Category Archives: Clinical Decision Support

Health IT Special Issue of The American Journal of Managed Care: Dec 2010

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AJMC Publishes Health Information Technology Special Issue Online Dec 20, 2010
“Featuring scholarly articles and perspectives from policymakers, payers, providers, pharmaceutical companies, health IT vendors, health services researchers, patients, and medical educators, this [December 2010 special] issue of  The American Journal of Managed Care is a reflection” of  “the  dramatic growth of interest in the potential for HIT to improve health and healthcare delivery,” writes Sachin H. Jain, MD, MBA and David Blumenthal, MD, MPP in their introductory article titled “Health Information Technology Is Leading Multisector Health System Transformation.”  Both Jain and Blumenthal are with the Office of the National Coordinator for Health Information Technology.

Authors of 23 Articles in Special Issue
Sachin H. Jain, MD, MBA; and, David Blumenthal, MD, MPP; Cynthia L. Bero, MPH; and Thomas H. Lee, MD; Aaron McKethan, PhD; and Craig Brammer; John Glaser, PhD; Pete Stark; Newt Gingrich, PhD, MA; and Malik Hasan, MD; James N. Ciriello, MS; and Nalin Kulatilaka, PhD, MS; Seth B. Cohen, MBA, MPA; Kurt D. Grote, MD; Wayne E. Pietraszek, MBA; and Francois Laflamme, MBA; Amol S. Navathe, MD, PhD; and Patrick H. Conway, MD, MSc; Reed V. Tuckson, MD; Denenn Vojta, MD; and Andrew M. Slavitt, MBA; Marc M. Triola, MD; Erica Friedman, MD; Christopher Cimino, MD; Enid M. Geyer, MLS, MBA; Jo Wiederhorn, MSW; and Crystal Mainiero; Nancy L. Davis, PhD; Lloyd Myers, RPh; and Zachary E. Myers; Bryant A. Adibe, BS; and Sachin H. Jain, MD, MBA; Spencer S. Jones, PhD; John L. Adams, PhD; Eric C. Schneider, MD; Jeanne S. Ringel, PhD; and Elizabeth A. McGlynn, PhD; Jeffrey L. Schnipper, MD, MPH; Jeffrey A. Linder, MD, MPH; Matvey B. Palchuk, MD, MS; D. Tony Yu, MD; Kerry E. McColgan, BA; Lynn A. Volk, MHS; Ruslana Tsurikova, MA; Andrea J. Melnikas, BA; Jonathan S. Einbinder, MD, MBA; and Blackford Middleton, MD, MPH, MS;Alexander S. Misono, BA; Sarah L. Cutrona, MD, MPH; Niteesh K. Choudhry, MD, PhD; Michael A. Fischer, MD, MS; Margaret R. Stedman, PhD; Joshua N. Liberman, PhD; Troyen A. Brennan, MD, JD; Sachin H. Jain, MD, MBA; and William H. Shrank, MD, MSHS; Amir Dan Rubin, MBA, MHSA; and Virginia A. McFerran, MA; Fredric E. Blavin, MS; Melinda J. Beeuwkes Buntin, PhD; and Charles P. Friedman, PhD Robert D. Hill, PhD; Marilyn K. Luptak, PhD, MSW; Randall W. Rupper, MD, MPH; Byron Bair, MD; Cherie Peterson, RN, MS; Nancy Dailey, MSN, RN-BC; and Bret L. Hicken, PhD, MSPH; Jeffrey A. Linder, MD, MPH; Jeffrey L. Schnipper, MD, MPH; Ruslana Tsurikova, Msc, MA; D. Tony Yu, MD, MPH; Lynn A. Volk, MHS; Andrea J. Melnikas, MPH; Matvey B. Palchuk, MD, MS; Maya Olsha-Yehiav, MS; and Blackford Middleton, MD, MPH, MSc; Emily Ruth Maxson, BS; Melinda J. Beeuwkes Buntin, PhD; and Farzad Mostashari, MD, ScM; Daniel C. Armijo, MHSA; Eric J. Lammers, MPP; and Dean G. Smith, PhD; Katlyn L. Nemani, BA.

Look for an upcoming post on e-Healthcare Marketing reviewing this special issue of AJMC.

‘Health IT: Making Health Care Better’: Commentary on America’s Health Rankings Site

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‘Health IT: Making Health Care Better’ by Sachin Jain
On the Web site dedicated for 20 years to using data to promote better health in the United States, Sachin H. Jain, MD, MBA, wrote a commentary on the role of the national HITECH initiative to collect and exchange health information for better patient care.  Titled  “Health IT: Making Health Care Better,” Jain’s commentary appears on the 21st Edition of America’s Health Rankings®: A Call to Action for Individuals and Their Communities. Jain is special assistant to the National Coordinator for Health Information Technology.

