Comparing methods to identify general internal medicine clinic patients with chronic heart failure.

Udris EM, Au DH, McDonell MB, Chen L, Martin DC, Tierney WM, Fihn SD. Comparing methods to identify general internal medicine clinic patients with chronic heart failure. American heart journal. 2001 Dec 1; 142(6):1003-9.

Related HSR&D Project(s)

• CPG 97-001 – Computerized Guidelines Enhanced by Symptoms and History: Clinical Effects

Dimensions for VA is a web-based tool available to VA staff that enables detailed searches of published research and research projects.

If you have VA-Intranet access, click here for more information vaww.hsrd.research.va.gov/dimensions/

VA staff not currently on the VA network can access Dimensions by registering for an account using their VA email address.    Search Dimensions for VA for this citation
* Don't have VA-internal network access or a VA email address? Try searching the free-to-the-public version of Dimensions

Search for Abstract from PubMed

---

Abstract:

OBJECTIVES: Identification of patients with left ventricular systolic dysfunction is the first step in identifying which patients may benefit from clinical practice guidelines. The purpose of this study was to develop and validate a computerized tool using clinical information that is commonly available to identify patients with left ventricular systolic dysfunction (LVSD). METHODS: We performed a cross-sectional study of patients seen in a Department of Veterans Affairs General Internal Medicine Clinic who had echocardiography or radionuclide ventriculography performed as part of their clinical care. RESULTS: We identified 2246 subjects who had at least one cardiac imaging study. A total of 778 (34.6%) subjects met study criteria for LVSD. Subjects with LVSD were slightly older than subjects without LVSD (70 years vs 68 years, P = .00002) but were similar with regard to sex and race. Subjects with LVSD were more likely to have prescriptions for angiotensin-converting enzyme (ACE) inhibitors, carvedilol, digoxin, loop diuretics, hydralazine, nitrates, and angiotensin II receptor antagonists. Of the variables included in the final predictive model, ACE inhibitors, loop diuretics, and digoxin exerted the greatest predictive power. Discriminant analysis demonstrated that models containing pharmacy information were consistently more accurate (75% accurate [65% sensitivity, 81% specificity]) than those models that contained only International Classification of Diseases, 9th revision (ICD-9), codes, including ICD-9 codes for congestive heart failure (72% accurate [80% sensitivity, 68% specificity]). CONCLUSIONS: We demonstrated that an automated, computer-driven algorithm identifying LVSD permits simple, rapid, and timely identification of patients with congestive heart failure by use of only routinely collected data. Future research is needed to develop accurate electronic identification of heart failure and other common chronic conditions.