THE DIGITAL INFRASTRUCTURE: COMPUTING, THE INTERNET, AND MOBILE TECHNOLOGIES

The past several decades have seen remarkable advances in technology, from personal computers, to cellular phones, to portable music players. The first mainframe computer offering a magnetic hard drive, the IBM RAMAC 305, was introduced in 1956, weighed a full ton, cost $250,000-$300,000 a year to lease in today's dollars, and stored less than 5 megabytes (Lesser and Haanstra, 1957; Levy, 2006). The price and capacity of computer storage have changed dramatically since then: in 2011, one could purchase a 32 gigabyte microSD card for $40,¹ which could store almost 7,000 times more information than the IBM RAMAC 305 at almost a thousandth of the price. One could also buy a disk drive capable of storing all of the world's music for only $600 (Manyika et al., 2011). And computer processing speed has grown by an average rate of 60 percent per year over the past several decades (Hilbert and López, 2011).

Advanced technologies that rely on this computing power have become widespread. In the United States, 85 percent of adults own a cellphone, almost half own a digital music player, and 76 percent own a laptop or desktop computer (Zickuhr, 2011). The ability to generate, communicate, share, and access information has also been revolutionized by the rapid growth of digital networks. The Internet pervades modern life, allowing for quick access to multiple sources of information and rapid communication. The number of Americans with access to the Internet grew from 14 percent in 1995 to almost 80 percent in 2011 (Pew Internet & American Life Project, 2011). The Internet has given rise to new ways to connect with others, such as through social networking sites. These sites are now pervasive, being used by 65 percent of Internet users as of 2011 (Purcell, 2011).

In recent years, connectivity has become mobile and ubiquitous. Since the turn of the century, the capacity to share information across telecommunications networks has grown by an average of 30 percent per year (Hilbert and López, 2011). With the rise of tablets and smartphones that offer Internet connectivity and additional applications, mobile devices have become more sophisticated and have gained greater functionality. It is estimated that by 2020, 10 billion such mobile Internet-connected devices will be in use (Huberty et al., 2011).

These advances have dramatically changed numerous sectors of the U.S. economy, and even society more broadly. Companies have developed new ways to streamline their work processes, share information within their organizations, and analyze trends and knowledge (see Box 4-1 for an example). Individuals now have a wealth of information at their fingertips, with the ability to learn about almost any new topic in seconds.

BOX 4-1

Using Data to Transform Business Practices. The explosion of data, along with new mechanisms for mining the data for insights, has transformed many businesses. One business that has made extensive use of this new opportunity is Ceasars Entertainment, (more...)

While technologies and communications have led to widespread societal changes, these capacities are still relatively early in their development in the health care arena, and there is substantial room for progress and improvements as technologies are implemented in the field. One way digital connectivity can lead to better performance in health care is by ensuring that clinical information for a given patient is available when and where it is needed. The infrastructure for this type of connectivity, however, is largely lacking. As of 2011, only 34 percent of office-based physicians used a basic electronic health record system (although projections are for 90 percent to have access by 2019) (Congressional Budget Office, 2009; Hsiao et al., 2011), and only 18 percent of hospitals had a basic system (DesRoches et al., 2012). Thus, substantial opportunities exist to improve the safety and efficiency of medical care by promoting greater use of digital records. Once in place, these systems create the potential for advanced uses of clinical data to improve outcomes (see Box 4-2 for an example). For instance, they allow providers to analyze their patient populations and identify those who may benefit from preventive care or other proactive clinical services. Several early results have been promising, with digital records encouraging greater adherence to national best practices and leading to improvements in health outcomes (Cebul et al., 2011; Friedberg et al., 2009).

BOX 4-2

Gleaning Real-Time Insights from Clinical Data. Although there has been an increase in the clinical knowledge being produced (see Chapter 2), the necessary evidence is lacking in many areas. However, the increased use of electronic medical records provides (more...)

