Improving Quality With Outpatient Decision Support
|First Received Date ICMJE||September 22, 2005|
|Last Updated Date||September 23, 2005|
|Start Date ICMJE||September 2000|
|Primary Completion Date||Not Provided|
|Current Primary Outcome Measures ICMJE
|Original Primary Outcome Measures ICMJE||Same as current|
|Change History||No Changes Posted|
|Current Secondary Outcome Measures ICMJE
|Original Secondary Outcome Measures ICMJE||Same as current|
|Current Other Outcome Measures ICMJE||Not Provided|
|Original Other Outcome Measures ICMJE||Not Provided|
|Brief Title ICMJE||Improving Quality With Outpatient Decision Support|
|Official Title ICMJE||Improving Quality With Outpatient Decision Support|
|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.|
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.
|Study Type ICMJE||Interventional|
|Study Phase||Not Provided|
|Study Design ICMJE||Allocation: Randomized
Endpoint Classification: Safety/Efficacy Study
Intervention Model: Parallel Assignment
Masking: Open Label
Primary Purpose: Prevention
|Study Arm (s)||Not Provided|
* Includes publications given by the data provider as well as publications identified by ClinicalTrials.gov Identifier (NCT Number) in Medline.
|Recruitment Status ICMJE||Completed|
|Completion Date||December 2006|
|Primary Completion Date||Not Provided|
|Eligibility Criteria ICMJE||
|Ages||18 Years and older|
|Accepts Healthy Volunteers||No|
|Contacts ICMJE||Contact information is only displayed when the study is recruiting subjects|
|Listed Location Countries ICMJE||United States|
|Removed Location Countries|
|NCT Number ICMJE||NCT00225628|
|Other Study ID Numbers ICMJE||5 U18 HS011046|
|Has Data Monitoring Committee||Not Provided|
|Responsible Party||Not Provided|
|Study Sponsor ICMJE||Agency for Healthcare Research and Quality (AHRQ)|
|Collaborators ICMJE||Not Provided|
|Information Provided By||Agency for Healthcare Research and Quality (AHRQ)|
|Verification Date||September 2005|
ICMJE Data element required by the International Committee of Medical Journal Editors and the World Health Organization ICTRP