Jain discusses using electronic health records to improve patient quality management, encourage better clincal decisions, providing health information where and when it is needed, and getting information from here to there.

To read Jain’s commentary, click here.

Challenges/Barriers to Clinical Decision Support (CDS) Implementation

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AHRQ Releases Report on “Challenges to Clinical Decision Support (CDS) Design and Implementation”
“A new report” produced for AHRQ  National Research Center for Health IT dated March 2010 and released on April 14, 2010, ”examines the challenges and barriers to implementing clinical decision support (CDS) and found workflow, design and clinician’s level of support are just some of the issues that can affect successful CDS implementation. Challenges and Barriers to Clinical Decision Support (CDS) Implementation (PDF, 254 Kb) describes the challenges and barriers that AHRQ contractors encountered as part of their CDS demonstration project. These challenges and barriers can be successfully addressed by employing several key strategies, which include utilizing standard data exchange formats, providing clinicians with appropriate training, and modifying CDS to address clinicians’ needs.”  Report authors are June Eichner, M.S. and Maya Das, M.D., J.D. of NORC at the University of Chicago.

The following are excerpts from the report Introduction, Lessons Learned, and Project Teams.
I. INTRODUCTION
Overview of Clinical Decision Support
“To improve the quality of medical care in the United States, efforts are being made to increase the practice of evidence-based medicine through the use of clinical decision support (CDS) systems. CDS provides clinicians, patients, or caregivers with clinical knowledge and patient-specific information to help them make decisions that enhance patient care. The patient’s information is matched to a clinical knowledge base, and patient-specific assessments or recommendations are then communicated effectively at appropriate times during patient care. Some CDS interventions include forms and templates for entering and documenting patient information, and alerts, reminders, and order sets for providing suggestions and other support. Although CDS interventions can be designed to be used by clinicians, patients, and informal caregivers, this report focuses on the use of CDS interventions by clinicians to improve their clinical decisionmaking process. In addition, while CDS interventions can be both paper and computer based, their application in the following projects is limited to electronic CDS because of its greater capability for decision support.

“The use of CDS systems offers many potential benefits. Importantly, CDS interventions can increase adherence to evidence-based medical knowledge and can reduce unnecessary variation in clinical practice. The process for development and implementation of CDS systems can establish a standard knowledge structure that aligns with written evidence-based guidelines published by medical specialty societies or Federal task forces, such as the U.S. Preventive Services Task Force (USPSTF). CDS systems can also assist with information management to support clinicians’ decisionmaking abilities, reduce their mental workload, and improve clinical workflows.3 When well designed and implemented, CDS systems have the potential to improve health care quality, and also to increase efficiency and reduce health care costs.

“Despite the promise of CDS systems, numerous barriers to their development and implementation exist. To date, the medical knowledge base is incomplete, in part because of insufficient clinical evidence. Moreover, methodologies are still being designed to convert the knowledge base into computable code, and interventions for conveying the knowledge to clinicians in a way they can easily use it in practice are in the early stages of development. Low clinician demand for CDS is another barrier to broader CDS system adoption. Clinicians’ lack of motivation to use CDS appears to be related to usability issues with the CDS intervention (e.g., speed, ease of use), its lack of integration into the clinical workflow, concerns about autonomy, and the legal and ethical ramifications of adhering to or overriding recommendations made by the CDS system. In addition, in many cases, acceptance and use of CDS systems are tied to the adoption of electronic medical records (EMRs), because EMRs can include CDS applications as part of computerized provider order entry (CPOE) and electronic prescribing (eRx) systems. This is evidenced by the results of the 2008 National Ambulatory Medical Care Survey, which show that only 38 percent of physicians used an EMR, and only 4 percent used an EMR with CDS system capabilities.

“Recent Federal and payer initiatives are providing support for EMR and CDS adoption. For example, the Agency for Healthcare Research and Quality (AHRQ) has funded CDS demonstrations. In addition, AHRQ and the U.S. Department of Health and Human Services Office of the National Coordinator for Health Information Technology (ONC) funded the development of a Roadmap for National Action on Clinical Decision Support and held workshops to support CDS system development and implementation. Most recently, the American Recovery and Reinvestment Act of 2009 (ARRA) created financial incentives through Medicare and Medicaid for providers to “meaningfully use qualified” electronic health records (EHRs). Under the Notice for Proposed Rulemaking (NPRM) for the EHR Incentive Program published by the Centers for Medicare & Medicaid Services (CMS), the criteria for meaningful use include the implementation of five CDS rules, including the ability to track compliance with those rules.

