Guidelines for Drug Therapy of Hypertension: Closing the Loop
調査の概要
状態
条件
詳細な説明
Background:
Hypertension is a major risk factor for heart disease and stroke. Evidence-based guidelines support the use of specific drugs for patients with specific comorbidities to maximize the decrease in cardiovascular risk; yet, many physicians do not follow these guidelines in choosing drug therapy.
Objectives:
The goal of this project was to evaluate methods of implementing clinical practice guidelines, using hypertension as a model. We hypothesized that providing patient-specific recommendations to clinicians at the time of clinic contact with hypertensive patients would substantially improve guideline concordance of drug therapy without adversely affecting (possibly improving) blood pressure control. Our long-term goal is to develop and evaluate methods of implementing clinical practice guidelines that build on current knowledge about the most effective approaches to changing clinician behavior, and to extend those methods to other cardiovascular diseases.
Methods:
This project, known as ATHENA, included two major components: (1) We conducted a randomized controlled trial of patient-specific recommendations about drug therapy for hypertension, delivered to primary care clinicians at the time of primary care clinic visits. The recommendations were based on VA Hypertension Guidelines. The trial included 36 clinicians and 4500 hypertensive patients enrolled in primary care clinics at VA Palo Alto Health Care System. We compared a general intervention to an individualized intervention. Both the general and the intervention groups of clinicians received extensive guideline education, as part of a VISN-mandated hypertension guideline implementation. Clinicians randomized to the individualized intervention received, in addition, computer-generated patient-specific recommendations about drug therapy of hypertension, delivered to the clinics with the encounter forms for each visit. (2) In the 2nd major component of the study, we collaborated with Stanford Medical Informatics to develop a hypertension decision support system (ATHENA DSS). ATHENA DSS combines detailed patient information from the VA electronic medical record (VistA) with hypertension guideline knowledge based on the VA and JNC 6 hypertension guidelines. A special feature of ATHENA DSS is that the knowledge in the system can be easily browsed and updated by clinician-managers, so that knowledge can be kept up to date with emerging clinical trial findings about best treatments. We developed an infrastructure to implement the system in a pop-up window in the CPRS-GUI in the primary care clinics at VA Palo Alto. We also conducted an offline test of the program logic by comparing the ATHENA DSS recommendations with those made by a physician for 100 randomly selected VA patients.
Status:
In the past year, we have completed the data collection and data analysis for the randomized trial, and testing for ATHENA DSS, and we are preparing manuscripts. A new project evaluating implementation of guidelines with ATHENA DSS at 3 VA medical centers began in October, 2000.
研究の種類
入学 (予想される)
段階
- 適用できない
連絡先と場所
研究場所
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California
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Palo Alto、California、アメリカ、94304-1290
- VA Palo Alto Health Care System, Palo Alto, CA
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参加基準
適格基準
就学可能な年齢
- 子
- 大人
- 高齢者
健康ボランティアの受け入れ
受講資格のある性別
説明
Inclusion Criteria:
Subjects were primary care clinicians, both physicians and nurse practitioners, at a large VA medical center. Patients were not subjects in this study.
Exclusion Criteria:
研究計画
研究はどのように設計されていますか?
デザインの詳細
- 割り当て:ランダム化
- 介入モデル:並列代入
- マスキング:独身
武器と介入
参加者グループ / アーム |
介入・治療 |
|---|---|
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他の:アーム1
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協力者と研究者
捜査官
- 主任研究者:Mary K. Goldstein, MD MS、VA Palo Alto Health Care System, Palo Alto, CA
出版物と役立つリンク
一般刊行物
- Shankar RD, Tu SW, Martins SB, Fagan LM, Goldstein MK, Musen MA. Integration of textual guideline documents with formal guideline knowledge bases. Proc AMIA Symp. 2001:617-21.
- Shankar RD, Martins SB, Tu SW, Goldstein MK, Musen MA. Building an explanation function for a hypertension decision-support system. Stud Health Technol Inform. 2001;84(Pt 1):538-42.
- Lin ND, Martins SB, Chan AS, Coleman RW, Bosworth HB, Oddone EZ, Shankar RD, Musen MA, Hoffman BB, Goldstein MK. Identifying barriers to hypertension guideline adherence using clinician feedback at the point of care. AMIA Annu Symp Proc. 2006;2006:494-8.
- Tu SW, Hrabak KM, Campbell JR, Glasgow J, Nyman MA, McClure R, McClay J, Abarbanel R, Mansfield JG, Martins SM, Goldstein MK, Musen MA. Use of declarative statements in creating and maintaining computer-interpretable knowledge bases for guideline-based care. AMIA Annu Symp Proc. 2006;2006:784-8.
- Goldstein MK, Hoffman BB, Coleman RW, Musen MA, Tu SW, Advani A, Shankar R, O'Connor M. Implementing clinical practice guidelines while taking account of changing evidence: ATHENA DSS, an easily modifiable decision-support system for managing hypertension in primary care. Proc AMIA Symp. 2000:300-4.
- Advani A, Tu S, O'Connor M, Coleman R, Goldstein MK, Musen M. Integrating a modern knowledge-based system architecture with a legacy VA database: the ATHENA and EON projects at Stanford. Proc AMIA Symp. 1999:653-7.
- Goldstein MK, Hoffman BB, Coleman RW, Tu SW, Shankar RD, O'Connor M, Martins S, Martins S, Advani A, Musen MA. Patient safety in guideline-based decision support for hypertension management: ATHENA DSS. Proc AMIA Symp. 2001:214-8.
- Advani A, Goldstein M, Musen MA. A framework for evidence-adaptive quality assessment that unifies guideline-based and performance-indicator approaches. Proc AMIA Symp. 2002:2-6.
- Goldstein MK, Lavori P, Coleman R, Advani A, Hoffman BB. Improving adherence to guidelines for hypertension drug prescribing: cluster-randomized controlled trial of general versus patient-specific recommendations. Am J Manag Care. 2005 Nov;11(11):677-85.
研究記録日
主要日程の研究
研究の完了 (実際)
試験登録日
最初に提出
QC基準を満たした最初の提出物
最初の投稿 (見積もり)
学習記録の更新
投稿された最後の更新 (見積もり)
QC基準を満たした最後の更新が送信されました
最終確認日
詳しくは
この情報は、Web サイト clinicaltrials.gov から変更なしで直接取得したものです。研究の詳細を変更、削除、または更新するリクエストがある場合は、register@clinicaltrials.gov。 までご連絡ください。 clinicaltrials.gov に変更が加えられるとすぐに、ウェブサイトでも自動的に更新されます。