Increasing the diffusion of a digital infrastructure that supports health care processes and access to information provides the necessary foundation for a continuously improving, learning health care system (President's Information Technology Advisory Committee, 2001, 2004). Using this infrastructure, the system can capture and use knowledge from clinical care in real time. However, the sheer scale and complexity of the digital health infrastructure, including legacy systems, new electronic health record systems, financial data systems, and other data sources, necessitate conceptualizing this infrastructure in a new way. As noted in the Institute of Medicine (IOM) publication Digital Infrastructure for the Learning Health System, managing this complex technological resource effectively will require allowing local users of the data maximum flexibility, minimizing the number of standards necessary, and promoting adaptability and incremental innovation. Achieving this vision will require addressing a number of challenges, including the need for interoperability (see Chapter 6), supportive care processes (see Chapter 9), governance, the building of trust among clinicians and patients, and patient and public engagement (see Chapter 7) (IOM, 2011).

Improved connectivity increases patients' access to clinical knowledge—from guidelines, to clinical research results, to peer support—and may improve their engagement in their care. The fact that 80 percent of Internet users now look for health information online, making this the third most popular Internet activity, demonstrates that individuals are interested in obtaining more health care information (Fox, 2011a,b). Patients also are increasingly interested in finding information that is customized to their particular circumstances and that relates to the experiences of similar patients (Fox, 2011b).

Likewise, these technologies can help clinicians access clinical evidence, as well as additional information about their patients. Several examples exist of initiatives, such as the National Library of Medicine's MedlinePlus Connect and Kaiser Permanente's Clinical Library, aimed at seamlessly integrating clinical information with an electronic medical record. Evidence indicates that clinicians already have started to take advantage of these types of resources. In a 2010 survey, 86 percent of physicians reported using the Internet to gather health, medical, or prescription drug information (Dolan, 2010). Moreover, new digital data systems can automatically apply clinical knowledge to patient situations and flag potential problems. For example, computerized physician order entry (CPOE) systems can highlight patients' allergies to medications or potential interactions between different prescriptions, as well as ensure that medications are delivered more reliably. Although there are benefits and drawbacks to any technology, studies have found that using such electronic systems can potentially improve safety. One study found a 41 percent reduction in potential adverse drug events following the implementation of a CPOE system, while another found that overall medication error rates dropped by 81 percent (Bates et al., 1998, 1999; Potts et al., 2004). Further improvements may be seen with the use of new computational designs, such as the IBM Watson system, which can review large numbers of journal articles, clinical trials, guidelines, and medical records to apply the best evidence to a specific patient care situation.

Digital technologies also provide a paradigm for managing chronic diseases. Remote monitoring, such as devices that monitor heart conditions and blood sugar levels, can feed data in near real time to electronic health record systems (Manyika et al., 2011). With these technologies, for example, diabetics could monitor changes in their blood sugar after eating different foods and after different levels of exercise, giving them greater control over their condition. Additionally, at each consecutive appointment their provider could see blood sugar data for every day since their previous appointment, giving the provider greater ability to spot trends and precisely fine-tune medications.

On another front, increases in computing power allow for the use of advanced statistical analysis, simulation, and modeling. These new statistical techniques can help segment results for different populations, as well as highlight the impact of different interventions on population health (Berry et al., 2006). Advanced analysis, simulation, and modeling techniques may also allow for more sophisticated population-level planning and policy development. In addition, the growth in computational power makes possible simulation models that can replicate physiological pathways and disease states (Eddy and Schlessinger, 2003; Stern et al., 2008). These models can then be used to simulate clinical trials and tailor clinical guidelines to a patient's particular situation and biology (Eddy et al., 2011). As computational power increases, the potential applications of these simulation and modeling tools will continue to advance.

Conclusion 4-1: Advances in computing, information science, and connectivity can improve patient-clinician communication, point-of-care guidance, the capture of experience, population surveillance, planning and evaluation, and the generation of real-time knowledge—features of a continuously learning health care system.

