Carolyn Thornton was at home baking on Thanksgiving day when her heart palpitations, which she had been experiencing for some time, suddenly got worse. A visit to her doctor confirmed that Carolyn had myocarditis and congestive heart failure. But Carolyn’s treatment would be different from that of other patients with her condition. After being discharged from the hospital, Carolyn was enrolled in Partners HealthCare’s Connected Cardiac Care program, a home monitoring and education program for patients at risk for hospitalization. Each morning, patients in the program use home telemonitoring technology to take their own weight, blood pressure, pulse, and oxygen levels and answer questions about their symptoms. The data from these tests are sent to a telemonitoring nurse, who reviews patients’ vitals and takes appropriate follow-up steps for out-of-parameter readings, including calling the patient or coordinating care with the patient’s care team (Partners HealthCare Center for Connected Health, 2012). These prompt interventions can often help avoid unplanned hospital admissions—to date, the Connected Cardiac Care program has achieved a 51 percent reduction in heart failure readmissions (Cosgrove et al., 2012). Telemonitoring nurses also guide patients through structured heart failure education sessions to help make them aware of the impact of their daily behaviors on their condition and to help them develop new self-management skills (Partners HealthCare Center for Connected Health, 2012). The program illustrates how
new remote monitoring and connectivity capabilities can help patients like Carolyn and others monitor and manage complex health conditions.
Although the challenges of complexity and value confronting U.S. health care today are formidable, opportunities exist to mold the system into one characterized by continuous learning and improvement. Advances have made vast computational power affordable and widely available, while improvements in connectivity have allowed information to be accessible in real time virtually anywhere. Progress in these areas has the potential to improve health care by increasing the reach of research knowledge, providing access to clinical records when and where needed, and assisting patients and providers in managing chronic diseases. Another area of opportunity lies with the human and organizational capabilities developed by diverse industries to improve safety, quality, reliability, and value; many of these capabilities can be adapted to health care settings to improve performance. Finally, recent changes in health policies present opportunities that can be leveraged to promote the growth of a learning health care system. Together, these opportunities can operate synergistically to enable more transformative change than can be accomplished with any of them individually. The path toward a more effective and efficient health care system will not be an easy one, but recent advances demonstrate the real potential for the necessary transformation.
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).
1Based on searches of major vendors.
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.
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.
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, which has focused on using data to improve its customer retention. These data originate from the company’s loyalty program, Total Rewards, which has generated a customer information database that grew to more than 40 million members in 2010. The data, tracked by each customer’s Total Rewards card, range from the total number of visits customers have made to a particular casino, to their buffet activity, to the amount of money they win or lose on an average visit. When it appears that customers may be frustrated in their experience, the company’s analysis allows the Total Rewards staff to make data-supported decisions on the timing, type, and magnitude of promotional offers that have the highest likelihood of bringing those customers back. By tracking these offers and customers’ subsequent visits, the company is able to monitor the success of the predictions. Through the use of evidence to predict the most effective offer for each customer, the company can ensure that a high proportion of customers will be enticed to return, which translates to guaranteed revenue for the business.
SOURCES: Greenfeld, 2010; National Public Radio, 2011.
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).
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
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 an opportunity to expand the evidence base on which clinicians can draw, especially in the absence of published data. For example, a group of pediatricians was treating a 13-year-old girl with systemic lupus erythematosus (SLE). Her autoimmune disease was complicated by conditions that put her at risk for blood clots, and her physicians considered the administration of an anticoagulant as a preventive measure. However, the physicians could not find any evidence (either peer-reviewed literature or expert opinion) pertaining to the patient’s situation. Given the need to make a decision quickly, they reviewed the medical records from their institution, collating the records of 98 other pediatric SLE cases handled by their division in the past 5 years. Based on these data, they conducted a cohort review and ascertained that children with similar complicating conditions had been more likely to develop blood clots. They then recommended anticoagulant use within 24 hours of the patient’s admission. The patient did not develop blood clots or experience any anticoagulant-related complications. Although this form of data review does not eliminate more extensive clinical research protocols, the data in the electronic medical records allowed a real-time clinical decision to be made based on the best available data, an approach that holds promise for larger-scale use.
SOURCE: Frankovich et al., 2011.
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.
- 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.
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.
Lessons for Enhancing Safety
The IOM publication To Err Is Human: Building a Safer Health System highlights several practices from other industries that health care practitioners could adopt to improve the safety of care (IOM, 1999). In particular, the health care system has opportunities to leverage the knowledge gained by industries that also confront high risk and complexity. Several of these industries have developed methods for substantially reducing the number of accidents and effectively mitigating human error.
One high-risk industry that has made substantial progress in safety is aviation. Improving mechanical components and ensuring that redundancies exist resulted in a sharp decline in aviation accidents. Even after these improvements, however, a residual level of accidents remained. Further improvement in the accident rate required addressing human factors. The industry adopted advanced safety measures centered on the assumptions that human error is inevitable and that systems must be designed to correct for individual mistakes (Nance, 2011; Wiegmann and Shappell, 2001). As a result, the safety of commuter air travel has improved dramatically. Domestic commercial commuter airlines reported 2.1 fatalities per 100,000 aircraft departures in 1980 and zero fatalities from 2007 to 2010 (Bureau of Transportation Statistics, 2011).
