Improving Quality With Outpatient Decision Support

The safety and scientific validity of this study is the responsibility of the study sponsor and investigators. Listing a study does not mean it has been evaluated by the U.S. Federal Government. Read our disclaimer for details. Identifier: NCT00225628
Recruitment Status : Completed
First Posted : September 26, 2005
Last Update Posted : September 26, 2005
Information provided by:
Agency for Healthcare Research and Quality (AHRQ)

Brief Summary:
Assesses physician compliance with paper-based and electronic guidelines, reminders, and alerts for outpatient settings. Target areas for the reminders and alerts are disease management, medication management, and interpretation of abnormal test results.

Condition or disease Intervention/treatment Phase
Diabetes Mellitus Coronary Artery Disease Osteoporosis Hypertension Hyperlipidemia Behavioral: Computerized Reminders Medications Monitoring Behavioral: Computerized Test Results Management Application Behavioral: Computerized Reminders Hypertension Management Behavioral: Computerized Reminders Osteoporosis Screening and Mgt Not Applicable

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Detailed Description:

The evidence base for practicing medicine continues to improve. However, abundant data show that gaps exist between best evidence and practice. Moreover, health care costs are climbing at an alarming rate. We propose to ask three related questions: 1) how effective are computer decision-support systems for improving compliance with evidence-based guidelines and costs in the ambulatory setting; 2) what is the impact on guideline compliance of applications that allow clinicians to track and follow-up test results; and 3) what are the main barriers to acceptance of guidelines delivered via real-time clinical decision-support systems.

Our work and that of others has shown that computerized decision-support in the form of alerts and reminders can improve outcomes and reduce costs in the inpatient setting. However, fewer data are available in the outpatient setting. An elegant series of studies from Regenstrief found that certain computer-based interventions, such as displaying charges for tests, prior test results, and the likelihood that a particular test would be abnormal, all reduced outpatient utilization, and that reminders to perform health maintenance procedures improved compliance. However, such systems are still not used broadly and the full potential of computer-based technology remains to be tested.

Also, there is ample evidence that physicians do not always act optimally on the results of patient studies and often are remiss at communicating satisfactorily with patients about the results of these studies. This situation may be exacerbated by increasing patient volumes in the face of managed care. The ability of the computer to assist in the tracking and follow-up of test results as well as communication with patients remains to be evaluated.

Even though some benefits of computer-based decision-support systems have been documented, such systems are slow to be adopted. Moreover, even when computerized guidelines have resulted in demonstrable improvements, often this improvement has been smaller than anticipated. This proposal aims to better understand the barriers to guideline acceptance so that the benefits of computer based decision-support can be realized.

Our organization, Brigham and Women's Hospital, is in a particularly good position to study these issues. We have in place a highly developed clinical information system including an outpatient electronic medical records (EMR) application that has been an active part of the clinical workflow since 1999. The EMR application currently is used by primary care physicians at one of our major medical centers to track their patients’ problems, medications, allergies, and health maintenance data. We are developing a new EMR that will be used more broadly across our network, and that features a new interface with added functionality. The new EMR will allow us to evaluate the state of the patient at the time of the visit and generate reminders if the patient is out of compliance for certain guidelines. It also includes outpatient order entry that allows physicians to enter medication and laboratory orders directly into the computer. Decision-support in order entry will allow us to guide physician decision making at the most opportune time, and then evaluate the result of that guidance. For automated decision-support applications to be widely adopted, it is critical that their benefits be demonstrated in a wide variety of situations. We plan to implement several different types of interventions targeted at various phases of the clinical workflow to determine which strategies can achieve the greatest benefit.

Specific Aims:

  1. To evaluate the effectiveness of paper-based and interactive computer-based alerts and reminders for improving compliance with guidelines and reducing costs in the ambulatory setting.
  2. To evaluate the impact of computer-based tracking and follow-up reminder systems on guideline compliance.
  3. To identify and address patient, clinician, and system barriers to the effective use of computer-based clinical decision-support strategies in a diverse array of clinical settings.

Study Type : Interventional  (Clinical Trial)
Enrollment : 3000 participants
Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: None (Open Label)
Primary Purpose: Prevention
Official Title: Improving Quality With Outpatient Decision Support
Study Start Date : September 2000
Study Completion Date : December 2006

Primary Outcome Measures :
  1. 1) Compliance to guidelines regarding the outpatient laboratory monitoring of prescription medication regiments
  2. 2) Compliance to guidelines regarding the follow-up of abnormal test results, including critically abnormal test results, abnormal cholesterol, abnormal HbA1c, abnormal pap smears and abnormal mammogram
  3. 3) Compliance to guidelines regarding the management of hypertension in the general ambulatory population and amongst ethnic minority groups
  4. 4) Compliance to guidelines regarding the screening and management of osteoporosis

Secondary Outcome Measures :
  1. 1) Patient satisfaction regarding communication with physicians
  2. 2) Physician satisfaction regarding follow-up of abnormal test results

Information from the National Library of Medicine

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Ages Eligible for Study:   18 Years and older   (Adult, Senior)
Sexes Eligible for Study:   All
Accepts Healthy Volunteers:   No

Inclusion Criteria:

  • All physicians in on-site and satellite adult outpatient clinics with the Brigham and Women's Hospital and Massachusetts General Hospital.
  • All practices must have adopted our home-grown electronic health record system, the Longitudinal Medical Record, for at least 24 months prior to the start of each intervention trial.

Exclusion Criteria:

Information from the National Library of Medicine

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.

Please refer to this study by its identifier (NCT number): NCT00225628

United States, Massachusetts
Brigham and Women's Hospital
Boston, Massachusetts, United States, 02472
Sponsors and Collaborators
Agency for Healthcare Research and Quality (AHRQ)
Principal Investigator: David W Bates, MD MSc Brigham and Women's Hospital

Publications of Results:

Other Publications:
Publications automatically indexed to this study by Identifier (NCT Number): Identifier: NCT00225628     History of Changes
Other Study ID Numbers: 5U18HS011046 ( U.S. AHRQ Grant/Contract )
First Posted: September 26, 2005    Key Record Dates
Last Update Posted: September 26, 2005
Last Verified: September 2005

Keywords provided by Agency for Healthcare Research and Quality (AHRQ):
Computerized clinical decision support
Patient Safety
Quality of Care
Electronic Medical Records
Chronic Disease Management
Drug Monitoring
Guideline Adherence
Reminder Systems

Additional relevant MeSH terms:
Diabetes Mellitus
Coronary Artery Disease
Myocardial Ischemia
Coronary Disease
Glucose Metabolism Disorders
Metabolic Diseases
Endocrine System Diseases
Heart Diseases
Cardiovascular Diseases
Arterial Occlusive Diseases
Vascular Diseases
Bone Diseases, Metabolic
Bone Diseases
Musculoskeletal Diseases
Lipid Metabolism Disorders