Related findings:

• Computing capacity is improving rapidly, enabling large-scale data analysis and improved care. Over the past three decades, computer processing speed has grown by an average rate of 60 percent per year, and the capacity to share information across telecommunications networks has grown by an average of 30 percent per year.
• The digital infrastructure for routine health care is developing rapidly. Projections are for 90 percent of physicians to have access to fully operational electronic health records by 2019, up from 34–35 percent in 2011.
• Digital capacity to provide electronic decision support prompts at the point of choice holds promise for transforming the safety and effectiveness of care. One study found that implementation of a computerized physician order entry (CPOE) system reduced potential adverse drug events by 41 percent.
• Developing digital communication capacity opens up the possibility of rapidly and seamlessly connecting researchers, patients, and providers. The number of Americans with access to the Internet grew from 14 percent in 1995 to almost 80 percent in 2011, and by 2020 there will be 10 billion mobile Internet-connected devices in use.
• Web-based health information holds considerable promise for informing patient decisions. Fully 80 percent of Internet users now look for health information online, making this the third most popular Internet activity.

LESSONS IN CONTINUOUS IMPROVEMENT FROM OTHER INDUSTRIES

Over the past several decades, many industries have developed new methods to improve safety, reliability, quality, and value. Several organizations have learned how to manage and analyze large volumes of information; how to coordinate their workers (numbering in the hundreds or thousands) to create products or services with consistent quality; and how to ensure reliable performance, even under conditions of high risk. Several of these methods could be adapted to health care to improve the system's performance. In such adaptation, it is important to consider unique aspects of health care, such as patient diversity and the technical complexity of modern medicine, that may limit the methods' applicability, as well as the many factors that could affect their implementation. A discussion of the factors that influence the diffusion of innovation, including characteristics of the discovery, characteristics of the potential adopter, and environmental factors, can be found in Chapter 6.

OPPORTUNITIES FROM A CHANGING HEALTH POLICY LANDSCAPE

Across the United States, there is growing momentum to implement novel partnerships and collaborations that test delivery system innovations aimed at high-value, high-quality health care. In many settings, federal, state, and local governments; public and private insurers; health care delivery organizations; employers; patients and consumers; and others are working together to pursue shared interests of controlling health care costs and improving health care quality. The convergence of these novel partnerships, a changing health care landscape, and investments in needed knowledge infrastructure establishes a potentially unique opportunity in the nation's history to achieve a learning health care system.

Many states have been at the forefront of initiatives to expand health insurance coverage, improve care quality and value, and advance the overall health of their residents. Massachusetts, the first state to enact a plan to achieve universal health insurance coverage for its residents, achieved a 98 percent coverage rate for its population following the passage of its 2006 health care reform law (Raymond, 2011). To extend coverage to previously uninsured state residents, the state established the Commonwealth Care Health Insurance Program (CommCare), a publicly funded health insurance program for low-income adults; Commonwealth Choice (CommChoice), a program that assists those individuals who are ineligible for CommCare but do not have access to employer-sponsored insurance; and the Connector, which provides an exchange that residents can use to purchase insurance plans. The Quality and Cost Council, established as a provision of the health care reform law, was charged with developing and coordinating quality improvement goals, with the objectives of lowering costs and improving care quality, and further legislative action on these goals is likely (McDonough et al., 2008; Raymond, 2011; Song and Landon, 2012). At the same time, private initiatives are being established to focus on health care payment and value.

Utah is another state that has established a health insurance exchange, which was created by legislation in 2009. The exchange supplies a technological foundation for providing information on health insurance and comparing different plans, as well as a standardized electronic application and enrollment system for purchasing insurance. One question that states consider when establishing exchanges is the extent to which they prefer to engage actively in the market, such as by setting minimum quality standards for plans, limiting variations in plan offerings, or including a bidding process. Some states have taken a more active role, while others have preferred to take a more market-oriented position (Corlette et al., 2011).

