Fatima is a 37-year-old in 2025 living in a large African city, pregnant with her third child, and also diagnosed with hypertension. She manages the majority of her health care from her smartphone. At the beginning of her pregnancy, she contacted her primary care center via text message. She received a link to complete her prenatal survey online. An algorithm determined her risk profile, which flagged her for an early midwife appointment because she has hypertension.
Most of Fatima’s appointments, however, take place at her house or down the street at her children’s school, where community health workers and midwives meet community residents for checkups and to answer questions about their health conditions. She also belongs to a WhatsApp counseling group facilitated by a health worker for pregnant women in her community so they can share their experiences and learn from one another. Through this group, she receives personalized weekly updates on her pregnancy, including how her baby is developing, changes she can expect in her body, and dietary recommendations. Receiving care during her pregnancy is much easier than when she was a child, and her parents had to save up for taxi fare or spend an entire day taking buses to the hospital and waiting for a doctor. She also has a wearable device on her wrist that tracks her exercise and heart rate. Recently, blood pressure devices have become available for rent at the market near her house, so she goes there every Monday, plugs the device into her phone, and takes her blood pressure measurements. Results are automatically uploaded to her electronic health record (EHR), and she receives direct communication from the midwife should her blood pressure increase.
Her EHR is stored in the Cloud but is at her fingertips when needed during appointments with different health care providers. For her last appointment, she hired an Uber driver from her phone and paid for her portion of the visit using the health savings section in her m-Pesa account, with the rest of the cost being covered by her insurance, which was sold through Google because she does not have access to employer insurance. After her appointment, she reordered her medication through Amazon, and stopped at one of its delivery centers near her house the next day to pick it up.
Health care systems across the world have been experiencing changes due to emerging digital technologies and tools, and many more exciting technological advances are on the horizon. They offer the potential for a new health care paradigm designed to support a coordinated patient journey throughout the life span, with high levels of communication and collaboration among health care teams. These digital health technologies can be amplified even further by using the systems approach described in Chapter 2 and focusing on the priorities of patients across their journeys—revamping primary care to be more easily navigable and delivered where
the patient is instead of limiting care delivery to brick-and-mortar health care facilities. Such a proactive approach can yield benefits in the face of changing epidemiologic burdens and demographic shifts. Costa Rica, for example, began reforming its primary care system in the 1990s, and between 2000 and 2012, deaths due to noncommunicable diseases (NCDs) decreased by 3 percent even as they rose globally (PHCPI, 2015). Along with these technological and systems changes, attention to the notion of patient involvement and patient ownership has been growing worldwide. The health care system of the future will need to account for more active patient and provider interactions and leverage the input of patients for better-designed digital health tools and more efficient care pathways.
While it was beyond the scope of this study to provide a full review of the future of health care, the committee remained cognizant of these changes, which entail both opportunities and risks for the health care sector and have important implications for the quality of care. For some countries, these scenarios and technologies will not be a reality for many years. Nonetheless, technology is advancing rapidly, and health care in every setting can work to tap into the potential it provides.
This chapter begins by exploring global trends in health care and the growing number of digital health technologies that are coming into play across various countries and settings. Next, it examines the implications of these changes for quality, especially in terms of person-centered care, accessibility, and equity. It then describes the benefits of moving from a reactive to a predictive system. Subsequent sections address the organizational and care delivery changes that need to be made to leverage these advances and the challenges that need to be kept in mind throughout this process to maintain and assure high quality. The chapter ends with a summary and recommendations.
Historically, health care has been paternalistic: power has rested with providers and health care staff. However, this situation is shifting, as patients are beginning to play a more active role in their health. The potential for low-resource settings is possibly the most exciting, as digital technologies and the shift to consumer ownership of health care can allow populations in low- and middle-income countries (LMICs) to leapfrog high-income country systems and avoid mistakes that have been made elsewhere. Consumer expectations in LMICs appear to match this trend. When respondents to a 2017 survey on global trends in health care were asked whether they expected their quality of care to improve or worsen in the coming years, the most frequent predictions for improvement came from mainly
middle-income countries, while the most frequent responses for worsening came mainly from high-income countries (see Figure 3-1).
Health care leaders are also beginning to view health care more through a wellness lens than the traditional perspectives of disease intervention and provision of care once a patient becomes sick. Moreover, health care organizations are also extending their reach, working to deliver care through more innovative methods in the community instead of just in hospitals, and understanding that the journeys of their patients take place in many locations over time, not just at one point. Implementing such an approach may require more complex interactions and understanding on the part of health care organizations, but with the wealth of community, government, and civil society partners and increases in connectivity and virtual tools, now is the time for systems to use these shifts as opportunities to meet the principles outlined in Chapter 2. At the same time, however, as discussed later in this chapter, these advances are not without risks, so while they present many opportunities, careful design and oversight are needed to ensure that they assure and improve the quality of care.
Use of Systems Thinking and Digital Health Technologies
Smart devices are creating revolutionary changes in health care by allowing people to accurately monitor their health remotely. These developments often occur outside of traditional settings to enable individual monitoring of health and empower people to take more responsibility for their own health (JASON, 2017). Much of this progress is attributable to increases in connectivity. While more than 45 percent of the world’s population does not utilize the Internet (World Economic Forum, 2016), the current goal of the International Telecommunication Union (ITU) is to increase this proportion to 55 percent of the population by 2020, up from 29 percent in 2010 (ITU, 2014; World Economic Forum, 2016). Given this increase, the wireless infrastructure has enabled a leapfrogging of the process typically required to connect rural areas, leading to plummeting costs and a lower bar of entry for those with limited income. In fact, toward the end of 2015, 83 developing countries had achieved the United Nations (UN) Broadband Commission’s affordability target for broadband Internet access of services costing less than 5 percent of monthly gross national income per capita (Broadband Commission for Sustainable Development, 2016). Even though fast connections, broadband, 3G, or better mobile connections reach only 30 percent of the world’s rural population, they are available to almost 70 percent of the world’s overall population (World Economic Forum, 2016). Similarly, mobile phone usage is prevalent and is projected to grow from an estimated 62.9 percent of the population worldwide in 2016 to 67 percent by 2019 (Statista, 2018a). This digital
revolution has the potential to provide individuals with increased access to care and empower them to take more responsibility for their own health (JASON, 2017).
Digital Health Technologies and Tools
With the explosion of new digital technologies in the past decade and new opportunities emerging each year, it is becoming possible to change and advance medicine and health care delivery systems in unprecedented ways. While some changes may initially be limited to high-income countries and to people with the resources to afford them, others have already become available to communities in low-income settings worldwide. Innovation is routinely of prime interest to companies in the information and communication technology (ICT) sector, and accordingly, many partnerships have been forming to improve health systems. For example, although initially for military applications, the use of aerial unmanned drones has increased commercially, and organizations are currently testing them to deliver blood supplies to remote areas of Rwanda. In just the past year, the drones have made more than 950 deliveries of essential blood supplies to Rwandan communities in need. Additional uses can include delivery of emergency defibrillators or drug overdose antidotes where needed (Nuki, 2018). Figure 3-2 shows the progression of technologies within the health sector.
The committee sees these tools as an avenue to strengthening health care delivery and improving quality, with exciting prospects. Corresponding to this explosion of tools, myriad terms for describing these types of technology have emerged. The committee has chosen to use the term “digital health technologies,” which include mobile health, health information technology, wearable devices, telehealth and telemedicine, big data, and personalized medicine (Iyawa et al., 2016). As discussed below, for these technology advances to assure high-quality, ethically sound services, a dedicated effort will be required on behalf of manufacturers, regulators, health care providers, and patients.
It is also important to recognize that the successful uptake and wider adoption of efficient and effective digital health systems will be determined by the integration of bottom-up and top-down approaches (see Table 3-1). The bottom-up approach focuses on how distributed tools are developed to gather and share data with the users of a digital health ecosystem, while the top-down approach considers how the ecosystems as a whole are developed to enable proficient use of the data among a network of agents.
