Computer-Based Decision Support in Managing Asthma in Primary Care
|Study Design:||Allocation: Randomized
Intervention Model: Parallel Assignment
Masking: Single Blind (Subject)
Primary Purpose: Treatment
|Official Title:||Evaluating the Impact of Computer-Based Decision Support for the Management of Asthma in Primary Care|
- poor asthma control [ Time Frame: 2006-2009 ] [ Designated as safety issue: No ]
- quality of care indicators (inhaled corticosteroid to beta2-agonist ratio) [ Time Frame: 2006-2009 ] [ Designated as safety issue: No ]
|Study Start Date:||October 2006|
|Study Completion Date:||June 2009|
|Primary Completion Date:||June 2009 (Final data collection date for primary outcome measure)|
No Intervention: 1
Physicians in this arm will be using the standard MOXXI electronic health record.
In addition to the standard MOXXI electronic health record, physicians in this arm will be using the computer-based decision support for asthma management
Device: computer-based decision support for asthma management
The asthma management decision support system uses data from the patient problem and medication list to provide patient-specific management recommendations based on Canadian Consensus guidelines for asthma management. Web-enabled technology for asthma education nurses is used to collect home-monitoring information from patients between visits and feedback to primary care physicians in accordance with options selected by the physician for each patient.
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Background: Asthma is a chronic condition that is responsible for substantial morbidity. Direct costs for physicians, hospital care and medications in Canada are conservatively estimated at $306 million per year for persons with asthma. Existing evidence suggests that considerable reductions in morbidity could be achieved by early prevention and timely treatment. Much of the costs of asthma care are related to poor disease control due to under-use of effective prophylactic therapies, inadequate monitoring of disease severity, and insufficient patient education. A recent Canadian survey found that only 64% of patients with poor asthma control had been prescribed an inhaled corticosteroid, and of these only 52% made use of the medication on a daily basis. Further, although asthma self-management has been shown to reduce the relative risk of hospitalization for asthma by 39%, only 21% of asthma patients are provided with an action plan to institute for disease exacerbation and only 22% of primary care physicians provide action plans for their asthma patients on a regular basis. Computerized decision-support systems have provided a new set of tools for enabling integrated evidence-based care, by providing physicians with patient-specific reminders and alerts for needed preventive care and management, and timely feedback from patients. However, there has been limited use of computer-enabled decision-support in primary care, and only one reported study in chronic disease management. A key barrier to success has been the challenge of providing primary care physicians with a computerized solution that will produce value-added benefits and can be integrated easily into their routine workflow. Our prior research has shown that an integrated electronic prescribing and drug management system can provide value-added benefits for physicians because it is linked to information on dispensed medications, and alerts for prescribing problems. Early uptake and utilization of this computerized drug management system by primary care physicians provides an opportunity to develop and evaluate the effectiveness of an integrated asthma management decision-support system to enhance the use of prophylactic therapies and timely monitoring of asthma severity in primary care.
Objective: To determine if computerized decision-support and home-monitoring systems for asthma that is integrated into an electronic prescription and drug management system can: a) increase quality of disease management, b) improve treatment outcomes for patients with asthma.
Research Plan: A cluster-randomized trial with 33 months of follow-up will be conducted in a population of approximately 100 primary care physicians in full-time private fee-for-service practice in approximately 40 clinics in Quebec, and an estimated 2,880 - 4500 participating asthma patients within their practices. Enrolled physicians will receive the MOXXI electronic prescription and drug management software, equipped with wireless modem to access the central databases and application server, and wireless printer. This system allows physicians to write and send prescriptions electronically, provides alerts for potential prescribing errors, a profile of current and past medications through automated links with the provincial drug insurance plan and community-based pharmacies, a medication compliance calculator based on dispensed prescriptions, and automated problem list creation based on treatment indication and verification of diagnostic codes on medical services claims files. Clinics will be randomized to receive a) computerized decision-support and home-monitoring for asthma integrated with the MOXXI system or b) the MOXXI system alone. The asthma management decision support system uses data from the patient problem and medication list to provide patient-specific management recommendations based on Canadian Consensus guidelines for asthma management. Web-enabled technology for asthma education nurses is used to collect home-monitoring information from patients between visits and feedback to primary care physicians in accordance with options selected by the physician for each patient.
The primary outcome, measured in each 3 month period of follow-up will be poor asthma control, defined as an ER visit or hospitalization for asthma in each 3 month period of follow-up or the dispensing of > 250 doses of fast-acting beta2-agonists. Secondary outcomes will include one evidence-based quality of care indicator (inhaled corticosteroid to beta2-agonist ratio, prescription of an action plan). Primary and secondary outcomes will be measured using data from the medical chart, records of prescribed and dispensed drugs, and Ministry of Health beneficiary, medical services and hospitalization databases. Effectiveness of computer-based decision support will be assessed by multivariate hierarchical modeling to take into account multiple measurements for the same patient, clustered within physician and clinic, and to adjust for baseline differences in patient characteristics. Also, we will examine whether the effectiveness of the intervention was modified by asthma control status and physicians' use of the MOXXI application by stratified analyses.
Please refer to this study by its ClinicalTrials.gov identifier: NCT00170248
|Montreal, Quebec, Canada, H3A 1A3|
|Principal Investigator:||Robyn Tamblyn, PhD||McGill University|