Vermont also has initiated a number of health care reforms, simultaneously establishing its own Vermont Health Benefit Exchange and beginning the transition to a single-payer system (State of Vermont, 2011). These reforms build on Vermont's 2006 health care reform legislation, which established the Catamount Health Plan to provide an insurance option for uninsured individuals with incomes below 300 percent of the poverty level, and developed initiatives to create a statewide, integrated electronic health information infrastructure (Kaiser Family Foundation, 2007). In parallel with coverage- and insurance-oriented reforms, Vermont passed legislation to implement delivery system reforms, including patient-centered medical homes, community-based support teams, coordinated transitions with medical and nonmedical services, multi-insurer payment reforms that align incentives with health care goals, a statewide health information network, and the data systems necessary to support knowledge generation and a learning health care system (Bielaszka-DuVernay, 2011).

Potential opportunities also lie in leveraging changes in recent national health care legislation. Recent legislation includes initiatives related to three objectives of particular relevance for a learning health care system: expanding clinical research knowledge, increasing digital capacity, and improving the value achieved from health care. While this legislation provides one potential path for advancing these three objectives, several other paths are possible. Regardless of the path followed, however, each of these objectives is critical for advancing a learning system.

Seeking to increase the level of clinical effectiveness research, the Patient Protection and Affordable Care Act (ACA) of 2010 established the Patient-Centered Outcomes Research Institute (PCORI), an independent, not-for-profit, private research organization. To accomplish its mission, the organization will support patient-centered outcomes research that compares the benefits and risks of different interventions, therapies, or delivery system initiatives. In support of these priorities, funding of $210 million has been provided for the first 3 years, rising to $500 million annually from 2014 to 2019 (Washington and Lipstein, 2011). While it is premature to judge PCORI's work, increasing the level of knowledge about comparative effectiveness is critical to building a learning system.

To promote the adoption of health information technologies, the Health Information Technology for Economic and Clinical Health (HITECH) Act, part of the American Recovery and Reinvestment Act, formalized the Office of the National Coordinator for Health Information Technology in the Department of Health and Human Services and provided substantial financial incentives for health care providers and hospitals to adopt and use electronic health records. Resources devoted to those programs include $2 billion for programs by the National Coordinator, as well as almost $30 billion in Medicare and Medicaid incentive payments to physicians and hospitals (Blumenthal, 2009; Buntin et al., 2010). Notably, the act encourages not only the adoption but also the meaningful use of such record systems, which is projected to yield savings of $93 billion between 2011 and 2019 (Congressional Budget Office, 2009).

A considerable portion of the ACA is focused on value initiatives. The law established pilot programs to test bundled payments, created value-based purchasing for several common conditions, and reduced Medicare payments to hospitals with high rates of avoidable readmissions and health care–acquired conditions (see Appendix C). One prominent program designed to improve value is the development of accountable care organizations (ACOs). ACOs are voluntary groups of physicians, hospitals, and other health care providers that assume responsibility for specified patient populations. As noted in the final October 20, 2011, regulation for the Medicare Shared Savings Plan, ACOs are responsible for delivering high-quality care as defined by specified quality measures, and share with Medicare any savings that result from better care coordination (Berwick, 2011). These programs are intended to spread the concept of coordinated care beyond Medicare to all payer arrangements.

Another ACA provision focused on value is the creation of the Center for Medicare & Medicaid Innovation. The Center is charged with testing and evaluating innovative payment and delivery system models that could improve care quality while slowing cost growth in Medicare, Medicaid, and the Children's Health Insurance Program (CHIP). While the ACA outlines approximately 20 areas the Center could consider at the outset, it gives the Center substantial flexibility to explore different models. Successful models may be extended to a larger patient population with approval by the Secretary of Health and Human Services. The Center's ultimate goal is to promote the rapid development and diffusion of innovative payment and delivery models that can improve quality and value (Guterman et al., 2010). In its first year, the Center introduced 16 initiatives and stimulated numerous other activities (Center for Medicare & Medicaid Innovation, 2012).

Passage of legislation alone will not lead to fundamental change in the health care enterprise. The legislation will have to be carefully implemented to better orient health care toward science and value. These reforms are an ongoing process and will evolve over time in response to changing national conditions.