Effects on the Patient Journey
The increasing use of wearable health devices, such as Apple Watch and Fitbit, is making it possible for people to take greater ownership of their health. Furthermore, such devices are allowing people to become more aware of their risk behaviors and lifestyle choices, thereby creating a bridge to the formal health care system. For example, patients with chronic conditions can use their smartphones and paired Bluetooth devices to take vital measurements and transmit them digitally to a general provider or special-
|Digital Health||Bottom-Up Approach||Top-Down Approach|
|Rationale||Enable ubiquitous gathering of personalized data||Enable data aggregation, access, and manipulation for health care system service purposes|
|Methods||Innovation in materials, engineering, and computing||Ecosystem design by innovation in information technology and computer science|
|Implementation||New devices and sensors to ensure portability||Ecosystem models of hardware and software to manage data|
SOURCE: Buckle et al., 2018.
ist to evaluate.1 Such devices have been found to be useful in emergency settings as well. For example, in April 2018 in the United States, a healthy 18-year-old woman, although sitting still, was alerted by her Apple Watch of an alarmingly high heart rate. After repeated alerts, her family sought care at the emergency room, where they discovered she had an underlying condition in which her kidneys were failing (Capatides, 2018).
As people continue to manage their health in these ways, the balance of power in health care will need to shift accordingly to include them as part of the decision-making team. Technology companies are laying the groundwork for this shift. In early 2018, Apple rolled out a feature that allows people to access their EHRs on their phones. This capability makes it possible for Apple’s underlying health app, Apple Health, and the data it stores to be connected with other digital tools, allowing people increasingly to make health decisions independently (Chopra and Rab, 2018). Additionally, consider the launch of MyHealthBank, a Web-based service in Taiwan that gives patients access to their entire medical record. Because Taiwan is a single-payer system, this service can be scaled nationwide, thereby enabling the country’s entire citizenry to become engaged more actively in health care decisions (Li et al., 2018). As such innovations continue to be introduced, people’s interactions with the health care system may become more self-directed and frequent, thereby resulting in better health management.
Even payment for health care services is being revolutionized, with the process becoming much more streamlined and easier for patients. In Kenya, for example, in the wake of the popularity of its mobile payment system through the M-Pesa platform, a new infrastructure with similar usability called M-Tiba was established for health care. It provides health care financing for patients, such as vouchers, managed funds, and low-cost insurance, and allows both insurers and patients to see where the money is being spent. This digital technology reduces transaction costs and improves data collection, while also creating opportunities for links to safety. M-Tiba is linked to the maintenance of quality standards through such programs as SafeCare,2 which establishes a national system for quality assessments and provides LMICs with stepwise quality improvement plans that are often linked to loans. If treatments and procedures are approved via the SafeCare quality standards, the money in a person’s M-Tiba account is transferred
2 SafeCare was developed to provide standards and a grading system for health care quality; an incremental quality improvement process that is divided into achievable, measurable steps; and a health financing model supported by the private sector. SafeCare standards have been implemented in more than 800 primary and secondary facilities in six sub-Saharan African countries (Ghana, Kenya, Namibia, Nigeria, Tanzania, and Zambia) (Johnson et al., 2016).
to the health care facility, creating a much more seamless process for the individual, with quality safeguards built in.
How people interact with the system is changing worldwide as well. Today, patients have often consulted with “Dr. Google” before even having their first professional medical consultation.3 This shift has created challenges for physicians in light of the volume of fake and irresponsible information on the Internet and in social media. A survey showing the levels of social media penetration among Latin American countries found the highest level in Uruguay (72 percent) and the lowest in Venezuela (44 percent) (Statista, 2018b). National health authorities thus have an opportunity to increase their contributions of quality health information to the Internet and social media. Patients also engage with their physicians today through other nontraditional modes of communication, such as text messages, telemedicine video chat, online portals, and even social media. In Chile, for example, the National Health Insurance program reimburses public health care providers for 100 percent of the cost of telemedicine services, including tele-radiology, tele-dermatology, tele-ophthalmology, and general tele-consultations. For communications occurring via social media, new ethical standards will be needed to balance this opportunity for access with the right of patients to quality medical advice, with professionalism, and with issues of litigation risk. See Box 3-1 for a description of China’s experience with the explosion of the WeChat platform for health care and the opportunities it provides for quality care, especially in terms of person-centeredness, effectiveness, and efficiency.
Artificial intelligence (AI) can take a variety of forms in health care, including machine learning, predictive algorithms, speech recognition, computer vision, and digital medical consults, ideally tailored to a particular region or community. AI can use large databases to recognize trends in disease manifestations and treatment outcomes, and when combined with the EHR, can be used to predict an individual’s risk for disease and to create a precise, personalized treatment plan (Krisberg, 2017). Truly taking AI and virtual care to the next level, the Center for Body Computing at the University of Southern California opened a Virtual Care Clinic in 2016. Through this operation, patients drive their care experience through an app that connects them with avatars of their real-life doctors. Mercy Hospital in Saint Louis, Missouri, has also created a “hospital without beds” through virtual care that monitors 2,431 patient beds (Frenk, 2006; Frenk and Goómez-Dantés,
3 Personal communication, T. Herbosa, paper read at Improving the Quality of Health Care Globally, Meeting 3, 2018.
2017). These virtual doctors are created with AI so they are able to answer thousands of questions on a variety of diagnoses. Patients have even been found to be more forthcoming and to share more information with the avatar version of their doctor than with its real-life counterpart.4
AI can also be used to analyze radiographic images (Jha and Topol, 2016) and dermatologic findings (Beam and Kohane, 2016). In the United Kingdom, AI is being used to interpret mammograms and evaluate patient data to produce highly accurate diagnostic information 30 times faster than is possible for a human. This capability allows clinicians to determine
4 Personal communication, L. Saxon, University of Southern California, February 28, 2018.
breast cancer risk efficiently and reduces the need for unnecessary biopsies (Griffiths, 2016). This advance has the potential to improve the quality of diagnoses and follow-up care in settings where the availability of radiologists, dermatologists, and other specialists is limited.
For any system to perform effectively, the role of the human in designing, interacting with, or completing the system must be recognized. All systems, even autonomous ones, involve human contributions (Buckle et al., 2018). Therefore, understanding the capabilities and limitations of humans within complex systems will be essential. A key misunderstanding is the implicit assumption that the capabilities of AI will automatically overcome the problems of large amounts of complex and imperfect health data. But these AI systems will be created, operated, and informed by humans. Thus, the potential exists for erroneous information to guide AI decision making and feedback, thereby causing harm or breeding distrust of AI applications for health (Crider, 2018). Facial recognition, for example, which is being tested by police in London, has been wrong as much as 98 percent of the time (Crider, 2018). Websites, apps, and companies have already emerged that, based on the available information, appear questionable (JASON, 2017). Guidelines and policies are needed to hold users of AI systems, as well as those who build them, accountable (Crider, 2018).
Medical Advances in Other Areas
In addition to the increasingly familiar digital health technologies of today, other medical advances offer exciting potential for health care and quality as well. Point-of-care (POC) testing, gene editing, precision medicine, robotics, blockchain technology, and regenerative medicine are a few examples of the innovations of the future. POC testing can aid clinicians in the rapid diagnosis and treatment of diseases at the time of patient contact in a variety of settings (NIBIB, 2013). It is currently being used to improve health care through the use of noninvasive, rapid, and accurate tests for diagnosing malaria (Abbott, 2018b), filariasis (Abbott, 2018a), and sexually transmitted diseases (WHO, 2018d), among other applications. A portable, cell phone–based transmission polarized light microscope system has been developed for imaging malaria pigment that is normally difficult for technicians to identify without polarized light. This design is low cost and easy to use, allowing for higher detection rates of malaria in LMICs (Pirnstill and Coté, 2015). Another example of POC testing is the use of a pocket ophthalmoscope (Blaikie et al., 2016) for patients who may not have access to ophthalmologists or diagnostic imaging tools. The Arclight, a pocket-sized ophthalmoscope, otoscope, and loupe powered by a solar-charged lithium battery (Arclight Medical, 2018), has been used to screen infants for retinoblastoma in Kenya and Uganda, trachoma in Ethiopia, and
middle-ear disease in Malawi. During discussions at a public meeting held in Nairobi for this study, the committee was briefed on an innovation called Mama Ope, a biomedical smart jacket engineered in Uganda that can aid in rapid diagnosis of pneumonia in young children without the use of imaging and is much more accurate than a doctor’s physical exam (MamaOpe, 2018). To diagnose pneumonia, the jacket monitors the patient’s chest and lung sounds, breathing rate, and temperature, and can sense the severity and point of infection, avoiding misdiagnosis as malaria and the waste of irrelevant drugs. Given the shortage of doctors in Uganda, many patients are unlikely to see a doctor and instead must see a less-skilled health worker for a physical examination, which often results in the disease being misdiagnosed as malaria (Koburongo, 2018).
