Clinical trial NCT00374452: VISN Collaborative for Improving Hypertension Management With ATHENA-HTN
Official title: VISN Collaborative for Improving Hypertension Management With ATHENA-HTN
Study type: INTERVENTIONAL
Overall status: COMPLETED
Phase: NA
Conditions: Hypertension
Keywords: hypertension
practice guidelines
quality of health care
decision support systems
evidence-based medicine
medical informatics
Lead sponsor: VA Office of Research and Development
Sponsor class: FED
First posted: 2006-09-11
Enrollment: 103
Sex: ALL
Standard ages: CHILD
ADULT
OLDER_ADULT
Accepts healthy volunteers: yes
Allocation: RANDOMIZED
Intervention model: PARALLEL
Primary purpose: HEALTH_SERVICES_RESEARCH

Brief summary: This project is a VA HSR\&D-funded Quality Enhancement Research Initiative (QUERI) project to translate into practice evidence about clinical management of primary hypertension. The project aims to contribute to quality improvement of care for patients with primary hypertension. The project implemented a clinical decision support (CDS) system for primary care clinicians and evaluated the implementation by studying the following: impact on the clinicians' prescribing and their patients' blood pressures; the clinician satisfaction with the CDS; and organizational factors in the implementation.

Detailed description: Background / Rationale:

Despite the existence of evidence-based guidelines, there is a gap between evidence-based recommended best medical practice and actual practice. In previous work, we used hypertension as a model to study the translation of research regarding clinical blood pressure targets and drug choice into primary care practice through computer-based implementation of clinical practice guidelines. In collaboration with experts in guideline-automation at Stanford Center for Biomedical Informatics Research (BMIR) (formerly known as Stanford Medical Informatics, SMI), we developed an innovative clinical decision support system: ATHENA-CDS-HTN (hypertension) also known as ATHENA-HTN. ATHENA-HTN is a knowledge-based CDS that uses knowledge bases (KBs) of clinical knowledge of hypertension encoded into computable formats. Clinical data from an electronic health records system is processed with the knowledge in the KB by an execution engine (also known as a guideline interpreter) that generates patient-specific outputs with conclusions about the current state of the patient with respect to the guidelines as shown in the patient's electronic health record data and also generates detailed recommendations for next steps in clinical management of the patient's hypertension. The system is designed to take account of multiple data elements in the patients' clinical data including co-morbid diagnoses that are relevant to hypertension and its treatment, other medications currently prescribed, history of adverse drug reactions/events, and selected laboratory values relevant to hypertension and its management. In previous work, we had demonstrated that deploying this CDS system in VA primary care clinics was feasible and that clinicians found the system usable and useful, as shown by their actual extensive use of the system and their response to a questionnaire survey. The current project was funded by the Department of Veterans Affairs Health Services Research and Development (HSR\&D), under a special funding initiative for Quality Enhancement Initiative (QUERI) projects designed to improve care for hypertension by collaboration with a Veterans Integrated Service Network (VISN) to implement programs to encourage use of established best-practices for managing hypertension according to evidence-based guidelines available at the time of the study. These studies were known as "VISN Collaboratives". The studies did not involve any new drugs or new uses of established drugs, but rather encouraging use of established drugs recommended in standard evidence-based guidelines for care. The focus of the study was implementation of existing known best practices in managing hypertension, using the CDS as a vehicle to bring information to the point-of-care, with detailed individualized recommendations about patients presented to the primary care provider at the time the provider sees patients in scheduled outpatient primary care clinic visits.

Objective(s):

Our objectives in this VISN Implementation Collaborative included: (1) implement evidence-based guidelines for hypertension in a CDS system by upgrading the ATHENA-HTN knowledge-base (KB) to the most recent guidelines; (2) deploy the CDS system in 5 medical centers within VISN 1 to generate individualized recommendations to primary care clinicians caring for patients in outpatient clinics; (3) evaluate the implementation including the organizational aspects.

Methods:

In Phase 1 we plan to update the KB and conduct offline testing; to revise the M (formerly known as MUMPS) program that extracts patient data daily from VistA to extract additional data elements; to streamline the system architecture to make it easier to implement in multiple sites; to work with the site-PIs to obtain IRB approval at 5 implementation sites in VISN 1 plus the coordinating site at VA Palo Alto; to improve the user interface design; to identify and resolve issues in implementing new information technology in multiple different VA medical centers (VAMC) with different Computerized Patient Record System (CPRS) implementations and different methods of distributing computer access to clinicians; to train the site PIs in use of the system; and perform baseline data analysis to inform the randomization. In Phase 2 we plan to recruit primary care providers from the participating 5 medical centers in VISN 1; randomize clinics to ATHENA-HTN intervention or usual care; deploy the system for intervention providers; train intervention providers in use of the system; and conduct a 12-month clinical trial of the system.

