Nudging best practice: the HITECH act and ...

Nudging best practice: the HITECH act and behavioral medicine

Translational Behavioral Medicine Practice, Policy, Research ISSN 1869-6716 Volume 1 Number 1 Behav. Med. Pract. Policy Res. (2011) 1:175-181 DOI 10.1007/ s13142-010-0001-3

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PRACTICE AND PUBLIC HEALTH POLICIES

Nudging best practice: the HITECH act and behavioral medicine B W Hesse, PhD,1 D K Ahern, PhD,1 S S Woods, MD, MPH1

1 Division of Cancer Control and Population Sciences, National Cancer Institute, Executive Plaza North, Room 4068, 6130 Executive Blvd., MSC 7365, Bethesda, MD 20892-7365, USA Correspondence to: B W Hesse [email protected]

Cite this as: TBM 2011;1:175–181 doi: 10.1007/s13142-010-0001-3

Abstract In February 2009, the US Congress passed the Health Information Technology for Economic and Consumer Health (HITECH) Act in order to stimulate the “meaningful use” of health information technology within medical practice. Economists have noted that other sectors in the economy have demonstrated substantive productivity improvements from investments in information technology but that the health sector lags behind. The “meaningful use” stipulation of the HITECH Act focuses systems redesign within the health sector on user’s behavior, a provision that opens a window of contribution from specialists in behavioral medicine. There are several ways for behavioral medicine to become involved in the redesign. One is to help craft a health services environment that optimizes communication between providers and patients, between primary care and specialist care providers, and between patients and their caregivers. Another is to help practitioners and policymakers create new “decisional architectures” for “nudging” behavior in positive ways through better incentives, understandable instructions, healthy defaults, instructive feedback, back-ups for error, and structured decision-making. New funding opportunities in research, implementation, and training may facilitate the involvement of behavioral medicine—an involvement that is crucial for ensuring the success of reform efforts in the long run. Keywords

Meaningful use, Informatics, Electronic health record, Sociotechnical On April 6, 2009, the director of the US Office of Management and Budget (OMB)—the agency responsible for bringing the national budget under control— had this to say about escalating healthcare costs: “Too many academic fields have tried to apply pure mathematical models to activities that involve human beings. And whenever that happens—whether it’s in economics or health care or medical science—whenever human beings are involved, an approach that is attracted by that purity will lead you astray.” The key to understanding the tenets of healthcare reform, the director went on to say, lies in “understanding human behavior” [43]. TBM

Implications Recent legislative activity is altering the context of healthcare in a substantive way. This paper analyzes the changes promoted by the Health Information Technology for Economic and Clinical Health Act (Title XIII of the American Recovery and Reinvestment—or stimulus—Bill) of 2009. The authors point out ways in which professionals in behavioral medicine can take advantage of the changes promoted by the HITECH Act to create an environment of care informed by evidence from Behavioral Medicine.

By personal admission, the newly appointed OMB director had been influenced heavily by the writings of behavioral economists Richard Thaler and Cass Sunstein. In their book Nudge: Improving Decisions About Health, Wealth, and Happiness [47], the two economists outlined the principles that would begin to undergird many of the policy recommendations emerging from working committees throughout academia and the federal government in this era of healthcare reform. The basic principles of that book should resonate well with those engaged in translational efforts in behavioral medicine: that the environment in which individuals work and live can have a substantive influence on affect, cognition, and behavior. Restructuring that environment with better-aligned incentives, understandable instructions, healthy defaults, instrumental feedback, corrective mechanisms for errors, and structured supports for decision-making can help channel behavior in self-enhancing rather than selfdestructive ways. The principles are also highly compatible with the systems orientation of the Institute of Medicine’s seminal reports on improving quality in healthcare, which focused on ways of preventing errors by altering the context in which care occurs [34,37,42].