Industries that manage complex risks, such as aviation and nuclear power, operate on the assumption that accidents can be prevented through good organizational design and management. These industries are characterized by a commitment to safety, standard work processes, and a strong organizational culture for continuous learning (IOM, 1999). For example, the culture of these organizations encourages workers to search routinely for environmental factors or processes that could cause failure. Uncovering these safety concerns as a matter of common practice can allow the organization to address problems at a stage when they are easily fixed and before they have led to an accident (Chassin and Loeb, 2011).
Efforts to introduce safety practices from other high-risk industries into health care have yielded positive results for patient safety. One initiative, for example, introduced several methods drawn from aviation, such as checklists and a focus on teamwork and communication, to address catheter-related bloodstream infections. These methods eliminated such infections in the intensive care units of most hospitals and resulted in an 80 percent
decrease in infections per catheter-day (Pronovost et al., 2006, 2009). The checklist concept has been diffused through the World Health Organization’s Surgical Safety Checklist. Implementing this checklist has reduced fatalities and surgical complications by approximately one-third globally (Haynes et al., 2009). In another example, Great Ormond Street Hospital for Children drew on the pit stop techniques of the Ferrari Formula One race car team to redesign several aspects of its process for handoff from cardiac surgery to intensive care unit, yielding a 50 percent reduction in error rates (Catchpole et al., 2007). While not all industry safety methods will be effective in a health care setting, these examples illustrate the potential for practices pioneered in other industries to improve patient safety when adapted to a health care environment (Lewis et al., 2011). Chapter 9 explores additional lessons for managing errors in terms of reporting, organizational culture, and mitigation of impacts.
Lessons for Improving Quality and Value
Other potential lessons for health care come from commercial strategies for managing and improving the quality and value of goods and services (Hammer, 2004; Kenney, 2008). These strategies, including lean, Six Sigma, and others, introduce methods for coordinating complex work across diverse organizations, identifying existing and potential problems, and addressing those problems systematically (Chassin and Loeb, 2011; Kaplan et al., 2010). All of these strategies imply that the goal should not be to make the system work perfectly immediately, but to establish a process of gradual improvement (Young et al., 2004).
One notable strategy for improvement is the Toyota production system (Bohmer, 2010; Kenney, 2011). Under this system and related strategies, work is viewed as a series of ongoing experiments that immediately reveal problems. First, each worker’s tasks are broken down into highly regimented sequences of steps. These steps make clear when workers are deviating from specifications and help both workers and their supervisors monitor adherence to the work process. Second, connections and communications among workers and between workers and outside suppliers and customers are standardized. Each communication unambiguously states the expected result of the request, the person or people responsible, and the time within which the request will be met. The third step of Toyota’s production system is to create simple, defined workflows for the products, services, and help requests that make up the company’s production lines. These workflows deliberately and systematically link sets of tasks and communications together, thereby reducing ambiguities. When ambiguities do arise, the fourth and final step of Toyota’s production system is to teach workers how to address them, requiring that changes to workflows be in
accordance with the scientific method, guided by a teacher, and made at the lowest possible level of the organization. To meet this requirement, Toyota trains its workers to frame problems and to formulate and test solutions. In this way, the organization fosters a learning environment in which workers at all levels are invested in identifying the root cause of problems and developing practical, implementable solutions (Spear and Bowen, 1999).
Additional methods that have shown success in improving quality come from the fields of systems engineering, industrial engineering, and operations research. Major corporations, from Wal-Mart to Boeing, could not operate their complex organizations without extensive use of engineering tools for the design, analysis, and control of complex production and distribution systems. These tools help companies coordinate deliveries from suppliers and manage complex production across multiple sites, and allow production to improve continuously. Several of these tools, including statistical process controls, supply chain management, modeling, and simulation, could be applied to improve health care processes (Agwunobi and London, 2009; IOM, 2005; IOM and NAE, 2011).
Initial results from the application of these methods to health care settings have been positive. For example, one hospital that applied the lessons of queuing theory and variability methodology was able to smooth the flow of patients, thereby increasing its surgical volume by 7 percent annually for 2 years without increasing staff or adding beds, while simultaneously improving the quality of care (Litvak and Bisognano, 2011). Similarly, a pharmacy unit at a large hospital applied production system methods to streamline its work. By undertaking systematic problem solving, the unit not only reduced the time spent searching for medications by 60 percent and the number of times medications were out of stock by 85 percent, but also substantially decreased the amount of medication that was spoiled or wasted (Spear, 2005).
Conclusion 4-2: Systematic, evidence-based process improvement methods applied in various sectors to achieve often striking results in safety, quality, reliability, and value can be similarly transformative for health care.
- Industries that regularly confront high risk and complexity have successfully transformed performance. For example, domestic commercial commuter airlines reported 2.1 fatalities per 100,000 aircraft departures in 1980 and zero fatalities from 2007 to 2010.
- The introduction of safety practices from high-risk industries into health care has already improved patient safety. In one study, the use of checklists inspired by the aviation industry eliminated catheter-related bloodstream infections in the intensive care units of most hospitals in the study and resulted in an 80 percent decrease in infections per catheter-day.
- Commercial strategies for improving the reliability of the delivery of goods and services have potential applicability to health care. A pharmacy unit, for example, undertook systematic problem solving and reduced the time spent searching for medications by 60 percent and the frequency of out-of-stock medications by 85 percent.
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.
- 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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