Another recent advance, gene editing, entails using biochemical tools to edit DNA sequences in living organisms (NASEM, 2015; NLM, 2018). Several approaches to gene editing, including clustered regularly interspaced short palindromic repeats (CRISPR) (Broad Institute, 2018), are being developed, with the goal of making it possible to correct mutations at precise locations in the human genome, thereby preventing and treating genetically linked diseases (Hsu et al., 2014). CRISPR systems are being used to treat genetic disorders in animals, and may in the future become a promising method for preventing and treating such genetically linked conditions as sickle cell disease (King, 2018) and using mosquito knockouts to control malaria (Dong et al., 2018).
Precision and regenerative medicine are other new areas of clinical care that hold promise for improving future health. As a future technology, regenerative medicine has the potential to improve care in LMICs through the creation of biocompatible substitutes for transfusion requirements, treatments for inherited blood disorders, hepatocyte transplants for liver disease, and autologous cell treatment for regeneration of heart muscle (Greenwood et al., 2006). The infrastructure for these applications is already being established in LMICs, including the development of a framework of guidelines and best practices for “genomic research and biobanking in Africa” in 2017 (H3Africa Working Group on Ethics, 2017). Importantly, this framework, led by the Human Heredity and Health in Africa Initiative, embraces the committee’s design principles in Chapter 2 of co-design with end users, transparency, and feedback to and sharing of benefits with all parties.
Although not typically associated with health care, blockchain technology is increasingly appearing in health-related discussions. According to Zambrano (2017), a blockchain “can be defined as a public spreadsheet that sequentially records transactions among users operating within a decentralized peer-to-peer network.” The use of blockchains in health care could create common databases of health information that clinicians could use regardless of the type of EHR they have (Marr, 2017), potentially
improving patient care. Blockchain technology may improve transparency by decentralizing the system and using a fully auditable and valid ledger of transactions that cannot be forged (Myler, 2017). Additionally, once a transaction has been recorded, it cannot be edited retroactively because doing so would require that all subsequent blocks be altered, making it impossible to delete a transaction or add a fraudulent one. This transparency eliminates the need for many typical checks and balances currently in use, which could in turn reduce financial reporting costs by up to 70 percent. The built-in transparency of the blockchain system may also allow its use as a method for countering corruption (Aldaz-Carroll and Aldaz-Carroll, 2018).
While these are all exciting advances illustrating what is possible on the horizon, advocates cannot forget that some countries will not have the legal, technological, and regulatory landscape to accommodate these advances for many years. Thus, regardless of the starting point today, it is important for countries to begin putting these important legal mechanisms into place and thinking about designing capabilities from a high level. The widespread introduction of digital tools and sensors can lead to disjointed and disorganized data generation in the clinical setting, especially if the technologies are not supported by a framework to guide the integration of health data streams. Leadership and involvement at the national level and alignment of the technology with the priorities of the country are paramount for successful implementation. Otherwise, health professionals could be faced with extra work, and patients would see no improvement in their patient journey or experience. Buckle and colleagues (2018) argue that without a top-down component that sees the big picture of where and when the data can be integrated in a flexible ecosystem, the full benefit of these technological advances will not be realized. Yet, if the implementation of these technologies is done well, they offer enormous potential to reach previously underserved populations, to improve the quality of care through cost-effective solutions, and to augment scarce workforces to reach more patients and serve them better.
The digital tools and changing systems described above clearly have implications for quality—both good and bad. Using these tools, and embracing the design principles for system change outlined in Chapter 2, the committee envisions three positive changes in particular within the quality dimensions of person-centeredness, accessibility, and equity, through patient ownership and empowerment, improved communication, and better measurement.
Increased Patient Ownership and Empowerment
By all accounts, health care systems of the future will, and should, dramatically shift to become more person-centered—centered around not only patients’ physical health needs but also their mental and social health needs, their caregivers, and the broader community. For this change to truly take place and be sustainable, however, the responsibility for high-quality health care will need to be shared among patients, providers, families, and the community. To be empowered, patients need to take ownership of decision making, have a better understanding of their health conditions, and demand high quality. A recent survey across 12 countries gauging the public’s willingness to use an AI-type “health care assistant” via smartphone or tablet revealed some striking results for those living in middle-income countries. Compared with high-income countries, participants in middle-income countries were much more willing to use a type of AI tool through a computer or smartphone (see Figure 3-3).
The need for co-design and cooperation with patients and the health care team also becomes clear when hospitals and clinics look at incident analysis. Often the investigation of patient injuries and errors in care focuses on singular events, narrowing the aperture even further to include only health care personnel. However, a limited focus on root-cause analysis may neglect systems thinking; it may ignore the reality of health care today (and that of the future): that care takes place in multiple places and over time. In most cases, an organization as a whole, complexly interacting systems, and multiple causes contribute to error, rather than a single clinical interaction. Instead of focusing on specific events, the emphasis of analysis needs to shift to care processes over time, or what this report refers to as the lifetime “patient journey.” Patients and their families traverse the health care system over time and through multiple places. Thus, they often have a greater understanding than clinicians of the care received longitudinally, and they have the ability to provide key information needed to identify causes contributing to an adverse event. Patients and families are essential aides in the investigation of a quality failure (Vincent et al., 2017).
Advances in digital health technologies can afford new opportunities for moving care into the community and out of potentially hazardous clinical settings. But this shift will require moving away from the paternalistic relationships that have characterized health care, demanding instead partnership and collaboration between patient and provider. Patients are certainly eager for more knowledge and want to be informed decision makers. A global survey found that 77 percent of respondents want more control when it comes to their health care decisions (Volpe, 2017). When asked if they seek out more information beyond what their doctor tells them, nearly 80 percent of respondents in China, India, Indonesia, and South Africa said,
“Yes.” Involving users in the design of health care systems and the incorporation of digital health tools can ensure that the systems are well adapted for people and minimize the need for people to adapt to accommodate the system. Early user involvement can also facilitate early identification of design problems, reduce development costs, and ultimately lead to higher levels of user acceptance and fewer usability problems (Buckle et al., 2018). This involvement will also require patient and community education, but can lead to a shared burden of illness and ideally result in better health outcomes and more productive societies.
An ideal future system delivering high-quality care will need to feature improved communication among all stakeholders. Means of communi-
cation have already changed dramatically over the past decade with the spread of mobile phones and Internet connectivity. In 2012, a survey of more than 150,000 women in a rural, low-resource district in Bangladesh revealed that 71 percent owned phones, compared with only 23 percent of those same homes that reported access to electricity (Labrique, 2018). In today’s digital world, with the pervasiveness of digital connectivity, people’s involvement in their own health is common.
Women in Tanzania receiving treatment for prevention of mother to child transmission reported three specific factors that decreased the quality of their health care experience, two of which were arguably related to communication issues: a visit time exceeding 2 hours, perception of poor communication skills by health care workers, and a lack of understanding of patient concerns (Naburi et al., 2016). Significant maltreatment in maternal care was also reported in Ghana and Nigeria (Izugbara and Wekesah, 2018; Moyer et al., 2014). Interpersonal relationships with health care staff and patients was cited as a priority by all patients, with exit interviews sometimes attributing provider friendliness and time spent with the patient as a main factor in the quality of the care experience. None of these findings should come as a surprise, yet there are numerous places around the world where, for a variety of reasons, patients are not treated well, and the communication skills of health care providers are not addressed.
Rather than just interacting with patients, moreover, health care providers also need to interact with the communities in which patients live. Following a multisector workshop in 2017, the World Health Organization (WHO) developed a “community engagement framework for quality, [person]-centered, and resilient health services.” As part of this framework, WHO defined community engagement as a “process of developing relationships that enable stakeholders to work together to address health-related issues and promote well-being to achieve positive health impact and outcomes” (WHO, 2017). Similarly, effective communication between a health facility or health system and its surrounding community can increase trust overall, which can in turn lead to a healthier population and a more resilient system.
