Roy M. Poses, MD; Donna K. McClish, PhD; Wally R. Smith, MD; Elizabeth C. Huber, MD; F. Lynne W. Clemo, MD; Brian P. Schmitt, MD; Donna Alexander, PhD; Edward M. Racht, MD; Christopher C. Colenda, III, MD
Grant Support: By a grant from the Agency for Healthcare Research and Quality (HS-06274) and a Robert Wood Johnson Foundation Generalist Physician Faculty Scholarship (Dr. Smith).
Requests for Single Reprints: Roy M. Poses, MD, Brown University Center for Primary Care and Prevention, Memorial Hospital of Rhode Island, 111 Brewster Street, Pawtucket, RI 02860; e-mail, firstname.lastname@example.org.
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Current Author Addresses: Dr. Poses: Brown University Center for Primary Care and Prevention, Memorial Hospital of Rhode Island, 111 Brewster Street, Pawtucket, RI 02860.
Dr. McClish: Department of Biostatistics, Virginia Commonwealth University, MCV Campus, Box 980032, Richmond, VA 23298-0032.
Dr. Smith: Division of Quality Health Care, Department of Internal Medicine, Virginia Commonwealth University, MCV Campus, Box 980306, Richmond, VA 23298-0306.
Drs. Huber and Clemo: Division of General Internal Medicine, Department of Internal Medicine, Virginia Commonwealth University, MCV Campus, Box 980102, Richmond, VA 23298-0102.
Dr. Schmitt: Chicago Veterans Affairs Medical Center, 333 East Huron Street, Chicago, IL 60611.
Dr. Alexander: Department of Psychology, John Tyler Community College, 13101 Jefferson Davis Highway, Chester, VA 23831-5316.
Dr. Racht: City of Austin/Travis County Emergency Medical Services, 517 South Pleasant Valley, Austin, TX 78741-1902.
Dr. Colenda: Department of Psychiatry, College of Human Medicine, A-222 East Fee Hall, Michigan State University, East Lansing, MI 48824-1316.
Author Contributions: Conception and design: R.M. Poses, D.K. McClish, W.R. Smith, E.C. Huber, F.L.W. Clemo, B.P. Schmitt, E.M. Racht, C.C. Colenda.
Analysis and interpretation of the data: R.M. Poses, D.K. McClish, W.R. Smith, E.C. Huber, F.L.W. Clemo, B.P. Schmitt.
Drafting of the article: R.M. Poses, D.K. McClish, W.R. Smith, E.C. Huber, F.L.W. Clemo.
Critical revision of the article for important intellectual content: R.M. Poses, D.K. McClish, W.R. Smith, E.C. Huber, F.L.W. Clemo, B.P. Schmitt, D. Alexander, C.C. Colenda.
Final approval of the article: R.M. Poses, D.K. McClish, W.R. Smith, E.C. Huber, F.L.W. Clemo, B.P. Schmitt.
Provision of study materials or patients: R.M. Poses, E.C. Huber, F.L.W. Clemo, E.M. Racht.
Statistical expertise: R.M. Poses, D.K. McClish.
Obtaining of funding: R.M. Poses.
Administrative, technical, or logistic support: R.M. Poses, F.L.W. Clemo, B.P. Schmitt, A. Alexander.
Collection and assembly of data: R.M. Poses, D.K. McClish, W.R. Smith, E.C. Huber, F.L.W. Clemo, B.P. Schmitt, D. Alexander, E.M. Racht.
The validity of outcome report cards may depend on the ways in which they are adjusted for risk.
To compare the predictive ability of generic and disease-specific survival prediction models appropriate for use in patients with heart failure, to simulate outcome report cards by comparing survival across hospitals and adjusting for severity of illness using these models, and to assess the ways in which the results of these comparisons depend on the adjustment method.
Analysis of data from a prospective cohort study.
A university hospital, a Veterans Affairs (VA) medical center, and a community hospital.
Sequential patients presenting in the emergency department with acute congestive heart failure.
Unadjusted 30-day and 1-year mortality across hospitals and 30-day and 1-year mortality adjusted by using disease-specific survival prediction models (two sickness-at-admission models, the Cleveland Health Quality Choice model, the Congestive Heart Failure Mortality Time-Independent Predictive Instrument) and generic models (Acute Physiology and Chronic Health Evaluation [APACHE] II, APACHE III, the mortality prediction model, and the Charlson comorbidity index).
The community hospital's unadjusted 30-day survival rate (85.0%) and the VA medical center's unadjusted 1-year survival rate (60.9%) were significantly lower than corresponding rates at the university hospital (92.7% and 67.5%, respectively). No severity model had excellent ability to discriminate patients by survival rates (all areas under the receiver-operating characteristic curve < 0.73). Whether the VA medical center, the community hospital, both, or neither had worse survival rates on simulated report cards than the university hospital depended on the prediction model used for adjustment.
Results of simulated outcome report cards for survival in patients with congestive heart failure depend on the method used to adjust for severity.
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Poses RM, McClish DK, Smith WR, Huber EC, Clemo FLW, Schmitt BP, et al. Results of Report Cards for Patients with Congestive Heart Failure Depend on the Method Used To Adjust for Severity. Ann Intern Med. 2000;133:10-20. doi: 10.7326/0003-4819-133-1-200007040-00003
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Published: Ann Intern Med. 2000;133(1):10-20.
Cardiology, Heart Failure, Hospital Medicine.
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