D C Classen

Computer Sciences Corp, Sydney, New South Wales, Australia

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Publications (104)726.05 Total impact

  • Source
    Dean F Sittig, David C Classen, Hardeep Singh
  • Source
    Dean F Sittig, David C Classen, Hardeep Singh
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    ABSTRACT: The Office of the National Coordinator for Health Information Technology is expected to oversee creation of a Health Information Technology (HIT) Safety Center. While its functions are still being defined, the center is envisioned as a public-private entity focusing on promotion of HIT related patient safety. We propose that the HIT Safety Center leverages its unique position to work with key administrative and policy stakeholders, healthcare organizations (HCOs), and HIT vendors to achieve four goals: (1) facilitate creation of a nationwide 'post-marketing' surveillance system to monitor HIT related safety events; (2) develop methods and governance structures to support investigation of major HIT related safety events; (3) create the infrastructure and methods needed to carry out random assessments of HIT related safety in complex HCOs; and (4) advocate for HIT safety with government and private entities. The convening ability of a federally supported HIT Safety Center could be critically important to our transformation to a safe and effective HIT enabled healthcare system.
    Journal of the American Medical Informatics Association : JAMIA. 10/2014;
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    ABSTRACT: To have impact on reducing harm in pediatric inpatients, an efficient and reliable process for harm detection is needed. This work describes the first step toward the development of a pediatric all-cause harm measurement tool by recognized experts in the field.
    Journal of Patient Safety 08/2014;
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    ABSTRACT: We will provide a context to health information technology systems (HIT) safety hazards discussions, describe how electronic health record-computer prescriber order entry (EHR-CPOE) simulation has already identified unrecognized hazards in HIT on a national scale, helping make EHR-CPOE systems safer, and we make the case for all stakeholders to leverage proven methods and teams in HIT performance verification. A national poll of safety, quality improvement, and health-care administrative leaders identified health information technology safety as the hazard of greatest concern for 2013. Quality, HIT, and safety leaders are very concerned about technology performance risks as addressed in the Health Information Technology and Patient Safety report of the Institute of Medicine; and these are being addressed by the Office of the National Coordinator of HIT of the U.S. Dept. of Human Services in their proposed plans. We describe the evolution of postdeployment testing of HIT performance, including the results of national deployment of Texas Medical Institute of Technology's electronic health record computer prescriber order entry (TMIT EHR-CPOE) Flight Simulator verification test that is addressed in these 2 reports, and the safety hazards of concern to leaders. A global webinar for health-care leaders addressed the top patient safety hazards in the areas of leadership, practices, and technologies. A poll of 76 of the 221 organizations participating in the webinar revealed that HIT hazards were the participants' greatest concern of all 30 hazards presented. Of those polled, 89% rated HIT patient/data mismatches in EHRs and HIT systems as a 9 or 10 on a scale of 1 to 10 as a hazard of great concern. Review of a key study of postdeployment testing of the safety performance of operational EHR systems with CPOE implemented in 62 hospitals, using the TMIT EHR-CPOE simulation tool, showed that only 53% of the medication orders that could have resulted in fatalities were detected. The study also showed significant variability in the performance of specific EHR vendor systems, with the same vendor product scoring as high as a 75% detection score in one health-care organization, and the same vendor system scoring below 10% in another health-care organization. HIT safety hazards should be taken very seriously, and the need for proven, robust, and regular postdeployment performance verification measurement of EHR system operations in every health-care organization is critical to ensure that these systems are safe for every patient. The TMIT EHR-CPOE flight simulator is a well-tested and scalable tool that can be used to identify performance gaps in EHR and other HIT systems. It is critical that suppliers, providers, and purchasers of health-care partner with HIT stakeholders and leverage the existing body of work, as well as expert teams and collaborative networks to make care safer; and public-private partnerships to accelerate safety in HIT. A global collaborative is already underway incorporating a "trust but verify" philosophy.
    Journal of Patient Safety 12/2013; 9(4):177-189.
  • David C Classen, Roger K Resar
    Joint Commission journal on quality and patient safety / Joint Commission Resources 07/2013; 39(7):291.
  • David C. Classen, Roger K. Resar
    Joint Commission journal on quality and patient safety / Joint Commission Resources 01/2013; 39(7).
