity across the world.In many countries, frontline community health workers (CHWs) serve as the only link to the health system for clients residing in rural or remote locations in the face of the global shortage of trained medical professionals. While clients in these settings are constrained by the costs, time and large distances to attend medical facilities, CHWs often times work in isolation from the health system they are meant to serve, under the constraints of poor communications infrastructure, and with little to no formal medical training. Mobile tele-health has helped ameliorate these constraints in task shifting by enhancing non-clinical staff's capacity to identify, stabilize and refer patients through the use mobile technology for provision of job aids, clinical decision support algorithms, remote consultations, and data sharing. Mobile devices have also been used as a medium for continuing medical education among health providers and CHWs in resource-limited settings. Mobile tele-health applications have been demonstrated in supporting paramedical professionals in ambulances, mobile telemedicine units, and for providing remote medical assistance during disaster management. Examples of these task shifting applications include:</p>
<p>Oscan, a scanning tool integrated with a camera phone, that can be used to document oral lesions. Images can be taken by health workers with basic knowledge of camera phones, and shared wirelessly with remote experts for diagnosis of oral cancer.</p>
<p></p>
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<li>
<p>eC3, a mobile phone camera-based cervical cancer screening tool which allows local health workers to capture images of suspicious cervical lesions and share them with remote experts for cervical cancer diagnosis.</p>
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<li>
<p>Small portable ultrasounds (e.g., General Electric's <i>VScan</i> , Mobisante's<i>MobiUS SP1</i> and Sigonostic's <i>Sinos</i> portable ultrasound device) with handheld touch screen monitors or the ability to link to smartphones permit imaging on-the-go by health workers and at a fraction of the cost of traditional facility-based ultrasound machines.</p>
</li>
<li>
<p>The <i>Chipatala Cha Pa Foni </i> 24-hour hotline service in Malawi which allows health workers to use a decision support software and electronic medical records to provide maternal and child health information, advice, and referrals to clients with access to mobile phones, potentially reducing time and costs of unnecessary travel to distant medical facilities for clients seeking health care.</p>
</li>
<li>
<p>Mobile technology platforms such as Sana which link to electronic medical records and offer a programmable workflow interface for sharing medical information (e.g., audio, images, location-based data, text) and decision support. Sana has been used in rural South India to provide decision support to frontline health workers screening for precancerous and cancerous oral lesions, and linking them to specialists at dental hospitals.</p>
</li>
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<p>Closed user groups, such as Switchboard’s MDNet in Ghana and Liberia, which empower different cadres of health providers to communicate and hence, improve their ability to provide quality medical care to patients in under-resourced settings.</p>
</li>
<li>
<p>The <i> eMocha TB Detect </i> application which streams multimedia education content and provides tuberculosis screening tools that can be accessed via mobile phones in resource-limited settings</p>
</li>
<li>
<p>The use of mobile phones to transmit images of patient x-rays and wounds during the 2010 earthquake in Haiti for consultation with medical experts in the US.</p>
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<p>These examples of task-shifting illustrate how mobile tele-health can be leveraged to allow lesser-trained workers to perform early phases of screening, thereby reducing the burden on advanced clinical staff, who may be in short supply.</p>
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<h4>The Promise of (and Hype around) ICT in Global Health</h4>
<p>The information and communications technologies (ICT) underlying the implementation of mobile telemedicine are rapidly evolving. Wearable tech and smartphones have taken the place of personal digital assistants and blackberries just in the matter of the last decade. While evolution in technology has been accompanied by an increase in efficiency and quality, it also implies new costs and efforts in upgrading existing infrastructures, the need for new standards and guidelines governing the use of new technologies for medical care, and the need for new methodologies for their evaluation. Many challenges remain in the implementation and testing of tele-health programs:</p>
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<li>
<p>Despite the long history of tele-health, there are few systematic evaluations of its efficacy and cost-effectiveness. Currently, the data to support clinical and cost-effectiveness of classical and mobile tele-health interventions are mixed, although the benefits of these interventions as a substitute for in-person care are well accepted.</p>
</li>
<li>
<p>While many patients welcome the opportunity to be connected to medical care or information irrespective of their location, others find this substitution to be impersonal and less trustworthy compared to a face-to-face encounter with the medical provider, especially in instances when medical prognosis is poor. However, there is data to suggest that the acceptability for using personal mobile devices for receiving health information and medical care is high, particularly among younger generations.</p>
</li>
<li>
<p>Acceptability of mobile tele-health among health providers also remains a challenge. Mainstream medicine has been slow to adopt tele-health services due to lack of standards and guidelines for remote medical care, issues with reimbursements, and licensure and legal challenges surrounding the practice of tele-health across state and national boundaries, to name a few. The future of mobile tele-health relies on the development and implementation of standards and legislation that overcome barriers to the sustainable integration of such services within mainstream medicine.</p>
