Advancing the Public’s Health by Scaling Innovations in Clinical Quality

Clinical care improvements that advance population health are important to public health policy and practice. Increasingly, evidence-based clinical care quality improvement efforts are reflected in the legally binding standards that govern the certification of health care entities and institutions, as well as private insurance coverage and payment. As clinical practice is reengineered to improve quality of care, these new practice standards can become embedded in the legal rules and norms governing health care in ways that spread innovation and create access to evidence-based services across the population.

This installment of Law and the Public’s Health provides a foundation for understanding the theory of innovation diffusion and opportunities for spreading innovations aimed at prevention in health care settings. Our research grows out of a project with the Division of Unintentional Injury Prevention at the Centers for Disease Control and Prevention (CDC) to examine how innovations in clinical practice related to falls prevention among community-dwelling older adults can more rapidly reach at-risk populations. Although this project focuses on falls prevention, it is relevant to public health policy and practice more generally.

The Evolution of Clinical Practice

Moving health care innovations from research to practice is challenging. Studies have shown that, on average, patients receive slightly more than half of recommended health care services ¹ ; however, it may take up to 2 decades for original research and recommendations to become part of routine clinical practice. ^{2 –4} The delays associated with this translation are a substantial barrier to improving the quality of health care. ⁵

Legal, regulatory, and/or policy changes are often required before evidence-based health care innovations become embedded into the standard of care. In some instances, the standard of care in medicine has been propelled through individual legal actions to redress injuries that in turn spur health care providers to improve clinical practice. A basic principle of American law is that industries are liable for death and injury resulting from failure to adopt readily available, low-cost technologies into everyday practice. ⁶ This principle has been applied to health care, most notably in Helling v Carey, in which the Washington State Supreme Court held that failure to incorporate low-cost screening technologies into clinical practice (in this case, a glaucoma test) could lead to liability for injury. ⁷

Although medical liability actions can drive the evolution of the professional standard of care, ⁸ medical liability actions are typically ineffective in achieving reform given that such lawsuits are often haphazard and infrequent. Only about 4% of patients with a potential negligent or preventable medical claim file a lawsuit, and only about one-quarter of these cases lead to a judgment against the health care provider. In many cases, juries and medical experts disagree as to whether or not a medical error occurred in the first place. ^9,10 In addition, evidence on whether the typical malpractice lawsuit can push health care practice forward in ways that lead to care improvement is conflicting; for example, lawsuits may encourage physicians to practice defensive medicine (ie, ordering more tests or hospital admissions without benefit to patients) in the hopes of diminishing legal liability. ^11,12

For decades, advocates of a modern approach to systemic health care quality reform have turned to other legal and regulatory tools to advance health care quality, aiming to incentivize the adoption of new evidence-based practices.

Scaling Innovation

Scaling is the process of translating an innovation that is proven to be effective into widespread practice. ¹³ Scaling health care innovations can take years, ^{2 –4} in part because of the complexity of the health care system. ¹⁴ Certain characteristics have been found to make innovations more readily adopted into health care practice. The literature highlights 6 key attributes that facilitate successful implementation of innovations ^{15 –17} :

Credibility: For innovations to be scaled successfully, they should be built on a strong evidence base. ¹⁸

Relative advantage: Innovations that have a clear, unambiguous advantage over current practice (eg, intervention improves health outcomes, reduces clinician workloads, or reduces cost) are more readily adopted and implemented. ^{18 –20}

Simplicity: Innovation complexity can hamper scaling efforts; when innovations are perceived as straightforward, even when they are supported by complex science, potential adopters are less intimidated. ^{21 –24}

Testability: Innovations may be adopted and assimilated more easily when intended users can, with minimal investment, pilot test and experiment with innovation design. ^14,17,22,25

Observability: Readily observable health care innovations generate discussion among potential adopters and help to spread new ideas; without observability, stakeholders may not easily understand the relative advantage of an innovation. ^22,25,26 Innovations aimed at prevention often have a particularly slow rate of adoption because the benefits of an intervention are not immediately observed.