CREATING NEW “DECISIONAL ARCHITECTURES” FOR HEALTH For Thaler and Sunstein, a significant point of intervention lies in creating an information environment for individuals that will reduce errors in page 175 of 181

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decision-making. They refer to the supports in these environments as “decisional architectures” [47]. According to their central thesis, people make hundreds of decisions every day, whether those decisions involve highly deliberative processes, as when selecting a healthcare plan, or they are carried out at a highly routine level, as when making purchasing decisions at the supermarket. In all of these situations, cues and constraints in the information environment can serve to influence decision processes in either facilitative or deleterious ways. An example of how a small change in the decisional environment can have large impacts on costs and health in the behavioral realm can be found in the first report published by the American Psychological Association’s “Decade of Behavior” campaign. The report offered a simple story about how a group of human factors researchers took aim at improving traffic safety by altering the placement of braking indicators on the backs of cars. By studying the visual field of drivers as well as the ergonomic factors surrounding rapid decision-making in traffic conditions, this group of behavioral scientists made a succinct recommendation: place a third brake light in a position that is more visibly salient to drivers in a location around the bottom of the rear window. As it turned out, this simple but meaningful manipulation in the decisional architectures for automobile handlers would end up saving the US economy some $650,000,000 in property damage per year, not to mention even greater savings in pain and suffering [7]. Consider now what the stakes might be for using the science of behavioral medicine to improve the decisional architectures supporting patient care and public health in the USA. In their report on the state of science in cancer control, the directors of the National Cancer Institute’s comprehensive cancer centers underscored their conclusion that practitioners can “substantially reduce deaths from cancer just by broadening the application of knowledge we have today” [13]. Some estimates [31] have suggested that 50% of the 565,650 [6] cancer deaths occurring annually could be prevented through better support for reducing the deleterious influence of behavioral risk factors alone [13,31]. Regardless of whether that number is high or low, health economists at the University of Illinois have estimated that even just a 1% reduction in cancer deaths would accrue over $400 billion in estimated savings to the national economy [13]. Similar predictions have been made for the benefits of reducing the impact of heart disease, diabetes, neurological disorders, and other pervasive chronic conditions that seem to have become the bane of the twenty-first century. With stakes this high, the question then remains: just what are the decisional architectures that could improve the translation of current knowledge into better practice in health and medicine? A founda-

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tional part of that answer, at least from the federal policy perspective, can be found in passage of the Health Information Technology for Economic and Clinical Health (HITECH) Act embedded as Title XIII of the American Recovery and Reinvestment Act (Recovery Act) of 2009. Within the HITECH Act, Congress directed the Department of Health and Human Services (DHHS) to accelerate the “meaningful use” of health information technology (HIT) as a way of improving outcomes for patients while ratcheting back the escalating costs of healthcare due to systemic inefficiencies. Economists have long noted that other sectors in the economy have improved their productivity and maximized returns on investment by taking strategic advantage of information technology [17,18]. Medicine has been slower in that regard and is incurring unsustainable costs as a result of sector-wide inefficiencies and waste. Because of its broad, overarching implications for clinical practice, many consider passage of the HITECH Act to have been the opening salvo in healthcare reform [12,33].

LEVERAGING “MEANINGFUL USE” FROM HITECH From the perspective of behavioral medicine, the “meaningful use” clause of the HITECH Act opens up a particularly compelling window of opportunity. Through the Act, Congress authorized the Centers for Medicare and Medicaid Services (CMS) to provide reimbursement incentives to eligible providers (physicians, dentists, certified nurse midwives, nurse practitioners, or physician assistants) if they were to adopt and implement a certified Electronic Health Records System (EHRs) within their practice. The Act also allows for penalties, at least in terms of reimbursement from Medicare and Medicaid, for lack of adoption in the long run (HITECH [8,19,32]). The hope is that the combination of these two policies will stimulate the adoption and meaningful use of EHRs throughout the economy in line with goals originally set by the previous presidential administration [11]. Additionally, the Act sets aside resources for the Department of Health and Human Services to work with the Department of Commerce (The National Institute of Standards and Technology) and other agencies of the federal government to stimulate the adoption of standards in Electronic Data Interchange, to engage in research as needed, and to offer technical support or training [10]. By fiat, the “meaningful use” clause directs the focus of the DHHS certifying body away from the implementation of HIT for the sake of advancing technology only, to focus instead on the effective use of HIT for improving patient outcomes [33,48]. In this sense, “meaningful use” is inherently a construct imbued with behavioral substance [5]. It accords with recommendations from the National Research Council that investments in computational technol-

