Electronic Prescribing and Electronic Transmission of Discharge Medication Lists (New York)

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Summary:

In the ambulatory setting, medication errors occur in approximately 8 to 21 percent of prescriptions and adverse drug events (ADEs) affect 25 percent of patients. Of those ADEs, 11 percent are preventable and 28 percent are ameliorable. Evidence indicates that health information technology (IT) decreases medication errors in the inpatient setting, but there is less evidence about outpatient settings and transitions from inpatient to outpatient settings. Moreover, most of this evidence has been driven by a few institutions that developed home-grown systems. The ability to generalize those findings to commercial systems that are more accessible to other institutions or providers is unclear.

This project used three approaches to measure the impact of electronic prescribing (e-prescribing) on patient safety in the ambulatory setting. The first was a multi-site, pre-post study measuring the effects of health IT on medication errors when transitioning from one electronic prescribing system to another, in this case from home-grown to a vendor-based system. The second study was a qualitative study to understand variations in human-computer interactions with the new electronic prescribing system and subsequent correlation with medication error rates. The third study was a cohort controlled study evaluating electronic transmission of discharge medication lists from the hospital to the ambulatory setting.

The specific aims of the study were to:

  • Measure the effects on medication errors of transitioning from one e-prescribing system to another in the ambulatory setting.
  • Measure the effects on human-computer interactions of transitioning from one e-prescribing system to another in the ambulatory setting.
  • Evaluate the impact on medication discrepancies of electronic transmission of medication lists at discharge from the hospital to the ambulatory setting at the first ambulatory visit following discharge.
  • Evaluate the impact on ADEs 30-days post-discharge of electronic transmission of medication lists at discharge from the hospital to the ambulatory setting.

The study results indicated that after transition to the new system, the prescribing error rate decreased over a 2-year period. The qualitative study with providers found that the transition was difficult for providers but that providers’ perceptions of usability and efficiency became more positive over time. Finally, the cohort controlled study did not find a reduction in the incidence of medication errors. The study demonstrated the importance of e-prescribing systems that support medication reconciliation and physician workflow.

Electronic Prescribing and Electronic Transmission of Discharge Medication Lists - 2011

Summary Highlights

  • Principal Investigator: 
  • Funding Mechanism: 
    RFA: HS07-006: Ambulatory Safety and Quality Program: Improving Quality through Clinician Use of Health Information Technology (IQHIT)
  • Grant Number: 
    R18 HS 017029
  • Project Period: 
    September 2007 - August 2011
  • AHRQ Funding Amount: 
    $1,187,674
  • PDF Version: 
    (PDF, 178.14 KB)

Summary: This project consists of three studies that assessed the impact of health information technology (IT) on patient safety in the ambulatory setting. The first was a multi-center pre-post study measuring the impact on medication errors when switching from a locally-developed electronic health record (EHR) with an electronic prescribing (e-prescribing) system to a vendor-based system. The second was a qualitative study of physicians using one-on-one-interviews and direct observation to understand variations in human-computer interactions with this new e-prescribing system, and how user patterns or system features may influence medication errors. The third study used a cohort controlled design to evaluate the effect of electronically transmitting discharge medication lists from the hospital to the ambulatory setting on: 1) medication discrepancies at the first ambulatory visit following discharge; and 2) adverse drug events (ADEs) 30 days post-discharge.

These studies added to the knowledge of medication safety and the impact of health information exchanges on patient safety. In addition, by including a qualitative component on human-computer interactions, this project yielded critical insights as to why certain health IT interventions work while others do not, and how future interventions should be designed to better align themselves with physicians' workflow. The studies also have implications for institutions and practices as they transition from one EHR to another. If error rates vary greatly between systems, there are potential policy implications for more stringent certification criteria of e-prescribing to ensure medication safety.

Specific Aims:

  • Measure the effects on medication errors of transitioning from one e-prescribing system to another in the ambulatory setting. (Achieved)
  • Measure the effects on human-computer interactions of transitioning from one e-prescribing system to another in the ambulatory setting. (Achieved)
  • Evaluate the impact on medication discrepancies of electronic transmission of medication lists at discharge from the hospital to the ambulatory setting at the first ambulatory visit following discharge. (Achieved)
  • Evaluate the impact on ADEs 30 days post-discharge of electronic transmission of medication lists at discharge from the hospital to the ambulatory setting. (Achieved)

2011 Activities: The first study, measuring the effects on medication errors and data collection when transitioning from one electronic prescribing system to another, was previously completed. For the second study, a qualitative study measuring the effects on human-computer interaction of this same transition, data from two sets of interviews were analyzed and a manuscript was submitted for publication. The third study evaluated the impact on medication discrepancies and ADEs of electronic transmission of medication lists at discharge. An experienced research nurse identified medication errors in the data and ADEs experienced by the patient. All medication errors were reviewed by two experienced physicians who used the tool to rate the severity of the errors and ADEs. Due to delays with data collection, Dr. Kaushal used a 1 year no-cost extension to complete data cleaning and analysis. As last self-reported in the AHRQ Research Reporting System, project progress was on track and project budget spending was on target. This project was completed in August 2011.