Compatibility: When innovations are compatible with current health care practices and reimbursement structures, they are more easily adopted. ^17,18,27,28

A health care organization’s decision to adopt and sustain a scalable innovation depends on several factors. Commitment to change from leaders (both administrative and clinical leaders) is critically important. ²⁹ The literature describes the importance of making the business case to leadership to show the advantage of a particular innovation, not just in terms of the 6 characteristics described previously, but also in terms of (1) justifying why resources should be spent on a particular innovation rather than on other priorities and (2) showing how the innovation, if successfully adopted, will fulfill the organization’s goals (eg, support quality measurement, help organization achieve community outreach goals). ²⁹

Organizations also need the internal capacity to embrace change. ¹⁶ Implementation may require organizations to develop or modify health information technology systems, purchase equipment, hire and train staff members, or coordinate with external organizations. ²⁹ Innovations aimed at prevention tend to be time intensive for clinicians, and many settings—especially community health centers and other entities that serve the most vulnerable populations—are so challenged with competing demands that it can be difficult to focus on wellness and disease prevention. ^{30 –32} When an innovation is coupled with incentives (eg, funding to pilot test an innovation or insurance reimbursement to pay for an innovation once implemented), uptake is more feasible. ²⁹

Methods of Scaling

Scaling requires strategic efforts to move innovations from research to practice. Passive methods to increase knowledge or change behavior (eg, scientific journal articles, professional presentations, collaborative learning forums, clinical practice guidelines) are generally ineffective when used alone. ^{33 –36} Although these techniques may increase knowledge about new innovations, they do not, on their own, incentivize change in provider practice or health care organizational structure to promote the adoption of innovation. Legal, regulatory, and/or policy changes are often required before evidence-based health care innovations become embedded into the standard of care.

Scaling Tools

Benefit Design

Health benefit mandates are laws that require health insurance carriers to include specific benefits in certain coverage plans. When health benefit mandates embed clinical practice improvements into insurance coverage, they ensure patient access to evidence-based care. Benefit redesign through laws, such as the coverage reforms contained in recent legislation and in state-specific mandates, requires insurers to cover (without cost sharing) services such as evidence-based preventive services rated as A (strongly recommended) or B (recommended) by the US Preventive Services Task Force (USPSTF). ³⁷ Benefit redesign can help ensure access to evidence-based innovations as they become available while promoting their rapid spread through the insurance market.

Payment Reform

The evolution of quality improvement theory and practice has led both public and private insurers to adopt financing structures that link payment to practice and outcome. The Affordable Care Act contains numerous provisions intended to reform how health care is delivered and paid for, including establishing accountable care organizations, advancing Medicare bundled payments, and establishing the Center for Medicare & Medicaid Innovation, whose purpose is to test innovative payment and service delivery models to reduce expenditures and enhance quality of care. ³⁸ Increasingly, quality improvements are tied to payment, which ensures that treatment innovations become routinized into patient care. ^26,39,40

Quality Reporting

Quality reporting can assist in diffusion of innovation by measuring and incentivizing health care provider compliance with a particular innovation. For example, the Merit-based Incentive Payment System, effective January 1, 2017, encourages physicians and group practices, through payment incentives, to report performance information to Medicare, incentivizing performance that improves quality metric scoring for quality measures previously included in the Medicare Physician Quality Reporting System. ⁴¹

Surveillance Systems and Disease Registries

Health care surveillance systems are relevant for scaling innovation, because they can yield the type of information that leads to the adoption of innovations. Disease registries—a type of surveillance designed to collect information about people with certain diagnoses or conditions ⁴² —have the potential to transform the way chronic diseases are managed, by prompting the adoption of improved approaches to treatment and management. ^43,44

Clinical Decision Support Tools

Electronic clinical decision support systems use evidence-based guidelines to help physicians make the best possible decisions for patient care by organizing and synthesizing information and filling information gaps. ⁴⁵ For example, a decision support tool can quantify health risks and guide interventions that are needed to reduce that risk. These tools can encourage physicians and organizations to adopt evidence-based care and adhere to clinical guidelines. ^46,47