More Holistic Measurement
Determining how to measure aspects of quality within a new health care system that focuses on person-centeredness, communication, and human-centered design is difficult. Indicators describing the infrastructure of buildings, whether a correct medicine was given or whether an accurate diagnosis was made in a timely manner, will not be sufficient. These are all critical elements of high-quality care, but in addition, indicators are needed that can be used to assess whether patients and family members feel engaged
as members of the health care team, whether they feel respected and listened to, and whether the health care system has an understanding of and meets their fundamental needs. One such advance is a tool designed to assess person-centered maternity care across multiple low-income contexts, which demonstrated validity and reliability when tested in rural and urban settings in Kenya (Afulani et al., 2017). While additional testing will be necessary, this tool shows the potential for enabling assessments that can adequately gauge the quality of care a patient is receiving and target ways to improve it, beyond inputs and processes (Berwick et al., 2017).
Examination of global health care practices reveals wide variance in experiences and perceptions. Patient satisfaction and experience studies conducted in contexts ranging from resource-plentiful settings in the United States to resource-constrained facilities in Burkina Faso demonstrate that the effectiveness of communication is poor, leading to patient dissatisfaction. While current patient satisfaction research may shed light on how providers and insurance companies are performing, it does not always illustrate the actual priorities of patients and what matters to them. Careful measurement and understanding of patient experiences and outcomes will be needed to track progress, as discussed in more detail in Chapter 4.
Education and Communication as Indicators
Education, or health literacy, and treatment through a culturally appropriate lens are imperative for improving the patient experience in countries around the world. In one study, members of an indigenous community in Australia were interviewed for their opinions on hepatitis B–related knowledge, perceptions, and experiences. The respondents expressed a strong desire for learning more about the disease and for having more culturally appropriate discussions in their first language about education and treatment (Davies et al., 2014). These findings accord with attitudes toward maternal care in Nigeria and the need for integration between methods and practices of traditional and modern medicine. Traditional birth attendants (TBAs) often offer support and low-cost treatment throughout Nigerian women’s pregnancies, but modern health facilities often refuse to let TBAs accompany the women in labor. Numerous women interviewed believe many of their negative birth experiences could have been alleviated or avoided had their TBA been allowed to accompany them (Izugbara and Wekesah, 2018). Delivering education and treatment through a culturally sensitive and appropriate lens can improve patients’ experiences and enable health care systems to create greater trust between patients and providers.
Digital health literacy is also becoming increasingly important as the health care delivery system shifts toward digital tools and consumer ownership, as described in this chapter. The Shanghai Declaration for Improving
Health in 2016 highlights this need for a commitment to health literacy—for citizens to be engaged both as patients and drivers of their own health and as leaders in decision making about care. The participants in the declaration committed to increasing citizens’ control of their own health by harnessing the power of technology, as called for by the committee to improve both quality and person-centeredness (WHO, 2016).
Common themes are seen among countries even when their policies, infrastructure, and resources are vastly different. The above findings from more resource-limited settings, for example, reveal the importance of considering such concerns as the availability of appointments at physicians’ offices in designing quality-improving interventions that are medically pluralistic. Improving health education to allow patients to have more self-efficacy in their health care decisions also aligns with the priorities of health care consumers (Boivin et al., 2014). Thus, creating interventions that can translate cross-culturally is crucial to improving the quality of care globally.
The increase in digital health technologies and the transition to more person- and community-centered care are not the only changes to expect as health care systems adapt to societal and technological changes. In part because of these increasingly available technologies, future health care systems will also focus much more on risk management and prediction relative to the traditional model of episodic disease management. This shift will also be driven by the enormous increase in NCDs worldwide, a change in the global epidemiologic burden that will make prevention much more cost-effective. Overall, health care delivery will need to shift from acute and episodic care to organized monitoring and evaluation of patient outcomes, preventive care, standardized quality, and systematic follow-up, especially for chronic diseases.
Successfully Delivering Primary Care Where People Are
Primary health care is a foundation for “equitable, efficient, and resilient” health care and enables care to meet the needs of people wherever they live (Bitton et al., 2017). The 13th WHO General Program of Work recognizes primary care as key for realizing universal health coverage (UHC) (WHO, 2018a). The strong evidence for the importance of investing in primary care (Starfield et al., 2005) provides an opportunity to emphasize people- and community-centered care and a new focus on the patient journey. If designed with the needs of users in mind and with contextual nuances of the community incorporated, primary care can be a critical tool in the quest for higher-quality care and better health outcomes. And lever-
aging the digital health technologies discussed throughout this chapter, with the consumer at the center, can amplify the positive effects of primary care. With telemedicine and virtual appointment options, patients will no longer be constrained by where health care facilities are located and have to worry about scheduling follow-up appointments at the hospital every few months for chronic diseases, wondering how their family will be able to find money for the trip. Investing in an evidence-based system using human-centered design can lead to lower costs, higher quality of life for patients, and a better overall patient experience. The recent joint global quality report from WHO, the World Bank, and the Organisation for Economic Co-operation and Development (OECD) highlights the exciting concept of using primary care as a coordination hub (see Figure 3-4).
The Alma-Ata Declaration of 1978, signed by 134 countries, was one of the first global consensus statements to identify the importance of primary health care (Rao and Pilot, 2014). It defined primary care as
the first level of contact of individuals, the family and community with the national health system bringing health care as close as possible to where people live and work, and constituting the first element of a continuing health care process. (WHO, 1978)
Yet, 40 years later, unfortunately, this vision remains unfulfilled in many places around the world, despite the establishment of several milestones in its support. As a result, integrated primary health care is lacking in LMICs, and the quality of primary care varies widely among and within regions (Das and Hammer, 2014; Das et al., 2008).
Low primary health care capacity is “exposed and exacerbated by the increasing burden of [NCDs], increases in care complexity,” and acute threats (such as infectious disease outbreaks) (Bitton et al., 2017). The problem is truly global: Primary care typically is highly undervalued in many countries by everyone from patients to providers to politicians, and insurance schemes tend to incentivize the use of hospital-based complex care and procedures over preventive services, making it difficult to realize the benefits of high-quality care (Rao and Pilot, 2014). Yet, given such converging forces as demands for quality, the rising costs of health care, and the increase in NCDs, the importance of a strong primary health care system is increasingly being recognized (PHCPI, 2017b).
Strong primary care systems can produce better health outcomes cost-efficiently (Starfield, 1998; Starfield et al., 2005) and offset the health impacts of poor socioeconomic conditions (Shi, 2012). These systems can be augmented even further when they are supported by the vast array of digital tools discussed above. Understanding this potential and implementing reforms that reflect the value of primary care can be key in establishing
high-quality systems. One case in point is Costa Rica, which undertook vast reforms to its primary care system over the past 20 years and has reaped the benefits. Before Costa Rica took on the challenge of nationwide reform of primary health care in the 1990s, only 25 percent of the population had access to primary care (Cercone and Jiminez, 2008); by 2006, this figure had increased to 95 percent (Cercone and Jiminez, 2008). Simultaneously, in addition to access to care, life expectancies rose, and Costa Rica currently ranks second-highest in life expectancy in the Western Hemisphere, behind only Canada and Chile (Pesec et al., 2017). An important feature of the country’s reform process was its iterative nature, with strong measurement and monitoring allowing for such properties of a learning system as adaptation and continuous refinement (Pesec et al., 2017).
Another important resource for improved primary care is the utilization of community health workers (CHWs), a role that has been used with great success around the world in various contexts. Evidence shows that CHWs can deliver “safe and effective care for childhood illnesses, reducing the spread of communicable diseases and [NCDs], promoting nutrition, and providing family planning services, at low cost” (WHO et al., 2018b, p. 42). In low-resource settings, CHWs play a vital role among mothers and young children, reducing maternal, neonatal, and child mortality (Gilmore and McAuliffe, 2013). They also are able to optimize risk factor management and early diagnosis in communities through screening and referral programs. Chou and colleagues (2017) ran a model to test the impact of expanding CHW programs for lifesaving interventions in 73 countries and found it to be a useful strategy for achieving UHC and ending preventable maternal and child deaths by 2030. Financial benefits can accrue as well. A high-level panel in 2016 found that investing in CHWs in sub-Saharan Africa could produce “an economic return of up to 10:1—due to increased productivity from a healthier population, potentially reducing the risk of epidemics such as Ebola” (Dahn et al., 2015, p. 2).