Impact and Findings: For the first study, the rates and types of prescribing errors made by physicians were assessed at four time periods: 1) baseline, when physicians were using the locally-developed EHR with minimal clinical decision support for e-prescribing; 2) three-months post-implementation of the commercial EHR with more advanced clinical decision support for e-prescribing; 3) one-year post-implementation; and 4) two-years post-implementation. The research team found that error rates were highest at baseline and lowest at 2 years. Improvements were primarily attributed to reducing inappropriate abbreviation errors. Other error types increased and remained elevated at 1-year post implementation, suggesting that transitioning from a locally-developed to a commercial EHR for e-prescribing can reduce certain errors; however, important safety threats remain. Over time, as users become accustomed to a system and iterative refinements are made, safety may continue to improve. Recognizing the challenges associated with transitions and refining clinical decision support within systems may help maximize safety benefits and allow potential safety threats to be better anticipated and managed.

For the second study, Dr. Kaushal used qualitative techniques to assess providers' perceptions of the two systems. The results again indicated that the transition was difficult for the providers, even though the providers all had experience using computers systems in clinical practice. Providers want systems that improve speed and ease of prescribing. Systems that were complicated were disliked, even when they had more robust clinical decision support. Providers overwhelmingly preferred certain features of the new vendor-based system, including remote access. Over time, providers became more positive in their perceptions about the new system, including its perceived impact on safety. Dr. Kaushal found that perceived system usability and efficiency for order writing were key determinants of provider satisfaction.

For the third study, 162 subjects completed all parts of the study, of which 82 patients were in the intervention arm. Overall, Dr. Kaushal found that medication discrepancies were extremely common. The intervention did not significantly reduce these discrepancies or ADEs for patients in the intervention group. Cardiovascular drugs, gastrointestinal drugs, non-narcotic analgesics, and anti-coagulants were the classes of medications with the highest error rates. The most common type of discrepancy detected was omitted medications. Risk factors for medication errors and ADEs included taking 11 or more medications, having two or more outpatient visits during the previous year, having less than a high school education, and receiving care from an intern as opposed to a senior resident.

Overall, this study underscores the importance and challenges of developing interventions that facilitate medication reconciliation while supporting provider workflow. The results also provide important information on the most common types of medication errors. This information can help providers identify patients who may be at higher risk for medication errors in an effort to reduce their risk of harm from medication discrepancies.

Target Population: Adults

Strategic Goal: Develop and disseminate health IT evidence and evidence-based tools to improve the quality and safety of medication management via the integration and utilization of medication management systems and technologies.

Business Goal: Implementation and Use

Electronic Prescribing and Electronic Transmission of Discharge Medication Lists - 2010

Summary Highlights

  • Principal Investigator: 
  • Funding Mechanism: 
    RFA: HS07-006: Ambulatory Safety and Quality Program: Improving Quality through Clinician Use of Health Information Technology (IQHIT)
  • Grant Number: 
    R18 HS 017029
  • Project Period: 
    September 2007 – March 2011, Including No-Cost Extension
  • AHRQ Funding Amount: 
    $1,187,674
  • PDF Version: 
    (PDF, 287.6 KB)


Target Population: Adults

Summary: This project consists of three studies assessing the impact of health information technology (IT) on patient safety in the ambulatory setting. The first is a multi-center before-and-after study measuring the impact on medication errors of switching from one electronic prescribing (e-prescribing) system to another, in this case from a home-grown to a vendor-based system. The second is a qualitative study of physicians using one-on-one-interviews and direct observation to understand variations in human-computer interactions with this new e-prescribing system and how user patterns or system features may influence medication errors. The third is a randomized, controlled trial evaluating the effect of electronically transmitting discharge medication lists from the hospital to the ambulatory setting using: 1) medication discrepancies at the first ambulatory visit following discharge; and 2) adverse drug events (ADEs) 30 days post-discharge as outcome measures.

These studies are important because they have the potential to substantially add to the knowledge of ambulatory medication safety as it relates to the value of vendor-based electronic prescribing systems for medication management in the ambulatory setting, and the impact of health information exchanges on patient safety at a critical time of transition. In addition, by including a qualitative component on human-computer interactions, this project has the potential to yield critical insights to why certain health IT interventions do or do not work, and how future interventions should be designed to better align themselves with physicians’ workflow. The studies also have implications for the many institutions and practices that are transitioning from one electronic health record (EHR) to another. If rates of errors vary greatly between commercial systems there are potential policy implications for more stringent certification criteria of e-prescribing to ensure medication safety.