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ogy for effective healthcare be balanced to offer “cognitive support” for decision-making “to physicians, patients and their families” [44]. Building on recommendations from the National Quality Forum, advisors to the ONC recommended that the criteria for “meaningful use” be organized around five general objectives. These objectives included: (a) improving quality, safety, and efficiency; (b) engaging patients and their families; (c) improving care coordination; (d) improving population and public health with an emphasis on reducing health disparities; and (e) ensuring privacy and security protections ([33]; HITECH [32]). The technical details underlying these five general objectives for meaningful use will undoubtedly take time to implement and over 2,000 comments from stakeholders regarding the interim meaningful use rule urged ONC–CMS to be less aggressive with thresholds and more flexible in achieving the requirements. The final meaningful use rule was released on July 13, 2010. Given the challenges to eligible providers in meeting the meaningful use rules, the ONC–CMS collaborative has chosen to roll out the certification for meaningful use in stages (see Table 1). Stage 1, beginning in 2011, will focus on capturing health information in coded format, using information to track key clinical conditions, communicating that information for care coordination purposes, implementing clinical decision support tools to facilitate disease management, and reporting quality measures for public health accountability. Stage 2 of the approach, beginning in 2013, will expand upon the Stage 1 criteria to encourage the use of HIT for continuous quality improvement at the point of care and will emphasize the transition of information in the most structured way possible including the use of computerized data entry formats. Stage 2 may also expand the criteria to include coverage at both inpatient and outpatient hospital settings. Stage 3, beginning in 2015, will build on the criteria established in the previous stages to fully embrace overarching goals of safety and efficiency, patient access to self-management tools, access to comprehensive patient data, and improving population health [22].

OPPORTUNITIES FOR BEHAVIORAL MEDICINE Coordinating an electronically enabled system of care within and between practice settings is a necessary, but not sufficient, step in achieving national goals for quality improvement. The real change will occur as practitioners, researchers, and planners identify the sociotechnical structures needed to “nudge” best practice, enabled and supported by HIT, in healthcare settings, community by community, throughout the USA. The goal will be to help medicine evolve from its industrial past in being reactive, inefficient, and mass produced to its twenty-first century ideal of enabling care that is predictive, preemptive, personalized, and participative [16]. The opportunities for involvement in this massive redesign effort are abundant. Following are just a few.

Optimizing patient–provider communication Because of its ability to maintain and transfer electronic information at the click of a mouse, HIT can be used to address the crisis in communication that often plagues an otherwise fragmented system of care [27,39]. Meaningful use of electronic health records, imbued with crucial data from personal and medical histories, can drive prompts for preventive services [23]. Best practice guidelines, embedded within the automated work flows and knowledge structures of a fully realized HIT strategic plan, can help “nudge” evidence-based practice both for treatments administered locally within a single practice and across multiple facilities or areas of specialization [20]. Tracking capabilities can guard against errors that might have otherwise occurred in the process of communication (say, in transmitting prescription information to external pharmacies) while secure messaging channels between patients and their care teams can alert the distributed provider team when symptoms get out of hand or adverse events occur [30]. Patient-facing applications, such as integrated personal health records [26,36,40], can help keep patients informed as to their progress in treatment at every step of the way [36] while predefined conditions or patient–provider requests can be used to prompt for the full inclusion of psychosocial and behavioral medicine services [1,36].

Table 1 | Stage of meaningful use criteria by payment year

First payment year 2011 2012 2013 2014 2015+b

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Payment year 2011 Stage 1

2012 Stage 1 Stage 1

2013 Stage 2 Stage 1 Stage 1

2014 Stage 2 Stage 2 Stage 2 Stage 1

a

Stage 3 criteria of meaningful use or a subsequent update to the criteria if one is established through rulemaking

b

Avoids payment adjustments only for EPs in the Medicare EHR Incentive Program

2015+a Stage 3 Stage 3 Stage 3 Stage 3 Stage 3

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All of these changes in the communication capacity of health systems can be influenced by evidence from behavioral medicine research. Every computer interface represents a set of messages that need to be optimized in order to communicate data in ways that are fault-tolerant for providers and empowering for patients [50]. Every signaling capacity represents a connection between crucial members of the care team and the patient support team that can be strengthened to support timely care, efficient services, and equitable outcomes [9,15,51]. Over the last 25 years, investigators in behavioral medicine have advanced communication science through systematic research to improve care coordination, tailored messaging, and collaborative self-management. Cumulative results from this portfolio of research can inform and guide the systemic changes that are needed in the healthcare system. From a review sponsored by the National Cancer Institute, the communication functions that will need to be optimized in order to support a patientcentered system of care include: (a) exchanging and managing information, (b) navigating the system, (c) dealing with emotions, (d) coping with uncertainty, (e) building a trusting relationship, and (f) supporting decisions [21].

targets for intervention following letters from an eponymous mnemonic (n*u*d*g*e*s). All of them represent opportunities for leveraging the evidence offered by behavioral medicine and are listed briefly below.

