1
CLINICAL DECISION SUPPORT

CHALLENGES TO CLINICAL DECISION MAKING

Facilitative clinical decision support (CDS) is a practical necessity for every clinician in our rapidly evolving health and healthcare landscape. A central promise of health information technology (health IT) within the learning health system is its potential to ameliorate the burden that exponentially expanding clinical knowledge as well as care and choice complexity place on the finite time and attention of clinicians, patients, and every other member of the care team. Realizing this promise demands that health IT deliver the right information, at the right point and format within the decision and care processes to optimize outcomes by consistently applying the best available knowledge in context of every patient’s needs and goals. Delivering information this way to all patients and care teams, routinely and at pace with our expanding knowledge, in turn demands shared and sustainable solutions. These solutions must be collaboratively developed across affected stakeholders to address key challenges and exponentially accelerate the availability of reliably curated information resources that are readily, affordably, and seamlessly incorporated with patient-centered, clinician-friendly workflows via interoperable health IT systems and patient data.

A continuously learning health system is driven by the seamless and rapid generation, processing, and practical application of the best available evidence for the circumstance. To achieve such a system, effective and timely approaches for managing the ever-expanding and complex array of clinical knowledge and person-specific data are essential for accelerating routine identification and delivery of the best available evidence to the point of choice by clinicians and patients. Yet our current health care system falls substantially short of both the need and the potential in this respect. As the Charter of the National Academy of Medicine’s (NAM) Leadership Consortium for a Value & Science-Driven Health System states: “Care that is important is often not delivered. Care that is

delivered is often not important.” In large part, the mismatch results from the failure to update and apply the available evidence.

The rapidly increasing growth in diagnostic and treatment options—accelerated still more by advances in genomics and proteomics and the burgeoning amount of available clinical data—presents a constant and ongoing gap between practice and potential. This gap will expand unless a systematic effort is undertaken to develop and apply tools that can accelerate the capture, assessment, validation, translation, and real-time delivery of best available, appropriately-tailored evidence for point of care decisions by clinicians, patients, and families.

Decision-making guidelines, prompts, and assists, (i.e., CDS tools that deliver the best available information seamlessly and effectively to the point of clinical decisions), are necessary for improved and efficient care. Although it is technically feasible to deliver timely, validated evidence in a useful fashion to clinicians, patients, and families, the actual implementation of such support has generally been the exception rather than the norm. Implementation of CDS tools experienced by clinicians, patients, and other care team members to date, have often been expensive, disruptive, inconsistent, unvalidated, and not presented in timely or fluid points in the decision process.

CLINICAL DECISION SUPPORT CONCEPTS

In the last decade, Electronic Health Record (EHR) adoption rates have soared. As of 2015, 87 percent of office-based physicians had adopted any EHR, 78 percent had adopted a certified EHR, and 54 percent had adopted a Basic EHR, (Jamoom & Yang 2016), paving the way for increased use of CDS tools that leverage EHR data to provide decision support to clinicians and patients. CDS capabilities operating in concert with EHRs hold great potential to help the nation’s health care systems provide access to the best current evidence in usable form and at strategic points within care and decision-making processes to help clinicians, patients, and other care team members improve health care outcomes and lower the overall cost of care. As described by the Office of the National Coordinator for Health Information Technology (ONC),¹ “CDS provides clinicians, staff, patients, and other individuals with knowledge and person-specific information, intelligently filtered or presented at appropriate times, to enhance health and health care. CDS encompasses a variety of tools to enhance decision-making in the clinical workflow. These tools include computerized alerts and

reminders to care providers and patients; clinical guidelines; condition-specific order sets; focused patient data reports and summaries; documentation templates; diagnostic support, and contextually relevant reference information, among other tools.” CDS is a sophisticated health IT functionality that does more than provide alerts, notifications, or explicit care suggestions.