While more than 45 countries have committed to CHWs as their frontline providers of health care, it is important to stress that each CHW system needs to be adapted locally to optimize these workers’ skills and potential regardless of where they are being deployed, and to nurture productive relationships between them and their patients. Integration of these workers into the community can make all the difference. Systematic reviews have found that community embeddedness—when community members have oversight of “the selection, monitoring, activities, and priority setting of CHWs” (Campbell and Scott, 2011)—can improve CHWs’ motivation and performance and, conversely, that a lack of community support can increase their attrition (Campbell and Scott, 2011; Kok et al., 2015).
The Brazilian Family Health Strategy (FHS) has been especially successful in utilizing a community-based approach. The core of each FHS team
consists of “a physician, a nurse, a nurse assistant, and four to six full-time community health agents” (Macinko and Harris, 2015). Each community health agent “is assigned to approximately 150 households … usually within the same micro-area where the agents live,” which the agents visit each at least once per month (Macinko and Harris, 2015). With the FHS program, Brazil has achieved improvements in breastfeeding rates, near-complete immunization coverage among children, a decrease in inequality and inequity in health care utilization, and a patient satisfaction rate of 85 percent approval for CHWs (Domingues et al., 2012; Wadge et al., 2016). Note that consideration of local context and the skills and perspectives of CHWs is especially significant when digital tools are being introduced in this type of decentralized environment (Daelmans et al., 2016; Hall and Taylor, 2003) (see Box 3-2).
As with other aspects of the transformation of health care, a “one-size-fits-all” approach to the utilization of CHWs will not suffice, and contextual adaptations of the basic design will be essential to success. According to Ballard and colleagues (2017, p. 3), “CHWs can contribute to advancing [UHC], but only if they are set up for success [by being integrated] into well-designed and adequately funded health care systems.” To help countries accomplish this at scale, six organizations with considerable experience on the ground developed a report outlining eight design elements that illustrate the minimum standards necessary for CHWs to succeed (see Box 3-3).
As an example of the implementation of these elements, following the Ebola outbreak in West Africa, Liberia’s Ministry of Health revised its policies for community health services and launched a multipartner program to increase the reach and quality of CHWs (Raghavan and Kelley, 2018). As a result, the number of people accessing care has increased, with multiple counties reporting increases in children receiving treatment for such conditions as malaria and pneumonia (Luckow et al., 2017; White et al., 2018, in press). At the same time, Liberia implemented a special focus on quality through a nationwide performance management system, which utilizes such metrics as timely payments to CHWs, supply restocking, quality of clinical supervision, and competency of CHWs (Raghavan and Kelley, 2018). The goal is to improve the accountability and adaptability of CHWs. Employing such design principles as co-design, continuous feedback, and solving problems at the source, the initiative regularly reviews data and identifies changes and adaptations that can improve quality in various areas.
CHW models are applied successfully not only in LMICs but also among low-income populations in higher-income countries such as the United States, where these models have helped achieve a more holistic patient journey and better health outcomes. For example, a Massachusetts program integrating health, behavioral, and social services for low-income
clients reduced hospitalization rates by more than 7 percent relative to the previous year; visits to the emergency room declined by about 6 percent (Klein et al., 2016). This type of model has inspired new programs such as CityBlock Health,5 which seeks to make care more personalized, accessible (i.e., through digital platforms, mobile access, or delivery of care outside of health facilities), and contextual by recruiting a team of residents in urban communities to co-design care pathways that make sense for themselves and their neighbors. Health care delivered in the community by people who understand the detailed circumstances of the patients with whom they are working may become be a fundamental element of high-quality primary care in the future.
A Critical Shift for the Growing Burden of Noncommunicable Diseases
Mortality from NCDs has been projected to grow by 15 percent globally from 2010 to 2020 (WHO, 2011). In 2015, more than 70 percent of global deaths were due to NCDs, primarily cardiovascular disease, cancers, diabetes, and chronic lung diseases. More than 75 percent of this highly preventable mortality is borne by populations in LMICs, with nearly half of these deaths occurring before the age of 70 (WHO, 2018c). Research has found that chronic disease can be treated effectively through primary care models (Harries et al., 2008; Nigatu, 2012), but in practice, primary care facilities in most resource-limited settings often refer NCD chronic care cases to secondary or tertiary centers because they lack the capacity to treat them, thus overwhelming higher-level facilities (Walley et al., 2012). In low-resource settings, moreover, secondary and tertiary health care facilities are typically much scarcer than primary care and concentrated in larger cities. As a result, patients and their families in smaller towns or rural areas face a travel and financial burden.
To address the growing burden of chronic disease, it is essential to innovate in the delivery of care for these conditions and think differently about how and where to treat these patients. Some examples of such innovations even outside of the primary health care system are beginning to emerge. In Ghana, for example, where the estimated prevalence of hypertension exceeds one-third of the population, community-based hypertension management is being implemented (Ofori-Asenso and Garcia, 2016). The Community-based Hypertension Improvement Project, supported by several partners, began in 2015 to shift these patients’ interface with the health care system from the hospital to the community. Local businesses, CHWs, and nurses are trained to screen, diagnose, and initiate first-line treatment for people with hypertension (Novartis Foundation, 2018). This approach removes the barrier of transport to and wait times for hospitals, and through digital health technology allows seamless connectivity between screening sites and physicians at referral sites for supported decision making. Such models share elements that include empowering patients to take more responsibility in the management of their own health; using nontraditional health care providers to optimize screening and diagnosis opportunities; linking them to the health care system through digital tools; and offering first-line treatment through community health care providers, thereby reducing the burden on the health care system.
Digital technology and tools described previously can facilitate and accelerate many types of interventions necessary to address NCDs. One example already reaching scale is that of CaSalud in Mexico, supported by the Carlos Slim Foundation. It includes screening and risk assessment for cardiovascular disease and diabetes, both in clinics and in patients’ homes,
as well as clinical decision support, online stock monitoring, and patient education platforms to reengineer the prevention and management of NCDs (Carlos Slim Health Institute, 2018). Another example is telemedicine, in increasingly common use. Novartis Foundation and the Ghana Health Service are integrating and scaling up telemedicine services across the country following a successful multisector partnership pilot. As of early 2018, six 24-hour tele-consultation centers had been established and staffed to connect CHWs and medical specialists, with full national coverage expected by 2019. Doctors, nurses, and midwives in the centers coach CHWs through their patient care (including care for acute and chronic conditions). This approach allows for improved quality of care through the centralization of (often scarce) expertise, and also empowers CHWs, who feel more confident and motivated to remain in their jobs. Perhaps most important, especially in rural areas where access to specialists is limited, this infrastructure improves the quality of care by avoiding unnecessary referrals and reducing transport times and costs for patients. The initiative’s developers found in 2016 that more than half of all tele-consultations could be resolved by phone, and that 31 percent avoided the need for referrals (Pennic, 2018).
Costa Rica is also struggling with the increasing burden of NCDs, but its strong primary health care system, described earlier, should help in adapting to the challenge. In fact, despite a rising burden of NCDs, deaths due to these conditions actually fell in Costa Rica between 2000 and 2012, from 15 to 12 percent of all deaths (PHCPI, 2017a). Ariadne Labs’ 2017 report (Pesec et al., 2017) outlines several factors that can account for this decline, which the committee sees as representing elements of a quality future health system with clear implications for an optimal patient journey:
- Continuity—Patients see the same provider for many years, enabling a shared understanding of goals, effective treatment, and motivating factors.
- Team-based care—This represents an effective approach to managing chronic illness because teams are better able than clinicians operating independently to provide coordinated, patient-centered, and effective care.
- Focus on prevention—Because Costa Rica’s system was designed around infectious disease, it can translate that emphasis and its lessons learned on prevention to NCDs.
- Community orientation—These programs have been shown to be cost-effective and could increase knowledge in the community of risk factors for and management of NCDs.
- Health data management structure—A countrywide, standardized measurement and monitoring system designed to ensure good health outcomes provides fundamental tools that can be applied to the NCD burden.