Federal and state government actions are complemented by multiple initiatives on the part of employers, specialty societies, patient and consumer groups, health care delivery organizations, health plans, and others seeking to improve the health care system:

• In 2012, the American Board of Internal Medicine (ABIM), along with nine other specialty societies, released its Choosing Wisely campaign, focused on reducing overuse of specific medical tests or procedures in different health care specialties (Cassel and Guest, 2012). The first stage of the campaign, piloted by the National Physicians Alliance, developed a list for use by primary care practitioners to promote the more effective use of health care resources (Good Stewardship Working Group, 2011); current initiatives are working to expand this list to additional medical specialties.
• Drawing on their experiences in improving outcomes and lowering costs through initiatives in their own institutions, a group of health care delivery leaders has developed “A CEO Checklist for High-Value Health Care,” which describes system-change approaches that can be adopted in most health care settings to improve outcomes and reduce costs of care (Cosgrove et al., 2012) (Appendix B).
• The Patient-Centered Primary Care Collaborative is an initiative that seeks to spread patient-centered medical homes.
• Other innovative approaches are being explored by partnerships among health systems, employers, payers, and other key stakeholders. In 2004, for example, Virginia Mason negotiated an arrangement with Aetna by which Virginia Mason production system's lean methods would be used to provide care more efficiently in exchange for Aetna's providing analyses of claims data to support the endeavor. Four major employers in the Seattle market—Costco, Starbucks, King Country, and Nordstrom—also participated, each choosing a condition prevalent among their workforces on which Virginia Mason should concentrate its efforts to deliver high-value care (Ginsburg et al., 2007; Pham et al., 2007).
• In Wisconsin, two multistakeholder groups—the Wisconsin Collaborative for Healthcare Quality and the Wisconsin Health Information Organization—work to collect, measure, and report health care quality and efficiency data with the aim of encouraging value-based payment (Toussaint et al., 2011).
• All-payer databases are being established in various states around the country.
• Community-based initiatives include the Aligning Forces for Quality program and the Chartered Value Exchange project.

As these examples illustrate, sustained transformation will require initiatives and partnerships that nurture continuous learning and promote improvement and innovation.

Conclusion 4-3: Innovative public- and private-sector health system improvement initiatives, if adopted broadly, could support many elements of the transformation necessary to achieve a continuously learning health care system.

Related findings:

• Many states have undertaken productive health system improvement initiatives. States ranging from Massachusetts to Utah to Vermont have introduced initiatives aimed at expanding health insurance coverage, improving care quality and value, and advancing the overall health of their residents.
• Incentives for the adoption of health information technology may promote learning and yield substantial savings. The Health Information Technology for Economic and Clinical Health (HITECH) Act provides $30 billion in Medicare and Medicaid incentive payments for the meaningful use of health information technology by clinicians and hospitals, which has been estimated to yield savings of $93 billion between 2011 and 2019.
• Efforts to encourage innovative payment and delivery models may help steward the transition to a continuously learning system. The Center for Medicare & Medicaid Innovation, created to promote the rapid development and diffusion of innovation that could improve the effectiveness and efficiency of care, has stimulated activities beyond the 16 initiatives introduced in its first year.
• Increased comparative effectiveness research may yield insights that can help clinicians and patients make better-informed health care decisions. The Patient-Centered Outcomes Research Institute (PCORI), created to increase the quality and quantity of information about what works best for whom, will receive annual funding of $500 million from 2014 through 2019.
• Partnerships and collaborations are increasingly identifying and testing opportunities for improving care delivery. Multiple initiatives by employers, specialty societies, patient and consumer groups, health care delivery organizations, health plans, and others are aimed at improving the health care system. These initiatives include the American Board of Internal Medicine (ABIM) Choosing Wisely campaign, the Good Stewardship project, the Patient-Centered Primary Care Collaborative, and others.

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Footnotes

1

Based on searches of major vendors.