  • Ashish K Jha, David C Classen
    New England Journal of Medicine 11/2011; 365(19):1756-8. · 54.42 Impact Factor
  • Source
    Hardeep Singh, David C Classen, Dean F Sittig
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    ABSTRACT: Electronic health records (EHRs) have potential quality and safety benefits. However, reports of EHR-related safety hazards are now emerging. The Office of the National Coordinator for Health Information Technology recently sponsored an Institute of Medicine committee to evaluate how health information technology use affects patient safety. In this article, we propose the creation of a national EHR oversight program to provide dedicated surveillance of EHR-related safety hazards and to promote learning from identified errors, close calls, and adverse events. The program calls for data gathering, investigation/analysis, and regulatory components. The first 2 functions will depend on institution-level EHR safety committees that will investigate all known EHR-related adverse events and near-misses and report them nationally using standardized methods. These committees should also perform routine safety self-assessments to proactively identify new risks. Nationally, we propose the long-term creation of a centralized, nonpartisan board with an appropriate legal and regulatory infrastructure to ensure the safety of EHRs. We discuss the rationale of the proposed oversight program and its potential organizational components and functions. These include mechanisms for robust data collection and analyses of all safety concerns using multiple methods that extend beyond reporting, multidisciplinary investigation of selected high-risk safety events, and enhanced coordination with other national agencies to facilitate broad dissemination of hazards information. Implementation of this proposed infrastructure can facilitate identification of EHR-related adverse events and errors and potentially create a safer and more effective EHR-based health care delivery system.
    Journal of Patient Safety 11/2011; 7(4):169-74.
  • David C Classen, David W Bates
    New England Journal of Medicine 09/2011; 365(9):855-8. · 54.42 Impact Factor
  • David C Classen, Shobha Phansalkar, David W Bates
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    ABSTRACT: Medications represent the most common intervention in health care, despite their benefits; they also lead to an estimated 1.5 million adverse drug events and tens of thousands of hospital admissions each year. Although some are not preventable given what is known today, many types are, and one key cause which is preventable is drug-drug interactions (DDIs). Most electronic health record systems include programs that can check and prevent these types of interactions as a routine part of medication ordering. Studies suggest that these systems as implemented often do not effectively screen for these DDIs. A major reason for this deficiency is the lack of any national standard for the critical DDIs that should be routinely operationlized in these complex systems. We review the leading critical DDI lists from multiple sources including several leading health systems, a leading commercial content provider, the Leapfrog CPOE Testing Standard, and the new Office of the National Coordinator (ONC) DDI List. Implementation of strong DDI checking is one of the important steps in terms of realizing the benefits of electronic prescribing with respect to safety. Hopefully, the ONC list will make it easier for organizations to ensure they are including the most important interactions, and the Leapfrog List may help these organizations develop an operational DDI list that can be practically implemented. In addition, this review has identified 7 common DDIs that can be the starting point for all organizations in this area of medication safety.
    Journal of Patient Safety 06/2011; 7(2):61-5.
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    ABSTRACT: Identification and measurement of adverse medical events is central to patient safety, forming a foundation for accountability, prioritizing problems to work on, generating ideas for safer care, and testing which interventions work. We compared three methods to detect adverse events in hospitalized patients, using the same patient sample set from three leading hospitals. We found that the adverse event detection methods commonly used to track patient safety in the United States today-voluntary reporting and the Agency for Healthcare Research and Quality's Patient Safety Indicators-fared very poorly compared to other methods and missed 90 percent of the adverse events. The Institute for Healthcare Improvement's Global Trigger Tool found at least ten times more confirmed, serious events than these other methods. Overall, adverse events occurred in one-third of hospital admissions. Reliance on voluntary reporting and the Patient Safety Indicators could produce misleading conclusions about the current safety of care in the US health care system and misdirect efforts to improve patient safety.
    Health Affairs 04/2011; 30(4):581-9. · 4.64 Impact Factor
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    ABSTRACT: Computerized physician order entry (CPOE) is the feature of electronic medical record (EMR) implementation that arguably offers the greatest quality and patient safety benefits. The gains are potentially greater for critically ill neonates, but the effect of CPOE on quality and safety is dependent upon local implementation decisions. OBJECTIVES: After completing this article, readers should be able to: Define the basic aspects of CPOE and clinical decision support (CDS) systems.Describe the potential benefits of implementing CPOE associated with CDS in a neonatal intensive care unit (NICU).