Given the excitement about and promise of these new system approaches, technologies, and ideas, it is important to step back and consider the barriers that could prevent them from realizing their potential. Many of these new developments are taking place in silos within countries and sectors. To help countries and health systems take advantage of the growing number of tools available, policy makers need to play an active role in shaping the markets and economies affecting the health system and ensuring that their citizens’ needs are well represented (Bloom et al., 2017). Yet, given the costs associated with the rising NCD burden, sufficient funding will be needed for many countries to undertake significant reforms, such as those instituted by Costa Rica, to strengthen their primary care systems to prepare for the future needs. Additionally, the systems thinking and design principles underpinning quality care discussed in Chapter 2 will be necessary to overcome the current fragmentation and paternalistic dynamic still present in many places. To better understand what will be needed for health care to complement the rapid development of digital health technologies, the committee identified and interviewed 12 subject-matter experts in the area of digital health ethics and regulation. These experts provided insight into what changes and policies could help protect patients and improve quality as health systems change, as well as some concerns due to the involvement of a larger number of stakeholders and the lack of regulatory oversight in many LMICs. They offered varying perspectives and some concrete, straightforward steps toward action, which are summarized in the section below, as well as the subsequent section on cautions for quality in the future system.
Human Factors and Human-Centered Design
As discussed in Chapter 2, the discipline of human factors and ergonomics (HFE) recognizes the importance of the interactions among multiple components of a system, including the variability introduced to those interactions by humans. Currently, the elements of human factors science are not widely understood or used to inform the design of health care systems, but they are deeply embedded in other industries. Lessons from those other industries can be gathered and applied to health care, offering the opportunity, for example, to integrate a variety of innovations and design changes into a broader health care system.
Considering the role of human factors can often demonstrate to health leaders the reasons why some health care reforms work and others do not.
The development of digital health within a health care ecosystem requires increased participation from potential stakeholders (using principles of co-design) to define how the data should be collected and used (Lupton, 2017; Pagoto and Bennett, 2013). To this end and to leverage the opportunities offered by digital tools, a community of global health nongovernmental organizations (NGOs) and donors launched the Principles for Digital Development in 2016 to build the rationale for a paradigm shift (Principles for Digital Development, 2018a) (see Figure 3-5). These principles reflect a set of best practices developed over the past decade that programs and governments can use to build their systems.
HFE methodologies can support the design and evaluation of safe and usable medical and information technologies. Buckle and colleagues (2018) argue that human factors science “should be the engine to rigorously support the digital transformation of healthcare.” Similar to HFE, human-centered design (HCD) is an approach to designing a system or tool so as to make it as effective as possible while prioritizing people’s needs, desires, and ordinary activities (Sharma and Holeman, 2017). While there is a technical definition of HCD according to the International Organization for Standardization (ISO), there is no universally agreed-on view of it in health care. Nonetheless, thanks to constantly evolving new research, technology, and innovation, this practice continues to evolve as well. Sharma and Holeman (2017) highlight three key elements MedicMobile employs when deploying digital health tools throughout its CHW network (Bazzano et al., 2017):
- Participatory design—Engaging people as partners instead of viewing designers as experts and potential users as informants. This approach is especially salient in the area of “configurable tools” that are often finalized through local tailoring.
- Supporting human skills—A commitment to augmenting people’s skills instead of making workers obsolete through automation and technology. This element discourages design that dehumanizes the workplace experience.
- Human values—Examining moral stances within a project and pairing stakeholder values with the priorities behind the system being designed. There should be a focus on methods for reflecting the values of people likely to be influenced by the intervention.
The way people participate in their own health is changing, but no one approach will work everywhere. Instead, to ensure that interventions, tools, and systems are designed for the users for whom they are intended, decision makers need to encourage these types of HCD approaches, beyond just the involvement of end users. For example, “function allocation” is a key concept in any system design. It entails identifying which tasks the technology is capable of performing and aligning those tasks to the extent possible—i.e., not assigning humans tasks that a computer could do better, and vice versa. Consideration of human factors in the transfer of technologies has also been found to be a major determinant of the success of a technology, and thus is important for health care and policy leaders when introducing new devices (Cunningham and Sarayrah, 1994; Meshkati, 1989). HCD approaches can shed light on the needs and perspectives of people using health technologies, thereby removing unnecessary barriers to high-quality health care for patients and making the workload more manageable for health care workers.
Integration Across the Health Care Continuum to Promote Primary Care
Health systems often grapple with the question of whether vertical or horizontal approaches are more effective at delivering high-quality care. Vertical programs dedicated to a singular disease, for example, can be effective because of their narrow focus and alignment of funding and goals, but advances are limited to the area of focus. Horizontal approaches, often referred to as “health system strengthening,” can address a broader range of health issues or disease areas, but successes are difficult to measure and attribute. Yet, depending on the country, the health infrastructure, the political environment, and many more factors, success will often require both, or a “diagonal” approach. Frenk (2006) defines a diagonal approach
as a “strategy in which we use explicit intervention priorities to drive the required improvements into the health system, dealing with such generic issues as human resource development, financing, facility planning, drug supply, rational prescription and quality assurance.” More recently, Frenk and Gomes-Dantes (2017) have argued that, to meet the complex health challenges of the interdependent 21st-century world successfully, it will be necessary to move away from the currently pervasive dichotomies and embrace integration. Several researchers have suggested that achieving a sustainable version of quality UHC will require moving toward integrated health systems, which will be accomplished in large part by prioritizing primary care (Kringos et al., 2013; Kruk et al., 2010; Macinko et al., 2009). This relationship will be bidirectional and symbiotic, as WHO (2018a) emphasizes that “effective and efficient primary health care requires integrated health care services.” Finally, given the ICT advances, HCD approaches, and community care delivery elements discussed throughout this chapter, successful integration of systems will depend on intersectoral collaboration. For example,
evidence emerging from Bangladesh, Pakistan, and Nepal suggests that integrated packages of community- and facility-based services provided across the continuum of maternal care, from pre-pregnancy through the postpartum period, could reduce neonatal mortality by 11 to 34 percent. (Labrique, 2018)
Meeting the demands of the Sustainable Development Goals (SDGs) will require this type of action and cooperation. Otherwise, many passionate and hard-working people will continue working in silos, often harder but less effectively, to achieve their stated goals.
Understanding and Partnering with the Private Sector
The private sector is making enormous investments in digital health across all countries, driven by long-term goals and aspirations. But without parallel investments and capacity building in the public health sector and new business models to encourage partnerships and data sharing, opportunities for improved care through digital health will not be fully realized. Given that the ICT sector is rarely publicly owned, most types of digital health investments or tools will be created through a public–private partnership model. Accordingly, countries need to consider how to build these partnerships and attract investment while still protecting patient data and privacy. Some of the largest global companies are making big bets on health care. Amazon, Apple, Google, and Uber all have announced their interest in disrupting a health care industry that has been slow to change
and maintained high costs to patients and facilities while being riddled with inefficiencies and room for growth. For example, Amazon is entering a partnership with JPMorgan Chase and Warren Buffet; Apple is establishing a line of medical clinics; Verily, Google’s sibling company under Alphabet, is assessing market potential under Medicaid; and Uber is seeking to disrupt services for ambulance care (Scott, 2018). These are all multinational companies, with massive potential to effect change in health systems globally and improve the quality of services being delivered.
The need for education in the rapidly growing and changing digital health sector is absolute. Given that health care quality will depend on the quality of the health care workforce and its pipeline, crucial changes in education are needed now. The use of digital content, for example, has been estimated to decrease the cost of training 1 million new CHWs in sub-Saharan Africa from $65 per person to $15 per person (Hausman, 2012). In addition, health care workers of the future will need a new set of skills, including the ability to manage complex cases; better bedside manner; and higher literacy to understand, use, and inform data analytical tools. According to Labrique (2018), “decision makers at every level of government, especially program implementers, will need to be retrained as consumers of information,” acquiring the ability to read and interpret data visualizations and a continuing thirst for data on program performance. Currently, few LMICs maintain trained informaticists and analysts to study data patterns and recommend course corrections within programs. Going in this direction could help the health systems in these countries achieve higher quality and understand more rapidly where mistakes are being made, helping them close the gap with many high-income countries, which are also just beginning this process.