CDS requires computable biomedical information, person-specific data, and a reasoning or inferencing mechanism that combines knowledge and data to generate and present helpful information to clinicians, patients, and care team members as care is being delivered. This information must be filtered, organized, and presented in a way that supports the current workflow, allowing the user to make an informed decision quickly and to take action on that decision. Different types of CDS may be ideal for different processes of care in different settings, and effective CDS must be relevant to those who can act on the information in a way that supports completion of the right action. CDS is not intended to replace clinician judgment, but rather to provide information to assist care team members in managing the complex and expanding volume of biomedical and person-specific data needed to make timely, informed, and higher quality decisions based on current clinical science.

CDS tools can be directed toward reduction of errors and adverse events, promotion of best practices for quality and safety, cost profile improvement, rapid response to public health emergencies, and more—such as supporting shared decision-making or tailoring plans of treatment to patient preferences. Successful CDS designs:

• provide measurable value in addressing a recognized problem area or area for improvement;
• leverage multiple data types to bring the most current and relevant evidence and evidence-based practice recommendations to bear on clinical decisions;
• produce actionable insights from the abundant multiple data sources;
• deliver information to the user that allows the user to make final practice decisions, rather than being opaque and acting autonomously;
• demonstrate good usability principles, including clear displays and rapid action options;
• are testable in small settings with a clear path to larger scalability; and
• support successful participation in quality and value improvement initiatives.

In the latter respect, CDS goes well beyond alerts to make use of various CDS activators and approaches aligned with policies, care models, and goals that focus on providing better care at better value. Example approaches include value-based Alternative Payment Models (APMs), the Patient-Centered Medical Home model, and the clinician-consumer Choosing Wisely initiative’s aims to help patients choose care that is needed and not duplicative, free from harm, and supported by evidence. These initiatives ask and—in a variety of ways ranging from reimbursement incentives to recognition to professional satisfaction—reward health care organizations, individual clinicians, and other members of care teams for delivering optimal care and value. Successful CDS implementations help clinicians continuously achieve and advance care quality and outcomes benchmarks.

STATUS AND BARRIERS

A growing body of literature demonstrates the positive impact CDS can have on care processes, clinical outcomes, and economic outcomes. The Agency for Healthcare Research and Quality (AHRQ) commissioned a literature review in 2012 that found evidence showing that CDS had positive impact on process measures, such as how reliably clinicians ordered necessary and evidence-based preventive and treatment services, and on increasing user knowledge relevant to a medical condition (Lobach et al., 2012). Studies have shown that well-executed CDS can reduce adverse events from drug-drug interactions (Smithburger et al., 2011; Sonnichsen et al., 2016) and medication errors (Fritz et al., 2012); decrease unnecessary laboratory testing (Felcher et al., 2017); reduce cardiovascular risk in patients with type 2 diabetes (Cleveringa et al., 2008); improve practitioner performance (Garg et al., 2005); increase cardiovascular disease risk assessment in routine primary care practice (Wells et al., 2008); improve public health outcomes associated with outbreaks of foodborne illness (Wu et al., 2012); and produce cost savings associated with hospital-based pharmacy interventions (Calloway et al., 2013).

Taken together, the available evidence shows that while there is significant room for improvement, CDS in the right context—implemented properly with the right kind of management—can reduce errors, improve the quality of care, reduce cost, and ease the cognitive burden on health care providers. As a result, achieving widespread adoption of CDS by the nation’s health systems and providers will be essential to assuring that the substantial and ongoing investments in biomedical science and innovation are translated as benefits to American taxpayers in terms of improved health and health care in a greatly accelerated timeframe.

Indeed, in a 10-year vision statement for health IT-enabled quality improvement, ONC called for advancing health IT capabilities centered around CDS and clinical quality measurement to enable robust and continuous quality improvement (ONC, 2014). These health IT capabilities will provide all members of the clinical care team real-time access to the best available evidence in a way that is aligned with and does not add burdens to their already heavy workload, but that instead takes advantage of the tremendous advances in computing power and computational analysis to help them efficiently manage, assimilate, and apply the best available evidence to support making better choices that lead to better outcomes for all patients.