    NeoReviews 01/2011; 12:393-396.
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    ABSTRACT: Computerized physician order entry is a required feature for hospitals seeking to demonstrate meaningful use of electronic medical record systems and qualify for federal financial incentives. A national sample of sixty-two hospitals voluntarily used a simulation tool designed to assess how well safety decision support worked when applied to medication orders in computerized order entry. The simulation detected only 53 percent of the medication orders that would have resulted in fatalities and 10-82 percent of the test orders that would have caused serious adverse drug events. It is important to ascertain whether actual implementations of computerized physician order entry are achieving goals such as improved patient safety.
    Health Affairs 04/2010; 29(4):655-63. · 4.64 Impact Factor
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    ABSTRACT: Selection of relevant patient safety interventions for the pediatric intensive care (PICU) requires identification of the types and severity of adverse events (AEs) and adverse drug events (ADEs) that occur in this setting. The study's objectives were to: 1) determine the rates of AEs/ADEs, including types, severity, and preventability, in PICU patients; 2) identify population characteristics associated with increased risk of AEs/ADEs; 3) develop and test a PICU specific trigger tool to facilitate identification of AEs/ADEs. Retrospective, cross-sectional, randomized review of 734 patient records who were discharged from 15 U.S. PICUs between September and December 2005. A novel PICU-focused trigger tool for AE/ADE detection. Sixty-two percent of PICU patients had at least one AE. A total of 1488 AEs, including 256 ADEs, were identified. This translates to a rate of 28.6 AEs and 4.9 ADEs per 100 patient-days. The most common types of AEs were catheter complications, uncontrolled pain, and endotracheal tube malposition. Ten percent of AEs were classified as life-threatening or permanent; 45% were deemed preventable. Higher adjusted rates of AEs were found in surgical patients (p = .02), patients intubated at some point during their PICU stay (p = .002), and patients who died (p < .001). Surgical patients had higher preventable adjusted AE (p = .01) and ADE rates (p = .02). The adjusted cumulative risk of an AE per PICU day was 5.3% and 1.6% for an ADE alone. There was a 4% increase in adjusted ADEs rates for every year increase in age. AEs and ADEs occur frequently in the PICU setting. These data provide areas of focus for evidence-based prevention strategies to decrease the substantial risk to this vulnerable pediatric population.
    Pediatric Critical Care Medicine 03/2010; 11(5):568-78. · 2.35 Impact Factor
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    ABSTRACT: It is the objective of this article to provide a guide to health care providers adopting computerized prescriber order entry (CPOE) and to explain recent developments of important concepts and initiatives such as "meaningful use" that will have significant impact on successful implementation of CPOE. The specific goals are to discuss key concepts relating to the NEW ARRA/HITECH-EHR meaningful use criteria and its relevance to CPOE Safe Practice and medication safety, summarize and update the recent scientific evidence evaluating CPOE, present the new 2010 CPOE safe practice, and suggest ways the CPOE safe practice may be expanded and harmonized with the new EHR meaningful use criteria. This article evaluates the latest published studies in the field of CPOE and reexamines the objectives, the requirements for achieving these objectives, and evidence of efficacy for this practice. It reviews relevant issues of medication safety, the likely impact of CPOE, the efficacy of CPOE in various studies, key measures of impact of the practice, and important implementation issues. The 2010 updates to the National Quality Forum CPOE practice are also reviewed with support from the evidentiary base. This paper has presented an update to the National Quality Forum Safe Practice on CPOE for 2010. Although the practice itself has not changed, the scientific evidence of the impact of CPOE on medication safety and quality of care continues to accumulate. However, the adoption of CPOE by hospitals in the United States remains very low, as low as 6% in 1 study. The adoption of CPOE has been low despite increasing evidence that hospital patients are still experiencing significant rates of preventable adverse drug events. This low adoption rate will likely be impacted by the new ARRA/HITECH legislation and the meaningful use concept.
    Journal of Patient Safety 03/2010; 6(1):15-23.