“The incorporation of evidence-based guidelines into an EMR by using CDS interventions that include quality measures may help align care delivery with payment incentives. Federal and private payers’ current and proposed payment models offer incentives based on the quality of care provided.  CDS alerts, reminders, and standardized order sets can also help clinicians follow these guidelines and support the payment of clinicians based on their performance (e.g., pay-for-performance). In addition, CDS documentation can be used to evaluate care from a population-based perspective and to move from the measurement of care processes to the measurement of patient outcomes.”

Overview of AHRQ’s Clinical Decision Support Demonstration Projects

“In 2008, AHRQ funded two demonstration projects in support of the design, development, and implementation of CDS systems. These projects aimed to:

• Incorporate CDS into EMRs that have been certified by the Certification Commission for Health IT (CCHIT).

• Demonstrate that CDS can operate on multiple information systems.

• Establish lessons learned for CDS implementation relevant to the health information technology (IT) vendor community.

• Assess potential benefits and drawbacks of CDS, including effects on patient satisfaction, measures of efficiency, cost, and risk.

• Evaluate methods of creating, storing, and replicating CDS across multiple clinical sites and ambulatory practices.”

“The projects were required to select two or more clinical practice guidelines in the public domain that had not yet been translated into a broadly available electronic CDS intervention. The chosen clinical practice guidelines were to address either preventive services or management of multiple common chronic conditions. The contractors were then to implement the CDS intervention in at least one health IT product certified by CCHIT, applying American National Standards Institute (ANSI) Health Information Technology Standards Panel (HITSP) standards when available and applicable. The CDS system being developed was to be demonstrated in ambulatory settings. In addition, the projects were required to evaluate methods for creating, storing, and replicating the CDS system across multiple clinical sites and EMR systems.

“The two demonstration project contracts were awarded to Brigham and Women’s Hospital (BWH) for its Clinical Decision Support Consortium (CDSC) project and Yale University School of Medicine for its GuideLines Into DEcision Support (GLIDES) project. Each project is funded for $2.5 million for a 2-year period, with an option for AHRQ to continue funding the projects for up to an additional 3 years.”

Objectives of This Report
“This report briefly describes the two AHRQ CDS demonstrations, as well as the challenges and barriers that the contractors encountered during the initial periods of their CDS demonstration project, how they addressed these obstacles, and the effectiveness of their strategies. The goal of this report is to share the experiences of the contractors throughout the planning, design, and implementation phases to aid others who are considering funding or undertaking similar efforts.”

Methodology
“The information for this report is based on the contractors’ monthly status reports, project proposals, evaluation plans, and other documents submitted to AHRQ project officers. In addition, discussions were held with the contractors’ staff onsite and by telephone from June to September 2009. A review of the general CDS literature was also performed in order to provide a context for the contractors’ activities.”

Terminology
“The list below defines terms used throughout the report that may have multiple definitions. These definitions are used consistently throughout the document.

• “Guidelines” refers to written statements developed by medical specialty societies, disease-focused organizations, or expert panels to assist practitioner and patient decisions about appropriate health care for specific clinical circumstances.

• “Rules” refers to the abstraction of guidelines into programmable prediction statements (i.e., IF-and-THEN statements).

• “CDS Service” refers to a CDS functionality accessible over standard Internet protocols that is independent of the underlying EMR platform or programming language.

• “CDS intervention” refers to the variety of CDS applications (e.g., alerts, reminders, order sets) used to communicate knowledge to the clinician.

• “Knowledge management tool” refers to resources designed to assist with the extraction, evaluation, storage, and retrieval of guidelines, frameworks, pieces of code, and other artifacts related to CDS system development (e.g., Documentum’s Web Publisher, Content Management Services, the Guideline Elements Model (GEM) software tool GEMCutter, EXTRACTOR, Conference on Guideline Standardization (COGS) statement, Guideline Implementability Appraisal (GLIA)).

• SmartForm is an electronic form with electronic completion, dynamic sections, database calls, electronic submission, and other capabilities. It enables writing a multi-problem visit note while capturing coded information and providing sophisticated decision support in the form of tailored recommendations for care.

• Dashboard is a Web-based application available to clinicians that displays relevant and timely information to support clinical decisionmaking for patient care, quality reporting, and population management. Dashboards may support viewing of condition-specific information and/or functionality to take action (e.g., ordering of a lab test) from the application itself.”