A straightforward first step would be to implement changes at the college and university level, as these institutions are currently vertically oriented, making it difficult to work across sectors outside of one’s specialization. However, the health care workforce will also need to acquire knowledge and skills in such areas as connectivity, data validation, and algorithm engineering, which are not routinely taught in any premedical or nursing programs. Universities have an opportunity to act proactively to meet this need by creating more multidisciplinary programs not only in medical and nursing programs, but also scaled for health care administrator and corporate training, thus providing a baseline of knowledge across all pipelines feeding into the health care sector. Taking this idea a step further, international organizations and academic associations could create a full digital health curriculum to increase the capacity for using real-time data in
health systems management and planning. With many analysts and futurists predicting that the future of health care is heading in this direction, building these curricula and making changes in the education system now would be a prudent and efficient move.
Similarly, it will be important to keep in mind that the new technicians and engineers developing many of these health tools are not trained as traditional clinicians. This means they likely did not receive training in bioethics and do not necessarily operate under the same “do no harm” ethos that governs health care providers. Thus, there is a need for cross-fertilization among different sectors to ensure that all stakeholders working in the health care system of the future have the right knowledge base for assuring and improving quality. Education and training will also be needed on the regulatory side, as regulatory bodies will require expertise to examine the validity of data and the algorithmic processes of new devices and tools to ensure that they are supportive of patient safety and clinical efficiency.
The explosion of digital innovation and its potential to transform the health care sector invites a focus on the positive implications of these new tools, but they bring risks as well. Recognition of this potential demands strong leadership and multisector participation for the co-development of these tools and technologies to better achieve high-quality, equitable care for all the populations for which they are intended. Optimists may believe that digital health technologies will alleviate the current fragmentation and geographic limitations of health care systems. Yet, ethical considerations arise. For example, what are the negative consequences when people with low levels of health literacy take advice from an unregulated health app? If they follow the guidelines of the app and experience an adverse event, who will be held accountable? Multiple interviews with digital health subject-matter experts identified five major themes surrounding these important issues, which are explored below: the “digital divide,” regulatory issues, patient safety issues, the need to avoid institutionalizing bias, and the need for data governance standards.
The Digital Divide
Compounding some of the ethical concerns mentioned previously is the digital divide in many countries. Although mobile phones are becoming ubiquitous around the world, many people (most often women and girls) still lack access to this technology, and the poorest populations will not benefit from the new digital innovations and tools. A study in India, for example, found that among poor households without mobile phones,
access to private doctors decreased by 10 percent, while among those with phones, access grew by 4 percent (Haenssgen, 2018). This divide also exists between genders, with Internet penetration rates being “higher for men and boys than women and girls in all regions of the world today” (Broadband Commission for Sustainable Development, 2017). This disparity has significant consequences for women’s empowerment and entrepreneurship, impacting communities and economies. Fortunately, this problem is receiving attention from such groups as the Broadband Commission, which is developing recommendations for overcoming this gap, as well as from the UN High Commissioner for Human Rights (OHCHR, 2018). However, if the rapid growth among those possessing the right technology continues, these divides—whether geographically or gender based—will deepen, creating more inequity and impeding the ability of some nations to meet their UHC goal. As Internet and cellular coverage increases, governments need to ensure that the digital divide is addressed.
What will the right level of oversight be in countries without strong regulatory bodies to protect populations and ensure that safety and quality-of-care standards are met while still encouraging innovation and involvement from the private sector? A 2014 study addresses the vast number of digital health tools and the benefits of more granular patient data and customized diagnoses. It also points out the challenges these advances pose for such regulatory bodies as the U.S. Food and Drug Administration (FDA). As of that article’s release, only 100 of about 100,000 health care apps had been FDA approved (Cortez et al., 2014). Apps and tools often encounter additional challenges during the post-marketing period, as the usual requirements do not align neatly with digital health tools. The software industry typically releases beta versions, followed by continual updates and improvements, and getting everything perfect prior to FDA approval is unlikely. Issues also arise with respect to determining who is responsible for dealing with adverse events and data privacy for unregulated digital health solutions (Cortez et al., 2014). The lack of regulation of these types of tools in many countries makes these issues all the more concerning. Countries need to build their capacity to think through the guidelines and frameworks necessary to protect the users of these tools. Ghana (Data Protection Commission, 2018), Kenya, and Tanzania (Domasa, 2017) are in the process of passing laws on protection of personal data, but “more than half of Africa’s 54 countries have no data protection and privacy laws, and of the 14 that do, 9 have no regulators to enforce them” (Fick and Akwagyiram, 2018).
The paucity of regulations and the inconsistency among the regulations that do exist present significant barriers and risks to international
organizations that frequently deal with sensitive and critical data. The lack of data protection laws in Uganda, for example, resulted in three NGOs in that country being raided. The frequent occurrence of such events in many African countries led to the creation of the African Union Convention on Cyber Security and Personal Data Protection, also known as the Malabo Convention, in 2014. Its goal is to provide guidance on how to establish effective domestic data protection and information on how privacy demands could affect national security. While only 10 of 55 member states have signed on to the convention, 3 more have ratified it, and 18 have used it as guidance for drafting their own cyber legislation. The establishment and implementation of data protection laws will improve relationships with international organizations, and the committee endorses these moves to help assure high-quality care in the future (Green, 2018).
Another example of this concern is emerging in China, where patients and providers are very familiar with digital health technologies. Yet, while the WeChat platform, described earlier in Box 3-1, certainly increases convenience and decreases fragmentation, regulatory and ethical concerns have been raised. The widespread usage of WeChat has allowed unrestricted access to users’ medical data, and China has not yet established regulations or laws to protect personal information. The access to medical data is used to profile users and create marketing tools for big pharmaceutical and insurance companies (ITU, 2014). With the growing number of stakeholders including providers, facility administrators, developers, data engineers, and others becoming involved in health care, ethics need to be considered. Without co-creation mechanisms and HCD approaches embracing human factors, will all of these players understand the cultures they are serving well enough so that their populations will actually use the tools that are being developed? Together with donors, NGOs, the private sector, and other invested stakeholders, governments need to develop a strategy for building a common vision that enables innovation while incorporating mechanisms to prevent and mitigate threats to safety and other dimensions of quality. This strategy needs to encourage the alignment of country and regional improvement priorities with the tools developed for increased efficiency and effectiveness.
Patient Safety Issues
If algorithms are kept proprietary by a company and developed without the input of the intended end users, they or the decision support mechanisms for which they are employed can be flawed without users’ knowledge. If patients or providers rely on such flawed tools to diagnose or treat a condition, the result can be incorrect practice, wrong treatment, or errors in clinical decision making. Recent evidence from the United Kingdom,
for example, shows that because of an error in a National Health Service algorithm since 2009, many women who should have received an invitation for breast cancer screening did not. At least 450,000 women were affected, and thousands of them did not come in for a screening. A computer model suggests that 135–270 women may have died as a result (Erickson, 2018).
A recent report commissioned by the U.S. Department of Health and Human Services and the Robert Wood Johnson Foundation similarly identifies the need for reliable data to inform accurate, consistent, and discriminate diagnosis (JASON, 2017). It additionally highlights the dangers of misinformation and ambiguous algorithms infiltrating the emerging field of AI for health (JASON, 2017). For example, consider Skinvision, an app from the Netherlands that offers to provide skin cancer diagnosis using an uploaded picture. Very little information exists about the methods used to inform diagnoses, and the developers make the disclaimer (stealthily) that the app is not a diagnostic device, thereby calling into question its reliability (JASON, 2017). Such nefarious examples notwithstanding, the use of accurate data is vital; however, many health care organizations have not invested in data validity capabilities (Accenture Consulting, 2018). While the opportunities offered by AI and other similar tools are exciting for health care, leaders are increasingly realizing the need to be cautious. In fact, 81 percent of health care executives interviewed for one study expressed the view that health care organizations are not prepared to explain AI-based actions should societal or liability issues arise (Accenture Consulting, 2018). To realize the full potential of these technologies and prevent adverse events, ethical concerns need to be addressed, beginning in the design stage. Furthermore, guidance and endorsement by learned bodies (or an organization that guides and governs a discipline) may be needed to identify best practices for deployment of AI tools (JASON, 2017).