</li>
<li>
<p>There is no doubt that the evidence base for mobile tele-health is being strengthened through research efforts, however, there is still a lingering skepticism regarding its scalability and sustainability as few mobile tele-health projects have been demonstrated at scale to date beyond initial periods of funding.</p>
</li>
<li>
<p>Other challenges in the mainstream adoption of mobile tele-health include patient privacy and security of medical data being transmitted wirelessly. Access to data is also an issue, with the current system of electronic medical records being inaccessible to patients involved in disease self-management. Data portability and software interoperability between different applications is another important challenge if telemedicine applications are to be used universally, highlighting the critical need for uniform data dictionaries and standards.</p>
</li>
</ul>
<p>Several experts argue that mobile tele-health programs will continue to play a critical role in health systems, despite the many challenges in implementing and testing such programs. While the road to ubiquitous healthcare may be long, with increasing mobile phone coverage and reducing costs of communication technologies, especially in the developing world, the promise of putting health information and medical care at the fingertips of every human being on earth is slowly coming to fruition.</p>
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<legend id="3f789ae7e52f4353894255547ea3fe84_2_1-legend" class="response-fieldset-legend field-group-hd">Challenges to tele-health from a global health perspective include:</legend>
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<h2 class="hd hd-2 unit-title">Introduction to Data Science and Management</h2>
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<h4>A New Era of Data-Driven Global Health</h4>
<p>The primary use of health data is to improve delivery of clinical care to individuals. In high resource health settings this is exemplified by the use of electronic medical records (EMRs) to deliver improved services by collating clinical records, generating patient-specific alerts and automating outputs. In the United States, uptake of EMRs has been promulgated by a 2009 USD 27 billion federal government commitment to have EMRs used by hospitals and health care providers. Although there are technical challenges in implementation, adoption of EMR in primary care is steadily increasing and has been linked to cost savings and improved clinical care. However, health records provide only a fragment of information on the determinants of population health. The promise of big data for health is in developing new insights from varied sources of information being linked together, a process called secondary data use.</p>
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<h4>Secondary Use of Health Data</h4>
<p>Secondary data use encompasses all analysis beyond the primary intended use - i.e. individual health care delivery in the case of EMR. We divide secondary data use into two broad entities. Direct secondary data in health includes clinical audit, research and population level health projects. This data is sourced directly from health records, collated and analyzed to inform future care at both the individual and population level. The critical characteristic is the creation of this data during routine provision of individual health care. In contrast, a vast amount of information can be sourced from data not intended for health purposes such as death certificates, hospital and physician billing data, vehicle registration information, criminal records, public health surveillance, municipal zoning registries, commercial databases, census databases and so on. When carefully assembled together, these multiple sources of information can be linked to inform population health interventions. This data repurposing is termed indirect secondary data use in health. This data was not initially created for the provision of individual health care, but can be used to inform population health strategy or targeted care delivery.</p>
<p>Secondary data use, whether direct or indirect, makes it possible to use information routinely collected to better understand risks and determinants of health for populations and improve disease management. Thus, secondary data use provides a mechanism to tackle determinants of health status that are unrelated to direct service provision. This chapter outlines the risks and opportunities of secondary uses of data in health. Although we focus primarily on direct secondary data use for health, the principles apply to both direct and indirect uses. The role of secondary data use in high resource setting is then contrasted with opportunities in low- and middle-income countries (LMIC), before challenges and future steps are discussed.</p>
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<h4>Data Science in Global Health</h4>
<p>The diffusion of new technology in LMIC is commonly a mix of appropriation, diffusion and often the 'leap-frogging' of intermediate development phases. 'Leapfrogging' is starkly exemplified by the penetration of mobile phones in low resource settings over the last 15 years without a preceding period of fixed line telephone ownership. The use of mobile phones has already provided a pertinent example of indirect secondary data use.</p>
<p>Buckee and colleagues demonstrated how tracking mobile phone use could help fight malaria by revealing where to focus mosquito eradication efforts. They used mobile phone use to analyze the regional travel patterns of nearly 15 million individuals over the course of a year in and found that people making calls or sending text messages originating at the Kericho tower were three times more likely to visit a region northeast of Lake Victoria, a malaria hot spot. The Kericho tower thus represented a waypoint for transmission of malaria. A similar model has been used in the 2014 Ebola outbreak.</p>