Despite its potential, CDS implementation and actualization remain nascent due to the many barriers to realizing the full benefits of CDS-facilitated value improvement. A key barrier is the present need for most health care organizations to independently develop, deploy, and manage CDS content, leading to high costs and redundant work across the system. Factors contributing to these challenges include:

• lack of reliable, shareable CDS content and capabilities that can be easily adopted across health care organizations and health IT systems;
• absence of systematic means to validate content for provision across delivery venues in a reliable, accessible, and updatable fashion;
• the technical difficulties of sharing CDS across institutions and EHR systems; and
• suboptimal user interfaces, implementation choices, and workflows that result in many clinicians viewing CDS more as a nuisance than as a helpful tool.

See Chapter 3 for a discussion of the challenges facing widespread adoption of CDS. To address these challenges and realize the full potential of CDS within real-world environments requires the identification of key priorities for action focused on achieving the potential of these tools to improve the quality, safety, and efficiency of health care.

NAM-ONC PROJECT ON CDS STRATEGIES

In an effort to identify necessary key priorities for action, the NAM Leadership Consortium for a Value & Science-Driven Health System, with support from the ONC, convened a collaborative effort with health care leaders to better understand potential opportunities and practical strategies for improving CDS practices and adoption. Over a three-meeting series, expert authorities

met to describe current and emerging CDS practices, identify collaborative opportunities to accelerate progress in the real-time application and use of CDS to inform health and health care decision making, and provide guidance on implementation challenges and strategies at a national scale. In addition to the meeting series, the CDS Steering Committee initiated small subcommittee workgroups to address a number of priority elements of CDS including content development (CDS authoring), platform integration (technical implementation), functionality and measurement (operations), and dissemination (distribution). This project and the associated meeting series were driven by a partnership between the NAM Leadership Consortium and ONC, with the meetings, work groups, and other activities organized by a steering committee.

Steering committee

NAM staff collaborated with ONC staff to gather information and health IT-specific perspectives and then identified a steering committee and other engaged expert authorities who, over the course of nearly a year, worked together and in consultation with others in the field to describe current and emerging CDS practices, identify approaches to their validation, explore collaborative opportunities to accelerate progress in the real-time application and use of CDS of proven efficacy in informing health and health care decision-making, and consider implementation challenges and strategies at a national scale. The steering committee members were Suzanne Bakken, professor of biomedical informatics at Columbia University; Hugh Bonner III, associate program director at Saint Francis Family Medicine Residency Program, Saint Francis Healthcare; Tejal K. Gandhi, president and chief executive officer of the National Patient Safety Foundation; Meredith Josephs, senior medical director and senior director for clinical information technology and training at Privia Health; Edwin A. Lomotan, medical officer and chief of clinical informatics at the Agency for Healthcare Research and Quality (AHRQ); Erin Mackay, associate director for health IT programs at the National Partnership for Women and Families; James E. Tcheng (chair), professor and interventional cardiologist at Duke University School of Medicine; Jonathan M. Teich, emergency medicine physician at Brigham and Women’s Hospital; and Scott Weingarten, senior vice president and chief clinical transformation officer at Cedars-Sinai Health System.

Workflow and working groups

The first meeting, held March 16, 2016, had the goal of exploring issues and opportunities to take the real-time application and use of CDS to the next

level in informing health and health care decision-making. The presentations and discussions at the first meeting described current and emerging CDS practices, identified approaches to validating CDS resources, and considered implementation challenges facing frontline providers, governance issues, and strategies to spread and scale effective CDS approaches. The second meeting, convened on October 27, 2016, highlighted opportunities and practical strategies for improving CDS practices and adoption, and featured reports from four working groups focused on CDS content, system integration, operations, and spread. This meeting also included discussions about potential key priorities for next steps for the field and steps that ONC and the NAM could take to accelerate progress. In preparation for the second meeting, the CDS steering committee initiated small workgroups to address four specific topics: content development (CDS authoring), platform integration (technical implementation), functionality and measurement (operations), and dissemination (distribution). Each workgroup met virtually before the meeting to develop brief action plans for their assigned topics.