Achieving meaningful use It is easy to envision how the evidence of behavioral medicine can contribute to discussions on how to implement HIT in a way that supports the major objectives of “meaningful use.” The task of creating a system that is safe, efficient, and of high quality lies well within the purview of human factors specialists, ergonomicists, cognitive scientists, organizational scientists, and behavioral informaticians [29,34,37,49]. To talk about engaging patients and their families in line with the second goal is to employ the lingua franca of behavioral medicine scientists with experience working on issues related to self-determination, self-management, self-regulation, and adherence [3,14,28]. Similarly, improving care coordination is a topic of focus under study by many organizational scientists and system modelers, who can use their expertise to improve situational awareness among care teams and to create new efficiencies unifying social support networks [45,46]. Finally, social scientists are especially skilled at taking a population-level, or public health, perspective of outcomes in line with the fifth goal [25,31], while ethicists in behavioral medicine are well-versed in the social/motivational side of informed consent and privacy issues [38].

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Leveraging behavioral science to support best practice The premise of the Thaler and Sunstein book is that cognition and behavior can be influenced in positive ways by attending to supports in the environment. In their book, the two authors offer six prescriptive page 178 of 181

& Incentives: Behavioral scientists with knowledge

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in the nuances of intrinsic and extrinsic motivation and the experience and skills in implementing incentives could offer a perspicacious view on how to create and deploy incentive systems that support active participation of all parties in high quality care [4]. Basic as well as translational research is needed to find the motivational leverage points to foster a sense of self-efficacy and engagement among patients and to foster diffusion of evidence-based care principles among physicians. Understand cognitive maps: Health cognition specialists would have much to contribute in developing interfaces that supported the mental models of patients and professionals. Usability specialists could work hand in hand with patient educators and systems designers to ensure that all aspects of care (from patient portals to the EHR interfaces supporting medical decision-making) are understandable and that they mesh seamlessly with expected processes and workflows. Defaults: Decision scientists and public health interventionists have already collected data on the defaults that contribute to positive health outcomes. New research is needed to understand how the information environs of electronically enabled health systems can be altered—in the context of both the HITECH and Affordable Care Acts—to embed these defaults within systems of care. Give feedback: Clarifying data is already beginning to emerge on the role of EHRs in generating time-sensitive reminders and in offering a coordinating backbone for systems feedback. Work is needed at the individual level to understand how to overcome cognitive artifacts such as “reminder fatigue” and how to tie in data from personally accessible instruments into better tools for personal health management. At the systems level, work is needed to ensure that the data collected within EHRs can be used to improve evidencebased care equitably across populations. Expect error: Human factors specialists and cognitive scientists have gone a long way in developing systems that are fault-tolerant. New efforts are needed to extend the rigors of that research into systems that are becoming increasingly distributed across home and clinical settings and across systems of care. Attention may also be given to the differential roles of automated vs. personnel-based agents in identifying and rectifying potential errors before they occur. Structure decision-making: As personalized medicine becomes a reality, HIT will become instruTBM


mental in delivering the right information to the right people at the right time. Communication scientists experienced in the tailored delivery of health messages should be able to assist program developers in creating EHRs and PHRs that deliver information in tailored ways. Decision scientists can help create systems that reduce the influence of faulty heuristics while promoting a context of shared decision-making between patients and providers.