Status:

The project has been completed. We completed Institutional Review Board (IRB) approvals at all five medical centers. We updated the knowledge base of computable knowledge regarding hypertension and conducted offline testing. Our system was deployed to all five medical centers. While we were preparing for deployment of the CDS, one site changed from a rich-client environment to a thin-client environment for the medical center computers; we developed new code to run the system in a thin client environment. The previous programming computed recommendations of the CDS based on clinical data available the night before the clinic visit (in order to pre-compute advisories for faster display during clinic); in this project we developed software code to obtain automatic blood pressure updates for the day of visit if these were entered by clinical staff at the time of the visit. VA Palo Alto staff worked with staff at each VAMC to validate clinical data extraction at each site. We developed code for a clinician to select, optionally, for blood pressure write-back to VA VistA so that if clinicians entered to our CDS a blood pressure measurement that they had just taken so they could view updated recommendations based on the repeat blood pressure they would not also have to enter that blood pressure separately to electronic health record. We recruited primary care providers (clinicians) at each of 5 medical centers to participate in the project. One of the 5 medical centers completed the installation of the ATHENA-HTN system, but did not continue with the intervention period, so the intervention included 4 rather than 5 medical centers. Our site-principal investigators and project coordinator trained intervention providers on use of the system by offering short phone calls for training or in-person introduction, and by making the system available for a short period of time for familiarity. Records of patients seen by the clinicians in this training period were excluded from analyses. We completed a 6-8 month intervention period for the clinical trial at the 4 participating medical centers. Our random allocation was at clinic level, where a clinic is a substation of a medical center (station). Before initiating data analyses, we prepared a detailed data analysis plan.

Eligibility criteria: Inclusion Criteria:

* Must be primary care clinicians (for example, physician or nurse practitioner) at one of the participating VA medical centers. This study is NOT recruiting patients.
* The primary care clinician must have a panel of patients for whom he or she provides direct care.

Exclusion Criteria:

* Anyone who does not meet inclusion criteria.

Primary outcomes:
measure: Mean Percentages of Events After Index Visit to Primary Care by Patient
timeFrame: up to one year after index visit
Secondary outcomes:
Other outcomes:
Locations:
city: Palo Alto
country: United States
facility: VA Palo Alto Health Care System
state: California
city: Newington
country: United States
facility: VA Connecticut Health Care System (Newington)
state: Connecticut
city: West Haven
country: United States
facility: VA Connecticut Health Care System (West Haven)
state: Connecticut
city: Bedford
country: United States
facility: Edith Nourse Rogers Memorial Veterans Hospital, Bedford
state: Massachusetts
city: Boston
country: United States
facility: VA Boston Healthcare System Jamaica Plain Campus, Jamaica Plain, MA
state: Massachusetts
city: Manchester
country: United States
facility: VA Medical Center, Manchester
state: New Hampshire
city: Providence
country: United States
facility: VA Medical Center, Providence
state: Rhode Island
Study officials:
affiliation: VA Palo Alto Health Care System
name: Mary K. Goldstein, MD MS
role: PRINCIPAL_INVESTIGATOR
References:
citation: Martins SB, Lai S, Tu S, Shankar R, Hastings SN, Hoffman BB, Dipilla N, Goldstein MK. Offline testing of the ATHENA Hypertension decision support system knowledge base to improve the accuracy of recommendations. AMIA Annu Symp Proc. 2006;2006:539-43.
citation: Chan AS, Shankar RD, Coleman RW, Matins SB, Hoffman BB, Goldstein MK. Leveraging point-of-care clinician feedback to study barriers to guideline adherence. AMIA Annu Symp Proc. 2005;2005:915.
citation: Trafton J, Martins S, Michel M, Lewis E, Wang D, Combs A, Scates N, Tu S, Goldstein MK. Evaluation of the acceptability and usability of a decision support system to encourage safe and effective use of opioid therapy for chronic, noncancer pain by primary care providers. Pain Med. 2010 Apr;11(4):575-85. doi: 10.1111/j.1526-4637.2010.00818.x. Epub 2010 Mar 1.
citation: Michel M, Trafton J, Martins S, Wang D, Tu S, Johnson N, Goldstein MK. Improving Patient Safety Using ATHENA-Decision Support System Technology: The Opioid Therapy for Chronic Pain Experience. In: Henriksen K, Battles JB, Keyes MA, Grady ML, editors. Advances in Patient Safety: New Directions and Alternative Approaches (Vol. 4: Technology and Medication Safety). Rockville (MD): Agency for Healthcare Research and Quality (US); 2008 Aug. Available from http://www.ncbi.nlm.nih.gov/books/NBK43756/
citation: Bosworth HB, Olsen MK, Dudley T, Orr M, Goldstein MK, Datta SK, McCant F, Gentry P, Simel DL, Oddone EZ. Patient education and provider decision support to control blood pressure in primary care: a cluster randomized trial. Am Heart J. 2009 Mar;157(3):450-6. doi: 10.1016/j.ahj.2008.11.003. Epub 2009 Jan 10.
citation: Goldstein MK. Using health information technology to improve hypertension management. Curr Hypertens Rep. 2008 Jun;10(3):201-7. doi: 10.1007/s11906-008-0038-6.
citation: Cucciare MA, Ketroser N, Wilbourne P, Midboe AM, Cronkite R, Berg-Smith SM, Chardos J. Teaching motivational interviewing to primary care staff in the Veterans Health Administration. J Gen Intern Med. 2012 Aug;27(8):953-61. doi: 10.1007/s11606-012-2016-6. Epub 2012 Feb 28.
citation: Steinman MA, Goldstein MK. When tight blood pressure control is not for everyone: a new model for performance measurement in hypertension. Jt Comm J Qual Patient Saf. 2010 Apr;36(4):164-72. doi: 10.1016/s1553-7250(10)36028-4.