Organization
“The remainder of this report is organized into three sections. The next section provides a description of each project and summary of the challenges and barriers faced by each of the contractors. This is followed by an analysis and discussion of their experiences. The last section offers overall conclusions and recommendations for future work to promote CDS design and implementation.”

To read descriptions of the projects and analysis and discussion, see the report pdf. This post skips to conclusions.

Lessons Learned
“The experience to date of these two contractors provides lessons that are particularly relevant to guideline developers, IT vendors, standards development organizations, health care provider organizations, and policymakers. The lessons particularly pertinent to each group are given below.”

Guideline developers:
 “Guidelines should be specific, unambiguous, and clear.

 Guideline development committees should include individuals with programming expertise and health informaticians.

 Updates of the guideline recommendations are needed. Guideline developers should consider issuing statements of update when new medical evidence is brought forth and providing regular review and updates of guidelines. For example, the USPSTF re-reviews each topic every 5 years.”

IT vendors:
 “As most organizations utilize vendor systems with hard-coded functionality, vendors should consider ways to reduce the need for an organization to rebuild the CDS content when upgrading or implementing a new EMR system (e.g., adopting a module or service-oriented approach).

 Incentives for vendor participation in CDS initiatives should be aligned with efforts, such as defining meaningful use criteria, to encourage standards adoption.”

Standards development organizations:
 “Implementation specifications and guides should be produced that simplify existing standards and support consistent application of standards for messaging, interfacing, and mapping purposes.

 The development of standards and implementation specifications and guides should accommodate appropriate clinical practice variations.

 When developing newer versions of standards, ways to reduce interoperability problems and data-mapping issues should be considered.”

Health care provider organizations:
 “The goals of CDS development and implementation projects should align with organizational priorities to promote buy-in from both management and staff.

 The organizational working environment should foster meaningful EMR usage, including not only software and hardware needs but also the attitudinal changes needed to support adoption.

 Engaging a well-respected clinician “champion” to lead CDS education, training, and implementation efforts will promote clinician adoption.

 Institutions wishing to utilize a knowledge management process will need access to personnel with specialized knowledge in clinical informatics and experience in designing new tools or using existing tools to support CDS development.”

Policymakers:
 “The development of standards and clinical guidelines can promote the goals for interoperability as well as support the development of the knowledge base necessary for developing CDS systems.

 Incentives by funding bodies, including governmental entities, can promote EMR installation, implementation, and use of these systems. To achieve the promise of EMR to improve the quality of health care through interventions such as CDS systems, policymakers need to continually reexamine ways to promote adoption of quality practices, including performance-based payments, incentives, and providing clinicians and patients with comparative data.”

Future Work To Support CDS
“Although the contractors were able to overcome many of the challenges and barriers they faced, they were not able to overcome them all. Additional research and work are needed to address these outstanding obstacles, as they are important for the advancement of the design and implementation of CDS systems. These include:”

° “Development of a stronger evidence base for guidelines (single conditions, comorbidities, associated treatment options).

° Creation of more specific implementation guides and specifications to promote consistent application of standards.

° Comparison of the resources required by a provider organization to develop its own knowledge management system vs. use of a ready-made knowledge management portal.

° Long-term evaluation to determine whether clinicians’ use of the EMR and CDS systems changes or stabilizes over time.

° Understanding of factors that enable EMR and CDS intervention acceptance and use by clinicians.

° Effectiveness of the various CDS interventions on clinician performance and clinical outcomes.”

The Two Demonstration Project Teams

1. Clinical Decision Support Consortium
“The CDSC project was awarded to Brigham and Women’s Hospital and also includes Partners HealthCare System (Partners), an integrated health care system that includes primary care and specialty clinicians, community hospitals, two founding academic medical centers (including BWH), specialty facilities, and other health-related entities. For this project, BWH is collaborating with the Regenstrief Institute, the Veterans Health Administration (Roudebush Veterans Administration Medical Center), Kaiser Permanente, the University of Medicine and Dentistry of New Jersey (UMDNJ), MidValley Independent Physicians Association (MVIPA), and EMR vendors (i.e., Siemens Medical Solutions, GE Healthcare, and NextGen). Management of and technical expertise for this project are provided by staff of the Partners HealthCare System’s Clinical Informatics Research and Development (CIRD) group.”

2. GuideLines Into DEcision Support
“The GuideLines Into DEcision Support (GLIDES) project is a collaboration between Yale University School of Medicine, Yale New Haven Health System, and the Nemours Foundation.”