The CDS authoring workgroup, led by Kensaku Kawamoto, associate chief medical information officer, director of knowledge management and mobilization, and assistant professor of biomedical informatics at the University of Utah, addressed standardized approaches and best practices for creating, managing, and curating computable CDS content. This workgroup also considered models for CDS learning, ONC’s role in managing standardization and CDS polarization, and opportunities for funding CDS authoring activities.

Steering Committee member Scott Weingarten led the platform integration and technical implementation workgroup, which examined preferred and best practice CDS implementation approaches, data interchange and interoperability foundations and prerequisites, and the role the federal government and industry could play in managing CDS technical implementation standards.

The operations workgroup, led by Steering Committee member Jonathan Teich, reviewed the available tools for workflow assessment and representation, the challenge of creating consistent and reliable team-based CDS workflow insertion points, and the need for metrics to measure and validate CDS implementation.

The distribution workgroup, led by Blackford Middleton, chief informatics and innovation officer at Apervita, Inc., examined the CDS marketplace for content dissemination and discussed business rules that would assure a vibrant and successful marketplace. This workgroup also considered constructs for feedback loops to inform value, and the financial business case for CDS development and adoption, and the possible role of public-private partnerships and incentives in efforts to spread CDS systems.

The partner organizations

ONC, which funded this project, is at the forefront of the federal government’s health IT efforts and is a resource to the nation’s entire health system to support effective use of health IT and promote nationwide health information exchange to improve health care. ONC is the principal federal entity charged with coordinating nationwide efforts to implement and use the most advanced health IT and develop standards to facilitate electronic exchange of health information. Congress mandated the position and office of the National Coordinator for Health Information Technology in the Health Information Technology for Economic and Clinical Health Act (HITECH Act) in 2009. ONC is located within the Office of the Secretary of the Department of Health and Human Services (HHS).

As the convening body for this initiative, the NAM, through the Leadership Consortium for a Value & Science Driven Health System, was tasked with bringing together experts and stakeholders to consider and reflect upon the key issues for optimizing clinical decision support, and to synthesize the information and insights gathered in this NAM Special Publication. Broadly, the NAM

Leadership Consortium was formed to help transform how the nation generates and uses evidence on clinical effectiveness to improve health and health care, including facilitating continuous improvement in the health care system through enhanced transparency on outcomes and cost. Its vision is a continuously learning health system in which:

• science, informatics, incentives, and culture are aligned for continuous improvement and innovation;
• best practices are seamlessly embedded in the care process;
• patients and families are active participants in all elements; and
• new knowledge is captured as an integral by-product of the care experience.

The NAM Leadership Consortium’s approach to address the goal that 90 percent of clinical decisions will be supported by accurate, timely, and up-to-date clinical information and reflect the best available evidence is to serve as a forum to facilitate the collaborative assessment and action around issues central to achieving its vision and goal. To address the challenges of improving evidence development, evidence application, and the capacity to advance progress on both dimensions, Leadership Consortium members, all leaders in their fields, work with their colleagues to identify the issues not being adequately addressed, the nature of the barriers and possible solutions, and the priorities for action. They then work to marshal the resources of the sectors represented on the Leadership Consortium to work for sustained public-private cooperation for change. Activities include collaborative exploration of new and expedited approaches to assessing the effectiveness of diagnostic and treatment interventions, better use of the patient care experience to generate evidence on effectiveness and efficiency of care, identification of assessment priorities, and communication strategies to enhance provider and patient understanding and support for interventions proven to work best and deliver value in health care.

A common commitment to certain principles and priorities guides the activities of the Leadership Consortium and its members. These include:

• the commitment to the right health care for each person;
• putting the best evidence into practice;
• establishing the effectiveness, efficiency, and safety of medical care delivered;
• building constant measurement into the nation’s health care investments;
• establishing health care data as a public good;
• shared responsibility distributed equitably across stakeholders, both public and private;

• collaborative stakeholder involvement in priority setting;
• transparency in executing activities and reporting results; and
• subjugating individual political or stakeholder perspectives in favor of the common good.