Hepatitis C as a Model for Scaling Innovation

Typically, scaling techniques occur in parallel. For example, evidence shows that people born between 1945 and 1965 are more likely to have hepatitis C virus (HCV) infection than people born during other periods. ⁴⁸ Since June 2013, the USPSTF has recommended, with a B rating, one-time HCV screening for this population. ⁴⁹ With this rating, new private health plans (for plans or policy years beginning on or after September 23, 2010) and expansion Medicaid plans are required to cover the HCV screening test in network without cost sharing. Medicare has covered, without cost sharing, one-time HCV screening for people born from 1945 through 1965 since June 2014 ⁵⁰ and added HCV screening for the target population to the Physician Quality Reporting System in 2015. ⁵¹ Some states mandate that certain clinicians provide HCV screening, ⁵² and the American Gastroenterological Association developed a clinical decision support tool for HCV screening. ⁵³ This alignment of scaling tools—including benefit design laws, quality reporting, and clinical decision support tools—has, in turn, promoted the uptake of HCV screening among people born between 1945 and 1965. ⁵⁴ Although challenges to screening adoption remain, ^55,56 evidence suggests that the HCV screening rate for the target population increased by as much as 10% from July 2012 to July 2014. ⁵⁷ Individual primary care practices have seen greater increases in HCV screening rates when they incorporated a clinical decision support tool in their electronic health record compared with when no clinical decision support tool was added. For example, in one practice, HCV screening rates among patients with no previous testing increased 254% with the help of an electronic clinical reminder. ⁵⁸

Falls are common among community-dwelling older adults, and several evidence-based interventions can aid in prevention, such as medication management and vitamin D supplementation, as recommended by CDC’s Stopping Elderly Accidents, Deaths & Injuries initiative. ^59,60 However, although 1 in 4 people aged ≥65 who live in the community fall every year, ⁶¹ fewer than half of these patients talked to their health care provider about their risk of falls in the previous year. ⁶² What may contribute to low levels of screening and assessment for risk of falls is that, unlike for HCV screening, few national-level policies support the widespread diffusion of programs to prevent falls. For example, falls-risk screening and assessment does not have an A or B recommendation by the USPSTF, ⁶³ and no unique Current Procedural Terminology code for falls-risk assessment is tied to insurance reimbursement. Without direct reimbursement, it is harder to convince physicians to focus on falls-risk prevention in the limited time allotted to wellness visits. Furthermore, Medicare quality measures in place account for the assessment of high-risk patients but not the initial screening to identify those at risk ⁶⁴ ; as a result, quality measures may not motivate providers to screen patients to determine which older adults ultimately require a falls-risk assessment. These realities mean the health care system does not push practitioners toward screening older adults for falls. As a result, some patients may never receive a comprehensive falls-risk assessment, even if their risk is high.

Efforts under way, such as the USPSTF’s current review of falls prevention ⁶⁵ and quality measures in development, ⁶⁶ may yield new incentives to providers to offer falls prevention services, but other challenges remain. Barriers in clinical practices may inhibit uptake of falls prevention services: for example, time, provider awareness and knowledge, competing priorities, scheduling issues, and reimbursement concerns. ^67,68 HCV screening and other similar preventive services may be simpler and more compatible with health care workflows—for example, administering a simple blood test when blood is being drawn for other reasons vs engaging patients in a discussion about the risks of falling in their home—making it more difficult for falls-risk screening and assessment to become embedded into routine practice. A 2016 study outlined several keys to successfully overcoming these barriers in clinical practices, including developing health information technology tools, designing workflows to guide clinical practice, and having proactive leadership of clinical champions. ⁶⁹

Implications for Public Health Policy and Practice

This review of changes in the diffusion and innovation of health care summarizes the tools for scaling innovation that are in use today and illustrates how these tools can be aligned to achieve maximum effect. As the field of public health increasingly turns to clinical practice as a key strategy for achieving public health goals, understanding how these tools operate alone and in coordination to advance population health becomes an essential part of public health practice, particularly in an era of health care reform. Mechanisms such as payment reform, quality reporting, surveillance, and clinical decision support can work together to advance public health aims. The ability to use these tools to achieve measurable change at the population level should be a core element of public health practice.