Contributing to research, implementation, and training Enabling a new system of care based on best practice in health system redesign will take the efforts of many players, working across systems and disciplines, in “aligning forces for quality.” To bring the right sets of expertise together, the ONC has been active in designing a series of programmatic initiatives for research, implementation, and training. Table 2 lists just a few of these programs by name. The ONC is joined in its efforts by many of its companion agencies including the National Institutes of Health (NIH), the Centers for Disease Control and Prevention (CDC), the Agency for

Research on Quality and Health (ARHQ), the National Institute of Standards and Technology (NIST), the Centers for Medicare and Medicaid Services (CMS), the National Science Foundation (NSF), and the Veterans’ Administration (VA). Future funding announcements should be forthcoming across many of these agencies as the different components of government contribute to national efforts from their own distinct perspectives. Nongovernmental funding agencies such as those sponsored by the Robert Wood Johnson Foundation, the Bill and Melinda Gates Foundation, the Google Foundation, and others should add to the list of opportunities for behavioral researchers, practitioners, and trainers. As may be expected, many important research and methodology questions remain to be addressed in an electronically enabled system of care [2]. The Agency for Research on Healthcare and Quality (AHRQ) shares an interest with the National Institutes of Health to enable the data structures needed to accelerate quality improvement through a “learning health system” [35,41]. Within a learning system of care, researchers and practitioners can use data from the bedside to make comparisons in similarly constituted treatments to see which treat-

Table 2 | HITECH programs announced by the DHHS Office of the National Coordinator of Health Information Technology as of July 2010 (taken from the ONC website present at http://healthit.hhs.gov/portal/server.pt)

State Health Information Exchange Cooperative Agreement Program: a grant program to support states or statedesignated entities (SDEs) in establishing health information exchange (HIE) capability among healthcare providers and hospitals in their jurisdictions Health Information Technology Extension Program: a grant program to establish health information technology regional extension centers to offer technical assistance, guidance, and information on best practices to support and accelerate healthcare providers’ efforts to become meaningful users of electronic health records (EHRs) Strategic Health IT Advanced Research Projects (SHARP) Program: a grant program to fund research focused on achieving breakthrough advances to address well-documented problems that have impeded adoption: (1) security of health information technology, (2) patient-centered cognitive support, (3) healthcare application and network platform architectures, and (4) secondary use of EHR data Community College Consortia to Educate Health Information Technology Professionals Program: a grant program that seeks to rapidly create health IT education and training programs at community colleges or expand existing programs. Community colleges funded under this initiative will establish intensive, non-degree training programs that can be completed in 6 months or less. This is one component of the Health IT Workforce Program Curriculum Development Centers Program: a grant program to provide $10 million in grants to institutions of higher education (or consortia thereof) to support health information technology (health IT) curriculum development. This is one component of the Health IT Workforce Program Program of Assistance for University-Based Training: a grant program to rapidly increase the availability of individuals qualified to serve in specific health information technology professional roles requiring university-level training. This is one component of the Health IT Workforce Program Competency Examination for Individuals Completing a Non-degree Training Program: a grant program to provide $6 million in grants to an institution of higher education (or consortia thereof) to support the development and initial administration of a set of health IT competency examinations. This is one component of the Health IT Workforce Program Beacon Community Program: a grant program for communities to build and strengthen their health information technology (health IT) infrastructure and exchange capabilities. These communities will demonstrate the vision of a future where hospitals, clinicians, and patients are meaningful users of health IT, and together the community achieves measurable improvements in health care quality, safety, efficiency, and population health State Health Information Exchange Cooperative Agreement Program: a grant program to support states or statedesignated entities (SDEs) in establishing health information exchange (HIE) capability among healthcare providers and hospitals in their jurisdictions TBM

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ments may lead to costs savings or more effective, patient-centered care [24]. The statistical and methodological details for how to implement a selfcorrective system of care in behavioral medicine have yet to be worked out. New efforts are needed to inform the field with the best analytic techniques available for dealing with large, multidimensional databases [35].

CONCLUSION On April 6, 2010, presidential appointee David Blumenthal gave a keynote address at a conference sponsored by the Friends of the National Library of Medicine on the topic of EHRs and personalized medicine. “This is something unparalleled in Medicine since the time of Hypocrites,” Blumenthal reflected, “to make information as pointed, and specific as possible … delivered at the right time and the right place.” There is a lot of truth, and not just hyperbole, in what the National Coordinator for Health I.T. said. Nevertheless, we should acknowledge that the risk from unintended consequences is also great. As the newly appointed director of the OMB stated in 2009, any system that is designed without taking into consideration “human behavior” is destined for failure. Behavioral medicine should play its part to ensure that the new system of care lives up to its promise at an unparalleled moment in medical history.

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