COMMON THEMES AND PRIORITIES

Informed by discussions, presentations, and concurrent work throughout the course of project period, this publication reports and reflects on the following issues: 1) current state-of-the-art and emerging CDS practices; 2) barriers to and strategies for implementing CDS within the context of existing EHR systems; and 3) challenges for developing and validating CDS content. The publication concludes by presenting priorities for action to expand CDS adoption and use by the nation’s health care systems and providers.

Common themes

Common themes raised throughout this project include:

• Much like in-person peer learning (e.g., grand rounds with residents), CDS should serve as a tool to help clinicians at the front-line think through options at the point of care.
• Current challenges include the various pathways for implementation of CDS within different health care organizations, lack of standards and incentives to use and improve CDS, poor data quality, and gaps in the evidence.
• One of the greatest challenges for scaling CDS adoption is its limited financial business case. It remains difficult to demonstrate the return on investment of CDS, especially against many competing priorities at the delivery system level.
• Current CDS lacks measurement practices and standards. Evaluation of current and future CDS should assess whether it measurably improves quality, health outcomes, safety, cost, and physician productivity.
• The current health ecosystem presents opportunities for:
  • increased engagement of stakeholders in the design, implementation, and use of CDS;
  • the incorporation of new knowledge, including patient-reported outcomes and contextual information, into CDS;
  • a renewed focus on clinical decision support for health care teams;
  • the creation of new multistakeholder partnerships to develop practical implementation tools and lead standardization and regulatory efforts;

• the development and deployment of CDS for public health response; and
• the strengthening of the CDS implementation evidence-base.

Priorities

In addition to these common themes, a number of priorities emerged throughout the meetings’ discussions. These were crystalized in a comprehensive list of key actions for optimizing strategies for CDS adoption and use (Box 1–1) developed between meeting two and meeting three of the series, reflecting an approximation of the actionable, collaborative next steps that health systems, researchers, and EHR developers could initiate over the next five years. These priorities for action then served as the focus for the third meeting’s presentations and discussions, which in addition to considering these priorities also aimed to identify the organizations that will take the lead in their implementation. These actions will require commitment by multiple stakeholders and are intended to move forward in a way that complements and enhances clinical practice.

The purpose of this project was not to replicate the many exemplar efforts—described in Chapter 2—to study, regulate, or implement CDS that have occurred (and are occurring) throughout the field. Instead, this partnership of key stakeholders formed to take into account the current political/regulatory/financial environment and incorporate existing best practices, study findings, and expertise to facilitate discussion on actionable next steps for optimizing strategies for CDS within the U.S. health system. This publication summarizes those discussions as they were presented over the course of three meetings and outlines approaches to achieve widespread adoption of CDS.

REFERENCES

ONC. 2014. Health it enabled quality improvement: A vision for better health and health care. Washington, DC: Office of the National Coordinator for Health Information Technology.

Smithburger, P. L., M. S. Buckley, S. Bejian, K. Burenheide, and S. L. Kane-Gill. 2011. A critical evaluation of clinical decision support for the detection of drug-drug interactions. Expert Opin Drug Saf 10(6):871–882.

Sönnichsen, A., U. S. Trampisch, A. Rieckert, G. Piccoliori, A. Vögele, M. Flamm, T. Johansson, A. Esmail, D. Reeves, and C. Löffler. 2016. Polypharmacy in chronic diseases–reduction of inappropriate medication and adverse drug events in older populations by electronic decision support (prima-eds): Study protocol for a randomized controlled trial. Trials 17(1):57.

Wells, S., S. Furness, N. Rafter, E. Horn, R. Whittaker, A. Stewart, K. Moodabe, P. Roseman, V. Selak, D. Bramley, and R. Jackson. 2008. Integrated electronic decision support increases cardiovascular disease risk assessment four fold in routine primary care practice. Eur J Cardiovasc Prev Rehabil 15(2):173–178.

Wu, W. Y., G. Hripcsak, J. Lurio, M. Pichardo, R. Berg, M. D. Buck, F. P. Morrison, K. Kitson, N. Calman, and F. Mostashari. 2012. Impact of integrating public health clinical decision support alerts into electronic health records on testing for gastrointestinal illness. J Public Health Manag Pract 18(3):224–227.

This page intentionally left blank.