Study of an Intervention to Improve Problem List Accuracy and Use (MAPLE)
Attention Deficit Disorder With Hyperactivity
Coronary Artery Disease
Congestive Heart Failure
Sickle Cell Disease
|Study Design:||Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Open Label
Primary Purpose: Diagnostic
|Official Title:||Making Accurate Problem Lists in the EHR|
- Intervention acceptance [ Time Frame: 6 months (May 2010-Nov2010) ]Of those providers who were shown (or who would have been shown, for the control group) the intervention, the number that added a problem across control and intervention groups.
- Problem list prevalence [ Time Frame: pre and post intervention ]Number of patients with selected problems on their problem list pre and post intervention across intervention and control groups.
- Problem list incidence [ Time Frame: pre and post intervention ]For the conditions of interest, the percent of patients that had the problem added during the study period
- Quality improvement based on problem list accuracy/completion [ Time Frame: post intervention ]For those with problems added due to the intervention, the number of new triggered reminders or other clinical actions.
|Study Start Date:||May 2010|
|Estimated Study Completion Date:||November 2017|
|Primary Completion Date:||November 2010 (Final data collection date for primary outcome measure)|
Experimental: Receive CDS intervention
Providers in clinics that will receive the CDS alert, as their clinic was randomized into our study.
MAPLE is a CDS intervention within the EHR that will alert providers to problem lists gaps and present an opportunity to correct them.
|No Intervention: No CDS intervention|
The clinical problem list is a cornerstone of the problem-oriented medical record. Problem lists are used in a variety of ways throughout the process of clinical care. In addition to its use by clinicians, the problem list is also critical for decision support and quality measurement.
Patients with gaps in their problem list face significant risks. For example, if a hypothetical patient has diabetes properly documented, his clinician would receive appropriate alerts and reminders to guide care. Additionally, the patient might be included in special care management programs and the quality of care provided to him would be measured and tracked. Without diabetes on his problem list, he might receive none of these benefits.
In this study, the investigators developed an clinical decision support intervention that will identify patients with problem lists gaps. The investigators will alert providers of these likely gaps and offer providers the opportunity to correct them.
Please refer to this study by its ClinicalTrials.gov identifier: NCT01105923
|United States, Massachusetts|
|Brigham and Women's Hospital|
|Boston, Massachusetts, United States, 02115|
|Principal Investigator:||Adam Wright, PhD||Brigham and Women's Hospital|