Avoiding Institutionalizing Bias
Absent an HCD approach, the development of devices and tools that yield incorrect information and wrong diagnoses poses a continuing ethical and clinical danger. A particular problem is that, either intentionally or unwittingly, algorithm creators will build in their own perspectives and values (Rainie and Anderson, 2017). In a 2017 Pew Research report, these authors highlight this as an area of deep concern, backed by similar views expressed by numerous experts. According to one expert,
Unless the algorithms are essentially open source and as such can be modified by user feedback in some fair fashion, the power that likely algorithm-producers (corporations and governments) have to make choices favorable to themselves, whether in internet terms of service or adhesion contracts
or political biases, will inject both conscious and unconscious bias into algorithms. (Rainie and Anderson, 2017)
Biases can also affect a tool as a result of sampling design, because the use of design ethicists in this area is extremely rare. In the United States, human bias in public assistance systems has created deep inequalities for decades (Edes and Bowman, 2018). If not accounted for, these biases can seep into technology tools and algorithms and simply automate the bias and inequity.
Data Governance Standards
While innovation is exciting and encouraged by many national governments, this dynamic field requires balance. In many countries, data governance standards are old and in need of an upgrade. While some countries or regions within countries are still operating via a paper system for health records, many have begun migrating to digital health information systems. As the use of such systems grows, countries at all stages need to take note of important considerations related to data governance and management. To ensure quality in these systems, organizations need to implement robust data life-cycle management, including data pipelines that can be trusted over time. These pipelines need to have built-in feedback loops to ensure that ongoing monitoring and updating are occurring, as the data are likely leading to important decisions about people’s health, and these systems should not be operating with outdated information and algorithms. Correctly designed, these feedback loops can support a “fail-fast” mentality, which encourages stopping a system to report issues instead of continuing with a flawed process. This approach can allow for faster redirection and pivoting while also ensuring that quality and safety are being measured, supporting an environment for continual improvement. Figure 3-6 illustrates the support that an “enabling ecosystem” can provide for the cycle of data production and information use.
Many health systems are also in need of improved data management. This function could be improved in part through advocacy among the donor community for good data management practices by governments and other project implementers, including incorporating data management requirements in requests for proposals and following through at the end of the award period to ensure that these requirements have been met. Over time, imposing these requirements can entrench best practices in data management and make them more commonplace as the default approach. Currently, it is also very difficult to track and validate which individuals are skilled in which disciplines, so it is challenging for countries to identify the right expertise to help develop national policies on digital health and
informatics. A regional certification body could assist in addressing this issue and give governments access to the right professionals who have already been vetted and also have an understanding of their regional or national culture and its nuances. Countries further along in this process, moreover, can share lessons in creating policies and standard operating procedures that embody data quality assessments, including data ethics.
Sustainability also needs to be considered for data governance, especially in LMICs, as donors or outside companies implement countless digital health pilots. Without sufficient thought regarding the uptake of the program or device being tested, such projects can and do easily fail. Even projects that show great promise at the outset, such as the acclaimed telemedicine program implemented in Bihar, India, may not improve quality (Mohanan et al., 2017). This observation underscores the importance of rigorous evaluations and robust (and human-centered) program design for new innovations. Multiple studies have found that poor reproducibility or scalability with numerous pilots can impede digital health efforts in lower-income settings (Shuchman, 2014; Tomlinson et al., 2013; Waugaman, 2016) by eroding trust and community buy-in and by causing confusion that can compromise the quality of care.
Many of these issues have been raised by various stakeholders, and several countries have already seen much success when investing in technology and leveraging the tools already in use. WHO has made it a priority to leverage digital health technology for improvements in health care quality and patient safety. In an address to delegates at a conference on health care on digital technology,6 WHO Director-General Dr. Tedros Adhanom Gebreyesus highlighted the impact of digital technologies on training health care workers, empowering patients and families, and improving patient safety and quality. For effective and sustainable improvements to occur, however, strong leadership at the national and local levels, clear policies and governance mechanisms, and data-driven improvements will be necessary (WHO, 2018b).
Global health care today is at a crossroads. Leaders have an opportunity now to make intentional and important changes to the way digital tools are designed and how they are implemented in the health care sector. If they fail to act on this opportunity, these technologies could actually be harmful, and those who are most vulnerable may be the ones most likely to suffer.
6 Dr. Tedros Adhanom Gebreyesus made this address at the 2nd International Conference of Ministers of Health and Ministers for Digital Technical Technology on Health Security in Africa (CIMSA) in June 2018.
The health care system of the future will differ fundamentally from those of the present and past. Digital technologies are a key enabler to optimize health systems and improve the quality of care for individuals and populations. Fully tapping the potential of digital systems and tools will require new skills, attitudes, and culture in the workforce and new, more active roles for patients, families, and communities in shaping, evaluating, and delivering the care they need. New health-related human resource competencies will be necessary to understand and take advantage of the
new health technologies and tools. Given the potential of big data and AI to transform systems, education programs need to be designed to better train health professionals in quantitative skills, statistics, and data analysis and use and to help leaders connect health policy with data and new evidence. Successful programs highlighted in this chapter have already begun this transition, shifting the focus to utilization of digital health technology as well as predictive rather than reactive care models. While the programs’ successes are specific to the context in which they were implemented, they offer insight into methods and strategies that have the potential to be scaled and altered to be successful in a variety of contexts:
- The Brazilian Family Health Strategy, which focuses on the utilization of CHWs, has resulted in increased breastfeeding rates, near-complete immunization coverage among children, decreased inequality and inequity in health care utilization, and a patient satisfaction rate of 85 percent approval for CHWs.
- A Massachusetts program integrating health, behavioral, and social services for low-income clients led to a decline in hospitalization rates of more than 7 percent relative to the previous year; visits to the emergency room fell by about 6 percent.
- Novartis and Ghana Health Service implemented a pilot program aimed at integrating and scaling telemedicine services in Ghana. The result was that more than half of all tele-consultations were resolved by phone, and 31 percent avoided the need for referrals.
- Transitioning current training content to digital form to enable broad dissemination could lower the marginal cost of 1 million new CHWs in sub-Saharan Africa from an estimated $65 per person to $15 per person.
The health care system of the future will have a focus on prevention, risk factor management, and personalized care using precision medicine and predictive analytics. In this scenario, care will be delivered as close to the patient as possible, and will rely more on community resources and less on hospitals. Already with the introduction of digital technologies, the balance of power is shifting from providers to shared power and responsibility between providers and empowered patients.
This shift is being driven by public demand, and in the process may be shaped in ways not experienced before. Technology is a disruptor and has proven so in many other sectors. What remains to be seen is whether technology will close gaps and disparities in health care or widen them, such that those who can afford new technology and the options it provides will benefit, and those without resources will not. Health systems need to take a proactive approach to this shift, or they may be left behind in the process.
Recommendation 3-1: Build a Global Community for Digital Advances in Health and Health Care Delivery
The United Nations System should convene an international task force with multisectoral representation to provide guidance to the global community on advances in digital health technologies. This task force should develop:
- data standards, norms, ethical frameworks, and guidance for modernized regulation and human resource capacity to enable countries to better benefit from the transformative technologies in the health sector;
- engineering and design standards that emphasize interoperability, human factors, and human-centered design to align technologies and innovation with the aspirations of global health care quality; and
- an international resource to guide countries in incorporating regulation of digital health technologies so as to protect users and their privacy while fostering innovation, with input from an external board of experts.
Recommendation 3-2: Adopt and Adapt the New Technological Realities of the Present and Future
Countries should prepare for and embrace the technological (especially digital) changes in health care by adopting and adapting standards; eth-
ical frameworks; and governance, payment, regulation, and workforce designs that are anticipatory and that embrace, rather than impede, the potential of transformed care.
- Ministries of health should collaborate with ministries of communication and technology to build national health strategies that embed digital technology as an integral part of the health system and address their countries’ priority health needs.
- Governments and organizations should develop and support multisectoral task forces to guide their digital health strategies so as to ensure that all deployed digital health technologies are evidence-based and coordinated, that patient safety is protected, and that risks are mitigated.
- Government and private-sector leaders should revise competency requirements and educational curricula to better meet the workforce needs created by digital health advances, including skills in data science and analytics, interpersonal skills for teamwork and person-centered care, and systems-based thinking.
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