<p>The incentives collection and use also differ between high and low resource settings. Proprietary systems dominate the EMR market in the developed world and data may be 'owned' by health care providers or consortiums. However, different market dynamics in LMIC mean that more mHealth and eHealth projects are conducted by governments and not for profit actors. These providers tend to use open source EMR products and often have a stated goal of improving population outcomes in addition to individual care. However, ad hoc mHealth systems may not follow interoperability standards. This can complicate data linkage and limit analysis.</p>
<p>Indirect use of secondary data is also influenced by differing incentives. In many parts of the world, reliable data may be more likely to be collected by mobile phone operators or banks than government-directed health data sources. However, the private sector may have strikingly different priorities and commercial sensitivities determining the use of data. These issues affect the potential use of indirect secondary data in the interest of humanitarian or public health outcomes. Paradoxically, an uncritical urge to share data of vulnerable populations in order to 'do good' can increase the risk of inadequate consultation or unforeseen consequences. Authors of a London School of Economic report caution that 'the challenge for developing countries and humanitarian operations is that we have a tendency to think and act on behalf of the citizens and patients' and call for a rights based approach to data sharing and collection.</p>
<p>The staggering pace of use of primary and secondary data use for health in LMIC may offer novel opportunities to embed appropriate mechanisms for secondary health data use in first generation platforms. One of the most promising opportunities for big data in global health can be seen in India's ambitious personal identification program. In 2010, the government of India began issuing'Aadhaar' cards with unique identifying numbers to all 1.2 billion of its citizens. Biometric identification captured through fingerprints and iris identification offers the opportunity for generating and monitoring health and social data. Use of Aadhaar linked to immunization records could help ensure individual children received the appropriate vaccine according to national schedules. Furthermore, secondary analysis of de-identified data may make it possible to identify areas with low immunization rates necessitating targeted immunization campaigns.</p>
<p>One of the greatest challenges in fulfilling the potential of secondary use of data in resource-limited settings is the ability to analyze quantitative outputs. The uptake of mHealth in LMIC reflects low barriers to entry; namely widespread mobile phone ownership and the rapidly appreciable utility of text messages or other tangible rewards for participation. In contrast, the value of the secondary use of health data resides in centralizing and linking datasets, which requires technical skills, specialized equipment, interoperability standards, coherent collection, analytical systems and regulatory oversight. Moreover, the distance between individuals contributing data and systems outputs and benefits can be immense. However, signs of data ownership from LMIC are emerging; for example, a new network, critical of existing data sharing approaches, is collating public health research data from health and demographic surveillance systems of over 3 million people in 48 populations. Overcoming the analytic capacity challenges in LMIC may make it possible to leapfrog the nascent secondary use of health data in high resource settings and embed secondary use capacity in mHeatlh and eHealth projects in low resource settings.</p>
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<h4>Data Integration: The biggest challenge</h4>
<p>Linkage of data sets for the improvement of health remains in its infancy in LMIC. It offers both unprecedented promises, but also great challenges. Informed, reflective and resourced stewardship is critical to enable positive outcomes. However, the structures for global health governance are relatively fragile. The United Nations established 'Global Pulse' in 2009 as an initiative of the Executive Office. The division is charged with 'fostering development of the analytical, technological and organizational capacities that decision makers need to access and utilize new digital data sources and real-time analytics'. However, data protection standards for Global Pulse are grounded in a 1990 UN resolution named 'guidelines for the regulation of computerized personal data files'- which remains an iconic example of how the division falls short of providing much needed contemporary guidelines for governance.</p>
<p>Guidance efforts have been made in the World Economic Forum's Global Health Data Charter, framed around the vision for 'better data for better health'. Eight key data health challenges have been identified and 'enabling' activities highlighted. However few practical steps are articulated. Given the scope, cost and risks of big data projects, far stronger governance is needed. Unfortunately, the global health community has a patchy record of cohesive governance and stewardship of technical developments. Optimizing the application of big data is much more than establishing confidentiality safeguards and minimum standards. A broad effort to establish enforceable interoperability standards is imperative to creating linkages between datasets that can offer insight. Big data then needs a strategically driven approach to maximize benefits in the global health setting. Global health governance needs to move from a reactive model to a proactive, norm forming, approach.</p>
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<p>The following video is presented by:</p>
<p>Leo Anthony Celi MD MS MPH<br />Assistant Professor of Medicine, Harvard Medical School<br />Principal Research Scientist, Massachusetts Institute of Technology</p>
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<h3 class="hd hd-2">Health Data Science in LMICs</h3>
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