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    Dean F Sittig, David C Classen
    JAMA The Journal of the American Medical Association 02/2010; 303(5):450-1. · 29.98 Impact Factor
  • J. Metzger, D. W. Bates, D. C. Classen
    Health Affairs - HEALTH AFFAIR. 01/2010; 29(7):1417-1417.
  • David C Classen, Lisa Jaser, Daniel S Budnitz
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    ABSTRACT: Although adverse drug events (ADEs) are a well-recognized problem among hospitalized patients, there is no system for monitoring them. Six high-alert medications and associated adverse events were selected for inclusion in the Medicare Patient Safety Monitoring System (MPSMS), a national surveillance system designed to identify and track over time inpatient adverse events within the hospitalized fee-for-service Medicare population. Explicit chart review algorithms were used to identify medication exposures and associated adverse events from the the 2004 MPSMS sample's medical records. The associations of ADEs with patient characteristics, length of stay, mortality, and 30-day readmission were assessed with bivariate analyses and hierarchical linear regression modeling (HGLM) approaches. National ADE rates and numbers of adverse events were estimated using weighted HGLM. On the basis of 25,145 hospital visits in the 2004 MPSMS sample, an estimated 8.2% of patients exposed to warfarin experienced associated ADEs, as did 13.6% exposed to heparin, 10.7% exposed to insulin/hypoglycemic agents, and 0.5% exposed to digoxin. Some 0.6% of patients exposed to antibiotics experienced antibiotic-associated Clostridium difficile infection (CDI). Patients with ADEs had increased length of stay and in-hospital and 30-day mortality, except that patients with antibiotic-associated CDI did not have increased in-hospital mortality, and patients with ADEs associated with heparin did not have increased 30-day mortality. An estimated 888,000 ADEs occurred in hospitalized Medicare patients from these medications alone. This new approach to detecting ADEs and estimating the national burden of ADEs from selected medications may be adapted for other types of ADEs in the Medicare population and may offer guidance to policymakers on appropriate areas of focus for patient safety.
    Joint Commission journal on quality and patient safety / Joint Commission Resources 01/2010; 36(1):12-21.
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    ABSTRACT: The medication use process is one of the most complex and risky clinical care processes in the hospital. It involves a large number of caregivers in widely diverse areas: physicians, nurses, pharmacists and respiratory therapists. Studies performed over the past several years have shown that medication errors and adverse events occur in all parts of the medication use process. Technologies are available to improve medication safety across the entire medication use process, but implementation can be expensive, intrusive and complex. To gain the benefits from various technologies, organizations must consider how the interplay between these technologies affects the workflow and how best to implement these technologies. Our approach for planning for these implementations--along with a suggested sequence--will be discussed in this article.
    Journal of healthcare information management: JHIM 01/2009; 23(4):17-23.
  • Infection Control and Hospital Epidemiology 10/2008; 29 Suppl 1:S22-30. · 4.02 Impact Factor

Publication Stats

6k Citations
726.05 Total Impact Points


  • 2010–2011
    • Computer Sciences Corp
      Sydney, New South Wales, Australia
    • University of Texas Health Science Center at Houston
      • School of Biomedical Informatics
      Houston, TX, United States
  • 1990–2011
    • University of Utah
      • • Department of Internal Medicine
      • • Division of Infectious Diseases
      • • School of Medicine
      Salt Lake City, Utah, United States
  • 2008
    • Icahn School of Medicine at Mount Sinai
      Manhattan, New York, United States
    • Washington University in St. Louis
      San Luis, Missouri, United States
    • Institute for Healthcare Improvement
      Cambridge, Massachusetts, United States
    • University of Manitoba
      Winnipeg, Manitoba, Canada
    • Duke University Medical Center
      Durham, North Carolina, United States
    • University of Washington Seattle
      • Department of Pediatrics
      Seattle, WA, United States
    • Brigham and Women's Hospital
      • Department of Medicine
      Boston, MA, United States
    • The Children's Hospital of Philadelphia
      Philadelphia, Pennsylvania, United States
  • 2007
    • New York Presbyterian Hospital
      New York City, New York, United States
  • 2006–2007
    • Stanford University
      • Department of Pediatrics
      Stanford, CA, United States
    • Duke University
      Durham, North Carolina, United States