Specific Aims:

  • Measure the effects on medication errors of transitioning from one e-prescribing system to another in the ambulatory setting. (Ongoing)
  • Measure the effects on human-computer interactions of transitioning from one e-prescribing system to another in the ambulatory setting. (Ongoing)
  • Evaluate the impact on medication discrepancies of electronic transmission of medication lists at discharge from the hospital to the ambulatory setting at the first ambulatory visit following discharge. (Ongoing)
  • Evaluate the impact on ADEs 30 days post-discharge of electronic transmission of medication lists at discharge from the hospital to the ambulatory setting. (Ongoing)

2010 Activities: The first study, measuring the effects on medication errors and data collection of transitioning from one electronic prescribing system to another, is nearly complete. Data have been collected for all four time periods (baseline, 3 months, 1 year, and 2 years post-implementation). Data cleaning and analysis are complete for the first three periods and in progress for the fourth. One manuscript has been submitted for publication and a second has been started.

The second study, a qualitative study measuring the effects on human-computer interaction of this same transition, is also near completion. The team completed two sets of interviews, the first with 15 providers and the second with 13 providers. Data from the first set of interviews have been analyzed and a manuscript has been submitted. Data from the second round of interviews are being assessed and a manuscript will be developed.

The third study evaluates the impact on medication discrepancies and ADEs of electronic transmission of medication lists at discharge. The chief medical information officer and the medical director of information services for Weill Cornell Physician Organization (the investigators) developed an application to electronically transmit discharge information, including medication lists from the inpatient setting to the outpatient setting. This tool has been implemented at New York-Presbyterian Hospital. Dr. Kaushal’s team, in collaboration with Dr. Jeffrey Schnipper from Brigham and Women’s Hospital and Harvard Medical School, also developed data collection tools to identify and characterize medication discrepancies, including a patient background form that obtains demographic and health status information from patients in the hospital, and a patient medication survey that collects medication data and ADEs at approximately 30 days post-discharge. The team further developed a medication error and adverse drug event tool. An experienced research nurse will use the tool to identify medication errors in the data and ADEs experienced by the patient. All medication errors will be reviewed by two experienced physicians who will use this tool to rate the severity of the medication errors and ADEs. The data collection period has been extended to attain a large enough sample size to reach the statistical power necessary for analysis. Data cleaning is concurrent with data collection. Analysis and manuscript preparation will follow.

Grantee’s Most Recent Self-Reported Quarterly Status (as of December 2010): The project is making good progress and spending is roughly on target. Data collection in complete for the first two studies and in progress nearing completion for the third study. Data cleaning and analysis is in progress for all three studies.

Preliminary Impact and Findings: For the quantitative study, the rates and types of prescribing errors made by physicians were assessed at three time periods: baseline (when physicians were using the locally developed EHR with minimal clinical decision support for e-prescribing); 3 months post-implementation of a commercial EHR with more advanced clinical decision support for e-prescribing; and 1 year post-implementation. The research team found that error rates were highest at baseline and lowest at 1 year. Improvements were primarily attributed to reducing inappropriate abbreviation errors. Other error types increased and remained elevated at 1 year post-implementation suggesting that transitioning from a locally developed EHR to a commercial EHR for e-prescribing can reduce certain errors; however, important safety threats remain. Overall, despite intensive efforts to ease the transition, most providers found transitioning extremely difficult. The commercial system was not perceived as improving medication safety, despite the more advanced clinical decision support. Additionally, physicians felt the commercial system was too complex and therefore reduced efficiency. This has important implications for the design and implementation of commercial systems with advanced clinical decision support for e-prescribing.

Strategic Goal: Develop and disseminate health IT evidence and evidence-based tools to improve the quality and safety of medication management via the integration and utilization of medication management systems and technologies.

Business Goal: Implementation and Use

Electronic Prescribing and Electronic Transmission of Discharge Medication Lists - Final Report

Citation:
Kaushal R. Electronic Prescribing and Electronic Transmission of Discharge Medication Lists - Final Report. (Prepared by Weill Cornell Medical College under Grant No. R18 HS017029). Rockville, MD: Agency for Healthcare Research and Quality, 2012. (PDF, 85.37 KB)

The findings and conclusions in this document are those of the author(s), who are responsible for its content, and do not necessarily represent the views of AHRQ. No statement in this report should be construed as an official position of AHRQ or of the U.S. Department of Health and Human Services.
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