Improving Quality With Outpatient Decision Support

This study has been completed.
Sponsor:
Information provided by:
Agency for Healthcare Research and Quality (AHRQ)
ClinicalTrials.gov Identifier:
NCT00225628
First received: September 22, 2005
Last updated: September 23, 2005
Last verified: September 2005
  Purpose

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 Intervention
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

Study Type: Interventional
Study Design: Allocation: Randomized
Endpoint Classification: Safety/Efficacy Study
Intervention Model: Parallel Assignment
Masking: Open Label
Primary Purpose: Prevention
Official Title: Improving Quality With Outpatient Decision Support

Resource links provided by NLM:


Further study details as provided by Agency for Healthcare Research and Quality (AHRQ):

Primary Outcome Measures:
  • 1) Compliance to guidelines regarding the outpatient laboratory monitoring of prescription medication regiments
  • 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) Compliance to guidelines regarding the management of hypertension in the general ambulatory population and amongst ethnic minority groups
  • 4) Compliance to guidelines regarding the screening and management of osteoporosis

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

Estimated Enrollment: 3000
Study Start Date: September 2000
Estimated Study Completion Date: December 2006
  Hide Detailed Description

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.
  Eligibility

Ages Eligible for Study:   18 Years and older
Genders Eligible for Study:   Both
Accepts Healthy Volunteers:   No
Criteria

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:

  • None
  Contacts and Locations
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Please refer to this study by its ClinicalTrials.gov identifier: NCT00225628

Locations
United States, Massachusetts
Brigham and Women's Hospital
Boston, Massachusetts, United States, 02472
Sponsors and Collaborators
Investigators
Principal Investigator: David W Bates, MD MSc Brigham and Women's Hospital
  More Information

Publications:

Additional publications automatically indexed to this study by ClinicalTrials.gov Identifier (NCT Number):
ClinicalTrials.gov Identifier: NCT00225628     History of Changes
Other Study ID Numbers: 5 U18 HS011046
Study First Received: September 22, 2005
Last Updated: September 23, 2005
Health Authority: United States: Federal Government

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:
Hypertension
Diabetes Mellitus
Coronary Artery Disease
Myocardial Ischemia
Coronary Disease
Osteoporosis
Hyperlipidemias
Vascular Diseases
Cardiovascular Diseases
Glucose Metabolism Disorders
Metabolic Diseases
Endocrine System Diseases
Heart Diseases
Arteriosclerosis
Arterial Occlusive Diseases
Bone Diseases, Metabolic
Bone Diseases
Musculoskeletal Diseases
Dyslipidemias
Lipid Metabolism Disorders

ClinicalTrials.gov processed this record on October 19, 2014